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- q101/random_k2/question.json +2 -2
- q101/random_k2/random_1.md +0 -0
- q101/random_k2/random_2.md +0 -0
- q101/random_k4/question.json +4 -4
- q101/random_k4/random_1.md +0 -0
- q101/random_k4/random_2.md +0 -0
- q101/random_k4/random_3.md +0 -0
- q101/random_k4/random_4.md +0 -0
- q106/random_k2/question.json +2 -2
- q106/random_k2/random_1.md +613 -944
- q106/random_k2/random_2.md +0 -0
- q106/random_k4/question.json +4 -4
- q106/random_k4/random_1.md +613 -944
- q106/random_k4/random_2.md +0 -0
- q106/random_k4/random_3.md +1200 -567
- q106/random_k4/random_4.md +809 -1
- q107/random_k2/question.json +2 -2
- q107/random_k2/random_1.md +0 -0
- q107/random_k2/random_2.md +0 -0
- q107/random_k4/question.json +4 -4
- q107/random_k4/random_1.md +0 -0
- q107/random_k4/random_2.md +0 -0
- q107/random_k4/random_3.md +1011 -542
- q107/random_k4/random_4.md +1978 -1
- q130/random_k2/question.json +2 -2
- q130/random_k2/random_1.md +704 -622
- q130/random_k2/random_2.md +1123 -474
- q130/random_k4/question.json +4 -4
- q130/random_k4/random_1.md +704 -622
- q130/random_k4/random_2.md +1123 -474
- q130/random_k4/random_3.md +0 -0
- q130/random_k4/random_4.md +0 -0
- q131/random_k2/question.json +2 -2
- q131/random_k2/random_1.md +346 -693
- q131/random_k2/random_2.md +392 -528
- q131/random_k4/question.json +4 -4
- q131/random_k4/random_1.md +346 -693
- q131/random_k4/random_2.md +392 -528
- q131/random_k4/random_3.md +0 -0
- q131/random_k4/random_4.md +1971 -598
- q136/random_k2/question.json +2 -2
- q136/random_k2/random_1.md +645 -119
- q136/random_k2/random_2.md +0 -0
- q136/random_k4/question.json +4 -4
- q136/random_k4/random_1.md +645 -119
- q136/random_k4/random_2.md +0 -0
- q136/random_k4/random_3.md +2323 -299
- q136/random_k4/random_4.md +655 -477
- q137/random_k2/question.json +2 -2
- q137/random_k2/random_1.md +0 -0
q101/random_k2/question.json
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],
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"original_filenames": [
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"modality": "markdown"
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q101/random_k2/random_1.md
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q101/random_k4/question.json
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q101/random_k4/random_4.md
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q106/random_k2/question.json
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"original_filenames": [
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"original_filenames": [
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| 528 |
-
|
| 529 |
-
|
| 530 |
-
|
| 531 |
-
|
| 532 |
-
|
| 533 |
-
|
| 534 |
-
|
| 535 |
-
|
| 536 |
-
|
| 537 |
-
|
| 538 |
-
|
| 539 |
-
|
| 540 |
-
|
| 541 |
-
|
| 542 |
-
|
| 543 |
-
|
| 544 |
-
|
| 545 |
-
|
| 546 |
-
|
| 547 |
-
|
| 548 |
-
|
| 549 |
-
|
| 550 |
-
|
| 551 |
-
|
| 552 |
-
|
| 553 |
-
|
| 554 |
-
|
| 555 |
-
|
| 556 |
-
|
| 557 |
-
|
| 558 |
-
|
| 559 |
-
|
| 560 |
-
|
| 561 |
-
|
| 562 |
-
|
| 563 |
-
|
| 564 |
-
|
| 565 |
-
|
| 566 |
-
|
| 567 |
-
|
| 568 |
-
|
| 569 |
-
|
| 570 |
-
|
| 571 |
-
|
| 572 |
-
|
| 573 |
-
|
| 574 |
-
|
| 575 |
-
|
| 576 |
-
|
| 577 |
-
|
| 578 |
-
|
| 579 |
-
|
| 580 |
-
|
| 581 |
-
|
| 582 |
-
|
| 583 |
-
|
| 584 |
-
|
| 585 |
-
|
| 586 |
-
|
| 587 |
-
|
| 588 |
-
|
| 589 |
-
|
| 590 |
-
|
| 591 |
-
|
| 592 |
-
|
| 593 |
-
|
| 594 |
-
|
| 595 |
-
|
| 596 |
-
|
| 597 |
-
|
| 598 |
-
|
| 599 |
-
|
| 600 |
-
|
| 601 |
-
|
| 602 |
-
|
| 603 |
-
|
| 604 |
-
|
| 605 |
-
|
| 606 |
-
|
| 607 |
-
|
| 608 |
-
|
| 609 |
-
|
| 610 |
-
|
| 611 |
-
|
| 612 |
-
|
| 613 |
-
|
| 614 |
-
Administration & Other Expenses
|
| 615 |
-
| | | | 14660 | 15116 |
|
| 616 |
-
| --- | --- | --- | ----- | ----- |
|
| 617 |
-
Advertisement Exp
|
| 618 |
-
| Salary & Other Benefits | | | 1775 | 2069 |
|
| 619 |
-
| ----------------------- | --- | --- | ---- | ---- |
|
| 620 |
-
Pa'ymerrt \o Auditors
|
| 621 |
-
Audit Fees
|
| 622 |
-
5510
|
| 623 |
-
| | Taxation Fees | 7500 | 13010 | 12900 |
|
| 624 |
-
| --------------------- | ------------- | ---- | ----- | ----- |
|
| 625 |
-
| Professional Charges | | | 30535 | 34083 |
|
| 626 |
-
| Listing Fees | | | 1QGGG | 1000G |
|
| 627 |
-
| Printing & Stationary | | | | 540 |
|
| 628 |
-
1134
|
| 629 |
-
| Office Rent | | | 6000 | 6000 |
|
| 630 |
-
| -------------------------------- | --- | --- | ----- | ----- |
|
| 631 |
-
| Donation' | | | 1000 | 0 |
|
| 632 |
-
| Rep . 4. Main.tan.ce of Computer | | | 0 | 667 |
|
| 633 |
-
| Miscellenous Expenses | | | 6635 | 8730 |
|
| 634 |
-
| | | | 84749 | S0105 |
|
| 635 |
-
SCHEDULE K
|
| 636 |
-
Interest Paid
|
| 637 |
-
| Interest Paid to Others | | | 702 | 2502 |
|
| 638 |
-
| ------------------------------------- | --- | --- | ----- | ---- |
|
| 639 |
-
| interest Paid against Bank Loan - FDR | | | 42739 | 0 |
|
| 640 |
-
| | | | 43441 | 2502 |
|
| 641 |
-
|
| 642 |
-
FRONTIER LEASING & FINANCE LTD.
|
| 643 |
-
SCHEDULE - L : NOTES ON ACCOUNTS.
|
| 644 |
-
1. Significant Accounting Policies :-
|
| 645 |
-
The financial statements are prepared under the historical cost convention, on an accrual
|
| 646 |
-
basis and in accordance with the applicable accounting standards.
|
| 647 |
-
1.1) Fixed Assets:-
|
| 648 |
-
Fixed Assets are stated at cost, less accumulated depreciation. Cost comprises
|
| 649 |
-
the purchase price and any attributable cost of bringing the asset to its working
|
| 650 |
-
condition for its intended use.
|
| 651 |
-
1.2) Depreciation :-
|
| 652 |
-
Depreciation on Fixed Assets is provided on Written Down Method at the rates
|
| 653 |
-
and in the manner specified in the Schedule XIV of the Companies Act, 1956.
|
| 654 |
-
1.3) Investments :-
|
| 655 |
-
Long Term Investments are stated at cost.
|
| 656 |
-
1.4) Revenue Recognition :
|
| 657 |
-
Interest is recorded on time basis. Dividend income on investments is accounted
|
| 658 |
-
for when the right to receive the payment is established.
|
| 659 |
-
1.5) Taxation :-
|
| 660 |
-
The provision for Current Tax is determined on the basis of taxable income for the
|
| 661 |
-
current accounting year in accordance with the Income Tax Act, 1961.
|
| 662 |
-
The Deferred Tax is recognised, considering the prudence, on timing difference
|
| 663 |
-
that originate in one period and capable of reversal in subsequent period.
|
| 664 |
-
Deferred tax assets are recognised on Long Term Capital ioss on the basis of
|
| 665 |
-
reasonable certainty that such deferred tax asset can be realised against future
|
| 666 |
-
taxable Long Term Capital Gain.
|
| 667 |
-
Deferred tax Liability recognised in earlier year on difference between Book
|
| 668 |
-
depredation and depreciation under Income Tax Act 1961 is reversed to the extent
|
| 669 |
-
of realization.
|
| 670 |
-
1.6) Retirement Benefits :-
|
| 671 |
-
The Gratuity liability is provided on cash basis.
|
| 672 |
-
1 7) Segment Information :-
|
| 673 |
-
Since the company is dealing in only one segment, i.e. financing, there is no
|
| 674 |
-
reportable segment as per AS-17 on "Segment Reporting" issued by Institute of
|
| 675 |
-
Chartered Accountant of India.
|
| 676 |
-
|
| 677 |
-
2. Contingent Liability not provided for
|
| 678 |
-
| | | | As on | As on | | |
|
| 679 |
-
| --- | --- | --- | -------- | ------- | --- | --- |
|
| 680 |
-
| | | | 31.3.05 | 31.3.04 | | |
|
| 681 |
-
Estimated amount of contracts remaining
|
| 682 |
-
to be executed on capital account and
|
| 683 |
-
| | not provided for | | Nil | Nil | | |
|
| 684 |
-
| --- | ----------------------------------- | --- | -------- | ------- | --- | --- |
|
| 685 |
-
| | | | As on | As on | | |
|
| 686 |
-
| | | | 31.3.05 | 31.3.04 | | |
|
| 687 |
-
| 3. | a) Expenditure in Foreign Currency | | Nii | | Nii | |
|
| 688 |
-
b) Amount remitted during the year in
|
| 689 |
-
| | Foreign Currency on account & Divided | | Nil | | Nil | |
|
| 690 |
-
| --- | -------------------------------------- | --- | ---- | --- | --- | --- |
|
| 691 |
-
| | c) Earning in Foreign Exchange | | Nil | | Nil | |
|
| 692 |
-
4 Other information pursuant to paragraph 3,4C, 4D of Part II of Schedule VI of the
|
| 693 |
-
Companies Act, 1956 are not applicable.
|
| 694 |
-
5 Payment made to Auditors :
|
| 695 |
-
| | | | As on | As on | | |
|
| 696 |
-
| --- | --- | --- | ------- | ------- | --- | --- |
|
| 697 |
-
| | | | 31.3.05 | 31.3.04 | | |
|
| 698 |
-
| | | | 5000 | 5000 | | |
|
| 699 |
-
a) As Audit Fees
|
| 700 |
-
| | b) Other Matters | | 7500 | 7500 | | |
|
| 701 |
-
| --- | ---------------- | --- | ---- | ---- | --- | --- |
|
| 702 |
-
400
|
| 703 |
-
| | c) Service Tax | | 510 | | | |
|
| 704 |
-
| --- | -------------- | --- | ----- | ----- | --- | --- |
|
| 705 |
-
| | | | 13010 | 12900 | | |
|
| 706 |
-
6 The basic earning per share is computed by dividing the net profit attributable to the equity
|
| 707 |
-
shareholders for the year by the weighted average number of equity shares outstanding
|
| 708 |
-
during the year. As there is no presence of diiutive potential equity shares, the diluted EPS
|
| 709 |
-
is same as basis EPS as follows :
|
| 710 |
-
| | | | | | As on | As on |
|
| 711 |
-
| --- | --- | ---------------------------------------- | --- | ----------- | ------- | ---------- |
|
| 712 |
-
| | | | | 31/03/2005 | | 31/03/2004 |
|
| 713 |
-
| | | Profit after Tax | | | 168679 | 99375 |
|
| 714 |
-
| | | Add : Excess /(Short) Provision for Tax | | | 235 | 847 |
|
| 715 |
-
| | | Less: Transfer to Statutory Reserve | | | 34000 | 20000 |
|
| 716 |
-
Net Profit attributable to Equity Shareholders 134914 80222
|
| 717 |
-
| | | Weighted average number of shares | | 245000 | | 245000 |
|
| 718 |
-
| --- | --- | ---------------------------------- | --- | ------- | --- | ------ |
|
| 719 |
-
Earning per share
|
| 720 |
-
| | | Basic & Diluted | | | 0.55 | 0.33 |
|
| 721 |
-
| --- | --- | ---------------- | --- | --- | ----- | ---- |
|
| 722 |
-
|
| 723 |
-
7. Deferred Tax :-
|
| 724 |
-
5.1) Net Deferred Tax income for the year is Rs. 3522 and the same has been charged to
|
| 725 |
-
the Profit and Loss Account.
|
| 726 |
-
6.2) The break-up of deferred tax assets and fiabifities are as foilows :
|
| 727 |
-
| | As on | As on |
|
| 728 |
-
| --- | -------- | -------- |
|
| 729 |
-
| | 31.03.05 | 31.03.04 |
|
| 730 |
-
Deferred Tax Assets
|
| 731 |
-
| On Long Term Capital Loss of Prev.Years | 233 | 160347 |
|
| 732 |
-
| --------------------------------------- | ----- | ------ |
|
| 733 |
-
| Measured @ 20.91% (20.50%) | 33761 | 32871 |
|
| 734 |
-
Deferred Tax Liability
|
| 735 |
-
Difference between Book Value of
|
| 736 |
-
depreciable assets and WDV for Tax
|
| 737 |
-
| purposes. | (2914) | 38562 |
|
| 738 |
-
| ----------------------------- | ------ | ------ |
|
| 739 |
-
| Measured @ 36.60% (35.87%) | 11200 | 13832 |
|
| 740 |
-
| Net Deferred Tax Liabilities. | 22561 | 190391 |
|
| 741 |
-
6. Refated Party Transaction (AS-18)
|
| 742 |
-
a) List of Related Parties and Relationships.
|
| 743 |
-
The following is the information on transactions with the related parties:
|
| 744 |
-
Name Relationship
|
| 745 |
-
Key Management Personnel:- Kawaljit S. Chawla Whole Time Director
|
| 746 |
-
Ramnath Choudhary Whole Time Director
|
| 747 |
-
Vasudev R.Yadav Whole Time Director
|
| 748 |
-
b) Relatives of Key Management Personnel >
|
| 749 |
-
Relationship
|
| 750 |
-
Name
|
| 751 |
-
| Jeet Machines Tools Ltd | Father of Director is director in | |
|
| 752 |
-
| ----------------------- | --------------------------------- | --- |
|
| 753 |
-
the said Company
|
| 754 |
-
c) Refated Party Transactions : Relatives of Key Management
|
| 755 |
-
Personnel
|
| 756 |
-
Interest Paid Rs. 702/-
|
| 757 |
-
9. There are no amounts due to any enterprise which is small scale and ancillary
|
| 758 |
-
undertaking, for more than 30 days
|
| 759 |
-
10 Previous year figures are regrouped or rearranged wherever necessary
|
| 760 |
-
|
| 761 |
-
11. BALANCE SHEET ABSTRACT AND COMPANY'S GENERAL BUSINESS PROFILE
|
| 762 |
-
I REGISTRATION DETAILS
|
| 763 |
-
| Registration No | | | 33328 | |
|
| 764 |
-
| ------------------ | --- | --- | ---------- | --- |
|
| 765 |
-
| State Code | No | | 11 | |
|
| 766 |
-
| Balance Sheet Date | | | 31.03.2005 | |
|
| 767 |
-
II CAPITAL RAISED DURING THE YEAR
|
| 768 |
-
| Public Issue | | | : Nil | |
|
| 769 |
-
| ------------------ | ---------------- | --- | --------------- | --------- |
|
| 770 |
-
| Riujrt | Issue | | •. Nil | |
|
| 771 |
-
| Bonus Issue | | | : Nil | |
|
| 772 |
-
| Private Placement | | | : Nil | |
|
| 773 |
-
| HI POSITION | OF MOBILIZATION | | AND DEPLOYMENT | OF FUNDS |
|
| 774 |
-
(Amounts in Rupees Thousands )
|
| 775 |
-
| | Total Liabilities | | . 5046 | |
|
| 776 |
-
| --- | ------------------ | --- | ------- | --- |
|
| 777 |
-
| | Total Assets | | : 5046 | |
|
| 778 |
-
SOURCE OF FUND
|
| 779 |
-
| | Paid up Capital | | : 2450 | |
|
| 780 |
-
| --- | ----------------- | --- | ------- | --- |
|
| 781 |
-
| | Reserve & Surplus | | 2585 | |
|
| 782 |
-
| | Secured Loan | | Nil | |
|
| 783 |
-
| | Unsecured Loan | | 11 | |
|
| 784 |
-
APPLICATION OF FUNDS
|
| 785 |
-
| | Net Fixed Assets | | : 32 | |
|
| 786 |
-
| --- | ------------------- | ------ | ------- | --- |
|
| 787 |
-
| | Investments | | : 802 | |
|
| 788 |
-
| | NeV Current Assets | | . 4189 | |
|
| 789 |
-
| | Misc. Expenditure | | : Nil | |
|
| 790 |
-
| | Accumulated | Losses | : Nil | |
|
| 791 |
-
| | Deterred Tax Assets | | : 23 | |
|
| 792 |
-
IV PERFORMANCE OF THE COMPANY(Anw>unts in Rupees Thousands)
|
| 793 |
-
| Turnover | | | : 348 | |
|
| 794 |
-
| -------------------------- | --- | --- | ------- | --- |
|
| 795 |
-
| Total Expenditure | | | : 137 | |
|
| 796 |
-
| Profit Before Tax | | | ; 211 | |
|
| 797 |
-
| Profit After Tax | | | : 169 | |
|
| 798 |
-
| Earning Per Shares (In Rs) | | | : 0.55 | |
|
| 799 |
-
| Dividend | | | : Nil | |
|
| 800 |
-
|
| 801 |
-
V. GENERIC NAMES OF THREE PRINCIPAL PRODUCTS / SERVICES OF COMPANY
|
| 802 |
-
(As per monetary term)
|
| 803 |
-
Item Code No. (ITC CODE ) : NA
|
| 804 |
-
Product Description : Finance & Investment.
|
| 805 |
-
As per report of even date
|
| 806 |
-
FOR J.S. BHATIA & CO. For and on behvAf of th« Board.
|
| 807 |
-
CHARTERED ACCOUNTANT.
|
| 808 |
-
KAWALJIT SINGH CHAWLA
|
| 809 |
-
J.S. BHATrA VASUDEVR. VADAV
|
| 810 |
-
PROPRIETOR
|
| 811 |
-
DIRECTORS.
|
| 812 |
-
Place : Mumbai Place : Mumbai
|
| 813 |
-
Date : 25* August 2005 Date : 25* August 2005
|
| 814 |
-
|
| 815 |
-
FRONTIER LEASING & FINANCE LTD.
|
| 816 |
-
CASHFLOW STATEMENT FOR THE YEAR ENDED MARCH 31.2008
|
| 817 |
-
Amount m Rupees
|
| 818 |
-
| | 31/03/2005 | 31/03/2004 |
|
| 819 |
-
| --- | ----------- | ---------- |
|
| 820 |
-
I CASH FLOW FROM OPERATING ACTIVITIES
|
| 821 |
-
Net Profit before Tax & Extraordinary items 211.157.00 154.506.00
|
| 822 |
-
Add / (Less): Adjustments for
|
| 823 |
-
| Dividend income | (20000) | (200.00) |
|
| 824 |
-
| ------------------------------------ | ------------ | ----------- |
|
| 825 |
-
| Depreciation | 9,096.00 | 13,497.00 |
|
| 826 |
-
| ( Profit y loss on fixed Assets sold | 0.00 | (28,771.00) |
|
| 827 |
-
| | (132.436.00) | 0.00 |
|
| 828 |
-
(Profit) /-Loss on Sale of Investment
|
| 829 |
-
| Demat & Brokerage charges | 652.00 | 0.00 |
|
| 830 |
-
| ------------------------- | ------ | ---- |
|
| 831 |
-
Increase / (Decrease) in Trade & Other Payable (3,869.00) 10,190.00
|
| 832 |
-
| Direct taxes paid | (44.676.00) | (62.971.00) |
|
| 833 |
-
| ----------------- | ----------- | ----------- |
|
| 834 |
-
(Increase)/ Decrease in Trade & Other Receivable (643,302.00) (90.602.00)
|
| 835 |
-
CASH FLOW FROM OPERATING ACTIVITIES -1 (603.578.00) (4.351.00)
|
| 836 |
-
II CASH FLOW FROM INVESTING ACTIVITIES
|
| 837 |
-
| (Purchase) / sate of Fixed Assets | 0.00 | 41,525.00 |
|
| 838 |
-
| --------------------------------- | ---- | --------- |
|
| 839 |
-
(Purchase V Sale of Investments (Net of Pur.&Saies) (19,825.00) 0.00
|
| 840 |
-
| | 523.811.00 | 0.00 |
|
| 841 |
-
| --- | ---------- | ---- |
|
| 842 |
-
(Increase)/ Decrease in Loans & Advances
|
| 843 |
-
| Profit on Sale of Investments | 132,436.00 | 0.00 |
|
| 844 |
-
| -------------------------------------- | ---------- | --------- |
|
| 845 |
-
| Dividend received | 200.00 | 200.00 |
|
| 846 |
-
| NET CASH FROM INVESTING ACTIVITIES - R | 636,622.00 | 41.725.00 |
|
| 847 |
-
III CASH FLOW FROM FINANCING ACTIVITIES
|
| 848 |
-
| Demat & Brokerage charges | (652.00) | 0.00 |
|
| 849 |
-
| -------------------------------------- | -------- | ----------- |
|
| 850 |
-
| Proceeds / (Repayment) from borrowings | 702.00 | (32,044.00) |
|
| 851 |
-
| | 50.00 | (32,044.00) |
|
| 852 |
-
NET CASH FROM FINANCING ACTIVITIES • •
|
| 853 |
-
| NET INCREASE/(DECREASE) IN CASH ( | 33,094.00 | 5,330.00 |
|
| 854 |
-
| --------------------------------- | --------- | -------- |
|
| 855 |
-
OPENING BALANCE OF CASH & CASH EQUIVALENT 17,997.00 12,667 00
|
| 856 |
-
CLOSING BALANCE OF CASH & CASH EQUIVALENT 51.091.00 17,997.00
|
| 857 |
-
Notes 1) Cash and cash equivatents consists of cash on hand and balances with bank
|
| 858 |
-
2) Figures in brackets represents outflow of cash
|
| 859 |
-
3) Figures for the last year have been regrouped, wherever considered necessary
|
| 860 |
-
Per our report of even date
|
| 861 |
-
FOR J. S. BHATIA & CO. For and on behalf of the board
|
| 862 |
-
Chartered accountants
|
| 863 |
-
J. S. BHATIA KAWAUIT SINGH CHAWLA
|
| 864 |
-
PROPRIETOR
|
| 865 |
-
PLACE : MUMBAI
|
| 866 |
-
DATED : 25.08.2005
|
| 867 |
-
|
| 868 |
-
| T | Q R H | A T fA Jte | fV"fc | | 14A15, Ashoka Centre, |
|
| 869 |
-
| ---------- | --------- | ------------ | ------ | --- | ------------------------------ |
|
| 870 |
-
| J. b. | BHATIA & | | CO. | | 2nd Floor, LotonanyaTllakMaiB, |
|
| 871 |
-
| CHARTERED | | ACCOUNTANTS | | | Mumbal-400001. |
|
| 872 |
-
Tel.: Office: 2267 5066 / 2267 5067
|
| 873 |
-
Fax: 2269 2994
|
| 874 |
-
Rest.: 2620 2207 / 2620 3849
|
| 875 |
-
E-mail: jaipalsb6)bom3.vsnl.net.in
|
| 876 |
-
AUDITOR'S CERTIFICATE
|
| 877 |
-
To,
|
| 878 |
-
The Board of Directors,
|
| 879 |
-
Frontier Leasing & Finance Limited.
|
| 880 |
-
We have examined the attached Cash Flow Statement of Frontier Leasing &
|
| 881 |
-
Finance Limited for the year ended 31st March 2005. The Statement has been
|
| 882 |
-
prepared by the Company in accordance with the requirements of clause 32 of
|
| 883 |
-
the listing agreement with various Stock Exchanges and is based on and in
|
| 884 |
-
agreement with the corresponding Profit & Loss Account and Balance Sheet of
|
| 885 |
-
the Company covered by our report of even date to the members of the
|
| 886 |
-
Company.
|
| 887 |
-
For J. S. BHATIA & CO.,
|
| 888 |
-
| | | | | CHARTERED | AC CO UNTANTS |
|
| 889 |
-
| --- | --------------- | -------------- | --- | ---------- | ------------- |
|
| 890 |
-
| | PLACE : MUMBAI | | | | J. S. BHATIA |
|
| 891 |
-
| | DATE | : T-^/dZ/xooS | | - | (PROPRIETOR) |
|
| 892 |
-
|
| 893 |
-
FRONTIER LEASING & FINANCE LIMITED.
|
| 894 |
-
Registered Office : C/o. Victory Printing Press, Jyoti Studio
|
| 895 |
-
Compound, KB.A Irani Bridge,
|
| 896 |
-
Mumbai - 400 007.
|
| 897 |
-
PLEASE COMPLETE THE ATTENDANCE SLIP AND HAND IT
|
| 898 |
-
OVER AT THE ENTRANCE OF THE MEETING HALL.
|
| 899 |
-
1. Name of the Shareholder.
|
| 900 |
-
(In Block Letters)
|
| 901 |
-
2. Ledger Folio Number.
|
| 902 |
-
3. Name of the Proxy (In Block Letter) ,
|
| 903 |
-
(To be filled in only if the proxy attends instead of member)
|
| 904 |
-
4. No. of Shares held.
|
| 905 |
-
1 hereby record my presence at 21st Annual General Meeting of
|
| 906 |
-
the Company to be held on Thursday, 29th September 2005 at
|
| 907 |
-
C/o. Victory Printing Press, Jyoti Studio Compound, K.B» A Irani Bridge,
|
| 908 |
-
Mumbai - 400 007 at 3.00 p.m.
|
| 909 |
-
Signature of the Shareholder /Proxy
|
| 910 |
-
NOTES :
|
| 911 |
-
1. Shareholders/Proxy holders are requested to bring the attendance slip
|
| 912 |
-
with them when they come to the meeting. No attendance slip will be
|
| 913 |
-
issued at the time of meeting.
|
| 914 |
-
2. Shareholders who come to attend the meeting are requested to
|
| 915 |
-
bring their copies of Annual Report with them, as spare copies wQl
|
| 916 |
-
not available in the meeting.
|
| 917 |
-
|
| 918 |
-
FRONTIER LEASING & FINANCE LIMITED.
|
| 919 |
-
PROXY FORM
|
| 920 |
-
I/We
|
| 921 |
-
of being the Member/Members
|
| 922 |
-
of the named company hereby appoint
|
| 923 |
-
of or tailing
|
| 924 |
-
him
|
| 925 |
-
of or failmg
|
| 926 |
-
him
|
| 927 |
-
as / my proxy to vote for me / us on behalf at the 21 st Annual General Meeting of
|
| 928 |
-
the Company to beheld at3.00 p.m. on Thursday, 29th September 2005 and at
|
| 929 |
-
any adjournment thereof.
|
| 930 |
-
Ledger Folio No
|
| 931 |
-
No. of Shares held
|
| 932 |
-
: Affix :
|
| 933 |
-
: Revenue
|
| 934 |
-
: Stamp
|
| 935 |
-
Signature
|
| 936 |
-
Date
|
| 937 |
-
NOTES :
|
| 938 |
-
(a) The form should be signed across the stamp as per specimen signature
|
| 939 |
-
registered with the Company.
|
| 940 |
-
(b) The Companies Act, 1956 fays down that the instrument appointing a,
|
| 941 |
-
proxy shaft be deposited at the Registered Office of the Company
|
| 942 |
-
not less than FOURTY EIGHT HOURS before the time fixed for
|
| 943 |
-
holding the meeting.
|
| 944 |
-
(c) A Proxy need not be a Member.
|
|
|
|
| 1 |
+
The Step-by-Step Guide
|
| 2 |
+
to Recruiting Top Talent
|
| 3 |
+
|
| 4 |
+
Your blueprint to transform your talent acquisition practices
|
| 5 |
+
to attract the people you need.
|
| 6 |
+
|
| 7 |
+
Table of Contents
|
| 8 |
+
|
| 9 |
+
01
|
| 10 |
+
|
| 11 |
+
The Race for Talent
|
| 12 |
+
|
| 13 |
+
02
|
| 14 |
+
|
| 15 |
+
Does Your Talent Acquisition
|
| 16 |
+
Process Need a Tune-up?
|
| 17 |
+
|
| 18 |
+
03
|
| 19 |
+
|
| 20 |
+
5 Factors That Affect Your Talent
|
| 21 |
+
Acquisition Efforts
|
| 22 |
+
|
| 23 |
+
04
|
| 24 |
+
|
| 25 |
+
The Step-by-Step Guide to
|
| 26 |
+
Recruiting Top Candidates
|
| 27 |
+
|
| 28 |
+
page 3
|
| 29 |
+
|
| 30 |
+
page 4
|
| 31 |
+
|
| 32 |
+
page 5
|
| 33 |
+
|
| 34 |
+
page 7
|
| 35 |
+
|
| 36 |
+
BONUS
|
| 37 |
+
|
| 38 |
+
05
|
| 39 |
+
|
| 40 |
+
10 Must-Haves of a Great
|
| 41 |
+
Recruitment Management System
|
| 42 |
+
page 11
|
| 43 |
+
|
| 44 |
+
06
|
| 45 |
+
|
| 46 |
+
Find and Keep
|
| 47 |
+
the Talent You Need
|
| 48 |
+
|
| 49 |
+
page 12
|
| 50 |
+
|
| 51 |
+
2
|
| 52 |
+
|
| 53 |
+
BOOKMARKS
|
| 54 |
+
Click on the title to to be
|
| 55 |
+
directed to that page.
|
| 56 |
+
|
| 57 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.The Race for Talent
|
| 58 |
+
|
| 59 |
+
01
|
| 60 |
+
|
| 61 |
+
It’s a job seeker’s market.
|
| 62 |
+
|
| 63 |
+
High employment rates, an aging workforce, and
|
| 64 |
+
skills gaps in both technical and soft skills have put
|
| 65 |
+
employees in the driver’s seat.
|
| 66 |
+
|
| 67 |
+
What this means for you is that you’re going to
|
| 68 |
+
have to fight harder than ever to recruit and retain
|
| 69 |
+
the people you need.
|
| 70 |
+
|
| 71 |
+
You’re going to have to leverage technology, lean into
|
| 72 |
+
your values, improve your employer branding, and in
|
| 73 |
+
some cases take a sledgehammer to your current talent
|
| 74 |
+
acquisition strategies to create engaging and responsive
|
| 75 |
+
recruitment experiences that not only attract candidates
|
| 76 |
+
to your company but compel them to choose you over
|
| 77 |
+
the competition.
|
| 78 |
+
|
| 79 |
+
It can be a daunting task… but we’ve got you covered
|
| 80 |
+
-as HCM consultants and SAP® SuccessFactors®
|
| 81 |
+
specialists, we’ve helped countless businesses do
|
| 82 |
+
exactly this.
|
| 83 |
+
|
| 84 |
+
This eBook is the first step in the process. It includes the
|
| 85 |
+
step-by-step guide to recruiting the best talent. Use it to
|
| 86 |
+
evaluate where you stand and build a talent acquisition
|
| 87 |
+
process that gives you the workforce you need for a
|
| 88 |
+
successful future.
|
| 89 |
+
|
| 90 |
+
Let’s get started.
|
| 91 |
+
|
| 92 |
+
An overwhelming
|
| 93 |
+
majority of candidates
|
| 94 |
+
(69%) refuse to
|
| 95 |
+
re-apply to a company
|
| 96 |
+
if they have a poor
|
| 97 |
+
experience during the
|
| 98 |
+
application process.
|
| 99 |
+
|
| 100 |
+
3
|
| 101 |
+
|
| 102 |
+
1 2016 Talent Board NAM CandE Research Report FINAL 170202.pdf
|
| 103 |
+
link: http://www.thetalentboard.org/wp-content/uploads/2017/02/2016_Talent_Board_NAM_Can-
|
| 104 |
+
|
| 105 |
+
dE_Research_Report_FINAL_170202.pdf
|
| 106 |
+
|
| 107 |
+
69%© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.
|
| 108 |
+
Does Your Talent Acquisition
|
| 109 |
+
Process Need a Tune-up?
|
| 110 |
+
|
| 111 |
+
02
|
| 112 |
+
|
| 113 |
+
Let’s look under the hood at your talent acquisition strategy
|
| 114 |
+
and see what’s really there. Here are five key questions that
|
| 115 |
+
you need to answer to identify the roadblocks between where
|
| 116 |
+
you are, and where you want to be.
|
| 117 |
+
|
| 118 |
+
01
|
| 119 |
+
|
| 120 |
+
02
|
| 121 |
+
|
| 122 |
+
03
|
| 123 |
+
|
| 124 |
+
04
|
| 125 |
+
|
| 126 |
+
05
|
| 127 |
+
|
| 128 |
+
Is your recruiting based on
|
| 129 |
+
current best practices?
|
| 130 |
+
|
| 131 |
+
Do you have buy-in
|
| 132 |
+
from your team?
|
| 133 |
+
|
| 134 |
+
Is your technology up to date
|
| 135 |
+
and fully cloud capable?
|
| 136 |
+
|
| 137 |
+
HR trends are evolving more
|
| 138 |
+
rapidly now than ever before.
|
| 139 |
+
Make sure you’re not falling
|
| 140 |
+
behind the competition when
|
| 141 |
+
it comes to implementing best
|
| 142 |
+
practices.
|
| 143 |
+
|
| 144 |
+
Is your team aligned internally?
|
| 145 |
+
Do they share a common lens?
|
| 146 |
+
Great candidate experiences
|
| 147 |
+
depend on the interactions
|
| 148 |
+
candidates have with your
|
| 149 |
+
team during the various stages
|
| 150 |
+
of the acquisition process.
|
| 151 |
+
Buy-in from your team is vital.
|
| 152 |
+
|
| 153 |
+
If you haven’t moved to the
|
| 154 |
+
cloud yet, it is never too late.
|
| 155 |
+
If you’ve migrated but aren’t
|
| 156 |
+
satisfied with your current
|
| 157 |
+
system, it can be salvaged.
|
| 158 |
+
The right tech really does
|
| 159 |
+
make a difference.
|
| 160 |
+
|
| 161 |
+
Are you always looking
|
| 162 |
+
for ways to innovate your
|
| 163 |
+
recruiting approach?
|
| 164 |
+
|
| 165 |
+
Is your recruitment
|
| 166 |
+
management system (RCM)
|
| 167 |
+
making your job easier?
|
| 168 |
+
|
| 169 |
+
Technology is playing an
|
| 170 |
+
increasingly crucial role in the
|
| 171 |
+
talent acquisition process. You
|
| 172 |
+
need to always have an eye on
|
| 173 |
+
the horizon, ear to the ground,
|
| 174 |
+
and willingness to adapt
|
| 175 |
+
and innovate your approach.
|
| 176 |
+
Remember: good ideas can
|
| 177 |
+
come from anywhere.
|
| 178 |
+
|
| 179 |
+
The right tools should help
|
| 180 |
+
to increase efficiency. But
|
| 181 |
+
sometimes, the tool itself
|
| 182 |
+
sucks up your time. And that’s
|
| 183 |
+
frustrating. Make sure your
|
| 184 |
+
system and processes make
|
| 185 |
+
your job easier. That’s the most
|
| 186 |
+
valuable success metric.
|
| 187 |
+
|
| 188 |
+
4
|
| 189 |
+
|
| 190 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.5 Factors That Affect
|
| 191 |
+
Your Talent Acquisition Efforts
|
| 192 |
+
|
| 193 |
+
03
|
| 194 |
+
|
| 195 |
+
The first step to building an effective acquisition strategy is to know
|
| 196 |
+
what internal and external factors affect your recruitment efforts.
|
| 197 |
+
|
| 198 |
+
Based on our experience and a study of current market conditions, here’s
|
| 199 |
+
5 factors that you need to be aware of when building your strategy.
|
| 200 |
+
|
| 201 |
+
You need to determine how you’ll adapt, counter, and respond to
|
| 202 |
+
each of these.
|
| 203 |
+
|
| 204 |
+
5
|
| 205 |
+
|
| 206 |
+
Continued on next page >
|
| 207 |
+
|
| 208 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.01
|
| 209 |
+
|
| 210 |
+
GROWING DEMAND &
|
| 211 |
+
DWINDLING SUPPLY
|
| 212 |
+
|
| 213 |
+
02
|
| 214 |
+
|
| 215 |
+
TURNOVER &
|
| 216 |
+
BURNOUT
|
| 217 |
+
|
| 218 |
+
03
|
| 219 |
+
|
| 220 |
+
INCONSISTENT
|
| 221 |
+
HIRING PROCESSES
|
| 222 |
+
|
| 223 |
+
04
|
| 224 |
+
|
| 225 |
+
INTENSE FOCUS ON
|
| 226 |
+
COST MANAGEMENT
|
| 227 |
+
|
| 228 |
+
05
|
| 229 |
+
|
| 230 |
+
EVOLVING
|
| 231 |
+
EXPECTATIONS
|
| 232 |
+
|
| 233 |
+
With just about every major
|
| 234 |
+
industry facing staffing
|
| 235 |
+
shortages, the candidates are
|
| 236 |
+
now in the driver’s seat with the
|
| 237 |
+
option of picking an employer
|
| 238 |
+
that responds to their needs
|
| 239 |
+
in a location of their choosing.
|
| 240 |
+
While talent acquisition and
|
| 241 |
+
human resources teams can’t
|
| 242 |
+
change the growing supply/
|
| 243 |
+
demand imbalance, they need
|
| 244 |
+
to be aware of how this affects
|
| 245 |
+
their acquisition strategy and
|
| 246 |
+
take active steps to attract
|
| 247 |
+
Gen X, Millennials, and
|
| 248 |
+
pretty soon Gen Z before the
|
| 249 |
+
competition does.
|
| 250 |
+
|
| 251 |
+
The staffing shortage also has
|
| 252 |
+
an adverse effect on current
|
| 253 |
+
professionals who have to
|
| 254 |
+
work longer hours leading to
|
| 255 |
+
burnout and turnover – which
|
| 256 |
+
leads to a dangerous loop of
|
| 257 |
+
an exhausted workforce, an
|
| 258 |
+
ever-growing pile of work, and
|
| 259 |
+
more turnover. Furthermore, an
|
| 260 |
+
organization with a reputation
|
| 261 |
+
for high turnover and burnout
|
| 262 |
+
creates additional challenges
|
| 263 |
+
for recruitment teams when it
|
| 264 |
+
comes to hiring the best talent.
|
| 265 |
+
|
| 266 |
+
Modern businesses often have
|
| 267 |
+
complex org charts, siloed
|
| 268 |
+
branches, and evolving parts.
|
| 269 |
+
This creates inconsistent hiring
|
| 270 |
+
processes that vary from
|
| 271 |
+
department to department,
|
| 272 |
+
region to region, and result in
|
| 273 |
+
poor candidate experiences
|
| 274 |
+
that negatively affect the
|
| 275 |
+
organization’s brand image.
|
| 276 |
+
While the HR team can’t
|
| 277 |
+
control everything, cloud-based
|
| 278 |
+
comprehensive talent solutions
|
| 279 |
+
such as SAP SuccessFactors can
|
| 280 |
+
help companies centralize their
|
| 281 |
+
processes and bring visibility to
|
| 282 |
+
internal teams and candidates.
|
| 283 |
+
|
| 284 |
+
Companies are always under
|
| 285 |
+
pressure to control costs. Up
|
| 286 |
+
against this mentality, HR
|
| 287 |
+
managers struggle to secure
|
| 288 |
+
funding for talent management
|
| 289 |
+
initiatives and, as a result,
|
| 290 |
+
end up using disparate, on
|
| 291 |
+
premise or outdated recruitment
|
| 292 |
+
technologies. This leads to error
|
| 293 |
+
prone processes due to the
|
| 294 |
+
doubling of data across systems,
|
| 295 |
+
labor intensive and slow hiring
|
| 296 |
+
steps, and a disconnected
|
| 297 |
+
candidate experience.
|
| 298 |
+
|
| 299 |
+
The largest generation in the
|
| 300 |
+
workforce today is tech-savvy
|
| 301 |
+
and socially aware Millennials.
|
| 302 |
+
As candidates, Millennials
|
| 303 |
+
look for companies that
|
| 304 |
+
align with their values, offer
|
| 305 |
+
training and development,
|
| 306 |
+
and deliver opportunities for
|
| 307 |
+
career growth. They expect
|
| 308 |
+
their future employers to
|
| 309 |
+
be digitally connected with
|
| 310 |
+
an intuitive website that
|
| 311 |
+
showcases its brand and
|
| 312 |
+
culture. They want a simple,
|
| 313 |
+
mobile friendly job application
|
| 314 |
+
process, transparent and timely
|
| 315 |
+
communication, and an active
|
| 316 |
+
social media presence so they
|
| 317 |
+
can interact with the company
|
| 318 |
+
during the hiring process.
|
| 319 |
+
|
| 320 |
+
6
|
| 321 |
+
|
| 322 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.The Step-by-Step Guide to
|
| 323 |
+
Recruiting Top Candidates
|
| 324 |
+
|
| 325 |
+
04
|
| 326 |
+
|
| 327 |
+
Building an amazing team is just as important as building a great
|
| 328 |
+
customer base. But, hiring the cream of the crop isn’t as easy as it
|
| 329 |
+
used to be. In the race for talent, the candidate experience matters
|
| 330 |
+
more now than ever before! This step-by-step guide is the blueprint
|
| 331 |
+
you need to transform your recruitment processes to meet the
|
| 332 |
+
expectations of a truly multigenerational digital workforce.
|
| 333 |
+
|
| 334 |
+
7
|
| 335 |
+
|
| 336 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.1
|
| 337 |
+
|
| 338 |
+
2
|
| 339 |
+
|
| 340 |
+
EVALUATE YOUR HIRING PROCESS
|
| 341 |
+
FROM START TO FINISH
|
| 342 |
+
|
| 343 |
+
Start by evaluating your current hiring process to make
|
| 344 |
+
sure you know what your candidate experience is
|
| 345 |
+
truly like - we would even go so far to suggest secret-
|
| 346 |
+
shopping the hiring process.
|
| 347 |
+
|
| 348 |
+
Next, storyboard your hiring process and map out
|
| 349 |
+
outcomes. The goal here is to plot the set of experiences
|
| 350 |
+
a candidate could have and optimize every step.
|
| 351 |
+
|
| 352 |
+
Use the data insights to create repeatable and
|
| 353 |
+
consistent hiring processes that offer positive
|
| 354 |
+
experiences.
|
| 355 |
+
|
| 356 |
+
Always make sure your hiring processes align
|
| 357 |
+
with and reflect your values and culture.
|
| 358 |
+
|
| 359 |
+
TIP
|
| 360 |
+
|
| 361 |
+
8
|
| 362 |
+
|
| 363 |
+
CREATE A STRONG, ATTRACTIVE
|
| 364 |
+
BRAND THAT SHOWS YOUR VALUE
|
| 365 |
+
TO TOP TALENT
|
| 366 |
+
|
| 367 |
+
Your brand is your most valuable asset, when it comes to
|
| 368 |
+
recruiting talent.
|
| 369 |
+
|
| 370 |
+
The first step in creating an attractive brand is developing
|
| 371 |
+
your Employee Value Proposition - a good EVP outlines
|
| 372 |
+
your organization’s mission and values and commitment
|
| 373 |
+
to employees.
|
| 374 |
+
|
| 375 |
+
Once you have your EVP, the next step is to make sure
|
| 376 |
+
your career site not only reflects but showcases your EVP
|
| 377 |
+
- much like the buyer’s journey, the hiring journey now
|
| 378 |
+
begins with an online search.
|
| 379 |
+
|
| 380 |
+
Lastly, make sure you have a strong content strategy
|
| 381 |
+
as it will help you build your brand identity and ensure
|
| 382 |
+
candidates find and connect with you online.
|
| 383 |
+
|
| 384 |
+
Great content is relevant, trendy, and
|
| 385 |
+
provides value. We find setting up an
|
| 386 |
+
editorial board helps ensure you’re regularly
|
| 387 |
+
and consistently posting good content.
|
| 388 |
+
|
| 389 |
+
TIP
|
| 390 |
+
|
| 391 |
+
Continued on next page >
|
| 392 |
+
|
| 393 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.< Continued from previous page
|
| 394 |
+
|
| 395 |
+
3
|
| 396 |
+
|
| 397 |
+
BUILD A TALENT PIPELINE AND NURTURE TALENT
|
| 398 |
+
|
| 399 |
+
There’s no such thing as “Just-in-Time Recruiting”.
|
| 400 |
+
|
| 401 |
+
Smart recruiters know the importance of building and nurturing a talent pipeline.
|
| 402 |
+
To build a strong pipeline:
|
| 403 |
+
|
| 404 |
+
01
|
| 405 |
+
|
| 406 |
+
02
|
| 407 |
+
|
| 408 |
+
Source talent globally
|
| 409 |
+
through an omni-channel
|
| 410 |
+
approach. Connect with and
|
| 411 |
+
reach out to candidates on
|
| 412 |
+
job boards, social platforms
|
| 413 |
+
and in-person events.
|
| 414 |
+
|
| 415 |
+
Create a network of
|
| 416 |
+
communities, content,
|
| 417 |
+
and contact points so that
|
| 418 |
+
you’re constantly nurturing
|
| 419 |
+
candidates and making sure
|
| 420 |
+
your brand is top of mind.
|
| 421 |
+
|
| 422 |
+
03
|
| 423 |
+
|
| 424 |
+
04
|
| 425 |
+
|
| 426 |
+
Make it simple for candidates
|
| 427 |
+
to get in touch and follow
|
| 428 |
+
up with HR by leveraging
|
| 429 |
+
automation, chatbots, and
|
| 430 |
+
other AI technology.
|
| 431 |
+
|
| 432 |
+
05
|
| 433 |
+
|
| 434 |
+
Use technology to track
|
| 435 |
+
candidate progress and
|
| 436 |
+
development benchmarks.
|
| 437 |
+
|
| 438 |
+
Take every opportunity
|
| 439 |
+
to share your culture and
|
| 440 |
+
events with candidates by
|
| 441 |
+
sharing different types of
|
| 442 |
+
company news and not just
|
| 443 |
+
job updates.
|
| 444 |
+
|
| 445 |
+
Encourage your
|
| 446 |
+
organization��s
|
| 447 |
+
leaders to be
|
| 448 |
+
active online,
|
| 449 |
+
sharing stories
|
| 450 |
+
and updates, and
|
| 451 |
+
engaging with
|
| 452 |
+
candidates.
|
| 453 |
+
|
| 454 |
+
TIP
|
| 455 |
+
|
| 456 |
+
9
|
| 457 |
+
|
| 458 |
+
Continued on next page >
|
| 459 |
+
|
| 460 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.< Continued from previous page
|
| 461 |
+
|
| 462 |
+
4
|
| 463 |
+
|
| 464 |
+
5
|
| 465 |
+
|
| 466 |
+
ENHANCE THE CANDIDATE EXPERIENCE
|
| 467 |
+
|
| 468 |
+
It’s time to end the candidate feedback black hole.
|
| 469 |
+
|
| 470 |
+
According to the 2016 North American Talent Board
|
| 471 |
+
Candidate Experience research report, 47 percent of
|
| 472 |
+
candidates never receive any communication up to two
|
| 473 |
+
months after applying for an open position!2
|
| 474 |
+
|
| 475 |
+
Give yourself an edge over the competition by
|
| 476 |
+
leveraging your RCM to not only keep your internal
|
| 477 |
+
team on the same page but also track and
|
| 478 |
+
communicate with candidates regularly.
|
| 479 |
+
|
| 480 |
+
Additionally, make sure your career site is always up to
|
| 481 |
+
date with current openings and that it showcases your
|
| 482 |
+
culture through employee testimonials.
|
| 483 |
+
|
| 484 |
+
CREATE AND SHARE
|
| 485 |
+
A CONSISTENT MESSAGE
|
| 486 |
+
|
| 487 |
+
The last step is less of a one-time only step and more so
|
| 488 |
+
an ongoing process.
|
| 489 |
+
|
| 490 |
+
Once you’ve evaluated, streamlined, and automated
|
| 491 |
+
your hiring processes, developed your EVP, and built
|
| 492 |
+
out your pipeline strategies, you need to make sure your
|
| 493 |
+
organization continues to create and share consistent
|
| 494 |
+
content and messages with your online and offline
|
| 495 |
+
communities.
|
| 496 |
+
|
| 497 |
+
Companies that constantly connect and engage passive
|
| 498 |
+
talent will have greater success at sourcing and hiring
|
| 499 |
+
top talent.
|
| 500 |
+
|
| 501 |
+
Don’t forget to make your application
|
| 502 |
+
process mobile friendly.
|
| 503 |
+
|
| 504 |
+
TIP
|
| 505 |
+
|
| 506 |
+
10
|
| 507 |
+
|
| 508 |
+
Tell your story. Engage your current
|
| 509 |
+
workforce and ask them to share
|
| 510 |
+
testimonials about what a job with your
|
| 511 |
+
organization is really like. Candidates are
|
| 512 |
+
attracted to authentic messages driven by
|
| 513 |
+
the workforce, not mandated by leadership.
|
| 514 |
+
|
| 515 |
+
TIP
|
| 516 |
+
|
| 517 |
+
2 2016 Talent Board NAM CandE Research Report FINAL 170202.pdf
|
| 518 |
+
link: http://www.thetalentboard.org/wp-content/uploads/2017/02/2016_
|
| 519 |
+
Talent_Board_NAM_CandE_Research_Report_FINAL_170202.pdf
|
| 520 |
+
|
| 521 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.BONUS
|
| 522 |
+
|
| 523 |
+
10 Must-Haves of a Great
|
| 524 |
+
Recruitment Management System
|
| 525 |
+
|
| 526 |
+
05
|
| 527 |
+
|
| 528 |
+
There’s no denying that technology has changed the talent acquisition process – But, how do you know if the
|
| 529 |
+
technology you’re currently using is delivering what you need to build a motivated, high performing workforce?
|
| 530 |
+
|
| 531 |
+
Use this cheat-sheet of the 10 must-haves to evaluate your system.
|
| 532 |
+
|
| 533 |
+
Seamless cloud integration – easily access candidate and
|
| 534 |
+
employee information from anywhere.
|
| 535 |
+
|
| 536 |
+
A simplified workflow for recruiters & HR – make the hiring
|
| 537 |
+
process easier for top talent and your HR team to navigate.
|
| 538 |
+
|
| 539 |
+
Standardized, optimized processes & communication –
|
| 540 |
+
with consistent processes in place, you’ll reduce error and
|
| 541 |
+
dramatically improve communications.
|
| 542 |
+
|
| 543 |
+
Omni-channel job distribution – advertise open positions
|
| 544 |
+
across sites and social channels to increase job exposure.
|
| 545 |
+
|
| 546 |
+
Customized, mobile-friendly landing pages & web portals –
|
| 547 |
+
make the hiring process faster and easier.
|
| 548 |
+
|
| 549 |
+
06
|
| 550 |
+
|
| 551 |
+
07
|
| 552 |
+
|
| 553 |
+
08
|
| 554 |
+
|
| 555 |
+
09
|
| 556 |
+
|
| 557 |
+
10
|
| 558 |
+
|
| 559 |
+
Support for single and multi-stage applicant flows – make it
|
| 560 |
+
simpler to hire regardless of job complexity.
|
| 561 |
+
|
| 562 |
+
A candidate-first experience – cater to the people you want
|
| 563 |
+
most and build a consistent pipeline for top talent.
|
| 564 |
+
|
| 565 |
+
Empowered hiring managers – put the right information in the
|
| 566 |
+
hands of decisions makers.
|
| 567 |
+
|
| 568 |
+
A smooth transition from candidate to employee – get new
|
| 569 |
+
employees up and running faster, saving time and costs.
|
| 570 |
+
|
| 571 |
+
Full visibility through analytics – make data-driven hiring
|
| 572 |
+
decisions and track candidates from start to finish.
|
| 573 |
+
|
| 574 |
+
01
|
| 575 |
+
|
| 576 |
+
02
|
| 577 |
+
|
| 578 |
+
03
|
| 579 |
+
|
| 580 |
+
04
|
| 581 |
+
|
| 582 |
+
05
|
| 583 |
+
|
| 584 |
+
11
|
| 585 |
+
|
| 586 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.Find and Keep
|
| 587 |
+
the Talent You Need
|
| 588 |
+
|
| 589 |
+
Finding the right talent is key to growing your business. A major part of recruiting
|
| 590 |
+
success is the tools you use. Simplifying your data by replacing disparate, on-
|
| 591 |
+
premise systems with a unified, cloud-based HR system that provides real-time
|
| 592 |
+
data is a great start.
|
| 593 |
+
|
| 594 |
+
Our certified SAP SuccessFactors professionals can help you master your new
|
| 595 |
+
recruiting system. But most importantly, we help you align that system to your
|
| 596 |
+
overall HR strategy and your company culture. Our goal is to help you transform
|
| 597 |
+
your business so you can find and attract great talent.
|
| 598 |
+
|
| 599 |
+
Contact us today to find out how we can help you deliver a recruiting
|
| 600 |
+
solution designed to let your organization’s recruiting efforts thrive.
|
| 601 |
+
|
| 602 |
+
12
|
| 603 |
+
|
| 604 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved. This document is provided for information purposes
|
| 605 |
+
only, and the contents are subject to change without notice. This document is not warranted to be error-free, nor subject to
|
| 606 |
+
any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions
|
| 607 |
+
of merchantability or fitness for a particular purpose. We specifically disclaim any liability with respect to this document, and
|
| 608 |
+
no contractual obligations are formed either directly or indirectly by this document. This document may not be reproduced
|
| 609 |
+
or transmitted in any form or by any means, electronic or mechanical, for any purpose, without our prior written permission.
|
| 610 |
+
Rizing, Rizing HCM, and other Rizing products and services mentioned herein as well as their respective logos are trademarks
|
| 611 |
+
or registered trademarks of Rizing LLC or a Rizing affiliate company in the United States and other countries. All other product
|
| 612 |
+
and service names mentioned are the trademarks of their respective companies.
|
| 613 |
+
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|
q106/random_k2/random_2.md
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
q106/random_k4/question.json
CHANGED
|
@@ -17,10 +17,10 @@
|
|
| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
"a5879805d70c854ea4361e43a84e3bb2.pdf",
|
| 20 |
-
"
|
| 21 |
-
"
|
| 22 |
-
"
|
| 23 |
-
"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
|
|
|
|
| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
"a5879805d70c854ea4361e43a84e3bb2.pdf",
|
| 20 |
+
"web_88f0578d817bd13f.pdf",
|
| 21 |
+
"web_43df7d1ce2cae9ac.pdf",
|
| 22 |
+
"web_7bed9c57d39865f1.pdf",
|
| 23 |
+
"resize_r1_11.pdf"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
|
q106/random_k4/random_1.md
CHANGED
|
@@ -1,944 +1,613 @@
|
|
| 1 |
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| 563 |
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| 566 |
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| 571 |
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| 578 |
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| 582 |
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| 583 |
-
|
| 584 |
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|
| 585 |
-
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| 586 |
-
|
| 587 |
-
|
| 588 |
-
|
| 589 |
-
|
| 590 |
-
|
| 591 |
-
|
| 592 |
-
|
| 593 |
-
|
| 594 |
-
|
| 595 |
-
|
| 596 |
-
|
| 597 |
-
|
| 598 |
-
|
| 599 |
-
|
| 600 |
-
|
| 601 |
-
|
| 602 |
-
|
| 603 |
-
|
| 604 |
-
|
| 605 |
-
|
| 606 |
-
|
| 607 |
-
|
| 608 |
-
|
| 609 |
-
|
| 610 |
-
|
| 611 |
-
|
| 612 |
-
|
| 613 |
-
|
| 614 |
-
Administration & Other Expenses
|
| 615 |
-
| | | | 14660 | 15116 |
|
| 616 |
-
| --- | --- | --- | ----- | ----- |
|
| 617 |
-
Advertisement Exp
|
| 618 |
-
| Salary & Other Benefits | | | 1775 | 2069 |
|
| 619 |
-
| ----------------------- | --- | --- | ---- | ---- |
|
| 620 |
-
Pa'ymerrt \o Auditors
|
| 621 |
-
Audit Fees
|
| 622 |
-
5510
|
| 623 |
-
| | Taxation Fees | 7500 | 13010 | 12900 |
|
| 624 |
-
| --------------------- | ------------- | ---- | ----- | ----- |
|
| 625 |
-
| Professional Charges | | | 30535 | 34083 |
|
| 626 |
-
| Listing Fees | | | 1QGGG | 1000G |
|
| 627 |
-
| Printing & Stationary | | | | 540 |
|
| 628 |
-
1134
|
| 629 |
-
| Office Rent | | | 6000 | 6000 |
|
| 630 |
-
| -------------------------------- | --- | --- | ----- | ----- |
|
| 631 |
-
| Donation' | | | 1000 | 0 |
|
| 632 |
-
| Rep . 4. Main.tan.ce of Computer | | | 0 | 667 |
|
| 633 |
-
| Miscellenous Expenses | | | 6635 | 8730 |
|
| 634 |
-
| | | | 84749 | S0105 |
|
| 635 |
-
SCHEDULE K
|
| 636 |
-
Interest Paid
|
| 637 |
-
| Interest Paid to Others | | | 702 | 2502 |
|
| 638 |
-
| ------------------------------------- | --- | --- | ----- | ---- |
|
| 639 |
-
| interest Paid against Bank Loan - FDR | | | 42739 | 0 |
|
| 640 |
-
| | | | 43441 | 2502 |
|
| 641 |
-
|
| 642 |
-
FRONTIER LEASING & FINANCE LTD.
|
| 643 |
-
SCHEDULE - L : NOTES ON ACCOUNTS.
|
| 644 |
-
1. Significant Accounting Policies :-
|
| 645 |
-
The financial statements are prepared under the historical cost convention, on an accrual
|
| 646 |
-
basis and in accordance with the applicable accounting standards.
|
| 647 |
-
1.1) Fixed Assets:-
|
| 648 |
-
Fixed Assets are stated at cost, less accumulated depreciation. Cost comprises
|
| 649 |
-
the purchase price and any attributable cost of bringing the asset to its working
|
| 650 |
-
condition for its intended use.
|
| 651 |
-
1.2) Depreciation :-
|
| 652 |
-
Depreciation on Fixed Assets is provided on Written Down Method at the rates
|
| 653 |
-
and in the manner specified in the Schedule XIV of the Companies Act, 1956.
|
| 654 |
-
1.3) Investments :-
|
| 655 |
-
Long Term Investments are stated at cost.
|
| 656 |
-
1.4) Revenue Recognition :
|
| 657 |
-
Interest is recorded on time basis. Dividend income on investments is accounted
|
| 658 |
-
for when the right to receive the payment is established.
|
| 659 |
-
1.5) Taxation :-
|
| 660 |
-
The provision for Current Tax is determined on the basis of taxable income for the
|
| 661 |
-
current accounting year in accordance with the Income Tax Act, 1961.
|
| 662 |
-
The Deferred Tax is recognised, considering the prudence, on timing difference
|
| 663 |
-
that originate in one period and capable of reversal in subsequent period.
|
| 664 |
-
Deferred tax assets are recognised on Long Term Capital ioss on the basis of
|
| 665 |
-
reasonable certainty that such deferred tax asset can be realised against future
|
| 666 |
-
taxable Long Term Capital Gain.
|
| 667 |
-
Deferred tax Liability recognised in earlier year on difference between Book
|
| 668 |
-
depredation and depreciation under Income Tax Act 1961 is reversed to the extent
|
| 669 |
-
of realization.
|
| 670 |
-
1.6) Retirement Benefits :-
|
| 671 |
-
The Gratuity liability is provided on cash basis.
|
| 672 |
-
1 7) Segment Information :-
|
| 673 |
-
Since the company is dealing in only one segment, i.e. financing, there is no
|
| 674 |
-
reportable segment as per AS-17 on "Segment Reporting" issued by Institute of
|
| 675 |
-
Chartered Accountant of India.
|
| 676 |
-
|
| 677 |
-
2. Contingent Liability not provided for
|
| 678 |
-
| | | | As on | As on | | |
|
| 679 |
-
| --- | --- | --- | -------- | ------- | --- | --- |
|
| 680 |
-
| | | | 31.3.05 | 31.3.04 | | |
|
| 681 |
-
Estimated amount of contracts remaining
|
| 682 |
-
to be executed on capital account and
|
| 683 |
-
| | not provided for | | Nil | Nil | | |
|
| 684 |
-
| --- | ----------------------------------- | --- | -------- | ------- | --- | --- |
|
| 685 |
-
| | | | As on | As on | | |
|
| 686 |
-
| | | | 31.3.05 | 31.3.04 | | |
|
| 687 |
-
| 3. | a) Expenditure in Foreign Currency | | Nii | | Nii | |
|
| 688 |
-
b) Amount remitted during the year in
|
| 689 |
-
| | Foreign Currency on account & Divided | | Nil | | Nil | |
|
| 690 |
-
| --- | -------------------------------------- | --- | ---- | --- | --- | --- |
|
| 691 |
-
| | c) Earning in Foreign Exchange | | Nil | | Nil | |
|
| 692 |
-
4 Other information pursuant to paragraph 3,4C, 4D of Part II of Schedule VI of the
|
| 693 |
-
Companies Act, 1956 are not applicable.
|
| 694 |
-
5 Payment made to Auditors :
|
| 695 |
-
| | | | As on | As on | | |
|
| 696 |
-
| --- | --- | --- | ------- | ------- | --- | --- |
|
| 697 |
-
| | | | 31.3.05 | 31.3.04 | | |
|
| 698 |
-
| | | | 5000 | 5000 | | |
|
| 699 |
-
a) As Audit Fees
|
| 700 |
-
| | b) Other Matters | | 7500 | 7500 | | |
|
| 701 |
-
| --- | ---------------- | --- | ---- | ---- | --- | --- |
|
| 702 |
-
400
|
| 703 |
-
| | c) Service Tax | | 510 | | | |
|
| 704 |
-
| --- | -------------- | --- | ----- | ----- | --- | --- |
|
| 705 |
-
| | | | 13010 | 12900 | | |
|
| 706 |
-
6 The basic earning per share is computed by dividing the net profit attributable to the equity
|
| 707 |
-
shareholders for the year by the weighted average number of equity shares outstanding
|
| 708 |
-
during the year. As there is no presence of diiutive potential equity shares, the diluted EPS
|
| 709 |
-
is same as basis EPS as follows :
|
| 710 |
-
| | | | | | As on | As on |
|
| 711 |
-
| --- | --- | ---------------------------------------- | --- | ----------- | ------- | ---------- |
|
| 712 |
-
| | | | | 31/03/2005 | | 31/03/2004 |
|
| 713 |
-
| | | Profit after Tax | | | 168679 | 99375 |
|
| 714 |
-
| | | Add : Excess /(Short) Provision for Tax | | | 235 | 847 |
|
| 715 |
-
| | | Less: Transfer to Statutory Reserve | | | 34000 | 20000 |
|
| 716 |
-
Net Profit attributable to Equity Shareholders 134914 80222
|
| 717 |
-
| | | Weighted average number of shares | | 245000 | | 245000 |
|
| 718 |
-
| --- | --- | ---------------------------------- | --- | ------- | --- | ------ |
|
| 719 |
-
Earning per share
|
| 720 |
-
| | | Basic & Diluted | | | 0.55 | 0.33 |
|
| 721 |
-
| --- | --- | ---------------- | --- | --- | ----- | ---- |
|
| 722 |
-
|
| 723 |
-
7. Deferred Tax :-
|
| 724 |
-
5.1) Net Deferred Tax income for the year is Rs. 3522 and the same has been charged to
|
| 725 |
-
the Profit and Loss Account.
|
| 726 |
-
6.2) The break-up of deferred tax assets and fiabifities are as foilows :
|
| 727 |
-
| | As on | As on |
|
| 728 |
-
| --- | -------- | -------- |
|
| 729 |
-
| | 31.03.05 | 31.03.04 |
|
| 730 |
-
Deferred Tax Assets
|
| 731 |
-
| On Long Term Capital Loss of Prev.Years | 233 | 160347 |
|
| 732 |
-
| --------------------------------------- | ----- | ------ |
|
| 733 |
-
| Measured @ 20.91% (20.50%) | 33761 | 32871 |
|
| 734 |
-
Deferred Tax Liability
|
| 735 |
-
Difference between Book Value of
|
| 736 |
-
depreciable assets and WDV for Tax
|
| 737 |
-
| purposes. | (2914) | 38562 |
|
| 738 |
-
| ----------------------------- | ------ | ------ |
|
| 739 |
-
| Measured @ 36.60% (35.87%) | 11200 | 13832 |
|
| 740 |
-
| Net Deferred Tax Liabilities. | 22561 | 190391 |
|
| 741 |
-
6. Refated Party Transaction (AS-18)
|
| 742 |
-
a) List of Related Parties and Relationships.
|
| 743 |
-
The following is the information on transactions with the related parties:
|
| 744 |
-
Name Relationship
|
| 745 |
-
Key Management Personnel:- Kawaljit S. Chawla Whole Time Director
|
| 746 |
-
Ramnath Choudhary Whole Time Director
|
| 747 |
-
Vasudev R.Yadav Whole Time Director
|
| 748 |
-
b) Relatives of Key Management Personnel >
|
| 749 |
-
Relationship
|
| 750 |
-
Name
|
| 751 |
-
| Jeet Machines Tools Ltd | Father of Director is director in | |
|
| 752 |
-
| ----------------------- | --------------------------------- | --- |
|
| 753 |
-
the said Company
|
| 754 |
-
c) Refated Party Transactions : Relatives of Key Management
|
| 755 |
-
Personnel
|
| 756 |
-
Interest Paid Rs. 702/-
|
| 757 |
-
9. There are no amounts due to any enterprise which is small scale and ancillary
|
| 758 |
-
undertaking, for more than 30 days
|
| 759 |
-
10 Previous year figures are regrouped or rearranged wherever necessary
|
| 760 |
-
|
| 761 |
-
11. BALANCE SHEET ABSTRACT AND COMPANY'S GENERAL BUSINESS PROFILE
|
| 762 |
-
I REGISTRATION DETAILS
|
| 763 |
-
| Registration No | | | 33328 | |
|
| 764 |
-
| ------------------ | --- | --- | ---------- | --- |
|
| 765 |
-
| State Code | No | | 11 | |
|
| 766 |
-
| Balance Sheet Date | | | 31.03.2005 | |
|
| 767 |
-
II CAPITAL RAISED DURING THE YEAR
|
| 768 |
-
| Public Issue | | | : Nil | |
|
| 769 |
-
| ------------------ | ---------------- | --- | --------------- | --------- |
|
| 770 |
-
| Riujrt | Issue | | •. Nil | |
|
| 771 |
-
| Bonus Issue | | | : Nil | |
|
| 772 |
-
| Private Placement | | | : Nil | |
|
| 773 |
-
| HI POSITION | OF MOBILIZATION | | AND DEPLOYMENT | OF FUNDS |
|
| 774 |
-
(Amounts in Rupees Thousands )
|
| 775 |
-
| | Total Liabilities | | . 5046 | |
|
| 776 |
-
| --- | ------------------ | --- | ------- | --- |
|
| 777 |
-
| | Total Assets | | : 5046 | |
|
| 778 |
-
SOURCE OF FUND
|
| 779 |
-
| | Paid up Capital | | : 2450 | |
|
| 780 |
-
| --- | ----------------- | --- | ------- | --- |
|
| 781 |
-
| | Reserve & Surplus | | 2585 | |
|
| 782 |
-
| | Secured Loan | | Nil | |
|
| 783 |
-
| | Unsecured Loan | | 11 | |
|
| 784 |
-
APPLICATION OF FUNDS
|
| 785 |
-
| | Net Fixed Assets | | : 32 | |
|
| 786 |
-
| --- | ------------------- | ------ | ------- | --- |
|
| 787 |
-
| | Investments | | : 802 | |
|
| 788 |
-
| | NeV Current Assets | | . 4189 | |
|
| 789 |
-
| | Misc. Expenditure | | : Nil | |
|
| 790 |
-
| | Accumulated | Losses | : Nil | |
|
| 791 |
-
| | Deterred Tax Assets | | : 23 | |
|
| 792 |
-
IV PERFORMANCE OF THE COMPANY(Anw>unts in Rupees Thousands)
|
| 793 |
-
| Turnover | | | : 348 | |
|
| 794 |
-
| -------------------------- | --- | --- | ------- | --- |
|
| 795 |
-
| Total Expenditure | | | : 137 | |
|
| 796 |
-
| Profit Before Tax | | | ; 211 | |
|
| 797 |
-
| Profit After Tax | | | : 169 | |
|
| 798 |
-
| Earning Per Shares (In Rs) | | | : 0.55 | |
|
| 799 |
-
| Dividend | | | : Nil | |
|
| 800 |
-
|
| 801 |
-
V. GENERIC NAMES OF THREE PRINCIPAL PRODUCTS / SERVICES OF COMPANY
|
| 802 |
-
(As per monetary term)
|
| 803 |
-
Item Code No. (ITC CODE ) : NA
|
| 804 |
-
Product Description : Finance & Investment.
|
| 805 |
-
As per report of even date
|
| 806 |
-
FOR J.S. BHATIA & CO. For and on behvAf of th« Board.
|
| 807 |
-
CHARTERED ACCOUNTANT.
|
| 808 |
-
KAWALJIT SINGH CHAWLA
|
| 809 |
-
J.S. BHATrA VASUDEVR. VADAV
|
| 810 |
-
PROPRIETOR
|
| 811 |
-
DIRECTORS.
|
| 812 |
-
Place : Mumbai Place : Mumbai
|
| 813 |
-
Date : 25* August 2005 Date : 25* August 2005
|
| 814 |
-
|
| 815 |
-
FRONTIER LEASING & FINANCE LTD.
|
| 816 |
-
CASHFLOW STATEMENT FOR THE YEAR ENDED MARCH 31.2008
|
| 817 |
-
Amount m Rupees
|
| 818 |
-
| | 31/03/2005 | 31/03/2004 |
|
| 819 |
-
| --- | ----------- | ---------- |
|
| 820 |
-
I CASH FLOW FROM OPERATING ACTIVITIES
|
| 821 |
-
Net Profit before Tax & Extraordinary items 211.157.00 154.506.00
|
| 822 |
-
Add / (Less): Adjustments for
|
| 823 |
-
| Dividend income | (20000) | (200.00) |
|
| 824 |
-
| ------------------------------------ | ------------ | ----------- |
|
| 825 |
-
| Depreciation | 9,096.00 | 13,497.00 |
|
| 826 |
-
| ( Profit y loss on fixed Assets sold | 0.00 | (28,771.00) |
|
| 827 |
-
| | (132.436.00) | 0.00 |
|
| 828 |
-
(Profit) /-Loss on Sale of Investment
|
| 829 |
-
| Demat & Brokerage charges | 652.00 | 0.00 |
|
| 830 |
-
| ------------------------- | ------ | ---- |
|
| 831 |
-
Increase / (Decrease) in Trade & Other Payable (3,869.00) 10,190.00
|
| 832 |
-
| Direct taxes paid | (44.676.00) | (62.971.00) |
|
| 833 |
-
| ----------------- | ----------- | ----------- |
|
| 834 |
-
(Increase)/ Decrease in Trade & Other Receivable (643,302.00) (90.602.00)
|
| 835 |
-
CASH FLOW FROM OPERATING ACTIVITIES -1 (603.578.00) (4.351.00)
|
| 836 |
-
II CASH FLOW FROM INVESTING ACTIVITIES
|
| 837 |
-
| (Purchase) / sate of Fixed Assets | 0.00 | 41,525.00 |
|
| 838 |
-
| --------------------------------- | ---- | --------- |
|
| 839 |
-
(Purchase V Sale of Investments (Net of Pur.&Saies) (19,825.00) 0.00
|
| 840 |
-
| | 523.811.00 | 0.00 |
|
| 841 |
-
| --- | ---------- | ---- |
|
| 842 |
-
(Increase)/ Decrease in Loans & Advances
|
| 843 |
-
| Profit on Sale of Investments | 132,436.00 | 0.00 |
|
| 844 |
-
| -------------------------------------- | ---------- | --------- |
|
| 845 |
-
| Dividend received | 200.00 | 200.00 |
|
| 846 |
-
| NET CASH FROM INVESTING ACTIVITIES - R | 636,622.00 | 41.725.00 |
|
| 847 |
-
III CASH FLOW FROM FINANCING ACTIVITIES
|
| 848 |
-
| Demat & Brokerage charges | (652.00) | 0.00 |
|
| 849 |
-
| -------------------------------------- | -------- | ----------- |
|
| 850 |
-
| Proceeds / (Repayment) from borrowings | 702.00 | (32,044.00) |
|
| 851 |
-
| | 50.00 | (32,044.00) |
|
| 852 |
-
NET CASH FROM FINANCING ACTIVITIES • •
|
| 853 |
-
| NET INCREASE/(DECREASE) IN CASH ( | 33,094.00 | 5,330.00 |
|
| 854 |
-
| --------------------------------- | --------- | -------- |
|
| 855 |
-
OPENING BALANCE OF CASH & CASH EQUIVALENT 17,997.00 12,667 00
|
| 856 |
-
CLOSING BALANCE OF CASH & CASH EQUIVALENT 51.091.00 17,997.00
|
| 857 |
-
Notes 1) Cash and cash equivatents consists of cash on hand and balances with bank
|
| 858 |
-
2) Figures in brackets represents outflow of cash
|
| 859 |
-
3) Figures for the last year have been regrouped, wherever considered necessary
|
| 860 |
-
Per our report of even date
|
| 861 |
-
FOR J. S. BHATIA & CO. For and on behalf of the board
|
| 862 |
-
Chartered accountants
|
| 863 |
-
J. S. BHATIA KAWAUIT SINGH CHAWLA
|
| 864 |
-
PROPRIETOR
|
| 865 |
-
PLACE : MUMBAI
|
| 866 |
-
DATED : 25.08.2005
|
| 867 |
-
|
| 868 |
-
| T | Q R H | A T fA Jte | fV"fc | | 14A15, Ashoka Centre, |
|
| 869 |
-
| ---------- | --------- | ------------ | ------ | --- | ------------------------------ |
|
| 870 |
-
| J. b. | BHATIA & | | CO. | | 2nd Floor, LotonanyaTllakMaiB, |
|
| 871 |
-
| CHARTERED | | ACCOUNTANTS | | | Mumbal-400001. |
|
| 872 |
-
Tel.: Office: 2267 5066 / 2267 5067
|
| 873 |
-
Fax: 2269 2994
|
| 874 |
-
Rest.: 2620 2207 / 2620 3849
|
| 875 |
-
E-mail: jaipalsb6)bom3.vsnl.net.in
|
| 876 |
-
AUDITOR'S CERTIFICATE
|
| 877 |
-
To,
|
| 878 |
-
The Board of Directors,
|
| 879 |
-
Frontier Leasing & Finance Limited.
|
| 880 |
-
We have examined the attached Cash Flow Statement of Frontier Leasing &
|
| 881 |
-
Finance Limited for the year ended 31st March 2005. The Statement has been
|
| 882 |
-
prepared by the Company in accordance with the requirements of clause 32 of
|
| 883 |
-
the listing agreement with various Stock Exchanges and is based on and in
|
| 884 |
-
agreement with the corresponding Profit & Loss Account and Balance Sheet of
|
| 885 |
-
the Company covered by our report of even date to the members of the
|
| 886 |
-
Company.
|
| 887 |
-
For J. S. BHATIA & CO.,
|
| 888 |
-
| | | | | CHARTERED | AC CO UNTANTS |
|
| 889 |
-
| --- | --------------- | -------------- | --- | ---------- | ------------- |
|
| 890 |
-
| | PLACE : MUMBAI | | | | J. S. BHATIA |
|
| 891 |
-
| | DATE | : T-^/dZ/xooS | | - | (PROPRIETOR) |
|
| 892 |
-
|
| 893 |
-
FRONTIER LEASING & FINANCE LIMITED.
|
| 894 |
-
Registered Office : C/o. Victory Printing Press, Jyoti Studio
|
| 895 |
-
Compound, KB.A Irani Bridge,
|
| 896 |
-
Mumbai - 400 007.
|
| 897 |
-
PLEASE COMPLETE THE ATTENDANCE SLIP AND HAND IT
|
| 898 |
-
OVER AT THE ENTRANCE OF THE MEETING HALL.
|
| 899 |
-
1. Name of the Shareholder.
|
| 900 |
-
(In Block Letters)
|
| 901 |
-
2. Ledger Folio Number.
|
| 902 |
-
3. Name of the Proxy (In Block Letter) ,
|
| 903 |
-
(To be filled in only if the proxy attends instead of member)
|
| 904 |
-
4. No. of Shares held.
|
| 905 |
-
1 hereby record my presence at 21st Annual General Meeting of
|
| 906 |
-
the Company to be held on Thursday, 29th September 2005 at
|
| 907 |
-
C/o. Victory Printing Press, Jyoti Studio Compound, K.B» A Irani Bridge,
|
| 908 |
-
Mumbai - 400 007 at 3.00 p.m.
|
| 909 |
-
Signature of the Shareholder /Proxy
|
| 910 |
-
NOTES :
|
| 911 |
-
1. Shareholders/Proxy holders are requested to bring the attendance slip
|
| 912 |
-
with them when they come to the meeting. No attendance slip will be
|
| 913 |
-
issued at the time of meeting.
|
| 914 |
-
2. Shareholders who come to attend the meeting are requested to
|
| 915 |
-
bring their copies of Annual Report with them, as spare copies wQl
|
| 916 |
-
not available in the meeting.
|
| 917 |
-
|
| 918 |
-
FRONTIER LEASING & FINANCE LIMITED.
|
| 919 |
-
PROXY FORM
|
| 920 |
-
I/We
|
| 921 |
-
of being the Member/Members
|
| 922 |
-
of the named company hereby appoint
|
| 923 |
-
of or tailing
|
| 924 |
-
him
|
| 925 |
-
of or failmg
|
| 926 |
-
him
|
| 927 |
-
as / my proxy to vote for me / us on behalf at the 21 st Annual General Meeting of
|
| 928 |
-
the Company to beheld at3.00 p.m. on Thursday, 29th September 2005 and at
|
| 929 |
-
any adjournment thereof.
|
| 930 |
-
Ledger Folio No
|
| 931 |
-
No. of Shares held
|
| 932 |
-
: Affix :
|
| 933 |
-
: Revenue
|
| 934 |
-
: Stamp
|
| 935 |
-
Signature
|
| 936 |
-
Date
|
| 937 |
-
NOTES :
|
| 938 |
-
(a) The form should be signed across the stamp as per specimen signature
|
| 939 |
-
registered with the Company.
|
| 940 |
-
(b) The Companies Act, 1956 fays down that the instrument appointing a,
|
| 941 |
-
proxy shaft be deposited at the Registered Office of the Company
|
| 942 |
-
not less than FOURTY EIGHT HOURS before the time fixed for
|
| 943 |
-
holding the meeting.
|
| 944 |
-
(c) A Proxy need not be a Member.
|
|
|
|
| 1 |
+
The Step-by-Step Guide
|
| 2 |
+
to Recruiting Top Talent
|
| 3 |
+
|
| 4 |
+
Your blueprint to transform your talent acquisition practices
|
| 5 |
+
to attract the people you need.
|
| 6 |
+
|
| 7 |
+
Table of Contents
|
| 8 |
+
|
| 9 |
+
01
|
| 10 |
+
|
| 11 |
+
The Race for Talent
|
| 12 |
+
|
| 13 |
+
02
|
| 14 |
+
|
| 15 |
+
Does Your Talent Acquisition
|
| 16 |
+
Process Need a Tune-up?
|
| 17 |
+
|
| 18 |
+
03
|
| 19 |
+
|
| 20 |
+
5 Factors That Affect Your Talent
|
| 21 |
+
Acquisition Efforts
|
| 22 |
+
|
| 23 |
+
04
|
| 24 |
+
|
| 25 |
+
The Step-by-Step Guide to
|
| 26 |
+
Recruiting Top Candidates
|
| 27 |
+
|
| 28 |
+
page 3
|
| 29 |
+
|
| 30 |
+
page 4
|
| 31 |
+
|
| 32 |
+
page 5
|
| 33 |
+
|
| 34 |
+
page 7
|
| 35 |
+
|
| 36 |
+
BONUS
|
| 37 |
+
|
| 38 |
+
05
|
| 39 |
+
|
| 40 |
+
10 Must-Haves of a Great
|
| 41 |
+
Recruitment Management System
|
| 42 |
+
page 11
|
| 43 |
+
|
| 44 |
+
06
|
| 45 |
+
|
| 46 |
+
Find and Keep
|
| 47 |
+
the Talent You Need
|
| 48 |
+
|
| 49 |
+
page 12
|
| 50 |
+
|
| 51 |
+
2
|
| 52 |
+
|
| 53 |
+
BOOKMARKS
|
| 54 |
+
Click on the title to to be
|
| 55 |
+
directed to that page.
|
| 56 |
+
|
| 57 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.The Race for Talent
|
| 58 |
+
|
| 59 |
+
01
|
| 60 |
+
|
| 61 |
+
It’s a job seeker’s market.
|
| 62 |
+
|
| 63 |
+
High employment rates, an aging workforce, and
|
| 64 |
+
skills gaps in both technical and soft skills have put
|
| 65 |
+
employees in the driver’s seat.
|
| 66 |
+
|
| 67 |
+
What this means for you is that you’re going to
|
| 68 |
+
have to fight harder than ever to recruit and retain
|
| 69 |
+
the people you need.
|
| 70 |
+
|
| 71 |
+
You’re going to have to leverage technology, lean into
|
| 72 |
+
your values, improve your employer branding, and in
|
| 73 |
+
some cases take a sledgehammer to your current talent
|
| 74 |
+
acquisition strategies to create engaging and responsive
|
| 75 |
+
recruitment experiences that not only attract candidates
|
| 76 |
+
to your company but compel them to choose you over
|
| 77 |
+
the competition.
|
| 78 |
+
|
| 79 |
+
It can be a daunting task… but we’ve got you covered
|
| 80 |
+
-as HCM consultants and SAP® SuccessFactors®
|
| 81 |
+
specialists, we’ve helped countless businesses do
|
| 82 |
+
exactly this.
|
| 83 |
+
|
| 84 |
+
This eBook is the first step in the process. It includes the
|
| 85 |
+
step-by-step guide to recruiting the best talent. Use it to
|
| 86 |
+
evaluate where you stand and build a talent acquisition
|
| 87 |
+
process that gives you the workforce you need for a
|
| 88 |
+
successful future.
|
| 89 |
+
|
| 90 |
+
Let’s get started.
|
| 91 |
+
|
| 92 |
+
An overwhelming
|
| 93 |
+
majority of candidates
|
| 94 |
+
(69%) refuse to
|
| 95 |
+
re-apply to a company
|
| 96 |
+
if they have a poor
|
| 97 |
+
experience during the
|
| 98 |
+
application process.
|
| 99 |
+
|
| 100 |
+
3
|
| 101 |
+
|
| 102 |
+
1 2016 Talent Board NAM CandE Research Report FINAL 170202.pdf
|
| 103 |
+
link: http://www.thetalentboard.org/wp-content/uploads/2017/02/2016_Talent_Board_NAM_Can-
|
| 104 |
+
|
| 105 |
+
dE_Research_Report_FINAL_170202.pdf
|
| 106 |
+
|
| 107 |
+
69%© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.
|
| 108 |
+
Does Your Talent Acquisition
|
| 109 |
+
Process Need a Tune-up?
|
| 110 |
+
|
| 111 |
+
02
|
| 112 |
+
|
| 113 |
+
Let’s look under the hood at your talent acquisition strategy
|
| 114 |
+
and see what’s really there. Here are five key questions that
|
| 115 |
+
you need to answer to identify the roadblocks between where
|
| 116 |
+
you are, and where you want to be.
|
| 117 |
+
|
| 118 |
+
01
|
| 119 |
+
|
| 120 |
+
02
|
| 121 |
+
|
| 122 |
+
03
|
| 123 |
+
|
| 124 |
+
04
|
| 125 |
+
|
| 126 |
+
05
|
| 127 |
+
|
| 128 |
+
Is your recruiting based on
|
| 129 |
+
current best practices?
|
| 130 |
+
|
| 131 |
+
Do you have buy-in
|
| 132 |
+
from your team?
|
| 133 |
+
|
| 134 |
+
Is your technology up to date
|
| 135 |
+
and fully cloud capable?
|
| 136 |
+
|
| 137 |
+
HR trends are evolving more
|
| 138 |
+
rapidly now than ever before.
|
| 139 |
+
Make sure you’re not falling
|
| 140 |
+
behind the competition when
|
| 141 |
+
it comes to implementing best
|
| 142 |
+
practices.
|
| 143 |
+
|
| 144 |
+
Is your team aligned internally?
|
| 145 |
+
Do they share a common lens?
|
| 146 |
+
Great candidate experiences
|
| 147 |
+
depend on the interactions
|
| 148 |
+
candidates have with your
|
| 149 |
+
team during the various stages
|
| 150 |
+
of the acquisition process.
|
| 151 |
+
Buy-in from your team is vital.
|
| 152 |
+
|
| 153 |
+
If you haven’t moved to the
|
| 154 |
+
cloud yet, it is never too late.
|
| 155 |
+
If you’ve migrated but aren’t
|
| 156 |
+
satisfied with your current
|
| 157 |
+
system, it can be salvaged.
|
| 158 |
+
The right tech really does
|
| 159 |
+
make a difference.
|
| 160 |
+
|
| 161 |
+
Are you always looking
|
| 162 |
+
for ways to innovate your
|
| 163 |
+
recruiting approach?
|
| 164 |
+
|
| 165 |
+
Is your recruitment
|
| 166 |
+
management system (RCM)
|
| 167 |
+
making your job easier?
|
| 168 |
+
|
| 169 |
+
Technology is playing an
|
| 170 |
+
increasingly crucial role in the
|
| 171 |
+
talent acquisition process. You
|
| 172 |
+
need to always have an eye on
|
| 173 |
+
the horizon, ear to the ground,
|
| 174 |
+
and willingness to adapt
|
| 175 |
+
and innovate your approach.
|
| 176 |
+
Remember: good ideas can
|
| 177 |
+
come from anywhere.
|
| 178 |
+
|
| 179 |
+
The right tools should help
|
| 180 |
+
to increase efficiency. But
|
| 181 |
+
sometimes, the tool itself
|
| 182 |
+
sucks up your time. And that’s
|
| 183 |
+
frustrating. Make sure your
|
| 184 |
+
system and processes make
|
| 185 |
+
your job easier. That’s the most
|
| 186 |
+
valuable success metric.
|
| 187 |
+
|
| 188 |
+
4
|
| 189 |
+
|
| 190 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.5 Factors That Affect
|
| 191 |
+
Your Talent Acquisition Efforts
|
| 192 |
+
|
| 193 |
+
03
|
| 194 |
+
|
| 195 |
+
The first step to building an effective acquisition strategy is to know
|
| 196 |
+
what internal and external factors affect your recruitment efforts.
|
| 197 |
+
|
| 198 |
+
Based on our experience and a study of current market conditions, here’s
|
| 199 |
+
5 factors that you need to be aware of when building your strategy.
|
| 200 |
+
|
| 201 |
+
You need to determine how you’ll adapt, counter, and respond to
|
| 202 |
+
each of these.
|
| 203 |
+
|
| 204 |
+
5
|
| 205 |
+
|
| 206 |
+
Continued on next page >
|
| 207 |
+
|
| 208 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.01
|
| 209 |
+
|
| 210 |
+
GROWING DEMAND &
|
| 211 |
+
DWINDLING SUPPLY
|
| 212 |
+
|
| 213 |
+
02
|
| 214 |
+
|
| 215 |
+
TURNOVER &
|
| 216 |
+
BURNOUT
|
| 217 |
+
|
| 218 |
+
03
|
| 219 |
+
|
| 220 |
+
INCONSISTENT
|
| 221 |
+
HIRING PROCESSES
|
| 222 |
+
|
| 223 |
+
04
|
| 224 |
+
|
| 225 |
+
INTENSE FOCUS ON
|
| 226 |
+
COST MANAGEMENT
|
| 227 |
+
|
| 228 |
+
05
|
| 229 |
+
|
| 230 |
+
EVOLVING
|
| 231 |
+
EXPECTATIONS
|
| 232 |
+
|
| 233 |
+
With just about every major
|
| 234 |
+
industry facing staffing
|
| 235 |
+
shortages, the candidates are
|
| 236 |
+
now in the driver’s seat with the
|
| 237 |
+
option of picking an employer
|
| 238 |
+
that responds to their needs
|
| 239 |
+
in a location of their choosing.
|
| 240 |
+
While talent acquisition and
|
| 241 |
+
human resources teams can’t
|
| 242 |
+
change the growing supply/
|
| 243 |
+
demand imbalance, they need
|
| 244 |
+
to be aware of how this affects
|
| 245 |
+
their acquisition strategy and
|
| 246 |
+
take active steps to attract
|
| 247 |
+
Gen X, Millennials, and
|
| 248 |
+
pretty soon Gen Z before the
|
| 249 |
+
competition does.
|
| 250 |
+
|
| 251 |
+
The staffing shortage also has
|
| 252 |
+
an adverse effect on current
|
| 253 |
+
professionals who have to
|
| 254 |
+
work longer hours leading to
|
| 255 |
+
burnout and turnover – which
|
| 256 |
+
leads to a dangerous loop of
|
| 257 |
+
an exhausted workforce, an
|
| 258 |
+
ever-growing pile of work, and
|
| 259 |
+
more turnover. Furthermore, an
|
| 260 |
+
organization with a reputation
|
| 261 |
+
for high turnover and burnout
|
| 262 |
+
creates additional challenges
|
| 263 |
+
for recruitment teams when it
|
| 264 |
+
comes to hiring the best talent.
|
| 265 |
+
|
| 266 |
+
Modern businesses often have
|
| 267 |
+
complex org charts, siloed
|
| 268 |
+
branches, and evolving parts.
|
| 269 |
+
This creates inconsistent hiring
|
| 270 |
+
processes that vary from
|
| 271 |
+
department to department,
|
| 272 |
+
region to region, and result in
|
| 273 |
+
poor candidate experiences
|
| 274 |
+
that negatively affect the
|
| 275 |
+
organization’s brand image.
|
| 276 |
+
While the HR team can’t
|
| 277 |
+
control everything, cloud-based
|
| 278 |
+
comprehensive talent solutions
|
| 279 |
+
such as SAP SuccessFactors can
|
| 280 |
+
help companies centralize their
|
| 281 |
+
processes and bring visibility to
|
| 282 |
+
internal teams and candidates.
|
| 283 |
+
|
| 284 |
+
Companies are always under
|
| 285 |
+
pressure to control costs. Up
|
| 286 |
+
against this mentality, HR
|
| 287 |
+
managers struggle to secure
|
| 288 |
+
funding for talent management
|
| 289 |
+
initiatives and, as a result,
|
| 290 |
+
end up using disparate, on
|
| 291 |
+
premise or outdated recruitment
|
| 292 |
+
technologies. This leads to error
|
| 293 |
+
prone processes due to the
|
| 294 |
+
doubling of data across systems,
|
| 295 |
+
labor intensive and slow hiring
|
| 296 |
+
steps, and a disconnected
|
| 297 |
+
candidate experience.
|
| 298 |
+
|
| 299 |
+
The largest generation in the
|
| 300 |
+
workforce today is tech-savvy
|
| 301 |
+
and socially aware Millennials.
|
| 302 |
+
As candidates, Millennials
|
| 303 |
+
look for companies that
|
| 304 |
+
align with their values, offer
|
| 305 |
+
training and development,
|
| 306 |
+
and deliver opportunities for
|
| 307 |
+
career growth. They expect
|
| 308 |
+
their future employers to
|
| 309 |
+
be digitally connected with
|
| 310 |
+
an intuitive website that
|
| 311 |
+
showcases its brand and
|
| 312 |
+
culture. They want a simple,
|
| 313 |
+
mobile friendly job application
|
| 314 |
+
process, transparent and timely
|
| 315 |
+
communication, and an active
|
| 316 |
+
social media presence so they
|
| 317 |
+
can interact with the company
|
| 318 |
+
during the hiring process.
|
| 319 |
+
|
| 320 |
+
6
|
| 321 |
+
|
| 322 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.The Step-by-Step Guide to
|
| 323 |
+
Recruiting Top Candidates
|
| 324 |
+
|
| 325 |
+
04
|
| 326 |
+
|
| 327 |
+
Building an amazing team is just as important as building a great
|
| 328 |
+
customer base. But, hiring the cream of the crop isn’t as easy as it
|
| 329 |
+
used to be. In the race for talent, the candidate experience matters
|
| 330 |
+
more now than ever before! This step-by-step guide is the blueprint
|
| 331 |
+
you need to transform your recruitment processes to meet the
|
| 332 |
+
expectations of a truly multigenerational digital workforce.
|
| 333 |
+
|
| 334 |
+
7
|
| 335 |
+
|
| 336 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.1
|
| 337 |
+
|
| 338 |
+
2
|
| 339 |
+
|
| 340 |
+
EVALUATE YOUR HIRING PROCESS
|
| 341 |
+
FROM START TO FINISH
|
| 342 |
+
|
| 343 |
+
Start by evaluating your current hiring process to make
|
| 344 |
+
sure you know what your candidate experience is
|
| 345 |
+
truly like - we would even go so far to suggest secret-
|
| 346 |
+
shopping the hiring process.
|
| 347 |
+
|
| 348 |
+
Next, storyboard your hiring process and map out
|
| 349 |
+
outcomes. The goal here is to plot the set of experiences
|
| 350 |
+
a candidate could have and optimize every step.
|
| 351 |
+
|
| 352 |
+
Use the data insights to create repeatable and
|
| 353 |
+
consistent hiring processes that offer positive
|
| 354 |
+
experiences.
|
| 355 |
+
|
| 356 |
+
Always make sure your hiring processes align
|
| 357 |
+
with and reflect your values and culture.
|
| 358 |
+
|
| 359 |
+
TIP
|
| 360 |
+
|
| 361 |
+
8
|
| 362 |
+
|
| 363 |
+
CREATE A STRONG, ATTRACTIVE
|
| 364 |
+
BRAND THAT SHOWS YOUR VALUE
|
| 365 |
+
TO TOP TALENT
|
| 366 |
+
|
| 367 |
+
Your brand is your most valuable asset, when it comes to
|
| 368 |
+
recruiting talent.
|
| 369 |
+
|
| 370 |
+
The first step in creating an attractive brand is developing
|
| 371 |
+
your Employee Value Proposition - a good EVP outlines
|
| 372 |
+
your organization’s mission and values and commitment
|
| 373 |
+
to employees.
|
| 374 |
+
|
| 375 |
+
Once you have your EVP, the next step is to make sure
|
| 376 |
+
your career site not only reflects but showcases your EVP
|
| 377 |
+
- much like the buyer’s journey, the hiring journey now
|
| 378 |
+
begins with an online search.
|
| 379 |
+
|
| 380 |
+
Lastly, make sure you have a strong content strategy
|
| 381 |
+
as it will help you build your brand identity and ensure
|
| 382 |
+
candidates find and connect with you online.
|
| 383 |
+
|
| 384 |
+
Great content is relevant, trendy, and
|
| 385 |
+
provides value. We find setting up an
|
| 386 |
+
editorial board helps ensure you’re regularly
|
| 387 |
+
and consistently posting good content.
|
| 388 |
+
|
| 389 |
+
TIP
|
| 390 |
+
|
| 391 |
+
Continued on next page >
|
| 392 |
+
|
| 393 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.< Continued from previous page
|
| 394 |
+
|
| 395 |
+
3
|
| 396 |
+
|
| 397 |
+
BUILD A TALENT PIPELINE AND NURTURE TALENT
|
| 398 |
+
|
| 399 |
+
There’s no such thing as “Just-in-Time Recruiting”.
|
| 400 |
+
|
| 401 |
+
Smart recruiters know the importance of building and nurturing a talent pipeline.
|
| 402 |
+
To build a strong pipeline:
|
| 403 |
+
|
| 404 |
+
01
|
| 405 |
+
|
| 406 |
+
02
|
| 407 |
+
|
| 408 |
+
Source talent globally
|
| 409 |
+
through an omni-channel
|
| 410 |
+
approach. Connect with and
|
| 411 |
+
reach out to candidates on
|
| 412 |
+
job boards, social platforms
|
| 413 |
+
and in-person events.
|
| 414 |
+
|
| 415 |
+
Create a network of
|
| 416 |
+
communities, content,
|
| 417 |
+
and contact points so that
|
| 418 |
+
you’re constantly nurturing
|
| 419 |
+
candidates and making sure
|
| 420 |
+
your brand is top of mind.
|
| 421 |
+
|
| 422 |
+
03
|
| 423 |
+
|
| 424 |
+
04
|
| 425 |
+
|
| 426 |
+
Make it simple for candidates
|
| 427 |
+
to get in touch and follow
|
| 428 |
+
up with HR by leveraging
|
| 429 |
+
automation, chatbots, and
|
| 430 |
+
other AI technology.
|
| 431 |
+
|
| 432 |
+
05
|
| 433 |
+
|
| 434 |
+
Use technology to track
|
| 435 |
+
candidate progress and
|
| 436 |
+
development benchmarks.
|
| 437 |
+
|
| 438 |
+
Take every opportunity
|
| 439 |
+
to share your culture and
|
| 440 |
+
events with candidates by
|
| 441 |
+
sharing different types of
|
| 442 |
+
company news and not just
|
| 443 |
+
job updates.
|
| 444 |
+
|
| 445 |
+
Encourage your
|
| 446 |
+
organization��s
|
| 447 |
+
leaders to be
|
| 448 |
+
active online,
|
| 449 |
+
sharing stories
|
| 450 |
+
and updates, and
|
| 451 |
+
engaging with
|
| 452 |
+
candidates.
|
| 453 |
+
|
| 454 |
+
TIP
|
| 455 |
+
|
| 456 |
+
9
|
| 457 |
+
|
| 458 |
+
Continued on next page >
|
| 459 |
+
|
| 460 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.< Continued from previous page
|
| 461 |
+
|
| 462 |
+
4
|
| 463 |
+
|
| 464 |
+
5
|
| 465 |
+
|
| 466 |
+
ENHANCE THE CANDIDATE EXPERIENCE
|
| 467 |
+
|
| 468 |
+
It’s time to end the candidate feedback black hole.
|
| 469 |
+
|
| 470 |
+
According to the 2016 North American Talent Board
|
| 471 |
+
Candidate Experience research report, 47 percent of
|
| 472 |
+
candidates never receive any communication up to two
|
| 473 |
+
months after applying for an open position!2
|
| 474 |
+
|
| 475 |
+
Give yourself an edge over the competition by
|
| 476 |
+
leveraging your RCM to not only keep your internal
|
| 477 |
+
team on the same page but also track and
|
| 478 |
+
communicate with candidates regularly.
|
| 479 |
+
|
| 480 |
+
Additionally, make sure your career site is always up to
|
| 481 |
+
date with current openings and that it showcases your
|
| 482 |
+
culture through employee testimonials.
|
| 483 |
+
|
| 484 |
+
CREATE AND SHARE
|
| 485 |
+
A CONSISTENT MESSAGE
|
| 486 |
+
|
| 487 |
+
The last step is less of a one-time only step and more so
|
| 488 |
+
an ongoing process.
|
| 489 |
+
|
| 490 |
+
Once you’ve evaluated, streamlined, and automated
|
| 491 |
+
your hiring processes, developed your EVP, and built
|
| 492 |
+
out your pipeline strategies, you need to make sure your
|
| 493 |
+
organization continues to create and share consistent
|
| 494 |
+
content and messages with your online and offline
|
| 495 |
+
communities.
|
| 496 |
+
|
| 497 |
+
Companies that constantly connect and engage passive
|
| 498 |
+
talent will have greater success at sourcing and hiring
|
| 499 |
+
top talent.
|
| 500 |
+
|
| 501 |
+
Don’t forget to make your application
|
| 502 |
+
process mobile friendly.
|
| 503 |
+
|
| 504 |
+
TIP
|
| 505 |
+
|
| 506 |
+
10
|
| 507 |
+
|
| 508 |
+
Tell your story. Engage your current
|
| 509 |
+
workforce and ask them to share
|
| 510 |
+
testimonials about what a job with your
|
| 511 |
+
organization is really like. Candidates are
|
| 512 |
+
attracted to authentic messages driven by
|
| 513 |
+
the workforce, not mandated by leadership.
|
| 514 |
+
|
| 515 |
+
TIP
|
| 516 |
+
|
| 517 |
+
2 2016 Talent Board NAM CandE Research Report FINAL 170202.pdf
|
| 518 |
+
link: http://www.thetalentboard.org/wp-content/uploads/2017/02/2016_
|
| 519 |
+
Talent_Board_NAM_CandE_Research_Report_FINAL_170202.pdf
|
| 520 |
+
|
| 521 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.BONUS
|
| 522 |
+
|
| 523 |
+
10 Must-Haves of a Great
|
| 524 |
+
Recruitment Management System
|
| 525 |
+
|
| 526 |
+
05
|
| 527 |
+
|
| 528 |
+
There’s no denying that technology has changed the talent acquisition process – But, how do you know if the
|
| 529 |
+
technology you’re currently using is delivering what you need to build a motivated, high performing workforce?
|
| 530 |
+
|
| 531 |
+
Use this cheat-sheet of the 10 must-haves to evaluate your system.
|
| 532 |
+
|
| 533 |
+
Seamless cloud integration – easily access candidate and
|
| 534 |
+
employee information from anywhere.
|
| 535 |
+
|
| 536 |
+
A simplified workflow for recruiters & HR – make the hiring
|
| 537 |
+
process easier for top talent and your HR team to navigate.
|
| 538 |
+
|
| 539 |
+
Standardized, optimized processes & communication –
|
| 540 |
+
with consistent processes in place, you’ll reduce error and
|
| 541 |
+
dramatically improve communications.
|
| 542 |
+
|
| 543 |
+
Omni-channel job distribution – advertise open positions
|
| 544 |
+
across sites and social channels to increase job exposure.
|
| 545 |
+
|
| 546 |
+
Customized, mobile-friendly landing pages & web portals –
|
| 547 |
+
make the hiring process faster and easier.
|
| 548 |
+
|
| 549 |
+
06
|
| 550 |
+
|
| 551 |
+
07
|
| 552 |
+
|
| 553 |
+
08
|
| 554 |
+
|
| 555 |
+
09
|
| 556 |
+
|
| 557 |
+
10
|
| 558 |
+
|
| 559 |
+
Support for single and multi-stage applicant flows – make it
|
| 560 |
+
simpler to hire regardless of job complexity.
|
| 561 |
+
|
| 562 |
+
A candidate-first experience – cater to the people you want
|
| 563 |
+
most and build a consistent pipeline for top talent.
|
| 564 |
+
|
| 565 |
+
Empowered hiring managers – put the right information in the
|
| 566 |
+
hands of decisions makers.
|
| 567 |
+
|
| 568 |
+
A smooth transition from candidate to employee – get new
|
| 569 |
+
employees up and running faster, saving time and costs.
|
| 570 |
+
|
| 571 |
+
Full visibility through analytics – make data-driven hiring
|
| 572 |
+
decisions and track candidates from start to finish.
|
| 573 |
+
|
| 574 |
+
01
|
| 575 |
+
|
| 576 |
+
02
|
| 577 |
+
|
| 578 |
+
03
|
| 579 |
+
|
| 580 |
+
04
|
| 581 |
+
|
| 582 |
+
05
|
| 583 |
+
|
| 584 |
+
11
|
| 585 |
+
|
| 586 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.Find and Keep
|
| 587 |
+
the Talent You Need
|
| 588 |
+
|
| 589 |
+
Finding the right talent is key to growing your business. A major part of recruiting
|
| 590 |
+
success is the tools you use. Simplifying your data by replacing disparate, on-
|
| 591 |
+
premise systems with a unified, cloud-based HR system that provides real-time
|
| 592 |
+
data is a great start.
|
| 593 |
+
|
| 594 |
+
Our certified SAP SuccessFactors professionals can help you master your new
|
| 595 |
+
recruiting system. But most importantly, we help you align that system to your
|
| 596 |
+
overall HR strategy and your company culture. Our goal is to help you transform
|
| 597 |
+
your business so you can find and attract great talent.
|
| 598 |
+
|
| 599 |
+
Contact us today to find out how we can help you deliver a recruiting
|
| 600 |
+
solution designed to let your organization’s recruiting efforts thrive.
|
| 601 |
+
|
| 602 |
+
12
|
| 603 |
+
|
| 604 |
+
© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved.© 2020 Rizing LLC or a Rizing LLC affiliate company. All rights reserved. This document is provided for information purposes
|
| 605 |
+
only, and the contents are subject to change without notice. This document is not warranted to be error-free, nor subject to
|
| 606 |
+
any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions
|
| 607 |
+
of merchantability or fitness for a particular purpose. We specifically disclaim any liability with respect to this document, and
|
| 608 |
+
no contractual obligations are formed either directly or indirectly by this document. This document may not be reproduced
|
| 609 |
+
or transmitted in any form or by any means, electronic or mechanical, for any purpose, without our prior written permission.
|
| 610 |
+
Rizing, Rizing HCM, and other Rizing products and services mentioned herein as well as their respective logos are trademarks
|
| 611 |
+
or registered trademarks of Rizing LLC or a Rizing affiliate company in the United States and other countries. All other product
|
| 612 |
+
and service names mentioned are the trademarks of their respective companies.
|
| 613 |
+
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q106/random_k4/random_2.md
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
q106/random_k4/random_3.md
CHANGED
|
@@ -1,685 +1,1318 @@
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-
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| 75 |
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| 78 |
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The world is online. A brand’s website, therefore, is one of its most important
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| 80 |
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marketing tools. Low website traffic can mean fewer customers and lower profits.
|
| 81 |
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| 82 |
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To combat this challenge, your social team should focus its goals on creating links
|
| 83 |
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| 84 |
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directly to the website (whether they’re from your own social posts or influencers’).
|
| 85 |
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| 86 |
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Link to useful content, subpages and company images to position your website
|
| 87 |
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| 88 |
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and your brand as a resource rather than just another cog in the corporate wheel.
|
| 89 |
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| 90 |
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This traffic should increase leads and, in the long run, revenues.
|
| 91 |
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02
|
| 93 |
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| 94 |
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Challenge: Decreasing customer retention
|
| 95 |
-
|
| 96 |
-
According to The Chartered Institute of Marketing, it costs four to ten times more
|
| 97 |
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|
| 98 |
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to acquire a customer than to retain one. To keep your customers around, use
|
| 99 |
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|
| 100 |
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social as a tool to support, communicate and engage. A good social relationship
|
| 101 |
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|
| 102 |
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with your customers should translate into a better perception and offline
|
| 103 |
-
|
| 104 |
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relationship with your brand. By developing a strong social bond, customers will
|
| 105 |
-
|
| 106 |
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be more likely to stick with your brand time and time again.
|
| 107 |
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|
| 108 |
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Challenge: Poor customer service
|
| 109 |
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|
| 110 |
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People turn to social to engage with businesses. Therefore, it is important for your
|
| 111 |
-
|
| 112 |
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brand to be ready to help customers on any channel they can contact you
|
| 113 |
-
|
| 114 |
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through. Arm your social media team with the materials, education and authority
|
| 115 |
-
|
| 116 |
-
to respond to customer questions and issues. When you do so, you’ll be equipped
|
| 117 |
-
|
| 118 |
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to respond to your customers in a timely and accurate way, regardless of how they
|
| 119 |
-
|
| 120 |
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reach out to you.
|
| 121 |
-
|
| 122 |
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Challenge: Weak brand awareness
|
| 123 |
-
|
| 124 |
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Social allows you to reach a broad audience. But honing and perfecting that
|
| 125 |
-
|
| 126 |
-
message takes brain power and time. To create authentic and lasting brand
|
| 127 |
-
|
| 128 |
-
awareness, avoid a slew of promotional messages; instead, focus on creating
|
| 129 |
-
|
| 130 |
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meaningful content and a strong brand personality through your social channels.
|
| 131 |
-
|
| 132 |
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Determine relevant hashtags and industry influencers you can engage with, and
|
| 133 |
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|
| 134 |
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tap into those resources to extend your brand’s overall awareness.
|
| 135 |
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|
| 136 |
-
What are your social media goals?
|
| 137 |
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|
| 138 |
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(cid:31) Increase brand awareness
|
| 139 |
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|
| 140 |
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(cid:31) Drive website traffic
|
| 141 |
-
|
| 142 |
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(cid:31) Improve customer
|
| 143 |
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service and retention
|
| 144 |
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|
| 145 |
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(cid:31) Gather quality leads
|
| 146 |
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|
| 147 |
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(cid:31) Source job candidates
|
| 148 |
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|
| 149 |
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03
|
| 150 |
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|
| 151 |
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02
|
| 152 |
-
Extend efforts throughout
|
| 153 |
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your organization
|
| 154 |
-
|
| 155 |
-
Social has long lived within the marketing department, but that doesn’t mean it
|
| 156 |
-
|
| 157 |
-
can’t (and shouldn’t) have a hand in nearly every business function, from human
|
| 158 |
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|
| 159 |
-
resources to research and development. To create a fully integrated social media
|
| 160 |
-
|
| 161 |
-
marketing campaign, you’ll need to involve and integrate multiple departments,
|
| 162 |
-
|
| 163 |
-
especially if your goals have a direct impact on them. Work with all your teams to
|
| 164 |
-
|
| 165 |
-
determine how you can best support their goals and what key performance
|
| 166 |
-
|
| 167 |
-
indicators are important to them (we’ve outlined some ideas on both below).
|
| 168 |
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|
| 169 |
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Sales
|
| 170 |
-
|
| 171 |
-
Social selling is a term that has grown in popularity since the rise of social
|
| 172 |
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|
| 173 |
-
marketing. By searching for sales opportunities and then engaging in a helpful
|
| 174 |
-
|
| 175 |
-
and authentic manner, social media can be a great way to prime the sales funnel
|
| 176 |
-
|
| 177 |
-
and find new leads.
|
| 178 |
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|
| 179 |
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04
|
| 180 |
-
|
| 181 |
-
Customer service
|
| 182 |
-
|
| 183 |
-
Social media is quickly becoming one of the most important channels through
|
| 184 |
-
|
| 185 |
-
which companies interact with their current customers. Social is an easy and very
|
| 186 |
-
|
| 187 |
-
public way for customers to air their grievances with your brand. If you aren’t
|
| 188 |
-
|
| 189 |
-
responding, it can hurt your reputation and customer relationship.
|
| 190 |
-
|
| 191 |
-
Building great relationships on social is about more than responding to
|
| 192 |
-
|
| 193 |
-
complaints. For example, Seamless does a wonderful job of Retweeting positive
|
| 194 |
-
|
| 195 |
-
posts from satisfied customers and regularly engaging with all kinds of mentions.
|
| 196 |
-
|
| 197 |
-
Human resources
|
| 198 |
-
|
| 199 |
-
While the HR team probably spends a good amount of its time on social media
|
| 200 |
-
|
| 201 |
-
looking through the profiles of applicants, it can also use social as a way to
|
| 202 |
-
|
| 203 |
-
increase overall application numbers. Showcase job postings on social media and
|
| 204 |
-
|
| 205 |
-
encourage your employees to share them to their networks as well. Beyond just
|
| 206 |
-
|
| 207 |
-
05
|
| 208 |
-
|
| 209 |
-
job postings, social is a useful tool in showcasing your company culture to the
|
| 210 |
-
|
| 211 |
-
world. Highlight some behind-the-scenes images of what it is like to work for your
|
| 212 |
-
|
| 213 |
-
company so you can improve the perception of your brand among candidates.
|
| 214 |
-
|
| 215 |
-
Research and Development
|
| 216 |
-
|
| 217 |
-
Your brand’s social audience represents a group that is highly engaged, invested
|
| 218 |
-
|
| 219 |
-
and interested in your product or service. Why not leverage that to serve as an
|
| 220 |
-
|
| 221 |
-
online focus group for your company? Asking for and listening to customer
|
| 222 |
-
|
| 223 |
-
feedback on social media is a nimble and easy way to get instant feedback.
|
| 224 |
-
|
| 225 |
-
Additionally, social media can help expose gaps in a product or service.
|
| 226 |
-
|
| 227 |
-
Marketing
|
| 228 |
-
|
| 229 |
-
The marketing department, specifically advertising and PR, traditionally has a
|
| 230 |
-
|
| 231 |
-
strong role in the social media strategy. But there are always new ways to ensure
|
| 232 |
-
|
| 233 |
-
people are aware of and excited about your brand through social. Whether you’re
|
| 234 |
-
|
| 235 |
-
debuting a product, ad campaign or initiative, ensure that social has a strong hand
|
| 236 |
-
|
| 237 |
-
in spreading the word.
|
| 238 |
-
|
| 239 |
-
Customer service
|
| 240 |
-
|
| 241 |
-
Social media is quickly becoming one of the most important channels through
|
| 242 |
-
|
| 243 |
-
which companies interact with their current customers. Social is an easy and very
|
| 244 |
-
|
| 245 |
-
public way for customers to air their grievances with your brand. If you aren’t
|
| 246 |
-
|
| 247 |
-
responding, it can hurt your reputation and customer relationship.
|
| 248 |
-
|
| 249 |
-
Building great relationships on social is about more than responding to
|
| 250 |
-
|
| 251 |
-
complaints. For example, Seamless does a wonderful job of Retweeting positive
|
| 252 |
-
|
| 253 |
-
posts from satisfied customers and regularly engaging with all kinds of mentions.
|
| 254 |
-
|
| 255 |
-
Human resources
|
| 256 |
-
|
| 257 |
-
While the HR team probably spends a good amount of its time on social media
|
| 258 |
-
|
| 259 |
-
looking through the profiles of applicants, it can also use social as a way to
|
| 260 |
-
|
| 261 |
-
increase overall application numbers. Showcase job postings on social media and
|
| 262 |
-
|
| 263 |
-
encourage your employees to share them to their networks as well. Beyond just
|
| 264 |
-
|
| 265 |
-
job postings, social is a useful tool in showcasing your company culture to the
|
| 266 |
-
|
| 267 |
-
world. Highlight some behind-the-scenes images of what it is like to work for your
|
| 268 |
-
|
| 269 |
-
company so you can improve the perception of your brand among candidates.
|
| 270 |
-
|
| 271 |
-
Research and Development
|
| 272 |
-
|
| 273 |
-
Your brand’s social audience represents a group that is highly engaged, invested
|
| 274 |
-
|
| 275 |
-
and interested in your product or service. Why not leverage that to serve as an
|
| 276 |
-
|
| 277 |
-
online focus group for your company? Asking for and listening to customer
|
| 278 |
-
|
| 279 |
-
feedback on social media is a nimble and easy way to get instant feedback.
|
| 280 |
-
|
| 281 |
-
Additionally, social media can help expose gaps in a product or service.
|
| 282 |
-
|
| 283 |
-
Marketing
|
| 284 |
-
|
| 285 |
-
The marketing department, specifically advertising and PR, traditionally has a
|
| 286 |
-
|
| 287 |
-
strong role in the social media strategy. But there are always new ways to ensure
|
| 288 |
-
|
| 289 |
-
people are aware of and excited about your brand through social. Whether you’re
|
| 290 |
-
|
| 291 |
-
debuting a product, ad campaign or initiative, ensure that social has a strong hand
|
| 292 |
-
|
| 293 |
-
in spreading the word.
|
| 294 |
-
|
| 295 |
-
What teams are active on social?
|
| 296 |
-
|
| 297 |
-
(cid:31) Sales
|
| 298 |
-
|
| 299 |
-
(cid:31) Marketing
|
| 300 |
-
|
| 301 |
-
(cid:31) Advertising
|
| 302 |
-
|
| 303 |
-
(cid:31) Public relations
|
| 304 |
-
|
| 305 |
-
(cid:31) Customer service
|
| 306 |
-
|
| 307 |
-
(cid:31) Human resources
|
| 308 |
-
|
| 309 |
-
(cid:31) Research and
|
| 310 |
-
development
|
| 311 |
-
|
| 312 |
-
06
|
| 313 |
-
|
| 314 |
-
03
|
| 315 |
-
Focus on networks
|
| 316 |
-
that add value
|
| 317 |
-
|
| 318 |
-
Just because a network has billions of users doesn’t mean it will have a direct
|
| 319 |
-
|
| 320 |
-
contribution to your brand’s objectives. Instead of trying to be everything to
|
| 321 |
-
|
| 322 |
-
everybody, focus your efforts on networks that hold the key to your target
|
| 323 |
-
|
| 324 |
-
audience and objectives.
|
| 325 |
-
|
| 326 |
-
Each network has its own strengths and weaknesses, and each social media
|
| 327 |
-
|
| 328 |
-
marketer should carefully pick and choose which networks they want to take
|
| 329 |
-
|
| 330 |
-
advantage of. Here are some of the most popular networks as well as what they’re
|
| 331 |
-
|
| 332 |
-
best at.
|
| 333 |
-
|
| 334 |
-
Facebook
|
| 335 |
-
|
| 336 |
-
With an audience of 2.32 billion monthly active users, Facebook offers an
|
| 337 |
-
|
| 338 |
-
opportunity to reach a broad range of customers and potential customers. The
|
| 339 |
-
|
| 340 |
-
chart below breaks down Facebook’s demographic representation—your target
|
| 341 |
-
|
| 342 |
-
audience is most likely represented in some way.
|
| 343 |
-
|
| 344 |
-
07
|
| 345 |
-
|
| 346 |
-
But how can Facebook contribute to your overall goals? Because Facebook’s
|
| 347 |
-
|
| 348 |
-
News Feed is a very visible place for social posts, it’s one of the best places for
|
| 349 |
-
|
| 350 |
-
you to distribute your content in order to increase brand awareness, drive website
|
| 351 |
-
|
| 352 |
-
traffic and distinguish yourself as a thought leader. This strategy is even more
|
| 353 |
-
|
| 354 |
-
effective when you take advantage of Facebook’s targeting capabilities that allow
|
| 355 |
-
|
| 356 |
-
you to tailor your messages to users with certain interests.
|
| 357 |
-
|
| 358 |
-
Twitter
|
| 359 |
-
|
| 360 |
-
Where Facebook has the volume of users, Twitter has the volume of messages. In
|
| 361 |
-
|
| 362 |
-
fact, there are over 500 million Tweets sent every day. With all those social
|
| 363 |
-
|
| 364 |
-
messages, there is a great chance that someone is either mentioning your
|
| 365 |
-
|
| 366 |
-
company or starting a conversation that you would be interested in joining.
|
| 367 |
-
|
| 368 |
-
That’s why Twitter is best to use as a customer service and business development
|
| 369 |
-
|
| 370 |
-
channel. Monitor the network for inbound messages from dissatisfied customers,
|
| 371 |
-
|
| 372 |
-
and quickly turn them into happy interactions. At the same time, look for
|
| 373 |
-
|
| 374 |
-
prospective customers.
|
| 375 |
-
|
| 376 |
-
LinkedIn
|
| 377 |
-
|
| 378 |
-
LinkedIn has a robust network of over 500 million users, most of whom frequent
|
| 379 |
-
|
| 380 |
-
the site with a “working” mindset. The advantage with this is that LinkedIn is an
|
| 381 |
-
|
| 382 |
-
amazing network for B2B social media marketers. Whereas sites like Twitter and
|
| 383 |
-
|
| 384 |
-
Facebook catch users more or less on their personal time, LinkedIn gives you
|
| 385 |
-
|
| 386 |
-
access to customers when they’re at their professional best. Use this to build
|
| 387 |
-
|
| 388 |
-
relationships with future customers.
|
| 389 |
-
|
| 390 |
-
Which networks align with your business strategy?
|
| 391 |
-
|
| 392 |
-
(cid:31) Facebook
|
| 393 |
-
|
| 394 |
-
(cid:31) Twitter
|
| 395 |
-
|
| 396 |
-
(cid:31) Instagram
|
| 397 |
-
|
| 398 |
-
(cid:31) LinkedIn
|
| 399 |
-
|
| 400 |
-
(cid:31) Pinterest
|
| 401 |
-
|
| 402 |
-
(cid:31) YouTube
|
| 403 |
-
|
| 404 |
-
(cid:31) Snapchat
|
| 405 |
-
|
| 406 |
-
08
|
| 407 |
-
|
| 408 |
-
04
|
| 409 |
-
Create engaging content
|
| 410 |
-
|
| 411 |
-
Once you’ve involved the right stakeholders, department and networks, it’s time to
|
| 412 |
-
|
| 413 |
-
start building engaging content for your social channels. This content—whether a
|
| 414 |
-
|
| 415 |
-
video, tip sheet or simple Tweet—should all ladder up into your business
|
| 416 |
-
|
| 417 |
-
objectives.
|
| 418 |
-
|
| 419 |
-
Videos
|
| 420 |
-
• How-to videos can be a proactive approach to social customer care—answer
|
| 421 |
-
|
| 422 |
-
your customers’ questions before they’re asked.
|
| 423 |
-
|
| 424 |
-
• Behind-the-scenes videos give your audience a sense of your company culture
|
| 425 |
-
|
| 426 |
-
and brand personality.
|
| 427 |
-
|
| 428 |
-
Guides
|
| 429 |
-
• Position your organization as a thought leader and elevate your brand by
|
| 430 |
-
|
| 431 |
-
developing engaging content that speaks to your customers.
|
| 432 |
-
|
| 433 |
-
• Guides should cater to your target audience, ensuring you’re adding value.
|
| 434 |
-
|
| 435 |
-
09
|
| 436 |
-
|
| 437 |
-
Infographics
|
| 438 |
-
• Internal or external data can be turned into a beautiful, insightful infographic.
|
| 439 |
-
|
| 440 |
-
• When done right, infographics can be some of the most socially shared pieces
|
| 441 |
-
|
| 442 |
-
of content, so make them engaging and resourceful.
|
| 443 |
-
|
| 444 |
-
What content can you create with full force
|
| 445 |
-
and frequency?
|
| 446 |
-
|
| 447 |
-
(cid:31) Videos
|
| 448 |
-
|
| 449 |
-
(cid:31) Photos
|
| 450 |
-
|
| 451 |
-
(cid:31) Ebooks
|
| 452 |
-
|
| 453 |
-
(cid:31) Webinars
|
| 454 |
-
|
| 455 |
-
(cid:31) White papers
|
| 456 |
-
|
| 457 |
-
(cid:31) Blog posts
|
| 458 |
-
|
| 459 |
-
(cid:31) Case studies
|
| 460 |
-
|
| 461 |
-
(cid:31) Infographics
|
| 462 |
|
| 463 |
10
|
| 464 |
|
| 465 |
-
|
| 466 |
-
|
| 467 |
-
through social
|
| 468 |
-
|
| 469 |
-
With millions of messages being sent across social channels every day, there is
|
| 470 |
-
|
| 471 |
-
undoubtedly conversation happening around your brand. Social media listening,
|
| 472 |
|
| 473 |
-
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|
|
|
|
|
|
| 474 |
|
| 475 |
-
|
| 476 |
|
| 477 |
-
|
| 478 |
-
|
| 479 |
-
segment are asking for. You can get ahead of competitors by noticing emerging
|
| 480 |
-
|
| 481 |
-
trends in your area, and meet customers’ needs perfectly by developing features
|
| 482 |
-
|
| 483 |
-
and products that people are overwhelmingly requesting.
|
| 484 |
-
|
| 485 |
-
For example, listening can uncover how much of Hulu's audience of streaming TV
|
| 486 |
-
|
| 487 |
-
viewers is starting to expect a download option.
|
| 488 |
-
|
| 489 |
-
11
|
| 490 |
|
| 491 |
-
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| 492 |
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| 493 |
-
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| 494 |
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| 495 |
-
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| 496 |
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| 497 |
-
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|
| 498 |
|
| 499 |
-
|
| 500 |
|
| 501 |
-
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| 502 |
|
| 503 |
-
|
|
|
|
| 504 |
|
| 505 |
-
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|
|
| 506 |
|
| 507 |
-
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|
|
| 508 |
|
| 509 |
-
|
| 510 |
|
| 511 |
-
|
| 512 |
|
| 513 |
-
|
|
|
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|
| 514 |
|
| 515 |
-
|
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|
| 516 |
|
| 517 |
-
|
| 518 |
-
|
| 519 |
-
Go beyond simple keyword searches to stay on top of what audiences in your
|
| 520 |
-
|
| 521 |
-
segment are asking for. You can get ahead of competitors by noticing emerging
|
| 522 |
-
|
| 523 |
-
trends in your area, and meet customers’ needs perfectly by developing features
|
| 524 |
-
|
| 525 |
-
and products that people are overwhelmingly requesting.
|
| 526 |
-
|
| 527 |
-
For example, listening can uncover how much of Hulu's audience of streaming TV
|
| 528 |
-
|
| 529 |
-
viewers is starting to expect a download option.
|
| 530 |
-
|
| 531 |
-
Social sentiment
|
| 532 |
-
|
| 533 |
-
Don’t wait for complaints to start pouring in directly to your support accounts to
|
| 534 |
|
| 535 |
-
|
| 536 |
|
| 537 |
-
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|
| 538 |
|
| 539 |
-
|
| 540 |
|
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-
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|
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-
|
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|
|
| 544 |
|
| 545 |
-
|
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|
|
| 546 |
|
| 547 |
-
|
| 548 |
|
| 549 |
-
|
| 550 |
|
| 551 |
-
|
| 552 |
|
| 553 |
-
(
|
|
|
|
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|
| 554 |
|
| 555 |
-
|
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|
|
| 556 |
|
| 557 |
-
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
| 558 |
|
| 559 |
-
|
| 560 |
|
| 561 |
12
|
| 562 |
|
| 563 |
-
|
| 564 |
-
|
| 565 |
-
|
| 566 |
-
|
| 567 |
-
|
| 568 |
-
|
| 569 |
-
|
| 570 |
-
|
| 571 |
-
|
| 572 |
-
|
| 573 |
-
|
| 574 |
-
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
| 575 |
|
| 576 |
-
these customers, as well as responding with openness and transparency, can win
|
| 577 |
-
|
| 578 |
-
back frustrated audiences.
|
| 579 |
-
|
| 580 |
-
Slack turned a service outage into a positive for the customer, who ended up
|
| 581 |
-
|
| 582 |
-
praising their social team and Liking their responses.
|
| 583 |
-
|
| 584 |
-
How are you responding to your followers?
|
| 585 |
-
|
| 586 |
-
(cid:31) Dedicated social team
|
| 587 |
-
|
| 588 |
-
(cid:31) Shared social responsibility across departments
|
| 589 |
-
|
| 590 |
-
(cid:31) Social tools with built-in customer relationship management capabilities
|
| 591 |
-
|
| 592 |
-
13
|
| 593 |
13
|
| 594 |
|
| 595 |
-
|
| 596 |
-
Track, improve and market
|
| 597 |
-
your efforts
|
| 598 |
|
| 599 |
-
|
|
|
|
|
|
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|
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|
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|
|
|
|
| 600 |
|
| 601 |
-
|
|
|
|
| 602 |
|
| 603 |
-
|
| 604 |
|
| 605 |
-
|
|
|
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|
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|
|
|
|
| 606 |
|
| 607 |
-
|
| 608 |
|
| 609 |
-
|
| 610 |
|
| 611 |
-
|
|
|
|
| 612 |
|
| 613 |
-
|
|
|
|
| 614 |
|
| 615 |
-
|
| 616 |
|
| 617 |
-
|
| 618 |
|
| 619 |
-
|
| 620 |
|
| 621 |
-
|
| 622 |
|
| 623 |
-
|
| 624 |
|
| 625 |
-
|
|
|
|
|
|
|
| 626 |
|
| 627 |
-
|
| 628 |
|
| 629 |
-
|
| 630 |
|
| 631 |
-
|
| 632 |
|
| 633 |
-
|
| 634 |
|
| 635 |
-
|
| 636 |
|
| 637 |
-
|
| 638 |
|
| 639 |
-
|
| 640 |
|
| 641 |
-
|
| 642 |
|
| 643 |
-
|
| 644 |
|
| 645 |
-
|
| 646 |
-
not—and why.
|
| 647 |
|
| 648 |
-
|
| 649 |
-
presentations.
|
| 650 |
|
| 651 |
-
(
|
|
|
|
| 652 |
|
| 653 |
-
|
| 654 |
|
| 655 |
-
|
| 656 |
-
|
| 657 |
|
| 658 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
| 659 |
|
| 660 |
-
|
| 661 |
|
| 662 |
-
|
| 663 |
|
| 664 |
-
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
| 665 |
|
| 666 |
-
|
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|
|
|
|
|
|
| 667 |
|
| 668 |
-
|
| 669 |
|
| 670 |
-
|
| 671 |
|
| 672 |
-
|
|
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|
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|
|
|
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|
|
| 673 |
|
| 674 |
-
|
| 675 |
|
| 676 |
-
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
| 677 |
|
| 678 |
-
|
| 679 |
|
| 680 |
-
|
|
|
|
| 681 |
|
| 682 |
-
|
| 683 |
|
| 684 |
-
|
|
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| 685 |
|
|
|
|
| 1 |
+
3
|
| 2 |
+
2
|
| 3 |
+
0
|
| 4 |
+
2
|
| 5 |
+
|
| 6 |
+
t
|
| 7 |
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|
| 8 |
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|
| 9 |
+
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|
| 10 |
+
1
|
| 11 |
+
|
| 12 |
+
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|
| 13 |
+
I
|
| 14 |
+
|
| 15 |
+
A
|
| 16 |
+
.
|
| 17 |
+
s
|
| 18 |
+
c
|
| 19 |
+
[
|
| 20 |
+
|
| 21 |
+
4
|
| 22 |
+
v
|
| 23 |
+
6
|
| 24 |
+
6
|
| 25 |
+
3
|
| 26 |
+
1
|
| 27 |
+
1
|
| 28 |
+
.
|
| 29 |
+
3
|
| 30 |
+
0
|
| 31 |
+
3
|
| 32 |
+
2
|
| 33 |
+
:
|
| 34 |
+
v
|
| 35 |
+
i
|
| 36 |
+
X
|
| 37 |
+
r
|
| 38 |
+
a
|
| 39 |
+
|
| 40 |
+
Reflexion: Language Agents with
|
| 41 |
+
Verbal Reinforcement Learning
|
| 42 |
+
|
| 43 |
+
Noah Shinn
|
| 44 |
+
Northeastern University
|
| 45 |
+
noahshinn024@gmail.com
|
| 46 |
+
|
| 47 |
+
Federico Cassano
|
| 48 |
+
Northeastern University
|
| 49 |
+
cassano.f@northeastern.edu
|
| 50 |
+
|
| 51 |
+
Edward Berman
|
| 52 |
+
Northeastern University
|
| 53 |
+
berman.ed@northeastern.edu
|
| 54 |
+
|
| 55 |
+
Ashwin Gopinath
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Massachusetts Institute of Technology
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agopi@mit.edu
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Karthik Narasimhan
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Princeton University
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karthikn@princeton.edu
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Shunyu Yao
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Princeton University
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shunyuy@princeton.edu
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Abstract
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Large language models (LLMs) have been increasingly used to interact with exter-
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nal environments (e.g., games, compilers, APIs) as goal-driven agents. However,
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it remains challenging for these language agents to quickly and efficiently learn
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from trial-and-error as traditional reinforcement learning methods require exten-
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sive training samples and expensive model fine-tuning. We propose Reflexion, a
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novel framework to reinforce language agents not by updating weights, but in-
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stead through linguistic feedback. Concretely, Reflexion agents verbally reflect
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on task feedback signals, then maintain their own reflective text in an episodic
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memory buffer to induce better decision-making in subsequent trials. Reflexion is
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flexible enough to incorporate various types (scalar values or free-form language)
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and sources (external or internally simulated) of feedback signals, and obtains
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significant improvements over a baseline agent across diverse tasks (sequential
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decision-making, coding, language reasoning). For example, Reflexion achieves a
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91% pass@1 accuracy on the HumanEval coding benchmark, surpassing the previ-
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ous state-of-the-art GPT-4 that achieves 80%. We also conduct ablation and analysis
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studies using different feedback signals, feedback incorporation methods, and agent
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types, and provide insights into how they affect performance. We release all code,
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demos, and datasets at https://github.com/noahshinn024/reflexion.
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1
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Introduction
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Recent works such as ReAct [30], SayCan [1], Toolformer [22], HuggingGPT [23], generative
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agents [19], and WebGPT [17] have demonstrated the feasibility of autonomous decision-making
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agents that are built on top of a large language model (LLM) core. These methods use LLMs to
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generate text and ‘actions‘ that can be used in API calls and executed in an environment. Since
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they rely on massive models with an enormous number of parameters, such approaches have been
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so far limited to using in-context examples as a way of teaching the agents, since more traditional
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optimization schemes like reinforcement learning with gradient descent require substantial amounts
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of compute and time.
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Preprint. Under review.
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In this paper, we propose an alternative approach called Reflexion that uses verbal reinforcement
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to help agents learn from prior failings. Reflexion converts binary or scalar feedback from the
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environment into verbal feedback in the form of a textual summary, which is then added as additional
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context for the LLM agent in the next episode. This self-reflective feedback acts as a ‘semantic’
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gradient signal by providing the agent with a concrete direction to improve upon, helping it learn
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from prior mistakes to perform better on the task. This is akin to how humans iteratively learn to
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accomplish complex tasks in a few-shot manner – by reflecting on their previous failures in order to
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form an improved plan of attack for the next attempt. For example, in figure 1, a Reflexion agent
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learns to optimize its own behavior to solve decision-making, programming, and reasoning tasks
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through trial, error, and self-reflection.
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Generating useful reflective feedback is challenging since it requires a good understanding of where
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the model made mistakes (i.e. the credit assignment problem [25]) as well as the ability to generate
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a summary containing actionable insights for improvement. We explore three ways for doing
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this – simple binary environment feedback, pre-defined heuristics for common failure cases, and
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self-evaluation such as binary classification using LLMs (decision-making) or self-written unit
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tests (programming). In all implementations, the evaluation signal is amplified to natural language
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experience summaries which can be stored in long-term memory.
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Reflexion has several advantages compared to more traditional RL approaches like policy or value-
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based learning: 1) it is lightweight and doesn’t require finetuning the LLM, 2) it allows for more
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nuanced forms of feedback (e.g. targeted changes in actions), compared to scalar or vector rewards
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that are challenging to perform accurate credit assignment with, 3) it allows for a more explicit and
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interpretable form of episodic memory over prior experiences, and 4) it provides more explicit hints
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for actions in future episodes. At the same time, it does have the disadvantages of relying on the
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power of the LLM’s self-evaluation capabilities (or heuristics) and not having a formal guarantee for
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success. However, as LLM capabilities improve, we only expect this paradigm to get better over time.
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We perform experiments on (1) decision-making tasks to test sequential action choices over long
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trajectories, (2) reasoning tasks to test knowledge-intensive, single-step generation improvement,
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and (3) programming tasks to teach the agent to effectively use external tools such as compilers
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and interpreters. Across all three types of tasks, we observe Reflexion agents are better decision-
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makers, reasoners, and programmers. More concretely, Reflexion agents improve on decision-making
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AlfWorld [24] tasks over strong baseline approaches by an absolute 22% in 12 iterative learning
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steps, and on reasoning questions in HotPotQA [28] by 20%, and Python programming tasks on
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HumanEval [6] by as much as 11%.
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To summarize, our contributions are the following:
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• We propose Reflexion, a new paradigm for ‘verbal‘ reinforcement that parameterizes a
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policy as an agent’s memory encoding paired with a choice of LLM parameters.
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• We explore this emergent property of self-reflection in LLMs and empirically show that
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self-reflection is extremely useful to learn complex tasks over a handful of trials.
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• We introduce LeetcodeHardGym, a code-generation RL gym environment consisting of 40
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challenging Leetcode questions (‘hard-level‘) in 19 programming languages.
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• We show that Reflexion achieves improvements over strong baselines across several tasks,
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and achieves state-of-the-art results on various code generation benchmarks.
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2 Related work
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Reasoning and decision-making Self-Refine [15] employs an iterative framework for self-
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refinement to autonomously improve generation through self-evaluation. These self-evaluation
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and self-improvement steps are conditioned on given task constraints, such as "How can this genera-
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tion be written in a more positive way". Self-Refine is effective but is limited to single-generation
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reasoning tasks. Pryzant et al. [21] performs a similar semantic prompt-writing optimization, but is
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also limited to single-generation tasks. Paul et al. [20] fine-tune critic models to provide intermediate
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feedback within trajectories to improve reasoning responses. Xie et al. [27] use stochastic beam
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search over actions to perform a more efficient decision-making search strategy which allows the
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agent to use foresight advantage due to its self-evaluation component. Yoran et al. [31] and Nair et al.
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2
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Figure 1: Reflexion works on decision-making 4.1, programming 4.3, and reasoning 4.2 tasks.
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Related work on reasoning and decision-making
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Approach
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Self-refine [15]
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Beam search [27]
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Reflexion (ours)
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Self
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refine
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✓
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✓
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✓
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Hidden
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Decision
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constraints making
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✗
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✓
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✓
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✗
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✓
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✓
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Binary Memory
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reward
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✓
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✓
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✓
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Related work on programming
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Approach
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Test execution
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AlphaCode [14]
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CodeT [5]
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Self-debugging [7]
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CodeRL [12]
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Reflexion (ours)
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Test
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execution
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✓
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✓
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✓
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✓
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Debugging
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✗
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✓
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✓
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✓
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Self-generated Multiple
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languages
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✓
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✓
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tests
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✓
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✓
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Self-reflection
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✓
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[16] use decider models to reason over several generations. Kim et al. [10] use a retry pattern over
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a fixed number of steps without an evaluation step. Goodman [9] perform a qualitative evaluation
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step that proposes optimizations to the previous generation. In this paper, we show that several of
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these concepts can be enhanced with self-reflection to build a persisting memory of self-reflective
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experiences which allows an agent to identify its own errors and self-suggest lessons to learn from its
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mistakes over time.
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Programming Several past and recent works employ variations of test-driven development or
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code debugging practices. AlphaCode [14] evaluates a set of generations on hidden test cases.
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CodeT [5] uses self-generated unit tests that are used to score generated function implementations.
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Self-Debugging [7] employs a debugging component that is used to improve existing implementations
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given feedback from a code execution environment. CodeRL [12] sets the problem in an RL frame-
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work using an actor-critic setup to debug programs given feedback from an execution environment.
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AlphaCode, Self-Debugging and CodeRL are effective in fixing less-complex program bugs, but they
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rely upon ground truth test cases that invalidate pass@1 eligibility, and do not use self-reflection to
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bridge the gap between error identification and implementation improvement. CodeT does not access
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hidden test cases but does not implement a self-learning step to improve code writing.
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3 Reflexion: reinforcement via verbal reflection
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We develop a modular formulation for Reflexion, utilizing three distinct models: an Actor, denoted as
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Ma, which generates text and actions; an Evaluator model, represented by Me, that scores the outputs
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produced by Ma; and a Self-Reflection model, denoted as Msr, which generates verbal reinforcement
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cues to assist the Actor in self-improvement. We provide a detailed description of each of these
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models and subsequently elucidate their collaborative functioning within the Reflexion framework.
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3
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68)(cid:81)(cid:71)(cid:3)(cid:36)(cid:79)(cid:68)(cid:81)(cid:3)(cid:39)(cid:72)(cid:68)(cid:81)(cid:3)(cid:41)(cid:82)(cid:86)(cid:87)(cid:72)(cid:85)(cid:3)(cid:75)(cid:68)(cid:89)(cid:72)(cid:3)(cid:76)(cid:81)(cid:3)(cid:70)(cid:82)(cid:80)(cid:80)(cid:82)(cid:81)(cid:3)(cid:76)(cid:86)(cid:3)(cid:81)(cid:82)(cid:89)(cid:72)(cid:79)(cid:76)(cid:86)(cid:87)(cid:17)(cid:36)(cid:70)(cid:87)(cid:76)(cid:82)(cid:81)(cid:29)(cid:3)(cid:178)(cid:81)(cid:82)(cid:89)(cid:72)(cid:79)(cid:76)(cid:86)(cid:87)(cid:179)(cid:62)(cid:17)(cid:17)(cid:17)(cid:64)(cid:3)(cid:36)(cid:70)(cid:87)(cid:76)(cid:82)(cid:81)(cid:29)(cid:3)(cid:87)(cid:68)(cid:78)(cid:72)(cid:3)(cid:83)(cid:68)(cid:81)(cid:3)(cid:20)(cid:3)(cid:73)(cid:85)(cid:82)(cid:80)(cid:3)(cid:86)(cid:87)(cid:82)(cid:89)(cid:72)(cid:69)(cid:88)(cid:85)(cid:81)(cid:72)(cid:85)(cid:3)(cid:21)(cid:62)(cid:17)(cid:17)(cid:17)(cid:64)(cid:3)(cid:50)(cid:69)(cid:86)(cid:29)(cid:3)(cid:60)(cid:82)(cid:88)(cid:3)(cid:83)(cid:88)(cid:87)(cid:3)(cid:87)(cid:75)(cid:72)(cid:3)(cid:83)(cid:68)(cid:81)(cid:3)(cid:20)(cid:3)(cid:76)(cid:81)(cid:3)(cid:70)(cid:82)(cid:88)(cid:81)(cid:87)(cid:72)(cid:85)(cid:87)(cid:82)(cid:83)(cid:3)(cid:20)(cid:17)(cid:11)(cid:70)(cid:12)(cid:3)(cid:40)(cid:89)(cid:68)(cid:79)(cid:88)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:11)(cid:71)(cid:12)(cid:3)(cid:53)(cid:72)(cid:73)(cid:79)(cid:72)(cid:70)(cid:87)(cid:76)(cid:82)(cid:81)(cid:11)(cid:72)(cid:12)(cid:3)(cid:49)(cid:72)(cid:91)(cid:87)(cid:3)(cid:55)(cid:85)(cid:68)(cid:77)(cid:72)(cid:70)(cid:87)(cid:82)(cid:85)(cid:92)(cid:11)(cid:69)(cid:12)(cid:3)(cid:55)(cid:85)(cid:68)(cid:77)(cid:72)(cid:70)(cid:87)(cid:82)(cid:85)(cid:92)(cid:11)(cid:68)(cid:12)(cid:3)(cid:55)(cid:68)(cid:86)(cid:78)(cid:11)(cid:76)(cid:81)(cid:87)(cid:72)(cid:85)(cid:81)(cid:68)(cid:79)(cid:3)(cid:18)(cid:3)(cid:72)(cid:91)(cid:87)(cid:72)(cid:85)(cid:81)(cid:68)(cid:79)(cid:12)Algorithm 1 Reinforcement via self-reflection
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+
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Initialize Actor, Evaluator, Self-Reflection:
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Ma, Me, Msr
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Initialize policy πθ(ai|si), θ = {Ma, mem}
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Generate initial trajectory using πθ
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+
Evaluate τ0 using Me
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Generate initial self-reflection sr0 using Msr
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Set mem ← [sr0]
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+
Set t = 0
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+
while Me not pass or t < max trials do
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+
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+
Generate τt = [a0, o0, . . . ai, oi] using πθ
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+
Evaluate τt using Me
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Generate self-reflection srt using Msr
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Append srt to mem
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+
Increment t
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+
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+
end while
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return
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+
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Figure 2: (a) Diagram of Reflexion. (b) Reflexion reinforcement algorithm
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+
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Actor The Actor is built upon a large language model (LLM) that is specifically prompted to
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generate the necessary text and actions conditioned on the state observations. Analogous to traditional
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policy-based RL setups, we sample an action or generation, at, from the current policy πθ at time t,
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receive an observation from the environment ot. We explore various Actor models, including Chain of
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| 316 |
+
Thought [26] and ReAct [30]. These diverse generation models allow us to explore different aspects
|
| 317 |
+
of text and action generation within the Reflexion framework, providing valuable insights into their
|
| 318 |
+
performance and effectiveness. In addition, we also add a memory component mem that provides
|
| 319 |
+
additional context to this agent. This adaption was inspired by Brooks et al. [3], who suggest a policy
|
| 320 |
+
iteration approach using in-context learning. Details on how this is populated are provided below.
|
| 321 |
+
|
| 322 |
+
Evaluator The Evaluator component of the Reflexion framework plays a crucial role in assessing
|
| 323 |
+
the quality of the generated outputs produced by the Actor. It takes as input a generated trajectory
|
| 324 |
+
and computes a reward score that reflects its performance within the given task context. Defining
|
| 325 |
+
effective value and reward functions that apply to semantic spaces is difficult, so we investigate
|
| 326 |
+
several variants of the Evaluator model. For reasoning tasks, we explore reward functions based
|
| 327 |
+
on exact match (EM) grading, ensuring that the generated output aligns closely with the expected
|
| 328 |
+
solution. In decision-making tasks, we employ pre-defined heuristic functions that are tailored to
|
| 329 |
+
specific evaluation criteria. Additionally, we experiment with using a different instantiation of an
|
| 330 |
+
LLM itself as an Evaluator, generating rewards for decision-making and programming tasks. This
|
| 331 |
+
multi-faceted approach to Evaluator design allows us to examine different strategies for scoring
|
| 332 |
+
generated outputs, offering insights into their effectiveness and suitability across a range of tasks.
|
| 333 |
+
|
| 334 |
+
Self-reflection The Self-Reflection model instantiated as an LLM, plays a crucial role in the
|
| 335 |
+
Reflexion framework by generating verbal self-reflections to provide valuable feedback for future
|
| 336 |
+
trials. Given a sparse reward signal, such as a binary success status (success/fail), the current trajectory,
|
| 337 |
+
and its persistent memory mem, the self-reflection model generates nuanced and specific feedback.
|
| 338 |
+
This feedback, which is more informative than scalar rewards, is then stored in the agent’s memory
|
| 339 |
+
(mem). For instance, in a multi-step decision-making task, when the agent receives a failure signal, it
|
| 340 |
+
can infer that a specific action ai led to subsequent incorrect actions ai+1 and ai+2. The agent can
|
| 341 |
+
then verbally state that it should have taken a different action, a′
|
| 342 |
+
i+1
|
| 343 |
+
and a′
|
| 344 |
+
i+2, and store this experience in its memory. In subsequent trials, the agent can leverage its past
|
| 345 |
+
experiences to adapt its decision-making approach at time t by choosing action a′
|
| 346 |
+
i. This iterative
|
| 347 |
+
process of trial, error, self-reflection, and persisting memory enables the agent to rapidly improve its
|
| 348 |
+
decision-making ability in various environments by utilizing informative feedback signals.
|
| 349 |
+
|
| 350 |
+
i, which would have resulted in a′
|
| 351 |
+
|
| 352 |
+
Memory Core components of the Reflexion process are the notion of short-term and long-term
|
| 353 |
+
memory. At inference time, the Actor conditions its decisions on short and long-term memory, similar
|
| 354 |
+
|
| 355 |
+
4
|
| 356 |
+
|
| 357 |
+
ActionObs / RewardTrajectory(short-term memory)Experience(long-term memory)Self-reflection (LM)AgentActor (LM)EnvironmentEvaluator (LM)External feedbackInternalfeedbackReflectivetextto the way that humans remember fine-grain recent details while also recalling distilled important
|
| 358 |
+
experiences from long-term memory. In the RL setup, the trajectory history serves as the short-term
|
| 359 |
+
memory while outputs from the Self-Reflection model are stored in long-term memory. These two
|
| 360 |
+
memory components work together to provide context that is specific but also influenced by lessons
|
| 361 |
+
learned over several trials, which is a key advantage of Reflexion agents over other LLM action
|
| 362 |
+
choice works.
|
| 363 |
+
|
| 364 |
+
The Reflexion process Reflexion is formalized as an iterative optimization process in 1. In the
|
| 365 |
+
first trial, the Actor produces a trajectory τ0 by interacting with the environment. The Evaluator then
|
| 366 |
+
produces a score r0 which is computed as rt = Me(τ0). rt is only a scalar reward for trial t that
|
| 367 |
+
improves as task-specific performance increases. After the first trial, to amplify r0 to a feedback form
|
| 368 |
+
that can be used for improvement by an LLM, the Self-Reflection model analyzes the set of {τ0, r0}
|
| 369 |
+
to produce a summary sr0 which is stored in the memory mem. srt is a verbal experience feedback
|
| 370 |
+
for trial t. The Actor, Evaluator, and Self-Reflection models work together through trials in a loop
|
| 371 |
+
until the Evaluator deems τt to be correct. As mentioned in 3, the memory component of Reflexion
|
| 372 |
+
is crucial to its effectiveness. After each trial t, srt, is appended mem. In practice, we bound mem
|
| 373 |
+
by a maximum number of stored experiences, Ω (usually set to 1-3) to adhere to max context LLM
|
| 374 |
+
limitations.
|
| 375 |
+
|
| 376 |
+
4 Experiments
|
| 377 |
+
|
| 378 |
+
We evaluate various natural language RL setups on decision-making, reasoning, and code generation
|
| 379 |
+
tasks. Specifically, we challenge an agent to perform search-based question answering on HotPotQA
|
| 380 |
+
[28], multi-step tasks in common household environments in AlfWorld [24], and code writing tasks
|
| 381 |
+
in competition-like environments with interpreters and compilers in HumanEval [6], MBPP [2],
|
| 382 |
+
and LeetcodeHard, a new benchmark. Most notably, Reflexion improves performance over strong
|
| 383 |
+
baselines by 22% in AlfWorld, 20% in HotPotQA, and 11% on HumanEval.
|
| 384 |
+
|
| 385 |
+
4.1 Sequential decision making: ALFWorld
|
| 386 |
+
|
| 387 |
+
AlfWorld is a suite of text-based environments that challenge an agent to solve multi-step tasks
|
| 388 |
+
in a variety of interactive environments based on TextWorld [8]. Following Yao et al. [30], we
|
| 389 |
+
run the agent in 134 AlfWorld environments across six different tasks, including finding hidden
|
| 390 |
+
objects (e.g., finding a spatula in a drawer), moving objects (e.g., moving a knife to the cutting
|
| 391 |
+
board), and manipulating objects with other objects (e.g., chilling a tomato in the fridge). We use
|
| 392 |
+
ReAct [30] as the action generator as Yao et al. [30] has shown success in long trajectory decision-
|
| 393 |
+
making using explicit intermediate thoughts. AlfWorld tasks naturally require a self-evaluation step
|
| 394 |
+
as the environment can only signal if a task is complete. To achieve fully autonomous behavior,
|
| 395 |
+
we implement two self-evaluation techniques: natural language classification using an LLM and a
|
| 396 |
+
hand-written heuristic. The heuristic is simple: if the agent executes the same action and receives the
|
| 397 |
+
same response for more than 3 cycles, or if the number of actions taken in the current environment
|
| 398 |
+
exceeds 30 (inefficient planning), we self-reflect. In the baseline runs, if self-reflection is suggested,
|
| 399 |
+
we skip the self-reflection process, reset the environment, and start a new trial. In the Reflexion runs,
|
| 400 |
+
the agent uses self-reflection to find its mistake, update its memory, reset the environment, and start a
|
| 401 |
+
new trial. To avoid very long prompt windows that may exceed the maximum limit, we truncate the
|
| 402 |
+
agent’s memory to the last 3 self-reflections (experiences).
|
| 403 |
+
|
| 404 |
+
To avoid syntactic errors, we provide two domain-specific few-shot trajectories to the agent. We use
|
| 405 |
+
the same few-shot trajectory examples as Yao et al. [30] with GPT-3 for the LLM. AlfWorld tasks,
|
| 406 |
+
ReAct few-shot prompts, and Reflexion examples are included in the appendix.
|
| 407 |
+
|
| 408 |
+
Results ReAct + Reflexion significantly outperforms ReAct by completing 130 out of 134 tasks
|
| 409 |
+
using the simple heuristic to detect hallucinations and inefficient planning. Further, ReAct + Reflexion
|
| 410 |
+
learns to solve additional tasks by learning in 12 consecutive trials. In the ReAct-only approach, we
|
| 411 |
+
see that performance increase halts between trials 6 and 7.
|
| 412 |
+
|
| 413 |
+
Analysis A common error in baseline failed AlfWorld trajectories is when an agent thinks that it
|
| 414 |
+
has possession of an item but does not actually have the item. The agent proceeds to execute several
|
| 415 |
+
actions in a long trajectory and is not able to backtrack its actions to find the mistake. Reflexion
|
| 416 |
+
|
| 417 |
+
5
|
| 418 |
+
|
| 419 |
+
Figure 3: (a) AlfWorld performance across 134 tasks showing cumulative proportions of solved tasks
|
| 420 |
+
using self-evaluation techniques of (Heuristic) and (GPT) for binary classification. (b) Classification
|
| 421 |
+
of AlfWorld trajectories by reason of failure.
|
| 422 |
+
|
| 423 |
+
eliminates almost all of these cases by using self-reflection to distill long, failed trajectories into
|
| 424 |
+
relevant experiences that can are used as "self-hints" in the future. There are two main cases in which
|
| 425 |
+
long-term memory helps an agent in AlfWorld: 1) An early mistake in a long trajectory can be easily
|
| 426 |
+
identified. The agent can suggest a new action choice or even a new long-term plan. 2) There are too
|
| 427 |
+
many surfaces/containers to check for an item. The agent can exploit its experience memory over
|
| 428 |
+
several trials to thoroughly search a room. In 3, the learning curve suggests that the learning process
|
| 429 |
+
occurs over several experiences, meaning that the agent is successfully balancing cases 1 and 2 shown
|
| 430 |
+
in the immediate spike in the improvement between the first two trials, then a steady increase over
|
| 431 |
+
the next 11 trials to a near-perfect performance. On the other hand, 3 shows a ReAct-only agent
|
| 432 |
+
converging at a hallucination rate of 22% with no signs of long-term recovery.
|
| 433 |
+
|
| 434 |
+
4.2 Reasoning: HotpotQA
|
| 435 |
+
|
| 436 |
+
HotPotQA [28] is a Wikipedia-based dataset with 113k question-and-answer pairs that challenge
|
| 437 |
+
agents to parse content and reason over several supporting documents. To test improvement in
|
| 438 |
+
reasoning only ability, we implement Reflexion + Chain-of-Thought (CoT) [26] for step-by-step
|
| 439 |
+
Q → A and Q, Cgt → A implementations, where Q is the question, Cgt is the ground truth context
|
| 440 |
+
from the dataset, and A is the final answer. Since CoT is not a multi-step decision-making technique,
|
| 441 |
+
we give Cgt to the agent so that we can isolate the reasoning behavior over large sections of the
|
| 442 |
+
provided text. To test holistic question and answering ability, which requires reasoning and action
|
| 443 |
+
choice, we implement a Reflexion + ReAct [30] agent that can retrieve relevant context using a
|
| 444 |
+
Wikipedia API and infer answers using step-by-step explicit thinking. For CoT implementations, we
|
| 445 |
+
use 6-shot prompting; for ReAct, we use 2-shot prompting, and for self-reflection, we use 2-shot
|
| 446 |
+
prompting. All examples can be found in the appendix.
|
| 447 |
+
|
| 448 |
+
Robustly evaluating natural language answers is a long-standing problem in NLP. Therefore, between
|
| 449 |
+
trials, we use exact match answer grading using the environment to give a binary success signal to
|
| 450 |
+
the agent. After each trial, the self-reflection loop is employed to amplify the binary signal, similar to
|
| 451 |
+
the decision-making setup 4.1 in AlfWorld with a memory size of 3 experiences.
|
| 452 |
+
|
| 453 |
+
Results Reflexion outperforms all baseline approaches by significant margins over several learning
|
| 454 |
+
steps. Furthermore, ReAct-only, CoT-only, and CoT (GT)-only implementations fail to probabilisti-
|
| 455 |
+
cally improve on any tasks, meaning that no failed tasks from the first trial from any of the baseline
|
| 456 |
+
approaches were able to be solved in subsequent trials using a temperature of 0.7 In the Reflexion runs,
|
| 457 |
+
we allowed the agent to gather experience and retry on failed tasks until it produced 3 consecutive
|
| 458 |
+
failed attempts on the particular task. Naturally, the CoT (GT) achieved higher accuracy scores as it
|
| 459 |
+
was given access to the ground truth context of the question. Still, the CoT (GT) agent is unable to
|
| 460 |
+
correctly infer the correct answer for 39% of the questions, but Reflexion helps the agent to correct
|
| 461 |
+
its mistakes without access to the ground truth answer to improve its accuracy by 14%.
|
| 462 |
+
|
| 463 |
+
6
|
| 464 |
+
|
| 465 |
+
0246810Trial Number0.50.60.70.80.91.0Proportion of Solved Environments(a) ALFWorld Success RateReAct onlyReAct + Reflexion (Heuristic)ReAct + Reflexion (GPT)0246810Trial Number0.00.10.20.30.40.5Proportion of Environments(a) ALFWorld Success RateReAct only - hallucinationReAct only - inefficient planningReAct + Reflexion - hallucinationReAct + Reflexion - inefficient planningFigure 4: Chain-of-Thought (CoT) and ReAct. Reflexion improves search, information retrieval,
|
| 466 |
+
and reasoning capabilities on 100 HotPotQA questions. (a) Reflexion ReAct vs Reflexion CoT (b)
|
| 467 |
+
Reflexion CoT (GT) for reasoning only (c) Reflexion vs episodic memory ablation.
|
| 468 |
+
|
| 469 |
+
Analysis We perform an ablation experiment to isolate the advantage of the self-reflective step for
|
| 470 |
+
reasoning using CoT (GT) as the baseline approach 4. Recall that CoT (GT) uses Chain-of-Thought
|
| 471 |
+
reasoning with provided ground truth context, which tests reasoning ability over long contexts. Next,
|
| 472 |
+
we add an element of episodic memory (EPM) by including the most recent trajectory. For the
|
| 473 |
+
Reflexion agent, we implement the standard self-reflection step as a final pass. Intuitively, we test if
|
| 474 |
+
the agent is iteratively learning more effectively by using verbal explanation using language written
|
| 475 |
+
in the first person. 4 shows that self-reflection improves learning by an 8% absolute boost over
|
| 476 |
+
the episodic memory learning advantage. This result supports the argument that refinement-only
|
| 477 |
+
approaches are not as effective as self-reflection-guided refinement approaches.
|
| 478 |
+
|
| 479 |
+
4.3 Programming
|
| 480 |
+
|
| 481 |
+
We evaluate the baseline and Reflexion approaches on Python and Rust code writing on MBPP
|
| 482 |
+
[2], HumanEval [6], and LeetcodeHardGym, our new dataset. MBPP and HumanEval measure
|
| 483 |
+
function body generation accuracy given natural language descriptions. We use a benchmark language
|
| 484 |
+
compiler, MultiPL-E [4], to translate subsets of HumanEval and MBPP to the Rust language. MultiPL-
|
| 485 |
+
E is a collection of small compilers that can be used to translate Python benchmark questions to 18
|
| 486 |
+
other languages. We include experiments for Rust code generation to demonstrate that Reflexion
|
| 487 |
+
implementations for code generation are language-agnostic and can be used for interpreted and
|
| 488 |
+
compiled languages. Lastly, we introduce a new benchmark, LeetcodeHardGym, which is an
|
| 489 |
+
interactive programming gym that contains 40 Leetcode hard-rated questions that have been released
|
| 490 |
+
after October 8, 2022, which is the pre-training cutoff date of GPT-4 [18].
|
| 491 |
+
|
| 492 |
+
The task of programming presents a unique opportunity to use more grounded self-evaluation practices
|
| 493 |
+
such as self-generated unit test suites. Thus, our Reflexion-based programming task implementation is
|
| 494 |
+
eligible for pass@1 accuracy reporting. To generate a test suite, we use Chain-of-Thought prompting
|
| 495 |
+
[26] to produce diverse, extensive tests with corresponding natural language descriptions. Then, we
|
| 496 |
+
filter for syntactically valid test statements by attempting to construct a valid abstract syntax tree
|
| 497 |
+
(AST) for each proposed test. Finally, we sample n tests from the collection of generated unit tests
|
| 498 |
+
to produce a test suite T , denoted as {t0, t1, . . . , tn}. We set n to a maximum of 6 unit tests. Aside
|
| 499 |
+
from the unit test suite component, the setup for the learning loop for a Reflexion programming agent
|
| 500 |
+
is identical to the reasoning and decision-making agents with a max memory limit of 1 experience.
|
| 501 |
+
|
| 502 |
+
Benchmark + Language Prev SOTA Pass@1
|
| 503 |
+
|
| 504 |
+
SOTA Pass@1 Reflexion Pass@1
|
| 505 |
+
|
| 506 |
+
HumanEval (PY)
|
| 507 |
+
HumanEval (RS)
|
| 508 |
+
MBPP (PY)
|
| 509 |
+
MBPP (RS)
|
| 510 |
+
Leetcode Hard (PY)
|
| 511 |
+
|
| 512 |
+
65.8 (CodeT [5] + GPT-3.5)
|
| 513 |
+
–
|
| 514 |
+
67.7 (CodeT [5] + Codex [6])
|
| 515 |
+
–
|
| 516 |
+
–
|
| 517 |
+
|
| 518 |
+
80.1 (GPT-4)
|
| 519 |
+
60.0 (GPT-4)
|
| 520 |
+
80.1 (GPT-4)
|
| 521 |
+
70.9 (GPT-4)
|
| 522 |
+
7.5 (GPT-4)
|
| 523 |
+
|
| 524 |
+
91.0
|
| 525 |
+
68.0
|
| 526 |
+
77.1
|
| 527 |
+
75.4
|
| 528 |
+
15.0
|
| 529 |
+
|
| 530 |
+
Table 1: Pass@1 accuracy for various model-strategy-language combinations. The base strategy is a
|
| 531 |
+
single code generation sample. All instruction-based models follow zero-shot code generation.
|
| 532 |
+
|
| 533 |
+
7
|
| 534 |
+
|
| 535 |
+
0246Trial Number0.20.40.60.8Proportion of Solved Tasks(a) HotPotQA Success RateCoT onlyReAct onlyCoT + ReflexionReAct + Reflexion01234567Trial Number0.40.60.81.0Proportion of Solved Tasks(b) HotPotQA CoT (GT)CoT (GT) onlyCoT (GT) + Reflexion01234Trial Number0.50.60.70.80.91.0Proportion of Solved Tasks(c) HotPotQA Episodic MemoryCoT (GT) onlyCoT (GT) EPMCoT (GT) EPM + ReflexionBenchmark + Language Base Reflexion TP
|
| 536 |
+
|
| 537 |
+
FN
|
| 538 |
+
|
| 539 |
+
FP
|
| 540 |
+
|
| 541 |
+
TN
|
| 542 |
+
|
| 543 |
+
HumanEval (PY)
|
| 544 |
+
MBPP (PY)
|
| 545 |
+
HumanEval (RS)
|
| 546 |
+
MBPP (RS)
|
| 547 |
+
|
| 548 |
+
0.91
|
| 549 |
+
0.77
|
| 550 |
+
0.68
|
| 551 |
+
0.75
|
| 552 |
+
Table 2: Overall accuracy and test generation performance for HumanEval and MBPP. For Rust,
|
| 553 |
+
HumanEval is the hardest 50 problems from HumanEval Python translated to Rust with MultiPL-E
|
| 554 |
+
[4]. TP: unit tests pass, solution pass; FN: unit tests fail, solution pass; FP: unit tests pass, solution
|
| 555 |
+
fail; TN: unit tests fail, solution fail.
|
| 556 |
+
|
| 557 |
+
0.60
|
| 558 |
+
0.41
|
| 559 |
+
0.63
|
| 560 |
+
0.49
|
| 561 |
+
|
| 562 |
+
0.99
|
| 563 |
+
0.84
|
| 564 |
+
0.87
|
| 565 |
+
0.84
|
| 566 |
+
|
| 567 |
+
0.40
|
| 568 |
+
0.59
|
| 569 |
+
0.37
|
| 570 |
+
0.51
|
| 571 |
+
|
| 572 |
+
0.01
|
| 573 |
+
0.16
|
| 574 |
+
0.13
|
| 575 |
+
0.16
|
| 576 |
+
|
| 577 |
+
0.80
|
| 578 |
+
0.80
|
| 579 |
+
0.60
|
| 580 |
+
0.71
|
| 581 |
+
|
| 582 |
+
Results Reflexion outperforms all baseline accuracies and sets new state-of-the-art standards on
|
| 583 |
+
all benchmarks for Python and Rust except for MBPP Python 1. We further investigate the inferior
|
| 584 |
+
performance of Reflexion on MBPP Python.
|
| 585 |
+
|
| 586 |
+
Analysis We acknowledge that self-reflecting code-generation agents are bound to their ability to
|
| 587 |
+
write diverse, comprehensive tests. Therefore, in the case in which the model generates a flaky test
|
| 588 |
+
suite, it is possible that all tests pass on an incorrect solution and lead to a false positive label on a
|
| 589 |
+
code completion [11]. On the other hand, if the model produces an incorrectly written test suite, it
|
| 590 |
+
is possible for some of the tests to fail on a correct solution, leading to a self-reflection generation
|
| 591 |
+
that is conditioned on a false negative code completion. Given the implementation of Reflexion,
|
| 592 |
+
false negatives are preferred over false positives as the agent may be able to use self-reflection to
|
| 593 |
+
identify the incorrect test(s) and prompt itself to keep the original code completion intact. On the
|
| 594 |
+
other hand, if an invalid test suite returns a false positive completion (all internal test cases pass
|
| 595 |
+
but the implementation is incorrect), the agent will prematurely report an invalid submission. In 2,
|
| 596 |
+
various conditions are measured to analyze performance beyond pass@1 accuracy. Previously, we
|
| 597 |
+
displayed the inferior performance of Reflexion to the baseline GPT-4 on MBPP Python. In 2, we
|
| 598 |
+
observe a notable discrepancy between the false positive labels produced by internal test execution,
|
| 599 |
+
P(not pass@1 generation correct | tests pass). That is, the probability that a submission will fail given
|
| 600 |
+
that it passes all unit tests. For HumanEval and MBPP Python, the baseline pass@1 accuracies are
|
| 601 |
+
relatively similar, 82% and 80%, respectively. However, the false positive test execution rate for
|
| 602 |
+
MBPP Python is 16.3% while the rate for HumanEval Python is a mere 1.4%, leading to 91% overall
|
| 603 |
+
accuracy 1.
|
| 604 |
+
|
| 605 |
+
Approach
|
| 606 |
+
|
| 607 |
+
Test Generation
|
| 608 |
+
|
| 609 |
+
Self-reflection Pass@1 (Acc)
|
| 610 |
+
|
| 611 |
+
Base model
|
| 612 |
+
Test generation omission
|
| 613 |
+
Self-reflection omission
|
| 614 |
+
Reflexion
|
| 615 |
+
|
| 616 |
+
False
|
| 617 |
+
False
|
| 618 |
+
True
|
| 619 |
+
True
|
| 620 |
+
|
| 621 |
+
False
|
| 622 |
+
True
|
| 623 |
+
False
|
| 624 |
+
True
|
| 625 |
+
|
| 626 |
+
0.60
|
| 627 |
+
0.52
|
| 628 |
+
0.60
|
| 629 |
+
0.68
|
| 630 |
+
|
| 631 |
+
Table 3: Pass@1 accuracy for various compromised approaches on the Reflexion approach using
|
| 632 |
+
GPT-4 as the base model on HumanEval Rust - 50 hardest problems
|
| 633 |
+
|
| 634 |
+
Ablation study We test the composite approach of Reflexion for test generation and self-reflection
|
| 635 |
+
cooperation on a subset of the 50 hardest HumanEval Rust problems. Our Rust compiler environment
|
| 636 |
+
provides verbose error logs and helpful debugging hints, therefore serving as a good playground
|
| 637 |
+
for compromised approaches. First, we omit internal test generation and execution steps, which
|
| 638 |
+
test the agent to self-reflect without guidance from current implementations. 3 shows an inferior
|
| 639 |
+
52% vs 60% (baseline) accuracy, which suggests that the agent is unable to determine if the current
|
| 640 |
+
implementation is correct without unit tests. Therefore, the agent must participate in all iterations of
|
| 641 |
+
the run without the option to return early, performing harmful edits to the implementation.
|
| 642 |
+
|
| 643 |
+
Next, we test self-reflection contribution by omitting the natural language explanation step following
|
| 644 |
+
failed unit test suite evaluations.
|
| 645 |
+
Intuitively, this challenges the agent to combine the tasks of
|
| 646 |
+
error identification and implementation improvement across all failed unit tests. Interestingly, the
|
| 647 |
+
compromised agent does not improve performance over the baseline run. We observe that the test
|
| 648 |
+
generation and code compilation steps are able to catch syntax and logic errors, but the implementation
|
| 649 |
+
fixes do not reflect these indications. These empirical results suggest that several recent works that
|
| 650 |
+
|
| 651 |
+
8
|
| 652 |
|
| 653 |
+
propose blind trial and error debugging techniques without self-reflection are ineffective on harder
|
| 654 |
+
tasks such as writing complex programs in Rust.
|
| 655 |
|
| 656 |
+
5 Limitations
|
| 657 |
|
| 658 |
+
At its core, Reflexion is an optimization technique that uses natural language to do policy optimization.
|
| 659 |
+
Policy optimization is a powerful approach to improve action choice through experience, but it may
|
| 660 |
+
still succumb to non-optimal local minima solutions. In this study, we limit long-term memory to
|
| 661 |
+
a sliding window with maximum capacity, but we encourage future work to extend the memory
|
| 662 |
+
component of Reflexion with more advanced structures such as vector embedding databases or
|
| 663 |
+
traditional SQL databases. Specific to code generation, there are many practical limitations to test-
|
| 664 |
+
driven development in specifying accurate input-output mappings such as non-deterministic generator
|
| 665 |
+
functions, impure functions that interact with APIs, functions that vary output according to hardware
|
| 666 |
+
specifications, or functions that invoke parallel or concurrent behavior that may be difficult to predict.
|
| 667 |
|
| 668 |
+
6 Broader impact
|
| 669 |
|
| 670 |
+
Large language models are increasingly used to interact with external environments (e.g. the Internet,
|
| 671 |
+
software, robotics, etc.) and humans. Our work has the potential of reinforcing and empowering
|
| 672 |
+
these agents toward greater automation and work efficiency, but it also amplifies the risks when these
|
| 673 |
+
agents were put into misuse. We believe that this direction of research will need more effort in safety
|
| 674 |
+
and ethical considerations.
|
| 675 |
|
| 676 |
+
On the other hand, reinforcement learning has suffered from its black-box policy and optimiza-
|
| 677 |
+
tion setups in which interpretability and alignment have been challenging. Our proposed “verbal”
|
| 678 |
+
reinforcement learning might address some of the issues and turn autonomous agents more inter-
|
| 679 |
+
pretable and diagnosable. For example, in the case of tool-usage that may be too hard for humans to
|
| 680 |
+
understand, self-reflections could be monitored to ensure proper intent before using the tool.
|
| 681 |
|
| 682 |
+
7 Conclusion
|
| 683 |
|
| 684 |
+
In this work, we present Reflexion, an approach that leverages verbal reinforcement to teach agents
|
| 685 |
+
to learn from past mistakes. We empirically show that Reflexion agents significantly outperform
|
| 686 |
+
currently widely-used decision-making approaches by utilizing self-reflection.
|
| 687 |
+
In future work,
|
| 688 |
+
Reflexion could be used to employ more advanced techniques that have been thoroughly studied in
|
| 689 |
+
traditional RL settings, such as value learning in natural language or off-policy exploration techniques.
|
| 690 |
|
| 691 |
+
8 Reproducibility
|
| 692 |
|
| 693 |
+
We highly advise others to use isolated execution environments when running autonomous code
|
| 694 |
+
writing experiments as the generated code is not validated before execution.
|
| 695 |
|
| 696 |
+
9
|
| 697 |
|
| 698 |
+
References
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Press, second edition.
|
| 798 |
|
| 799 |
+
[26] Wei, J., Wang, X., Schuurmans, D., Bosma, M., Chi, E., Le, Q., and Zhou, D. (2022). Chain of
|
| 800 |
+
thought prompting elicits reasoning in large language models. arXiv preprint arXiv:2201.11903.
|
| 801 |
|
| 802 |
+
[27] Xie, Y., Kawaguchi, K., Zhao, Y., Zhao, X., Kan, M.-Y., He, J., and Xie, Q. (2023). Decomposi-
|
| 803 |
+
tion enhances reasoning via self-evaluation guided decoding. arXiv preprint arXiv:2305.00633.
|
| 804 |
|
| 805 |
+
[28] Yang, Z., Qi, P., Zhang, S., Bengio, Y., Cohen, W. W., Salakhutdinov, R., and Manning, C. D.
|
| 806 |
+
(2018). HotpotQA: A dataset for diverse, explainable multi-hop question answering. In Conference
|
| 807 |
+
on Empirical Methods in Natural Language Processing (EMNLP).
|
| 808 |
|
| 809 |
+
[29] Yao, S., Chen, H., Yang, J., and Narasimhan, K. (preprint). Webshop: Towards scalable
|
| 810 |
|
| 811 |
+
real-world web interaction with grounded language agents. In ArXiv.
|
| 812 |
|
| 813 |
+
[30] Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., and Cao, Y. (2023). ReAct:
|
| 814 |
+
Synergizing reasoning and acting in language models. In International Conference on Learning
|
| 815 |
+
Representations (ICLR).
|
| 816 |
|
| 817 |
+
[31] Yoran, O., Wolfson, T., Bogin, B., Katz, U., Deutch, D., and Berant, J. (2023). Answering
|
| 818 |
+
questions by meta-reasoning over multiple chains of thought. arXiv preprint arXiv:2304.13007.
|
| 819 |
|
| 820 |
+
11
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 821 |
|
| 822 |
+
A Evaluation with additional models
|
| 823 |
|
| 824 |
+
We further investigated the applicability of trial-and-error problem-solving with models of various
|
| 825 |
+
strengths. We found that the ability to specify self-corrections is an emergent quality of stronger,
|
| 826 |
+
larger models.
|
| 827 |
|
| 828 |
+
Approach Pass@1 accuracy (avg over 8 trials) Pass@1 accuracy (std)
|
| 829 |
|
| 830 |
+
Baseline
|
| 831 |
+
Reflexion
|
| 832 |
|
| 833 |
+
0.26
|
| 834 |
+
0.26
|
| 835 |
|
| 836 |
+
0.00481
|
| 837 |
+
0.00305
|
| 838 |
|
| 839 |
+
Table 4: Pass@1 accuracy on HumanEval Python using starchat-beta [13].
|
| 840 |
|
| 841 |
+
Model
|
| 842 |
|
| 843 |
+
Baseline accuracy Reflexion accuracy
|
| 844 |
|
| 845 |
+
CoT (GT) + text-davinci-003
|
| 846 |
+
CoT (GT) + gpt-3.5-turbo
|
| 847 |
+
CoT (GT) + gpt-4
|
| 848 |
+
ReAct + text-davinci-003
|
| 849 |
+
ReAct + gpt-3.5-turbo
|
| 850 |
+
ReAct + gpt-4
|
| 851 |
|
| 852 |
+
0.60
|
| 853 |
+
0.57
|
| 854 |
+
0.68
|
| 855 |
+
0.30
|
| 856 |
+
0.26
|
| 857 |
+
0.39
|
| 858 |
|
| 859 |
+
0.77
|
| 860 |
+
0.71
|
| 861 |
+
0.80
|
| 862 |
+
0.55
|
| 863 |
+
0.38
|
| 864 |
+
0.51
|
| 865 |
|
| 866 |
+
Table 5: Pass@1 accuracy on 100 HotPotQA using various models.
|
| 867 |
|
| 868 |
12
|
| 869 |
|
| 870 |
+
B Decision-making
|
| 871 |
+
|
| 872 |
+
Environment: You are in the middle of a room. Looking quickly around you, you see a bed 1, a desk
|
| 873 |
+
2, a desk 1, a drawer 6, a drawer 5, a drawer 4, a drawer 3, a drawer 2, a drawer 1, a garbagecan 1, a
|
| 874 |
+
laundryhamper 1, a safe 1, a shelf 6, a shelf 5, a shelf 4, a shelf 3, a shelf 2, and a shelf 1.
|
| 875 |
+
Task: examine the mug with the desklamp.
|
| 876 |
+
Trial #1
|
| 877 |
+
> think: To solve the task, I need to find and take a mug, then find and use a desklamp.
|
| 878 |
+
> think: First I need to find a mug. A mug is more likely to appear in drawer (1-6), desk (1-2), shelf
|
| 879 |
+
(1-6), garbagecan (1), laundryhamper (1). I can check one by one, starting with drawer 1.
|
| 880 |
+
> go to drawer 1
|
| 881 |
+
The drawer 1 is closed.
|
| 882 |
+
. . .
|
| 883 |
+
> open drawer 6
|
| 884 |
+
You open the drawer 6. The drawer 6 is open. In it, you see a keychain 2.
|
| 885 |
+
> go to desk 1
|
| 886 |
+
On the desk 1, you see a creditcard 3, a desklamp 1, a laptop 2, a mug 1, a pen 1, and a pencil 1.
|
| 887 |
+
> think: Now I find a mug (1). Next, I need to take it.
|
| 888 |
+
> take mug 1 from desk 1
|
| 889 |
+
You pick up the mug 1 from the desk 1.
|
| 890 |
+
> think: Now I take a mug (1). Next, I need to find a desklamp. A desklamp is more likely to appear
|
| 891 |
+
in desk (1-2), sidetable (1-2), shelf (1-6), bed (1), drawer (1-6). I can check one by one, starting with
|
| 892 |
+
desk 1.
|
| 893 |
+
> go to desk 1
|
| 894 |
+
Nothing happens.
|
| 895 |
+
> go to desk 2
|
| 896 |
+
On the desk 2, you see a alarmclock 1, a bowl 1, a mug 3, a pencil 3, and a pencil 2.
|
| 897 |
+
> think: Now I find a desklamp (1). Next, I need to use it.
|
| 898 |
+
> use desklamp 1
|
| 899 |
+
Nothing happens.
|
| 900 |
+
> use desklamp 1
|
| 901 |
+
Nothing happens.
|
| 902 |
+
Status: Fail
|
| 903 |
+
Reflection: In this environment, my plan was to find a mug then find and use a desklamp. However,
|
| 904 |
+
the task says to examine the mug with the desklamp. I should have looked for the desklamp first, then
|
| 905 |
+
looked for the mug. I noticed that the desklamp was found on desk 1. In the next trial, I will go to
|
| 906 |
+
desk 1, find the lamp, then look for the mug and examine it with the desklamp.
|
| 907 |
+
Trial #2
|
| 908 |
+
> go to desk 1
|
| 909 |
+
On the desk 1, you see a creditcard 3, a desklamp 1, a laptop 2, a mug 1, a pen 1, and a pencil 1.
|
| 910 |
+
> think: To solve the task, I need to find and take a mug, then find and use a desklamp.
|
| 911 |
+
> take mug 1 from desk 1
|
| 912 |
+
You pick up the mug 1 from the desk 1.
|
| 913 |
+
> think: To solve the task, I need to find and take a mug, then find and use a desklamp.
|
| 914 |
+
> use desklamp 1
|
| 915 |
+
You turn on the desklamp 1.
|
| 916 |
+
Status: Success
|
| 917 |
+
|
| 918 |
+
Figure 5: [Top] An AlfWorld trajectory in which the agent failed due to inefficient planning. In the
|
| 919 |
+
reflection, the agent recognizes that it should have looked for the desklamp then the mug, not the mug
|
| 920 |
+
then the desklamp. [Bottom] The agent is able to correct its reasoning trace and execute a sequence
|
| 921 |
+
of actions in a concise manner.
|
| 922 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 923 |
13
|
| 924 |
|
| 925 |
+
B.1 WebShop Limitation
|
|
|
|
|
|
|
| 926 |
|
| 927 |
+
In 5, we briefly state that Reflexion struggles to overcome local minima choices that require extremely
|
| 928 |
+
creative behavior to escape. We observe this shortcoming in an experiment on WebShop [29].
|
| 929 |
+
WebShop is a web-based problem-solving benchmark that tests agents to navigate an e-commerce
|
| 930 |
+
website to locate and purchase products given requests from clients. We test a two-shot ReAct +
|
| 931 |
+
Reflexion agent in 100 environments. However, after only four trials, we terminate the runs as the
|
| 932 |
+
agent does not show signs of improvement 6. Further, the agent does not generate helpful, intuitive
|
| 933 |
+
self-reflections after failed attempts. We conclude that Reflexion is unable to solve tasks that require
|
| 934 |
+
a significant amount of diversity and exploration. In AlfWorld, the agent is able to adequately explore
|
| 935 |
+
new environments because the permissible actions can be seen in the observations. In HotPotQA,
|
| 936 |
+
the agent faces a similar WebShop search query task but is more successful as the search space for
|
| 937 |
+
Wikipedia articles is more diverse and requires less precise search queries. A common problem for
|
| 938 |
+
e-commerce search engines is properly handling ambiguity in natural language search interpretations.
|
| 939 |
+
Thus, WebShop presents a task that requires very diverse and unique behavior from a Reflexion agent.
|
| 940 |
|
| 941 |
+
Figure 6: Reflexion vs React performance on WebShop across 100 customer shopping requests.
|
| 942 |
+
ReAct + Reflexion fails to significantly outperform ReAct.
|
| 943 |
|
| 944 |
+
C Programming
|
| 945 |
|
| 946 |
+
Programming LLM calls require strict instructions to produce function bodies only, due to the
|
| 947 |
+
extensive dialogue training of the LLMs. A few programming examples are reported below with
|
| 948 |
+
instructions highlighted in blue and templates. See the full implementation at https://github.
|
| 949 |
+
com/noahshinn024/reflexion.
|
| 950 |
|
| 951 |
+
C.1 Programming function implementation example (HumanEval Python)
|
| 952 |
|
| 953 |
+
Sample function signature:
|
| 954 |
|
| 955 |
+
1 def minSubArraySum ( nums ) :
|
| 956 |
+
2
|
| 957 |
|
| 958 |
+
"""
|
| 959 |
+
Given an array of integers nums , find the minimum sum of
|
| 960 |
|
| 961 |
+
3
|
| 962 |
|
| 963 |
+
4
|
| 964 |
|
| 965 |
+
5
|
| 966 |
|
| 967 |
+
6
|
| 968 |
|
| 969 |
+
any
|
| 970 |
|
| 971 |
+
non - empty sub - array of nums .
|
| 972 |
+
Example
|
| 973 |
+
minSubArraySum ([2 , 3 , 4 , 1 , 2 , 4]) == 1
|
| 974 |
|
| 975 |
+
14
|
| 976 |
|
| 977 |
+
0.00.51.01.52.02.53.0Trial Number0.100.150.200.250.300.350.400.450.50Proportion of Solved EnvironmentsWebShop Success RateReAct onlyReAct + Reflexion7
|
| 978 |
|
| 979 |
+
8
|
| 980 |
|
| 981 |
+
1
|
| 982 |
|
| 983 |
+
2
|
| 984 |
|
| 985 |
+
3
|
| 986 |
|
| 987 |
+
4
|
| 988 |
|
| 989 |
+
5
|
| 990 |
|
| 991 |
+
6
|
| 992 |
|
| 993 |
+
7
|
|
|
|
| 994 |
|
| 995 |
+
8
|
|
|
|
| 996 |
|
| 997 |
+
minSubArraySum ([ -1 , -2 , -3]) == -6
|
| 998 |
+
"""
|
| 999 |
|
| 1000 |
+
Sample function body implementation:
|
| 1001 |
|
| 1002 |
+
min_sum = float ( ’ inf ’)
|
| 1003 |
+
for i in range ( len ( nums ) ) :
|
| 1004 |
|
| 1005 |
+
current_sum = 0
|
| 1006 |
+
for j in range (i , len ( nums ) ) :
|
| 1007 |
+
current_sum += nums [ j ]
|
| 1008 |
+
if current_sum < min_sum :
|
| 1009 |
+
min_sum = current_sum
|
| 1010 |
|
| 1011 |
+
return min_sum
|
| 1012 |
|
| 1013 |
+
C.2 Reflexion Actor instruction
|
| 1014 |
|
| 1015 |
+
You are a Python writing assistant. You will be given your previous implementation of a function,
|
| 1016 |
+
a series of unit tests results, and your self-reflection on your previous implementation. Apply the
|
| 1017 |
+
necessary changes below by responding only with the improved body of the function. Do not include
|
| 1018 |
+
the signature in your response. The first line of your response should have 4 spaces of indentation so
|
| 1019 |
+
that it fits syntactically with the user provided signature. You will be given a few examples by the
|
| 1020 |
+
user.
|
| 1021 |
|
| 1022 |
+
Reflexion Actor generations follow the form:
|
| 1023 |
+
(Instruction)
|
| 1024 |
+
(Function implementation)
|
| 1025 |
+
(Unit test feedback)
|
| 1026 |
+
(Self-reflection)
|
| 1027 |
+
(Instruction for next function implmentation)
|
| 1028 |
|
| 1029 |
+
Full examples are shown in https://github.com/noahshinn024/reflexion
|
| 1030 |
|
| 1031 |
+
C.3 Reflexion Self-reflection instruction and example
|
| 1032 |
|
| 1033 |
+
You are a Python writing assistant. You will be given your previous implementation of a function,
|
| 1034 |
+
a series of unit tests results, and your self-reflection on your previous implementation. Apply the
|
| 1035 |
+
necessary changes below by responding only with the improved body of the function. Do not include
|
| 1036 |
+
the signature in your response. The first line of your response should have 4 spaces of indentation so
|
| 1037 |
+
that it fits syntactically with the user provided signature. You will be given a few examples by the
|
| 1038 |
+
user. Reflexion Self-Reflection generations follow the form:
|
| 1039 |
+
(Instruction)
|
| 1040 |
+
(Function implementation)
|
| 1041 |
+
(Unit test feedback)
|
| 1042 |
|
| 1043 |
+
C.4 Reflexion programming no Self-Reflection ablation example
|
| 1044 |
|
| 1045 |
+
Reflexion no Self-Reflection ablation Actor generations follow the form:
|
| 1046 |
+
(Instruction)
|
| 1047 |
+
(Function implementation)
|
| 1048 |
+
(Unit test feedback)
|
| 1049 |
+
(Self-reflection)
|
| 1050 |
+
(Instruction for next function implmentation)
|
| 1051 |
|
| 1052 |
+
C.5 Reflexion programming no test generation ablation example
|
| 1053 |
|
| 1054 |
+
Reflexion no test generation ablation Actor generations follow the form:
|
| 1055 |
+
(Instruction)
|
| 1056 |
|
| 1057 |
+
15
|
| 1058 |
|
| 1059 |
+
(Function implementation)
|
| 1060 |
+
(Unit test feedback)
|
| 1061 |
+
(Self-reflection)
|
| 1062 |
+
(Instruction for next function implmentation)
|
| 1063 |
+
|
| 1064 |
+
16
|
| 1065 |
+
|
| 1066 |
+
D Reasoning
|
| 1067 |
+
|
| 1068 |
+
D.1 Full example
|
| 1069 |
+
|
| 1070 |
+
Trial #2: Question: Grown-Ups starred the actor
|
| 1071 |
+
who was best known for which role on "’Allo
|
| 1072 |
+
’Allo!"?
|
| 1073 |
+
Thought 1: I need to search the actor who was
|
| 1074 |
+
best known for a role on "’Allo ’Allo!" and find
|
| 1075 |
+
out what role they were best known for.
|
| 1076 |
+
Action 1: Search[Grown-Ups]
|
| 1077 |
+
Observation 1: Grown-Ups is a 1980 British
|
| 1078 |
+
BBC television film devised and directed by
|
| 1079 |
+
It stars Lesley Manville, Philip
|
| 1080 |
+
Mike Leigh.
|
| 1081 |
+
Davis, Brenda Blethyn, Janine Duvitski, Lindsay
|
| 1082 |
+
Duncan and Sam Kelly. It was edited by Robin
|
| 1083 |
+
Sales and produced by Louis Marks for the BBC,
|
| 1084 |
+
and originally shown on BBC 2 on 28 November
|
| 1085 |
+
1980.
|
| 1086 |
+
Thought 2: The paragraph does not mention the
|
| 1087 |
+
actor who was best known for a role on "’Allo
|
| 1088 |
+
’Allo!". I need to search the actor’s name instead.
|
| 1089 |
+
Action 2: Search[Sam Kelly]
|
| 1090 |
+
Observation 2: Roger Michael Kelly (19 Decem-
|
| 1091 |
+
ber 1943 – 14 June 2014), known by the stage
|
| 1092 |
+
name Sam Kelly, was an English actor who ap-
|
| 1093 |
+
peared in film, television, radio and theatre. He
|
| 1094 |
+
is best known for his roles as Captain Hans Geer-
|
| 1095 |
+
ing in ’Allo ’Allo!, Warren in Porridge, Sam in
|
| 1096 |
+
On the Up, and Ted Liversidge in Barbara.
|
| 1097 |
+
Thought 3: Sam Kelly is best known for his role
|
| 1098 |
+
as Captain Hans Geering in "’Allo ’Allo!", so
|
| 1099 |
+
the answer is Captain Hans Geering.
|
| 1100 |
+
Action 3: Finish[Captain Hans Geering]
|
| 1101 |
+
Observation 3: Answer is CORRECT
|
| 1102 |
+
|
| 1103 |
+
Trial #1: Question: Grown-Ups starred the actor
|
| 1104 |
+
who was best known for which role on "’Allo
|
| 1105 |
+
’Allo!"?
|
| 1106 |
+
Thought 1: I need to search Grown-Ups and
|
| 1107 |
+
"’Allo ’Allo!", find the actor who starred in
|
| 1108 |
+
Grown-Ups, then find the role he was best known
|
| 1109 |
+
for in "’Allo ’Allo!".
|
| 1110 |
+
Action 1: Search[Grown-Ups]
|
| 1111 |
+
Observation 1: Grown-Ups is a 1980 British
|
| 1112 |
+
BBC television film devised and directed by
|
| 1113 |
+
Mike Leigh.
|
| 1114 |
+
It stars Lesley Manville, Philip
|
| 1115 |
+
Davis, Brenda Blethyn, Janine Duvitski, Lindsay
|
| 1116 |
+
Duncan and Sam Kelly. It was edited by Robin
|
| 1117 |
+
Sales and produced by Louis Marks for the BBC,
|
| 1118 |
+
and originally shown on BBC 2 on 28 November
|
| 1119 |
+
1980.
|
| 1120 |
+
Thought 2: Grown-Ups starred Lesley Manville,
|
| 1121 |
+
Philip Davis, Brenda Blethyn, Janine Duvitski,
|
| 1122 |
+
Lindsay Duncan and Sam Kelly. I need to search
|
| 1123 |
+
"’Allo ’Allo!" and find which actor was best
|
| 1124 |
+
known for which role.
|
| 1125 |
+
Action 2: Search["’Allo ’Allo!"]
|
| 1126 |
+
Observation 2: Could not find ["’Allo ’Allo!"].
|
| 1127 |
+
Similar: ["’Allo ’Allo!", "List of ’Allo ’Allo!
|
| 1128 |
+
characters", ’Gorden Kaye’, "’Allo ’Allo! (series
|
| 1129 |
+
2)", ’Allô, allô’, ’Francesca Gonshaw’, "’Allo
|
| 1130 |
+
’Allo! (series 4)", ’Kim Hartman’, "’Allo ’Allo!
|
| 1131 |
+
(series 6)", ’Jeremy Lloyd’]
|
| 1132 |
+
Thought 3: To find the actor who was best known
|
| 1133 |
+
for which role on "’Allo ’Allo!", I can search
|
| 1134 |
+
Gorden Kaye.
|
| 1135 |
+
Action 3: Search[Gorden Kaye]
|
| 1136 |
+
Observation 3: Gordon Irving Kaye (7 April
|
| 1137 |
+
1941 – 23 January 2017), known profession-
|
| 1138 |
+
ally as Gorden Kaye, was an English actor,
|
| 1139 |
+
best known for playing womanising café owner
|
| 1140 |
+
René Artois in the television comedy series ’Allo
|
| 1141 |
+
’Allo!.
|
| 1142 |
+
Thought 4: Gorden Kaye was best known for
|
| 1143 |
+
playing womanising café owner René Artois in
|
| 1144 |
+
the television comedy series "’Allo ’Allo!". So
|
| 1145 |
+
the answer is Rene Artois.
|
| 1146 |
+
Action 4: Finish[Rene Artois]
|
| 1147 |
+
Observation 4: Answer is INCORRECT
|
| 1148 |
+
Reflection: I searched the wrong title for the show, "’Allo ’Allo!", which resulted in no results. I
|
| 1149 |
+
should have searched the show’s main character, Gorden Kaye, to find the role he was best known for
|
| 1150 |
+
in the show.
|
| 1151 |
+
|
| 1152 |
+
Figure 7: Two HotPotQA trials within the same environment and task. The Reflexion + ReAct agent
|
| 1153 |
+
uses self-reflection to determine a better search method for the next trial.
|
| 1154 |
+
|
| 1155 |
+
17
|
| 1156 |
+
|
| 1157 |
+
D.2 Chain-of-Thought + Reflexion
|
| 1158 |
+
|
| 1159 |
+
Trial #2: Question: What profession does John
|
| 1160 |
+
Lanchester and Alan Dean Foster have in com-
|
| 1161 |
+
mon?
|
| 1162 |
+
Thought 1: Let’s think step by step. John Lanch-
|
| 1163 |
+
ester is a novelist, journalist, and financial jour-
|
| 1164 |
+
nalist. Alan Dean Foster is a novelist and screen-
|
| 1165 |
+
writer. So the profession John Lanchester and
|
| 1166 |
+
Alan Dean Foster have in common is novelist.
|
| 1167 |
+
Action 1: Finish[novelist]
|
| 1168 |
+
Observation 1: Answer is CORRECT
|
| 1169 |
+
|
| 1170 |
+
Trial #1: Question: What profession does John
|
| 1171 |
+
Lanchester and Alan Dean Foster have in com-
|
| 1172 |
+
mon?
|
| 1173 |
+
Thought 1: Let’s think step by step. John Lanch-
|
| 1174 |
+
ester is a novelist, journalist, and critic. Alan
|
| 1175 |
+
Dean Foster is a novelist and screenwriter. So
|
| 1176 |
+
the profession John Lanchester and Alan Dean
|
| 1177 |
+
Foster have in common is novelist and screen-
|
| 1178 |
+
writer.
|
| 1179 |
+
Action 1: Finish[novelist and screenwriter]
|
| 1180 |
+
Observation 1: Answer is INCORRECT
|
| 1181 |
+
Reflection: My reasoning for the profession John Lanchester and Alan Dean Foster have in common
|
| 1182 |
+
failed because I incorrectly assumed that they both had the same profession. In the future, when
|
| 1183 |
+
attempting this question, I should focus on better researching the individual backgrounds of both
|
| 1184 |
+
authors to ensure that I am accurately identifying their professions. Additionally, I should consider
|
| 1185 |
+
the possibility that they may have multiple professions in common.
|
| 1186 |
+
|
| 1187 |
+
D.3 HotPotQA Chain-of-Thought (GT) + Reflexion
|
| 1188 |
+
|
| 1189 |
+
Context: The Battle of White Plains was a battle in the New York and New Jersey campaign of the
|
| 1190 |
+
American Revolutionary War fought on October 28, 1776, near White Plains, New York. Following
|
| 1191 |
+
the retreat ...
|
| 1192 |
+
Trial #1: Question: What was a series of battles
|
| 1193 |
+
during the Revolutionary War, for control of New
|
| 1194 |
+
York City and the state of New Jersey, fought on
|
| 1195 |
+
October 28, 1776 near White Plains, New York?
|
| 1196 |
+
Thought 1: The question is asking about a se-
|
| 1197 |
+
ries of battles during the Revolutionary War for
|
| 1198 |
+
control of New York City and the state of New
|
| 1199 |
+
Jersey, fought on October 28, 1776 near White
|
| 1200 |
+
Plains, New York. From the context, I know that
|
| 1201 |
+
this was the Battle of White Plains.
|
| 1202 |
+
Action 1: Finish[Battle of White Plains]
|
| 1203 |
+
Observation 1: Answer is INCORRECT
|
| 1204 |
+
|
| 1205 |
+
Trial #2: Question: What was a series of battles
|
| 1206 |
+
during the Revolutionary War, for control of New
|
| 1207 |
+
York City and the state of New Jersey, fought on
|
| 1208 |
+
October 28, 1776 near White Plains, New York?
|
| 1209 |
+
Thought 1: The question is asking for a series of
|
| 1210 |
+
battles during the Revolutionary War, for control
|
| 1211 |
+
of New York City and the state of New Jersey,
|
| 1212 |
+
fought on October 28, 1776 near White Plains,
|
| 1213 |
+
New York. Based on the context, I know that
|
| 1214 |
+
this series of battles was the New York and New
|
| 1215 |
+
Jersey campaign.
|
| 1216 |
+
Action 1: Finish[The New York and New Jersey
|
| 1217 |
+
campaign]
|
| 1218 |
+
Observation 1: Answer is CORRECT
|
| 1219 |
+
|
| 1220 |
+
Reflection: Upon reflecting on the incorrect answer I provided, I realize that I may not have provided
|
| 1221 |
+
enough context to accurately answer the question. The question asked for a series of battles, but I
|
| 1222 |
+
only provided the name of one battle. To better answer this question in the future, I will make sure to
|
| 1223 |
+
provide more context, such as the name of the campaign, which was the New York and New Jersey
|
| 1224 |
+
campaign, and the fact that it was a series of battles. Additionally, I will make sure to include the
|
| 1225 |
+
dates of the battles, as well as the locations, to ensure that my answer is comprehensive and accurate.
|
| 1226 |
+
|
| 1227 |
+
18
|
| 1228 |
+
|
| 1229 |
+
D.4 HotPotQA episodic memory (EPM) ablation prompts
|
| 1230 |
+
|
| 1231 |
+
D.4.1
|
| 1232 |
+
|
| 1233 |
+
(EPM) Chain-of-Thought + Reflexion
|
| 1234 |
+
|
| 1235 |
+
Trial #1: Question: Which of Jonny Craig and
|
| 1236 |
+
Pete Doherty has been a member of more bands
|
| 1237 |
+
?
|
| 1238 |
+
Thought 1: Let’s think step by step. Jonny
|
| 1239 |
+
Craig has been a member of six bands, including
|
| 1240 |
+
Emarosa, Dance Gavin Dance, and Slaves. Pete
|
| 1241 |
+
Doherty has been a member of seven bands, in-
|
| 1242 |
+
cluding The Libertines, Babyshambles, and The
|
| 1243 |
+
Puta Madres. So Pete Doherty has been a mem-
|
| 1244 |
+
ber of more bands.
|
| 1245 |
+
Action 1: Finish[Pete Doherty]
|
| 1246 |
+
Observation 1: Answer is INCORRECT
|
| 1247 |
+
|
| 1248 |
+
Trial #2: Question: Which of Jonny Craig and
|
| 1249 |
+
Pete Doherty has been a member of more bands
|
| 1250 |
+
?
|
| 1251 |
+
Thought 1: Let’s think step by step. I will re-
|
| 1252 |
+
search the past and current bands of both musi-
|
| 1253 |
+
cians to ensure that I am accurately comparing
|
| 1254 |
+
their band memberships. After researching, I
|
| 1255 |
+
have found that Jonny Craig has been a mem-
|
| 1256 |
+
ber of seven bands, including Emarosa, Dance
|
| 1257 |
+
Gavin Dance, and Slaves. Pete Doherty has been
|
| 1258 |
+
a member of seven bands, including The Lib-
|
| 1259 |
+
ertines, Babyshambles, and The Puta Madres. So
|
| 1260 |
+
Jonny Craig has been a member of more bands.
|
| 1261 |
+
Action 2: Finish[Jonny Craig]
|
| 1262 |
+
Observation 2: Answer is CORRECT
|
| 1263 |
+
|
| 1264 |
+
Reflection: My reasoning for which musician has been a member of more bands failed because I did
|
| 1265 |
+
not take into account that Jonny Craig has been a member of more bands in the past, even though Pete
|
| 1266 |
+
Doherty is currently a member of more bands. In the future, when attempting this question, I should
|
| 1267 |
+
focus on researching the past and current bands of both musicians to ensure that I am accurately
|
| 1268 |
+
comparing their band memberships.
|
| 1269 |
+
|
| 1270 |
+
D.4.2
|
| 1271 |
+
|
| 1272 |
+
(EPM) Chain-of-Thought (GT) + Reflexion
|
| 1273 |
+
|
| 1274 |
+
Context: Hari Bahadur Basnet is a Nepalese politician. He is the head of the Foreign Relations
|
| 1275 |
+
Department of the Rastriya Janashakti Party. Basnet holds a M.Sc. in Engineering.
|
| 1276 |
+
A Master of Science (Latin: "Magister Scientiae" ; abbreviated MS, M.S., MSc, M.Sc., MSci, M.Sci.,
|
| 1277 |
+
ScM, Sc.M., SciM or Sci.M.) is a master’s degree in the field of science...
|
| 1278 |
+
Trial #1: Question: The head of the Foreign
|
| 1279 |
+
Relations Department of the Rastriya Janashakti
|
| 1280 |
+
Party holds a degree that can be abbreviated MS,
|
| 1281 |
+
M.S., or ScM, in what field?
|
| 1282 |
+
(Previous trajectory)
|
| 1283 |
+
|
| 1284 |
+
Trial #2: Question: The head of the Foreign Re-
|
| 1285 |
+
lations Department of the Rastriya Janashakti
|
| 1286 |
+
Party holds a degree that can be abbreviated MS,
|
| 1287 |
+
M.S., or ScM, in what field?
|
| 1288 |
+
(Previous trajectory)
|
| 1289 |
+
Thought 1: The question is asking what field
|
| 1290 |
+
of study the head of the Foreign Relations De-
|
| 1291 |
+
partment of the Rastriya Janashakti Party holds
|
| 1292 |
+
a degree in. From the context, I know that the
|
| 1293 |
+
degree is a Master of Science degree, which is
|
| 1294 |
+
typically granted for studies in sciences, engi-
|
| 1295 |
+
neering, and medicine. However, the question
|
| 1296 |
+
is asking for the field of study, not the degree.
|
| 1297 |
+
Based on the context, I know that Hari Bahadur
|
| 1298 |
+
Basnet holds a M.Sc. in Engineering.
|
| 1299 |
+
Action 1: Finish[Engineering]
|
| 1300 |
+
Observation 1: Answer is CORRECT
|
| 1301 |
+
|
| 1302 |
+
Thought 1: The question is asking what field
|
| 1303 |
+
of study the head of the Foreign Relations
|
| 1304 |
+
Department of the Rastriya Janashakti Party
|
| 1305 |
+
holds a degree in. From the context, I know
|
| 1306 |
+
that the degree is a Master of Science degree,
|
| 1307 |
+
which is typically granted for studies in sciences,
|
| 1308 |
+
engineering, and medicine.
|
| 1309 |
+
Action 1: Finish[Sciences, Engineering, and
|
| 1310 |
+
Medicine]
|
| 1311 |
+
Observation 1: Answer is INCORRECT
|
| 1312 |
+
|
| 1313 |
+
Reflection: For the first trial, I misunderstood the question. I thought the question was asking for a
|
| 1314 |
+
category of degrees, rather than a specific degree. I learned from my mistake and in the second trial, I
|
| 1315 |
+
focused more closely on the question to understand that it was asking for a specific field of study.
|
| 1316 |
+
|
| 1317 |
+
19
|
| 1318 |
|
q106/random_k4/random_4.md
CHANGED
|
@@ -1 +1,809 @@
|
|
| 1 |
-
OREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)IntroductionClimate & Health Vulnerability AssessmentPURPOSEThis vulnerability assessment is intended to inform public health professionals and community partners engaged in climate change adaptation and resilience planning. It focuses specifically on social vulnerability as a way to integrate the concepts of social determinants of health and environmental justice into climate change planning.PROCESSThe Climate and Health Program developed this assessment in consultation with other grantees of the CDC’s Climate Ready States and Cities Initiative. The assessment is based on associations identified in research literature, which are summarized in the 2014 Oregon Climate and Health Profile Report.The Climate and Health Program envisions this assessment being updated and expanded as our knowledge grows and conditions change. This first edition, published in Fall 2015, is limited to measures of population sensitivity. In the future, we anticipate adding measures of hazard exposure such as extreme heat, and adaptive capacity, such as access to air conditioning. Additionally, we hope to expand the composite vulnerability index in subsequent assessments to incorporate more measures of vulnerability, and we hope to add context by analyzing the key drivers in each community.We acknowledge that maps of social and demographic characteristics do not tell the whole story. For example, there may be strengths that enable some communities to readily overcome vulnerabilities. This assessment is just one of many pieces of information that can help Oregon’s public health system prepare for the impacts of climate change.FOR MORE INFORMATIONContact:Climate and Health Programbrendon.haggerty@state.or.us(971) 673-0335Or visit:healthoregon.org/climateOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivitySocial vulnerabilityABOUT THIS INDICATORThis index is a combination eleven indicators of social vulnerability including measures of demographics, socioeconomic status, and health. The indicators are drawn from US Census data and health statistics from the Oregon Health Authority. Each indicator is equally weighted, and the index is relative to other census tracts in the state. Census tracts shaded dark blue represent areas with higher social vulnerability. These tracts are distributed in many parts of the state, and largely overlap with broad indicators of socioeconomic status such as educational attainment.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYIndexes such as this one are based on the work of Susan Cutter (1), which established associations between natural hazards and indicators of social vulnerability. They are used to help understand vulnerability to climate impacts in many jurisdictions (2, 3).DATA SOURCESOregon Climate & Health Program, Public Health Division, Oregon Health Authority. July 2015.See bibliography for references.For more information, visit healthoregon.org/climateComposite vulnerability indexCensus TractsLowMediumHighCounty borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityBirth outcomesABOUT THIS INDICATORThe percentage of births that are pre-term is an indicator of risks for infants calculated from birth certificate records. While darker blue represents a larger percent of preterm births, counties are mostly similar on this metric, varying between about 6% and 11%.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYPreterm births are associated with extreme heat (1) and air pollution (2). Moreover, adverse birth outcomes like preterm birth or low birth weight are associated with problems during early childhood (3) as well as long term health effects including risk of cardiovascular disease (4). Existing illness such as those linked to adverse birth outcomes result in greater vulnerability to negative health impacts of climate change.DATA SOURCESBirth Risk Factors: Oregon Birth Certificates, Center for Health Statistics, Center for Public Health Practice, Public Health Divsion, Oregon Health Authority.See bibliography for references.For more information, visit healthoregon.org/climatePercent of infants born <36 weeks of pregnancyCounties6.2% - 7.4%7.5% - 8.1%8.2% - 10.5%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityChildrenABOUT THIS INDICATORThe population of the youngest Oregon residents is unevenly distributed, as reflected in the above map showing the percent of the population within under age 18. Darker blue tracts indicate higher concentrations of children. Statewide, 22% of the population is under 18 years of age.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYInfants and children are vulnerable to multiple climate impacts. Young children are more susceptible to extreme heat (1). Children are more vulnerable to environmental toxins of all types, since the same dose given to an adult is lower in proportion to body size (2). This makes children more sensitive to contaminated food, water, and air resulting from impacts of climate change. One study estimated that 88% of the additional burden of disease due to climate change falls upon children (3).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of population aged less than 18 yearsCensus tracts0% - 19.2%19.3% - 24.2%24.3% - 38.1%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityChronic DiseaseABOUT THIS INDICATORBody Mass Index (BMI) is a population-level indicator of obesity levels. The estimates in the map above are derived from de-identified driver license data, adjusted for age, and averaged over whole census tracts. BMI is indicative of chronic illness, since it is closely associated with diseases such as diabetes, cardiovascular disease, and depression.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYPeople with existing illness are more vulnerable to climate change impacts because the changing climate has potential to exacerbate many conditions. For example, extreme heat increases the risk of heat-related death for those with diabetes (1), and air quality issues arising from heat or wildfire can worsen asthma symptoms (2). Moreover, extreme weather events such as floods and landslides can disrupt care and access to needed medication (3).DATA SOURCESOregon Environmental Public Health Tracking. 2015.[data files]. Available at www.epht.oregon.govSee bibliography for references.For more information, visit healthoregon.org/climateCensus tracts0.0 - 26.226.3 - 27.127.2 - 30.4County borders05010025MilesAge-adjusted mean body mass indexOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityEducational AttainmentABOUT THIS INDICATORThe percent of adults aged 25 years or over without a high school diploma is a common measure of educational attainment collected by the US Census Bureau. In other jurisdictions, this indicator was found to be a primary driver of social vulnerability (1). This map displays the percentage of adults in each census tract who do not have a high school diploma or equivalent. Dark blue census tracts reflect higher percentages of adults with low educational attainment.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYLow educational attainment is associated with greater vulnerability to heat related illness (2, 3, 4) and exposure to air pollution (5,6). As noted in the Oregon Climate and Health Profile Report, exposure to these hazards is likely to increase in Oregon as a result of climate change.DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of adults aged 25+ without a high school diplomaCensus tracts0% - 6.7%6.8% - 12%12.1% - 56.3%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityForeign-born populationABOUT THIS INDICATORThis indicator is a partial substitute for indicators of vulnerability used in other assessments (1). The percent of the population born outside the US is indicative of potential linguistic isolation or citizenship status. In this map, areas of darkest blue represent the highest percentages of people born outside the US. These tracts are found primarily in the Willamette Valley and Columbia River Gorge.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYThis indicator is suggests linguistic isolation, limited capacity to access resources, and potential difficulty asserting labor and housing rights. Together, these traits are associated with vulnerability to a range of climate-related hazards, including heat related illness, extreme weather, and occupational exposures (2).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of population born outside of the United StatesCensus tracts0% - 4.6%4.7% - 10.1%10.2% - 44.7%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityIsolated older adultsABOUT THIS INDICATORThe percent of households that are single-person aged 65 years or older indicates the co-occurrence of two types of vulnerability: advanced age and social isolation. Social isolation can take many forms, but this indicator from the census is among the most readily available. The map above shows high percentages of single-person older adult households in dark blue. Unlike the percent of adults aged 65 or older, the percentage of single-person older householders shows a less distinct spatial pattern.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYSocial isolation can result in a lack of supportive contact networks that can be relied upon in extreme conditions. This indicator is associated with greater vulnerability to extreme heat (1, 2).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of households that are single-person aged 65 years or olderCensus tracts0% - 7%7.1% - 11.1%11.2% - 40.3%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityOlder adultsABOUT THIS INDICATORIn the above map, dark blue represents areas with higher percentages of older adults. A very clear pattern is present: there are higher percentages of older adults in rural areas. The lowest percentages are found in the state’s urban areas in the Willamette Valley, Central Oregon, and near Medford.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYOlder adults are more vulnerable to multiple hazards, especially extreme heat (1, 2, 3). This is partly because of the decreased ability to regulate body temperature that normally comes with age. Risk is elevated for many older adults because of medications or chronic conditions such as diabetes or cardiovascular disease. As a result, older adults have the highest rates of heat-related illness and heat-related death. Older adults are also more vulnerable to poor air quality and infectious diseases related to climate change (4).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of population aged 65 years or olderCensus tracts0% - 11%11.1% - 17.1%17.2% - 46%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityRace and ethnicityABOUT THIS INDICATORThis indicator measures the proportion of the population who identifies as a race or ethnicity other than non-Hispanic white. Greater percentages are represented by darker shades of blue. Diverse communities are found across Oregon, with some greater concentrations in the lower Willamette Valley, North Central area, and parts of Eastern and Southern Oregon.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYOregon’s communities of color are already disproportionately burdened by illness and lack of access to health-supportive resources (1). Research suggests ways communities of color are more vulnerable to certain climate hazards, including: greater sensitivity and exposure to air pollutants (2, 3), fewer resources for recovery from extreme weather events (4), and inadequacy of existing warning systems (5).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent identifying as a race other than non-Hispanic whiteCensus tracts0% - 15.9%16% - 27.2%27.3% - 97.2%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivitySocioeconomic statusABOUT THIS INDICATORThe percent of households earning less than 200% of the federal poverty level is an indicator of socioeconomic status at the census tract level. In 2015, the poverty level for a family of 4 was about $24,000. Low-income households are part of communities throughout Oregon.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYLow-income households have few resources to cope with climate-related health impacts. Compared to wealthier households, disasters have a greater impact on low-income populations as a result of geographic isolation, type of residence and social exclusion (1). Lower income households are more likely to live in urban heat islands, have higher exposure to air pollutants, and are less likely to be able to afford protective measures like air conditioning (2, 3, 4).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of households with incomes <200% of Federal Poverty LevelCensus tracts0% - 29.1%29.2% - 42.2%42.3% - 91.7%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityTenureABOUT THIS INDICATORThe US Census Bureau provides estimates of the proportion of occupied housing units that are occupied by renters. In this map, dark blue tracts represent areas with a high proportion of renters. While it may appear to be a small number of tracts, they are overwhelmingly concentrated in urban areas with greater density. The dark blue tracts represent 1/3 of Oregon’s population.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYRenters are less able to mitigate climate threats by investing time, labor, and equipment in protective measures. This is attributed to financial barriers and lack of incentive to engage in protective maintenance (e.g. removing trees that elevate fire risk) (1).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of housing occupants occupied by rentersCensus tracts0% - 27.2%27.3% - 42%42.1% - 100%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityUnemploymentABOUT THIS INDICATOREmployment status is commonly included in measures of vulnerability (1). The American Community Survey provides estimates of the percent of the population age 16 years or older who are unemployed. On the above map, darker shades of blue represent greater unemployment rates. Tracts with high unemployment are distributed throughout the state.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYLike other indicators of socioeconomic status, the percentage of adults who are unemployed helps to illustrate peoples’ capacity to cope with climate stressors. This indicator also provides a baseline by which we can judge whether changes to the economy resulting from climate instability are affecting workers. Additionally, there is evidence that employment status shapes migration patterns (2).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of population aged 16 years or older who are unemployedCensus tracts0% - 9%9.1% - 12.8%12.9% - 32.6%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)BibliographyBIRTH OUTCOMES1. Basu R., Malig B., Ostro B. (2010) High Ambient Temperature and the Risk of Preterm Delivery. American Journal of Epidemiology,172:1108–172. Fleischer, N.L., Merialdi, M., van Donkelaar, A., Vadillo-Ortega, F., Martin, R.V., Betran, A. P., & Souza, J. P. (2014). Outdoor air pollution, preterm birth, and low birth weight: analysis of the world health organization global survey on maternal and perinatal health. Environmental Health Perspectives, 122(4), 425.3. Kramer, M.S., Demissie, K., Yang, H., Platt, R.W., Sauvé, R., & Liston, R. (2000). The contribution of mild and moderate preterm birth to infant mortality. Journal of the American Medical Association, 284(7), 843-849.4. Rogers, L. K., & Velten, M. (2011). Maternal inflammation, growth retardation, and preterm birth: insights into adult cardiovascular disease. Life Sciences,89(13), 417-421.CHILDREN1. Sheffield P.E., Knowlton K., Carr J.L., Kinney P.L. (2011). Modeling of regional climate change effects on ground-level ozone and childhood asthma. American Journal of Preventive Medicine, 41:251–72. Basu, R. (2009). High ambient temperature and mortality: a review of epidemiologic studies from 2001 to 2008. Environmental Health, 8(1), 40.3. U.S. Environmental Protection Agency. America’s Children and the Environment [Internet]. (2000). Available from: http://yosemite.epa.gov/ochp/ochpweb.nsf/content/ACE-Report.htm/$File/ ACE-Report.pdfCHRONIC DISEASE1. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Diez-Roux, A.V., Brown, D.G., & Schwartz, J.D. (2009). Mapping community determinants of heat vulnerability. Environmental Health Perspectives, 117(11):1730-1736 2. Gent J.F., Triche E.W., Holford T.R., Belanger K., Bracken M.B., Beckett W.S., et al. Association of low-level ozone and fine particles with respiratory symptoms in children with asthma. Journal of the American Medical Association. 2003;290:1859– 67.3. Kessler R.C. (2007).Hurricane Katrina’s impact on the care of survivors with chronic medical conditions. Journal of General Internal Medicine, 22:1225–30.EDUCATIONAL ATTAINMENT1. Cooley, H., & Pacifica Institute. (2012). Social vulnerability to climate change in California. California Energy Commission.2. O’Neill, M. S., Zanobetti, A., & Schwartz, J. (2003). Modifiers of the temperature and mortality association in seven US cities. American Journal of Epidemiology, 157(12), 1074-1082.3. Basu, R. (2009). High ambient temperature and mortality: a review of epidemiologic studies from 2001 to 2008. Environmental Health, 8(1), 40.4. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Diez-Roux, A.V., Brown, D.G., & Schwartz, J.D. (2009). Mapping community determinants of heat vulnerability. Environmental Health Perspectives, 117(11):1730-1736 5. Krewski, D., R. T. Burnett, et al. (2000). Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of Particulate Air Pollution and Mortality. Boston, Massachusetts: Health Effects Institute.6. Pope III, C. A., & Dockery, D. W. (2006). Health effects of fine particulate air pollution: lines that connect. Journal of the Air & Waste Management Association, 56(6), 709-742FOREIGN-BORN POPULATION1. Cooley, H., & Pacifica Institute. (2012). Social vulnerability to climate change in California. California Energy Commission.2. Shonkoff, S. B., Morello-Frosch, R., Pastor, M., & Sadd, J. (2011). The climate gap: environmental health and equity implications of climate change and mitigation policies in California—a review of the literature. Climatic Change,109(1), 485-503.ISOLATED OLDER ADULTS1. McGeehin, M. A., & Mirabelli, M. (2001). The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States. Environmental health perspectives, 109(Suppl 2), 185.2. English, P. B., Sinclair, A. H., Ross, Z., Anderson, H., Boothe, V., Davis, C., Ebi, K., Kagey, B., Malecki, K., Shultz, R.m & Simms, E. (2009). Environmental health indicators of climate change for the United States: findings from the State Environmental Health Indicator Collaborative. Environmental Health Perspectives, 117(11), 1673-81.OLDER ADULTS1. Knowlton, K., Rotkin-Ellman, M., King, G., Margolis, H.G., Smith, D., Solomon, G., Trent R., & English, P. (2009). The 2006 California heat wave: impacts on hospitalizations and emergency department visits. Environmental Health Perspectives,117(1), 61-67.2. Basu, R., & Ostro, B. D. (2008). A multicounty analysis identifying the populations vulnerable to mortality associated with high ambient temperature in California. American Journal of Epidemiology, 168(6), 632-637.3. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Diez-Roux, A.V., Brown, D.G., & Schwartz, J.D. (2009). Mapping community determinants of heat vulnerability. Environmental Health Perspectives, 117(11):1730-1736 4. Gamble, J. L., Hurley, B. J., Schultz, P. A., Jaglom, W. S., Krishnan, N., & Harris, M. (2013). Climate change and older Americans: state of the science. Environmental Health Perspectives, 121(1), 15-22.OREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Bibliography - continuedRACE AND ETHNICITY1. Oregon Health Authority. State of Equity Report [Internet]. 2013. Available from: http://www.oregon.gov/ oha/oei/Pages/soe.aspx2. Gwynn R.C., Thurston G.D. (2001). The burden of air pollution: impacts among racial minorities. Environmental Health Perspectives,109 Suppl 501–6.3. Medina-Ramón M., Schwartz J. (2008). Who is more vulnerable to die from ozone air pollution? Epidemiology,19:672–9.4. Toldson I.A., Ray K., Hatcher S.S., Louis L.S. (2011). Examining the long-term racial disparities in health and economic conditions among Hurricane Katrina survivors: Policy implications for Gulf Coast recovery. Journal of Black Studies, 42:360–78.5. Hayden M.H., Drobot S., Radil S., Benight C., Gruntfest E.C., Barnes L.R. (2007). Information sources for flash flood warnings in Denver, CO and Austin, TX. Environmental Hazards, 7:211SOCIAL VULNERABILITY1. Cutter, S.L., Boruff, B.J., & Shirley, W.L. (2003). Social vulnerability to environmental hazards. Social Science Quarterly, 84(2), 242-261.2. Cooley, H., & Pacifica Institute. (2012). Social vulnerability to climate change in California. California Energy Commission.3. Minnesota Department of Health. 2014. Minnesota Climate Change Vulnerability Assessment 2014. October 2014, Saint Paul, MNSOCIOECONOMIC STATUS1. Fothergill A, Peek LA. (2004). Poverty and Disasters in the United States: A Review of Recent Sociological Findings. Natural Hazards, 32:89–1102. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Diez-Roux, A.V., Brown, D.G., & Schwartz, J.D. (2009). Mapping community determinants of heat vulnerability. Environmental Health Perspectives, 117(11):1730-1736 3. Basu, R., & Ostro, B.D. (2008). A multicounty analysis identifying the populations vulnerable to mortality associated with high ambient temperature in California. American Journal of Epidemiology, 168(6), 632-637.4. Harlan S.L., Brazel A.J., Prashad L., Stefanov W.L., Larsen L. (2006). Neighborhood microclimates and vulnerability to heat stress. Social Science and Medicine, 63:2847–63.TENURE1.Collins, Timothy W., & Bolin, B. (2009). Situating hazard vulnerability: people’s negotiations with wildfire environments in the US Southwest. Environmental Management, 44.3: 441-455.UNEMPLOYMENT1. Cutter, S.L., Boruff, B.J., & Shirley, W L. (2003). Social vulnerability to environmental hazards. Social Science Quarterly, 84(2), 242-261.2. Reuveny, R. (2007). Climate change-induced migration and violent conflict. Political Geography, 26(6), 656-673.
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|
| 1 |
+
Take-Two Interactive Software, Inc. Reports Results for Fiscal Third Quarter 2026
|
| 2 |
+
February 3, 2026 at 4:05 PM EST
|
| 3 |
+
Company raises fiscal year 2026 outlook
|
| 4 |
+
Fiscal third quarter Net Bookings were $1.76 billion, above Company's guidance range
|
| 5 |
+
Net Bookings for fiscal year 2026 are now expected to range from $6.65 to $6.7 billion
|
| 6 |
+
NEW YORK--(BUSINESS WIRE)--Feb. 3, 2026-- Take-Two Interactive Software, Inc. (NASDAQ:TTWO) today reported results for the third quarter of
|
| 7 |
+
its fiscal year 2026, ended December 31, 2025. For further information, please see the third quarter fiscal 2026 results slide deck posted to the
|
| 8 |
+
Company’s investor relations website at take2games.com/ir.
|
| 9 |
+
CEO Comments
|
| 10 |
+
Strauss Zelnick, Chairman and CEO of Take-Two Interactive, stated: “Our outstanding third quarter results reflect outperformance from all of our
|
| 11 |
+
labels, and we are once again raising our Net Bookings outlook for Fiscal 2026. With ongoing momentum across many of our businesses, and the
|
| 12 |
+
highly anticipated launch of Grand Theft Auto VI on November 19th, we continue to project record levels of Net Bookings in Fiscal 2027, which we
|
| 13 |
+
believe will establish a new financial baseline for our business, set us on a path to enhanced profitability, and provide further balance sheet strength
|
| 14 |
+
and flexibility.”
|
| 15 |
+
Third Quarter Fiscal 2026 Financial and Operational Highlights
|
| 16 |
+
Total Net Bookings* grew 28% to $1.76 billion, compared to $1.37 billion during last year’s fiscal third quarter.
|
| 17 |
+
Net Bookings from recurrent consumer spending** grew 23% and accounted for 76% of total Net Bookings.
|
| 18 |
+
The largest contributors to Net Bookings were NBA® 2K26, Grand Theft Auto® Online and Grand Theft Auto V,
|
| 19 |
+
Toon Blast™, Match Factory!™, Empires & Puzzles™, Color Block Jam™, Red Dead Redemption® 2 and Red
|
| 20 |
+
Dead Online, Red Dead Redemption® and Undead Nightmare, Words With Friends™, WWE® 2K25, and Toy
|
| 21 |
+
Blast™.
|
| 22 |
+
GAAP net revenue was $1.70 billion, compared to $1.36 billion in last year’s fiscal third quarter.
|
| 23 |
+
Recurrent consumer spending** increased 20% and accounted for 77% of total GAAP net revenue.
|
| 24 |
+
The largest contributors to GAAP net revenue were NBA 2K26 and NBA 2K25, Grand Theft Auto Online and Grand
|
| 25 |
+
Theft Auto V, Toon Blast, Match Factory!, Empires & Puzzles, Color Block Jam, Red Dead Redemption and
|
| 26 |
+
Undead Nightmare, Red Dead Redemption 2 and Red Dead Online, Words With Friends, WWE 2K25, and
|
| 27 |
+
Borderlands® 4.
|
| 28 |
+
GAAP net loss was $92.9 million, or $0.50 per share, as compared to $125.2 million, or $0.71 per share, for the
|
| 29 |
+
comparable period last year.
|
| 30 |
+
* Net Bookings is our operational metric and defined as the net amount of products and services sold digitally or sold-in physically during the period,
|
| 31 |
+
and includes licensing fees, merchandise, in-game advertising, strategy guides and publisher incentives.
|
| 32 |
+
** Recurrent consumer spending is generated from ongoing consumer engagement and includes virtual currency, add-on content, in-game purchases
|
| 33 |
+
and in-game advertising
|
| 34 |
+
Third Quarter Fiscal 2026 Financial Results
|
| 35 |
+
The following data is used internally by the Company’s management and Board of Directors to adjust the Company’s GAAP and Non-GAAP financial
|
| 36 |
+
results in order to facilitate comparison of its operating performance between periods and to better understand its core business:
|
| 37 |
+
Three Months Ended December 31, 2025
|
| 38 |
+
Financial Data
|
| 39 |
+
|
| 40 |
+
Change in deferred
|
| 41 |
+
Amortization of
|
| 42 |
+
Statement of net revenue and Stock-based Business Business Other
|
| 43 |
+
| in millions | | | | acquired | | | |
|
| 44 |
+
| ----------- | --- | --- | --- | --------- | --- | --- | --- |
|
| 45 |
+
Operations related cost of compensation reorganization acquisition (a)
|
| 46 |
+
intangibles
|
| 47 |
+
revenue
|
| 48 |
+
| GAAP | | | | | | | |
|
| 49 |
+
| ----------------- | --------- | ------ | ------ | -------- | --- | --- | --- |
|
| 50 |
+
| Total net revenue | $1,699.0 | 58.0 | | | | | |
|
| 51 |
+
| Cost of revenue | 753.5 | (3.1) | (3.6) | (160.7) | | | |
|
| 52 |
+
| Gross profit | 945.5 | 61.1 | 3.6 | 160.7 | | | |
|
| 53 |
+
Operating
|
| 54 |
+
| | 984.2 | | (86.7) | (15.1) | (0.6) | (4.0) | |
|
| 55 |
+
| --- | ------ | --- | ------- | ------- | ------ | ------ | --- |
|
| 56 |
+
expenses
|
| 57 |
+
(Loss) income
|
| 58 |
+
| | (38.7) | 61.1 | 90.3 | 175.8 | 0.6 | 4.0 | |
|
| 59 |
+
| --- | ------- | ----- | ----- | ------ | ---- | ---- | --- |
|
| 60 |
+
from operations
|
| 61 |
+
Interest and other,
|
| 62 |
+
| | (17.1) | (1.6) | | | | 4.5 | 0.1 |
|
| 63 |
+
| --- | ------- | ------ | --- | --- | --- | ---- | ---- |
|
| 64 |
+
net
|
| 65 |
+
(Loss) income
|
| 66 |
+
| before income | (55.8) | 59.6 | 90.3 | 175.8 | 0.6 | 8.5 | 0.1 |
|
| 67 |
+
| ------------- | ------- | ----- | ----- | ------ | ---- | ---- | ---- |
|
| 68 |
+
taxes
|
| 69 |
+
| | | | | | | | |
|
| 70 |
+
| -------- | ------ | ----- | ----- | --- | ---- | ---- | ---- |
|
| 71 |
+
| Non-GAAP | | | | | | | |
|
| 72 |
+
| EBITDA | 174.8 | 59.6 | 90.3 | | 0.6 | 6.5 | 0.1 |
|
| 73 |
+
The above table utilizes a management tax rate of 18%
|
| 74 |
+
Share count used to calculate management reporting diluted net income per share is 186.5 million
|
| 75 |
+
(a) Other includes adjustments for (i) the revaluation of the Turkish Lira against the U.S. Dollar and (ii) fair value adjustments related to certain equity
|
| 76 |
+
investments.
|
| 77 |
+
Outlook for Fiscal Year 2026
|
| 78 |
+
Take-Two is raising its outlook for the fiscal year and providing its initial outlook for its fiscal fourth quarter ending March 31, 2026:
|
| 79 |
+
Fiscal Year Ending March 31, 2026
|
| 80 |
+
The Company is also providing selected data, which is used internally by its management and Board of Directors to adjust the Company’s GAAP and
|
| 81 |
+
Non-GAAP financial outlook in order to facilitate comparison of its operating performance between periods and to better understand its core business
|
| 82 |
+
and future outlook:
|
| 83 |
+
| | Fiscal Year Ending March 31, 2026 | | | | | | |
|
| 84 |
+
| ------------------------ | ---------------------------------- | ---------------------- | --- | ----------- | --------------- | -------- | --- |
|
| 85 |
+
| | | Financial Data | | | | | |
|
| 86 |
+
| | | Change in deferred net | | | | Business | |
|
| 87 |
+
| $ in millions except for | | | | Stock-based | Amortization of | | |
|
| 88 |
+
Outlook (b) revenue and related cost of acquisition and
|
| 89 |
+
| per share amounts | | | | compensation | acquired intangibles | | |
|
| 90 |
+
| ----------------- | ----------------- | ------- | --- | ------------ | -------------------- | --------- | --- |
|
| 91 |
+
| | | revenue | | | | other (c) | |
|
| 92 |
+
| GAAP | | | | | | | |
|
| 93 |
+
| Total net revenue | $6,550 to $6,600 | $100 | | | | | |
|
| 94 |
+
|
| 95 |
+
| Cost of revenue | $2,781 to $2,797 | $(5) | $31 | $(641) | |
|
| 96 |
+
| ----------------------- | ----------------- | ----- | ------- | ------- | ------ |
|
| 97 |
+
| Operating expenses | $3,959 to $3,969 | | $(333) | $(68) | $(8) |
|
| 98 |
+
| Interest and other, net | $97 | | | | $(14) |
|
| 99 |
+
(Loss) income before
|
| 100 |
+
| | $(287) to $(263) | $105 | $302 | $709 | $22 |
|
| 101 |
+
| --- | ----------------- | ----- | ----- | ----- | ---- |
|
| 102 |
+
income taxes
|
| 103 |
+
| Net loss | $(369) to $(338) | | | | |
|
| 104 |
+
| -------- | ----------------- | --- | --- | --- | --- |
|
| 105 |
+
$(2.00) to
|
| 106 |
+
| Net loss per share | | | | | |
|
| 107 |
+
| ------------------ | --- | --- | --- | --- | --- |
|
| 108 |
+
$(1.84)
|
| 109 |
+
| Net cash provided by | approximately | | | | |
|
| 110 |
+
| -------------------- | ------------- | --- | --- | --- | --- |
|
| 111 |
+
| | | | | | |
|
| 112 |
+
| operating activities | $450 | | | | |
|
| 113 |
+
approximately
|
| 114 |
+
| Capital expenditures | | | | | |
|
| 115 |
+
| -------------------- | --- | --- | --- | --- | --- |
|
| 116 |
+
$180
|
| 117 |
+
| | | | | | |
|
| 118 |
+
| ------------------ | ----------------- | ----- | ----- | --- | --- |
|
| 119 |
+
| Non-GAAP | | | | | |
|
| 120 |
+
| EBITDA | $657 to $681 | $105 | $302 | | $8 |
|
| 121 |
+
| | | | | | |
|
| 122 |
+
| Operational metric | | | | | |
|
| 123 |
+
| Net Bookings | $6,650 to $6,700 | | | | |
|
| 124 |
+
Management reporting tax rate anticipated to be 18%
|
| 125 |
+
Share count used to calculate GAAP net loss per share is expected to be 183.9 million
|
| 126 |
+
Share count used to calculate management reporting diluted net income per share is expected to be 186.3 million
|
| 127 |
+
(b) The individual components of the financial outlook may not foot to the totals, as the Company does not expect actual results for every component to
|
| 128 |
+
be at the low end or high end of the outlook range simultaneously.
|
| 129 |
+
(c) Other includes adjustments for (i) business reorganization expenses, (ii) the revaluation of the Turkish Lira against the U.S. Dollar, and (iii) fair value
|
| 130 |
+
adjustments related to certain equity investments.
|
| 131 |
+
Fiscal Fourth Quarter Ending March 31, 2026
|
| 132 |
+
The Company is also providing selected data, which is used internally by its management and Board of Directors to adjust the Company’s GAAP and
|
| 133 |
+
Non-GAAP financial outlook in order to facilitate comparison of its operating performance between periods and to better understand its core business
|
| 134 |
+
and future outlook:
|
| 135 |
+
| | Three Months Ending March 31, 2026 | | | | |
|
| 136 |
+
| --- | ----------------------------------- | --------------- | --- | --- | --- |
|
| 137 |
+
| | | Financial Data | | | |
|
| 138 |
+
$ in millions except for Outlook (b) Change in deferred net revenue Stock-based Amortization of Business
|
| 139 |
+
| | | | | | |
|
| 140 |
+
| --- | --- | --- | --- | --- | --- |
|
| 141 |
+
per share amounts and related cost of revenue compensation acquired intangibles acquisition
|
| 142 |
+
| GAAP | | | | | |
|
| 143 |
+
| ---- | --- | --- | --- | --- | --- |
|
| 144 |
+
|
| 145 |
+
$1,573 to
|
| 146 |
+
| Total net revenue | | $(63) | | | |
|
| 147 |
+
| ----------------- | --- | ------ | --- | --- | --- |
|
| 148 |
+
$1,623
|
| 149 |
+
$675 to
|
| 150 |
+
| Cost of revenue | | $(10) | $1 | $(161) | |
|
| 151 |
+
| --------------- | --- | ------ | --- | ------- | --- |
|
| 152 |
+
$692
|
| 153 |
+
$973 to
|
| 154 |
+
| Operating expenses | | | $(79) | $(17) | |
|
| 155 |
+
| ------------------ | --- | --- | ------ | ------ | --- |
|
| 156 |
+
$983
|
| 157 |
+
| Interest and other, net | $26 | | | | $(4) |
|
| 158 |
+
| ----------------------- | ---- | --- | --- | --- | ----- |
|
| 159 |
+
(Loss) income before $(101) to
|
| 160 |
+
| | | $(53) | $78 | $178 | $4 |
|
| 161 |
+
| --- | --- | ------ | ---- | ----- | --- |
|
| 162 |
+
income taxes $(78)
|
| 163 |
+
$(129) to
|
| 164 |
+
| Net (loss) income | | | | | |
|
| 165 |
+
| ----------------- | --- | --- | --- | --- | --- |
|
| 166 |
+
$(99)
|
| 167 |
+
Net (loss) income per $(0.70) to
|
| 168 |
+
| | | | | | |
|
| 169 |
+
| --- | --- | --- | --- | --- | --- |
|
| 170 |
+
share $(0.54)
|
| 171 |
+
| | | | | | |
|
| 172 |
+
| -------- | --- | --- | --- | --- | --- |
|
| 173 |
+
| Non-GAAP | | | | | |
|
| 174 |
+
$138 to
|
| 175 |
+
| EBITDA | | $(53) | $78 | | |
|
| 176 |
+
| ------ | --- | ------ | ---- | --- | --- |
|
| 177 |
+
$161
|
| 178 |
+
| | | | | | |
|
| 179 |
+
| ------------------ | --- | --- | --- | --- | --- |
|
| 180 |
+
| Operational metric | | | | | |
|
| 181 |
+
$1,510 to
|
| 182 |
+
| Net Bookings | | | | | |
|
| 183 |
+
| ------------ | --- | --- | --- | --- | --- |
|
| 184 |
+
$1,560
|
| 185 |
+
Management reporting tax rate anticipated to be 18%
|
| 186 |
+
Share count used to calculate GAAP net loss per share is expected to be 185.3 million
|
| 187 |
+
Share count used to calculate management reporting diluted net income per share is expected to be 187.6 million
|
| 188 |
+
(b) The individual components of the financial outlook may not foot to the totals, as the Company does not expect actual results for every component to
|
| 189 |
+
be at the low end or high end of the outlook range simultaneously.
|
| 190 |
+
Key assumptions and dependencies underlying the Company’s outlook include: a continuation of the current economic backdrop; the timely delivery of
|
| 191 |
+
the titles included in this financial outlook; continued growth in the installed base of PlayStation 5 and Xbox Series X|S, as well as engagement on
|
| 192 |
+
Xbox One and PlayStation 4; the ability to develop and publish products that capture market share for these current generation systems while also
|
| 193 |
+
leveraging opportunities on PC, mobile and other platforms; factors affecting our performance on mobile, such as player acquisition costs; our ongoing
|
| 194 |
+
focus on our live services portfolio and new game pipeline; and stable foreign exchange rates. See also “Cautionary Note Regarding Forward Looking
|
| 195 |
+
Statements” below.
|
| 196 |
+
Product Releases
|
| 197 |
+
The following have been released since October 1, 2025:
|
| 198 |
+
| Label | Product | | Platforms | Release Date | |
|
| 199 |
+
| ----- | ------------------------- | --- | ------------ | ----------------- | --- |
|
| 200 |
+
| 2K | WWE 2K Mobile for Netflix | | iOS, Android | November 19, 2025 | |
|
| 201 |
+
Rockstar GamesRed Dead Redemption and Undead Nightmare PS5, Xbox Series X|S, Switch 2 December 2, 2025
|
| 202 |
+
Rockstar GamesRed Dead Redemption and Undead Nightmare for NetflixiOS, Android December 2, 2025
|
| 203 |
+
|
| 204 |
+
PS5, PS4, Xbox Series X|S, Xbox
|
| 205 |
+
Rockstar GamesGrand Theft Auto Online: A Safehouse in the Hills December 10, 2025
|
| 206 |
+
One, PC
|
| 207 |
+
Take-Two's future lineup announced to-date includes:
|
| 208 |
+
Label Product Platforms Release Date
|
| 209 |
+
2K Sid Meier's Civilization VII for Apple ArcadeiOS February 5, 2026
|
| 210 |
+
2K PGA TOUR 2K25 Switch 2 February 6, 2026
|
| 211 |
+
2K WWE 2K26 PS5, Xbox Series X|S, Switch 2, PCMarch 13, 2026
|
| 212 |
+
Rockstar Games Grand Theft Auto VI PS5, Xbox Series X|S November 19, 2026
|
| 213 |
+
Zynga CSR 3 iOS, Android TBA
|
| 214 |
+
Zynga Top Goal iOS, Android TBA
|
| 215 |
+
Ghost Story GamesJudas PS5, Xbox Series X|S, PC TBA
|
| 216 |
+
2K Project ETHOS TBA TBA
|
| 217 |
+
2K BioShock next iteration TBA TBA
|
| 218 |
+
Conference Call
|
| 219 |
+
Take-Two will host a conference call today at 4:30 p.m. Eastern Time to review these results and discuss other topics. The call can be accessed by
|
| 220 |
+
dialing (800) 715-9871 or (646) 307-1963 (conference ID: 9711440). A live listen-only webcast of the call will be available by visiting
|
| 221 |
+
http://ir.take2games.com and a replay will be available following the call at the same location.
|
| 222 |
+
Non-GAAP Financial Measure
|
| 223 |
+
In addition to reporting financial results in accordance with U.S. generally accepted accounting principles (GAAP), the Company uses a Non-GAAP
|
| 224 |
+
measure of financial performance: EBITDA, which is defined as GAAP net income (loss) excluding interest income (expense), provision for (benefit
|
| 225 |
+
from) income taxes, depreciation expense, and amortization and impairment of acquired intangibles.
|
| 226 |
+
The Company’s management believes it is important to consider EBITDA, in addition to net income, as it removes the effect of certain non-cash
|
| 227 |
+
expenses, debt-related charges, and income taxes. Management believes that, when considered together with reported amounts, EBITDA is useful to
|
| 228 |
+
investors and management in understanding the Company’s ongoing operations and in analysis of ongoing operating trends and provides useful
|
| 229 |
+
additional information relating to the Company’s operations and financial condition.
|
| 230 |
+
This Non-GAAP financial measure is not intended to be considered in isolation from, as a substitute for, or superior to, GAAP results. This Non-GAAP
|
| 231 |
+
financial measure may be different from similarly titled measures used by other companies. In the future, Take-Two may also consider whether other
|
| 232 |
+
items should also be excluded in calculating this Non-GAAP financial measure used by the Company. Management believes that the presentation of
|
| 233 |
+
this Non-GAAP financial measure provides investors with additional useful information to measure Take-Two's financial and operating performance. In
|
| 234 |
+
particular, this measure facilitates comparison of our operating performance between periods and may help investors to understand better the
|
| 235 |
+
operating results of Take-Two. Internally, management uses this Non-GAAP financial measure in assessing the Company's operating results and in
|
| 236 |
+
planning and forecasting. A reconciliation of this Non-GAAP financial measure to the most comparable GAAP measure is contained in the financial
|
| 237 |
+
tables to this press release.
|
| 238 |
+
Final Results
|
| 239 |
+
The financial results discussed herein are presented on a preliminary basis; final data will be included in Take-Two’s Quarterly Report on Form 10-Q
|
| 240 |
+
for the period ended December 31, 2025.
|
| 241 |
+
About Take-Two Interactive Software
|
| 242 |
+
Headquartered in New York City, Take-Two Interactive Software, Inc. is a leading developer, publisher, and marketer of interactive entertainment for
|
| 243 |
+
consumers around the globe. We develop and publish products principally through Rockstar Games, 2K, and Zynga. Our strategy is to create hit
|
| 244 |
+
entertainment experiences, delivered on every platform relevant to our audience through a variety of sound business models. Our pillars – creativity,
|
| 245 |
+
innovation, and efficiency – guide us as we strive to create the highest quality, most captivating experiences for our consumers. The Company’s
|
| 246 |
+
common stock is publicly traded on NASDAQ under the symbol TTWO. For more corporate and product information please visit our website at
|
| 247 |
+
http://www.take2games.com.
|
| 248 |
+
All trademarks and copyrights contained herein are the property of their respective holders.
|
| 249 |
+
|
| 250 |
+
Cautionary Note Regarding Forward-Looking Statements
|
| 251 |
+
The statements contained herein, which are not historical facts, including statements relating to Take-Two Interactive Software, Inc.'s ("Take-Two," the
|
| 252 |
+
"Company," "we," "us," or similar pronouns) outlook, are considered forward-looking statements under federal securities laws and may be identified by
|
| 253 |
+
words such as "anticipates," "believes," "estimates," "expects," "intends," "plans," "potential," "predicts," "projects," "seeks," "should," "will," or words of
|
| 254 |
+
similar meaning and include, but are not limited to, statements regarding the outlook for our future business and financial performance. Such forward-
|
| 255 |
+
looking statements are based on the current beliefs of our management as well as assumptions made by and information currently available to them,
|
| 256 |
+
which are subject to inherent uncertainties, risks, and changes in circumstances that are difficult to predict. Actual outcomes and results may vary
|
| 257 |
+
materially from these forward-looking statements based on a variety of risks and uncertainties, including risks relating to the timely release and
|
| 258 |
+
significant market acceptance of our games; the risks of conducting business internationally, including as a result of unforeseen geopolitical events;
|
| 259 |
+
the impact of changes in interest rates by the Federal Reserve and other central banks, including on our short-term investment portfolio; the impact of
|
| 260 |
+
inflation; volatility in foreign currency exchange rates; our dependence on key management and product development personnel; our dependence on
|
| 261 |
+
our NBA 2K and Grand Theft Auto products and our ability to develop other hit titles; our ability to leverage opportunities on PlayStation®5 and Xbox
|
| 262 |
+
Series X|S; factors affecting our mobile business, such as player acquisition costs; and the ability to maintain acceptable pricing levels on our games.
|
| 263 |
+
Other important factors and information are contained in the Company's most recent Annual Report on Form 10-K, including the risks summarized in
|
| 264 |
+
the section entitled "Risk Factors," the Company’s most recent Quarterly Report on Form 10-Q, and the Company's other periodic filings with the SEC,
|
| 265 |
+
which can be accessed at www.take2games.com. All forward-looking statements are qualified by these cautionary statements and apply only as of the
|
| 266 |
+
date they are made. The Company undertakes no obligation to update any forward-looking statement, whether as a result of new information, future
|
| 267 |
+
events or otherwise.
|
| 268 |
+
|
| 269 |
+
TAKE-TWO INTERACTIVE SOFTWARE, INC.
|
| 270 |
+
CONDENSED CONSOLIDATED STATEMENTS OF OPERATIONS (Unaudited)
|
| 271 |
+
(in millions, except per share amounts)
|
| 272 |
+
| | | | | | |
|
| 273 |
+
| --- | --- | --- | --- | --- | --- |
|
| 274 |
+
Three Months Ended December 31, Nine Months Ended December 31,
|
| 275 |
+
| | 2025 | 2024 | 2025 | 2024 | |
|
| 276 |
+
| ------------ | ---------- | ------------- | ------------ | ------------- | --- |
|
| 277 |
+
| Net revenue: | | | | | |
|
| 278 |
+
| Game | $ 1,570.3 | $ 1,243.1 | $ 4,593.7 | $ 3,693.7 | |
|
| 279 |
+
| Advertising | 128.7 | 116.7 | 382.9 | 357.4 | |
|
| 280 |
+
Total net revenue 1,699.0 1,359.8 4,976.6 4,051.1
|
| 281 |
+
| Cost of revenue: | | | | | |
|
| 282 |
+
| ---------------- | -------- | ----------- | ---------- | ----------- | --- |
|
| 283 |
+
| Product costs | 220.9 | 200.2 | 660.6 | 616.0 | |
|
| 284 |
+
Game intangibles 160.1 171.1 477.4 508.0
|
| 285 |
+
| Licenses | 118.3 | 88.8 | 343.6 | 241.1 | |
|
| 286 |
+
| -------- | -------- | ---------- | ---------- | ----------- | --- |
|
| 287 |
+
Internal royalties 167.4 103.1 335.0 249.3
|
| 288 |
+
Software development costs and royalties 86.8 36.7 289.0 177.8
|
| 289 |
+
Total cost of revenue 753.5 599.9 2,105.6 1,792.2
|
| 290 |
+
Gross profit 945.5 759.9 2,871.0 2,258.9
|
| 291 |
+
Selling and marketing 433.2 388.9 1,378.6 1,281.6
|
| 292 |
+
|
| 293 |
+
Research and development 282.7 240.9 812.1 707.4
|
| 294 |
+
General and administrative 218.6 189.6 650.6 653.1
|
| 295 |
+
Depreciation and amortization 49.1 49.5 148.3 141.6
|
| 296 |
+
Business reorganization 0.6 23.1 (3.5 ) 89.4
|
| 297 |
+
Total operating expenses 984.2 892.0 2,986.1 2,873.1
|
| 298 |
+
Loss from operations (38.7 ) (132.1 ) (115.1 ) (614.2 )
|
| 299 |
+
Interest and other, net (17.1 ) (20.8 ) (70.0 ) (75.2 )
|
| 300 |
+
Loss before income taxes (55.8 ) (152.9 ) (185.1 ) (689.4 )
|
| 301 |
+
Provision for (benefit from) for income taxes 37.1 (27.7 ) 53.6 63.3
|
| 302 |
+
| Net loss | $ (92.9 | ) $ (125.2 | ) $ (238.7 | ) $ (752.7 | ) | | |
|
| 303 |
+
| --------------- | -------- | ------------ | ----------- | ------------ | --- | --- | --- |
|
| 304 |
+
| | | | | | | | |
|
| 305 |
+
| Loss per share: | | | | | | | |
|
| 306 |
+
Basic and diluted loss per share $ (0.50 ) $ (0.71 ) $ (1.30 ) $ (4.31 )
|
| 307 |
+
| Weighted average shares outstanding | | | | | | | |
|
| 308 |
+
| ----------------------------------- | -------- | ----------- | ---------- | ----------- | --- | --- | --- |
|
| 309 |
+
| Basic | 185.0 | 176.0 | 183.4 | 174.5 | | | |
|
| 310 |
+
|
| 311 |
+
TAKE-TWO INTERACTIVE SOFTWARE, INC.
|
| 312 |
+
CONDENSED CONSOLIDATED BALANCE SHEETS
|
| 313 |
+
(in millions, except per share amounts)
|
| 314 |
+
|
| 315 |
+
| | | | | | December 31, | March 31, | |
|
| 316 |
+
| ------------------------------------ | --- | --- | --- | --- | ------------ | ------------ | --- |
|
| 317 |
+
| | | | | | | | |
|
| 318 |
+
| | | | | | 2025 | 2025 | |
|
| 319 |
+
| | | | | | (Unaudited) | | |
|
| 320 |
+
| ASSETS | | | | | | | |
|
| 321 |
+
| Current assets: | | | | | | | |
|
| 322 |
+
| Cash and cash equivalents | | | | | $ 2,160.0 | $ 1,456.1 | |
|
| 323 |
+
| Short-term investments | | | | | 199.0 | 9.4 | |
|
| 324 |
+
| Restricted cash and cash equivalents | | | | | 13.2 | 14.9 | |
|
| 325 |
+
|
| 326 |
+
Accounts receivable, net of allowances of $1.9 and $1.6 at December 31, 2025 and March 31, 2025, respectively 824.1 771.1
|
| 327 |
+
| Software development costs and licenses | 50.2 | 80.8 | |
|
| 328 |
+
| --------------------------------------- | ---------- | ------------ | --- |
|
| 329 |
+
| Contract assets | 87.3 | 80.8 | |
|
| 330 |
+
| Prepaid expenses and other | 344.8 | 402.8 | |
|
| 331 |
+
| Total current assets | 3,678.6 | 2,815.9 | |
|
| 332 |
+
| Fixed assets, net | 453.5 | 443.8 | |
|
| 333 |
+
| Right-of-use assets | 333.7 | 326.1 | |
|
| 334 |
+
Software development costs and licenses, net of current portion 2,244.7 1,892.6
|
| 335 |
+
| Goodwill | 1,065.7 | 1,057.3 | |
|
| 336 |
+
| ---------------------- | ---------- | ------------ | --- |
|
| 337 |
+
| Other intangibles, net | 1,845.8 | 2,336.0 | |
|
| 338 |
+
Long-term restricted cash and cash equivalents 78.6 88.2
|
| 339 |
+
| Other assets | 309.9 | 220.8 | |
|
| 340 |
+
| ------------------------------------ | ----------- | ------------ | --- |
|
| 341 |
+
| Total assets | $ 10,010.5 | $ 9,180.7 | |
|
| 342 |
+
| LIABILITIES AND STOCKHOLDERS' EQUITY | | | |
|
| 343 |
+
| Current liabilities: | | | |
|
| 344 |
+
| Accounts payable | $ 191.3 | $ 194.7 | |
|
| 345 |
+
Accrued expenses and other current liabilities 1,100.2 1,127.6
|
| 346 |
+
| Deferred revenue | 1,292.7 | 1,083.5 | |
|
| 347 |
+
| ----------------------------- | ---------- | ------------ | --- |
|
| 348 |
+
| Lease liabilities | 69.3 | 61.5 | |
|
| 349 |
+
| Short-term debt, net | 582.2 | 1,148.5 | |
|
| 350 |
+
| Total current liabilities | 3,235.7 | 3,615.8 | |
|
| 351 |
+
| Long-term debt, net | 2,487.0 | 2,512.6 | |
|
| 352 |
+
| Non-current deferred revenue | 20.1 | 25.4 | |
|
| 353 |
+
| Non-current lease liabilities | 372.8 | 383.3 | |
|
| 354 |
+
Non-current software development royalties 83.4 93.6
|
| 355 |
+
| Deferred tax liabilities, net | 190.8 | 259.6 | |
|
| 356 |
+
| ----------------------------- | -------- | ---------- | --- |
|
| 357 |
+
| Other long-term liabilities | 125.1 | 152.7 | |
|
| 358 |
+
|
| 359 |
+
| Total liabilities | $ | 6,514.9 $ 7,043.0 | |
|
| 360 |
+
| --------------------- | --- | -------------------- | --- |
|
| 361 |
+
| Stockholders' equity: | | | |
|
| 362 |
+
Preferred stock, $0.01 par value, 5.0 shares authorized; no shares issued and outstanding at December 31, 2025
|
| 363 |
+
| | | — — | |
|
| 364 |
+
| --- | --- | -------- | --- |
|
| 365 |
+
and March 31, 2025
|
| 366 |
+
Common stock, $0.01 par value, 300.0 and 300.0 shares authorized; 208.8 and 200.8 shares issued and 185.1 and
|
| 367 |
+
| | | 2.1 2.0 | |
|
| 368 |
+
| --- | --- | ------------ | --- |
|
| 369 |
+
177.1 outstanding at December 31, 2025 and March 31, 2025, respectively
|
| 370 |
+
| Additional paid-in capital | | 11,847.7 10,312.0 | |
|
| 371 |
+
| -------------------------- | --- | ---------------------- | --- |
|
| 372 |
+
Treasury stock, at cost; 23.7 and 23.7 common shares at December 31, 2025 and March 31, 2025, respectively (1,020.6 ) (1,020.6 )
|
| 373 |
+
| Accumulated deficit | | (7,297.5 ) (7,058.8 | ) |
|
| 374 |
+
| ------------------------------------ | --- | ---------------------- | --- |
|
| 375 |
+
| Accumulated other comprehensive loss | | (36.1 ) (96.9 | ) |
|
| 376 |
+
| Total stockholders' equity | $ | 3,495.6 $ 2,137.7 | |
|
| 377 |
+
Total liabilities and stockholders' equity $ 10,010.5 $ 9,180.7
|
| 378 |
+
|
| 379 |
+
TAKE-TWO INTERACTIVE SOFTWARE, INC.
|
| 380 |
+
CONDENSED CONSOLIDATED STATEMENTS OF CASH FLOWS (Unaudited)
|
| 381 |
+
(in millions)
|
| 382 |
+
| | | | |
|
| 383 |
+
| --------------------- | ------------------------------- | ------------ | --- |
|
| 384 |
+
| | Nine Months Ended December 31, | | |
|
| 385 |
+
| | 2025 | 2024 | |
|
| 386 |
+
| Operating activities: | | | |
|
| 387 |
+
| Net loss | $ (238.7 | ) $ (752.7 | ) |
|
| 388 |
+
Adjustments to reconcile net loss to net cash provided by (used in) operating activities:
|
| 389 |
+
Amortization and impairment of software development costs and licenses 282.9 181.2
|
| 390 |
+
| Stock-based compensation | 226.9 | 244.4 | |
|
| 391 |
+
| ------------------------ | -------- | ----------- | --- |
|
| 392 |
+
| Noncash lease expense | 42.3 | 45.1 | |
|
| 393 |
+
Amortization and impairment of intangibles 525.3 563.4
|
| 394 |
+
| Depreciation | 124.1 | 114.2 | |
|
| 395 |
+
| ---------------- | -------- | ----------- | --- |
|
| 396 |
+
| Interest expense | 114.2 | 123.9 | |
|
| 397 |
+
|
| 398 |
+
| Other, net | 25.8 | 25.2 | |
|
| 399 |
+
| ---------- | ------- | ---------- | --- |
|
| 400 |
+
Changes in assets and liabilities, net of effect from purchases of businesses:
|
| 401 |
+
| Accounts receivable | (51.8 | ) 2.9 | |
|
| 402 |
+
| ------------------- | -------- | --------- | --- |
|
| 403 |
+
Software development costs and licenses (518.5 ) (568.9 )
|
| 404 |
+
Prepaid expenses and other current and other non-current assets (65.9 ) 30.1
|
| 405 |
+
| Deferred revenue | 201.0 | 25.3 | |
|
| 406 |
+
| ---------------- | -------- | ---------- | --- |
|
| 407 |
+
Accounts payable, accrued expenses and other liabilities (278.7 ) (358.3 )
|
| 408 |
+
Net cash provided by (used in) operating activities 388.9 (324.2 )
|
| 409 |
+
| Investing activities: | | | |
|
| 410 |
+
| ---------------------------------- | --------- | ------------ | --- |
|
| 411 |
+
| Change in bank time deposits | (189.7 | ) 18.7 | |
|
| 412 |
+
| Purchases of fixed assets | (126.0 | ) (115.3 | ) |
|
| 413 |
+
| Divestitures | — | 36.0 | |
|
| 414 |
+
| Purchases of long-term investments | (21.2 | ) (21.4 | ) |
|
| 415 |
+
| Business acquisitions | (2.0 | ) 9.4 | |
|
| 416 |
+
| Asset acquisitions | (19.9 | ) (16.1 | ) |
|
| 417 |
+
Net cash used in investing activities (358.8 ) (88.7 )
|
| 418 |
+
| Financing activities: | | | |
|
| 419 |
+
| --------------------- | --- | --- | --- |
|
| 420 |
+
Tax payment related to net share settlements on restricted stock awards (2.4 ) —
|
| 421 |
+
| Issuance of common stock | 1,247.0 | 55.0 | |
|
| 422 |
+
| ------------------------ | ---------- | ---------- | --- |
|
| 423 |
+
Payment for settlement of convertible notes — (8.3 )
|
| 424 |
+
| Proceeds from issuance of debt | — | 598.9 | |
|
| 425 |
+
| ------------------------------ | --------- | ----------- | --- |
|
| 426 |
+
| Cost of debt | — | (5.4 | ) |
|
| 427 |
+
| Repayment of debt | (600.0 | ) — | |
|
| 428 |
+
Payment of contingent earn-out consideration — (12.0 )
|
| 429 |
+
Net cash provided by financing activities 644.6 628.2
|
| 430 |
+
Effects of foreign currency exchange rates on cash, cash equivalents, and restricted cash and cash
|
| 431 |
+
| | 17.9 | (8.4 | ) |
|
| 432 |
+
| --- | ------- | ---------- | --- |
|
| 433 |
+
equivalents
|
| 434 |
+
|
| 435 |
+
Net change in cash, cash equivalents, and restricted cash and cash equivalents 692.6 206.9
|
| 436 |
+
Cash, cash equivalents, and restricted cash and cash equivalents, beginning of year (1) 1,559.2 1,102.0
|
| 437 |
+
Cash, cash equivalents, and restricted cash and cash equivalents, end of period (1) $ 2,251.8 $ 1,308.9
|
| 438 |
+
|
| 439 |
+
(1) Cash, cash equivalents and restricted cash and cash equivalents shown on our Condensed Consolidated Statements of Cash Flow includes
|
| 440 |
+
amounts in the Cash and cash equivalents, Restricted cash and cash equivalents, and Long-term restricted cash and cash equivalents on our
|
| 441 |
+
Condensed Consolidated Balance Sheet.
|
| 442 |
+
|
| 443 |
+
TAKE-TWO INTERACTIVE SOFTWARE, INC. and SUBSIDIARIES
|
| 444 |
+
Net Revenue and Net Bookings by Geographic Region, Distribution Channel, and Platform Mix
|
| 445 |
+
| (in millions) | | | |
|
| 446 |
+
| ----------------------------------- | ------------------- | ------------------ | ----------- |
|
| 447 |
+
| | | | |
|
| 448 |
+
| | Three Months Ended | Three Months Ended | |
|
| 449 |
+
| | | | |
|
| 450 |
+
| | December 31, 2025 | December 31, 2024 | |
|
| 451 |
+
| | Amount % of total | Amount | % of total |
|
| 452 |
+
| Net revenue by geographic region | | | |
|
| 453 |
+
| United States | $ 1,012.2 60 | % $825.7 | 61 % |
|
| 454 |
+
| International | 686.8 40 | % 534.1 | 39 % |
|
| 455 |
+
| Total Net revenue | $ 1,699.0 100 | % $1,359.8 | 100 % |
|
| 456 |
+
| | | | |
|
| 457 |
+
| Net Bookings by geographic region | | | |
|
| 458 |
+
| United States | $ 1,047.0 60 | % $841.8 | 61 % |
|
| 459 |
+
| International | 710.1 40 | % 531.6 | 39 % |
|
| 460 |
+
| Total Net Bookings | $ 1,757.1 100 | % $1,373.4 | 100 % |
|
| 461 |
+
| | | | |
|
| 462 |
+
| | Three Months Ended | Three Months Ended | |
|
| 463 |
+
| | | | |
|
| 464 |
+
| | December 31, 2025 | December 31, 2024 | |
|
| 465 |
+
| | Amount % of total | Amount | % of total |
|
| 466 |
+
| Net revenue by distribution channel | | | |
|
| 467 |
+
| Digital online | $ 1,654.5 97 | % $1,310.7 | 96 % |
|
| 468 |
+
|
| 469 |
+
| Physical retail and other | 44.5 3 | % 49.1 | 4 % |
|
| 470 |
+
| ------------------------------------ | ------------------- | ------------------ | ----------- |
|
| 471 |
+
| Total Net revenue | $ 1,699.0 100 | % $1,359.8 | 100 % |
|
| 472 |
+
| | | | |
|
| 473 |
+
| Net Bookings by distribution channel | | | |
|
| 474 |
+
| Digital online | $ 1,711.7 97 | % $1,324.0 | 96 % |
|
| 475 |
+
| Physical retail and other | 45.4 3 | % 49.4 | 4 % |
|
| 476 |
+
| Total Net Bookings | $ 1,757.1 100 | % $1,373.4 | 100 % |
|
| 477 |
+
| | | | |
|
| 478 |
+
| | Three Months Ended | Three Months Ended | |
|
| 479 |
+
| | | | |
|
| 480 |
+
| | December 31, 2025 | December 31, 2024 | |
|
| 481 |
+
| | Amount % of total | Amount | % of total |
|
| 482 |
+
| Net revenue by platform | | | |
|
| 483 |
+
| Mobile | $ 865.8 51 | % $731.6 | 54 % |
|
| 484 |
+
| Console | 652.1 38 | % 507.9 | 37 % |
|
| 485 |
+
| PC and other | 181.1 11 | % 120.3 | 9 % |
|
| 486 |
+
| Total Net revenue | $ 1,699.0 100 | % $1,359.8 | 100 % |
|
| 487 |
+
| | | | |
|
| 488 |
+
| Net Bookings by platform | | | |
|
| 489 |
+
| Mobile | $ 860.9 49 | % $709.5 | 52 % |
|
| 490 |
+
| Console | 702.6 40 | % 538.0 | 39 % |
|
| 491 |
+
| PC and other | 193.6 11 | % 125.9 | 9 % |
|
| 492 |
+
| Total Net Bookings | $ 1,757.1 100 | % $1,373.4 | 100 % |
|
| 493 |
+
|
| 494 |
+
TAKE-TWO INTERACTIVE SOFTWARE, INC. and SUBSIDIARIES
|
| 495 |
+
Net Revenue and Net Bookings by Geographic Region, Distribution Channel, and Platform Mix
|
| 496 |
+
(in millions)
|
| 497 |
+
| | | | |
|
| 498 |
+
| --- | ----- | --- | --- |
|
| 499 |
+
|
| 500 |
+
| | Nine Months Ended | Nine Months Ended | |
|
| 501 |
+
| ------------------------------------ | ------------------- | ----------------- | ----------- |
|
| 502 |
+
| | | | |
|
| 503 |
+
| | December 31, 2025 | December 31, 2024 | |
|
| 504 |
+
| | Amount % of total | Amount | % of total |
|
| 505 |
+
| Net revenue by geographic region | | | |
|
| 506 |
+
| United States | $2,948.7 59 | % $2,460.7 | 61 % |
|
| 507 |
+
| International | 2,027.9 41 | % 1,590.4 | 39 % |
|
| 508 |
+
| Total Net revenue | $4,976.6 100 | % $4,051.1 | 100 % |
|
| 509 |
+
| | | | |
|
| 510 |
+
| Net Bookings by geographic region | | | |
|
| 511 |
+
| United States | $3,072.2 60 | % $2,484.7 | 61 % |
|
| 512 |
+
| International | 2,068.5 40 | % 1,581.8 | 39 % |
|
| 513 |
+
| Total Net Bookings | $5,140.7 100 | % $4,066.5 | 100 % |
|
| 514 |
+
| | | | |
|
| 515 |
+
| | Nine Months Ended | Nine Months Ended | |
|
| 516 |
+
| | | | |
|
| 517 |
+
| | December 31, 2025 | December 31, 2024 | |
|
| 518 |
+
| | Amount % of total | Amount | % of total |
|
| 519 |
+
| Net revenue by distribution channel | | | |
|
| 520 |
+
| Digital online | $4,824.2 97 | % $3,906.2 | 96 % |
|
| 521 |
+
| Physical retail and other | 152.4 3 | % 144.9 | 4 % |
|
| 522 |
+
| Total Net revenue | $4,976.6 100 | % $4,051.1 | 100 % |
|
| 523 |
+
| | | | |
|
| 524 |
+
| Net Bookings by distribution channel | | | |
|
| 525 |
+
| Digital online | $4,988.0 97 | % $3,928.5 | 97 % |
|
| 526 |
+
| Physical retail and other | 152.7 3 | % 138.0 | 3 % |
|
| 527 |
+
| Total Net Bookings | $5,140.7 100 | % $4,066.5 | 100 % |
|
| 528 |
+
| | | | |
|
| 529 |
+
| | Nine Months Ended | Nine Months Ended | |
|
| 530 |
+
| | | | |
|
| 531 |
+
| | December 31, 2025 | December 31, 2024 | |
|
| 532 |
+
|
| 533 |
+
| | | Amount | % of total | Amount | % of total | | | |
|
| 534 |
+
| ------------------------ | --- | ---------- | ----------- | ------------ | ----------- | --- | --- | --- |
|
| 535 |
+
| Net revenue by platform | | | | | | | | |
|
| 536 |
+
| Mobile | | $2,489.1 | 50 | % $2,194.3 | 54 | % | | |
|
| 537 |
+
| PC and other | | 1,922.7 | 39 | % 1,507.9 | 37 | % | | |
|
| 538 |
+
| Console | | 564.8 | 11 | % 348.9 | 9 | % | | |
|
| 539 |
+
| Total Net revenue | | $4,976.6 | 100 | % $4,051.1 | 100 | % | | |
|
| 540 |
+
| | | | | | | | | |
|
| 541 |
+
| Net Bookings by platform | | | | | | | | |
|
| 542 |
+
| Mobile | | $2,471.8 | 48 | % $2,141.9 | 52 | % | | |
|
| 543 |
+
| PC and other | | 2,084.9 | 41 | % 1,565.7 | 39 | % | | |
|
| 544 |
+
| Console | | 584.0 | 11 | % 358.9 | 9 | % | | |
|
| 545 |
+
| Total Net Bookings | | $5,140.7 | 100.0 | % $4,066.5 | 100 | % | | |
|
| 546 |
+
|
| 547 |
+
TAKE-TWO INTERACTIVE SOFTWARE, INC. and SUBSIDIARIES
|
| 548 |
+
ADDITIONAL DATA
|
| 549 |
+
(in millions)
|
| 550 |
+
| | | | | | | | | |
|
| 551 |
+
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
|
| 552 |
+
Cost of revenue -
|
| 553 |
+
Three Months Ended Cost of revenue - Cost of revenue - Cost of revenue Cost of revenue -
|
| 554 |
+
| | Net revenue | | | | | | Software development | |
|
| 555 |
+
| --- | ----------- | --- | --- | --- | --- | --- | --------------------- | --- |
|
| 556 |
+
December 31, 2025 Product costs Game intangibles - Licenses Internal royalties
|
| 557 |
+
costs and royalties
|
| 558 |
+
As reported $ 1,699.0 $ 220.9 $ 160.1 $ 118.3 $ 167.4 $ 86.8
|
| 559 |
+
Net effect from deferred
|
| 560 |
+
| revenue and related cost | 58.0 | 1.5 | | | | | (4.6 | ) |
|
| 561 |
+
| ------------------------- | ---- | -------- | ---- | --- | --- | --- | ------- | --- |
|
| 562 |
+
of revenue
|
| 563 |
+
Stock-based
|
| 564 |
+
| | | | | | | | (3.6 | ) |
|
| 565 |
+
| --- | --- | --- | --- | --- | --- | --- | ------- | --- |
|
| 566 |
+
compensation
|
| 567 |
+
Amortization of acquired
|
| 568 |
+
| | | (0.6 | ) (160.1 | ) | | | | |
|
| 569 |
+
| --- | --- | ------- | ----------- | ---- | --- | --- | --- | --- |
|
| 570 |
+
intangibles
|
| 571 |
+
| | | | | | | | | |
|
| 572 |
+
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
|
| 573 |
+
Depreciation
|
| 574 |
+
Three Months Ended Selling and Research and General and Business
|
| 575 |
+
| | | | | and | | | Interest and other, net | |
|
| 576 |
+
| --- | --- | --- | --- | ---- | --- | --- | ------------------------ | --- |
|
| 577 |
+
December 31, 2025 marketing development administrative reorganization
|
| 578 |
+
amortization
|
| 579 |
+
|
| 580 |
+
As reported $ 433.2 $ 282.7 $ 218.6 $ 49.1 0.6 $ (17.1 )
|
| 581 |
+
Net effect from deferred
|
| 582 |
+
| revenue and related cost | | | | | | (1.6 | ) |
|
| 583 |
+
| ------------------------- | --- | --- | --- | --- | --- | ------- | --- |
|
| 584 |
+
of revenue
|
| 585 |
+
Stock-based
|
| 586 |
+
| | (24.2 ) | (25.6 | ) (36.9 | ) | | | |
|
| 587 |
+
| --- | ----------- | ----- | ---------- | ---- | --- | --- | --- |
|
| 588 |
+
compensation
|
| 589 |
+
Amortization of acquired
|
| 590 |
+
| | | (7.2 | ) | (7.9 | ) | | |
|
| 591 |
+
| --- | --- | ------- | ---- | ------- | ---- | --- | --- |
|
| 592 |
+
intangibles
|
| 593 |
+
Acquisition related
|
| 594 |
+
| | | (0.3 | ) (3.7 | ) | | 4.5 | |
|
| 595 |
+
| --- | --- | ------- | --------- | ---- | --- | ------ | --- |
|
| 596 |
+
expenses
|
| 597 |
+
Impact of business
|
| 598 |
+
| | | | | | (0.6 | ) | |
|
| 599 |
+
| --- | --- | --- | --- | --- | ------- | ---- | --- |
|
| 600 |
+
reorganization
|
| 601 |
+
| Other | | | | | | 0.1 | |
|
| 602 |
+
| ----- | --- | --- | --- | --- | --- | ------ | --- |
|
| 603 |
+
Cost of revenue -
|
| 604 |
+
Three Months Ended Cost of revenue - Cost of revenue Cost of revenue Cost of revenue -
|
| 605 |
+
| | Net revenue | | | | | Software development | |
|
| 606 |
+
| --- | ----------- | --- | --- | --- | --- | --------------------- | --- |
|
| 607 |
+
December 31, 2024 Product costs -Game intangibles - Licenses Internal royalties
|
| 608 |
+
costs and royalties
|
| 609 |
+
As reported $ 1,359.8 $ 200.2 $ 171.1 $ 88.8 $ 103.1 $ 36.7
|
| 610 |
+
Net effect from deferred
|
| 611 |
+
revenue and related cost 13.7 2.7 0.1 (1.6 )
|
| 612 |
+
of revenue
|
| 613 |
+
Stock-based
|
| 614 |
+
| | | | | | | (2.6 | ) |
|
| 615 |
+
| --- | --- | --- | --- | --- | --- | ------- | --- |
|
| 616 |
+
compensation
|
| 617 |
+
Amortization and
|
| 618 |
+
| impairment of acquired | | (0.8 | ) (171.1 | ) | | | |
|
| 619 |
+
| ---------------------- | --- | ------- | ----------- | ---- | --- | --- | --- |
|
| 620 |
+
intangibles
|
| 621 |
+
| | | | | | | | |
|
| 622 |
+
| --- | --- | --- | --- | --- | --- | --- | --- |
|
| 623 |
+
Depreciation
|
| 624 |
+
Three Months Ended Selling and Research and General and Business
|
| 625 |
+
| | | | | and | | Interest and other, net | |
|
| 626 |
+
| --- | --- | --- | --- | ---- | --- | ------------------------ | --- |
|
| 627 |
+
December 31, 2024 marketing development administrative reorganization
|
| 628 |
+
amortization
|
| 629 |
+
As reported $ 388.9 $ 240.9 $ 189.6 $ 49.5 $ 23.1 $ (20.8 )
|
| 630 |
+
Net effect from deferred
|
| 631 |
+
| revenue and related cost | | | | | | 2.8 | |
|
| 632 |
+
| ------------------------- | --- | --- | --- | --- | --- | ------ | --- |
|
| 633 |
+
of revenue
|
| 634 |
+
Stock-based
|
| 635 |
+
| | (22.4 ) | (26.1 | ) (31.8 | ) | | | |
|
| 636 |
+
| --- | ----------- | ----- | ---------- | ---- | --- | --- | --- |
|
| 637 |
+
compensation
|
| 638 |
+
Amortization and
|
| 639 |
+
| impairment of acquired | (1.0 ) | (7.2 | ) | (9.2 | ) | | |
|
| 640 |
+
| ---------------------- | ---------- | ---- | ---- | ------- | ---- | --- | --- |
|
| 641 |
+
intangibles
|
| 642 |
+
Acquisition related
|
| 643 |
+
| | (0.2 ) | (0.8 | ) 7.8 | | | 2.9 | |
|
| 644 |
+
| --- | ---------- | ---- | -------- | ---- | --- | ------ | --- |
|
| 645 |
+
expenses
|
| 646 |
+
|
| 647 |
+
Impact of business
|
| 648 |
+
| | | | | | (23.1 | ) | |
|
| 649 |
+
| --- | --- | --- | --- | --- | -------- | ---- | --- |
|
| 650 |
+
reorganization
|
| 651 |
+
| Other | | | | | | 3.4 | |
|
| 652 |
+
| ----- | --- | --- | --- | --- | --- | ------ | --- |
|
| 653 |
+
|
| 654 |
+
TAKE-TWO INTERACTIVE SOFTWARE, INC. and SUBSIDIARIES
|
| 655 |
+
ADDITIONAL DATA
|
| 656 |
+
| (in millions) | | | | | | | |
|
| 657 |
+
| ------------- | --- | --- | --- | --- | --- | --- | --- |
|
| 658 |
+
Cost of revenue -
|
| 659 |
+
Nine Months Ended Cost of revenue - Cost of revenue - Cost of revenue Cost of revenue -
|
| 660 |
+
| | Net revenue | | | | | Software development | |
|
| 661 |
+
| --- | ----------- | --- | --- | --- | --- | --------------------- | --- |
|
| 662 |
+
December 31, 2025 Product costs Game intangibles - Licenses Internal royalties
|
| 663 |
+
costs and royalties
|
| 664 |
+
As reported $ 4,976.6 $ 660.6 $ 477.4 $ 343.6 $ 335.0 $ 289.0
|
| 665 |
+
Net effect from deferred
|
| 666 |
+
revenue and related cost 164.1 (0.6 ) 0.6 1.9
|
| 667 |
+
of revenue
|
| 668 |
+
Stock-based
|
| 669 |
+
| | | | | | | 32.6 | |
|
| 670 |
+
| --- | --- | --- | --- | --- | --- | ------- | --- |
|
| 671 |
+
compensation
|
| 672 |
+
Amortization of acquired
|
| 673 |
+
| | | (2.1 | ) (477.4 | ) | | | |
|
| 674 |
+
| --- | --- | ------- | ----------- | ---- | --- | --- | --- |
|
| 675 |
+
intangibles
|
| 676 |
+
| | | | | | | | |
|
| 677 |
+
| --- | --- | --- | --- | --- | --- | --- | --- |
|
| 678 |
+
Depreciation
|
| 679 |
+
Nine Months Ended Selling and Research and General and Business
|
| 680 |
+
| | | | | and | | Interest and other, net | |
|
| 681 |
+
| --- | --- | --- | --- | ---- | --- | ------------------------ | --- |
|
| 682 |
+
December 31, 2025 marketing development administrative reorganization
|
| 683 |
+
amortization
|
| 684 |
+
As reported $ 1,378.6 $ 812.1 $ 650.6 $ 148.3 $ (3.5 ) $ (70.0 )
|
| 685 |
+
Net effect from deferred
|
| 686 |
+
| revenue and related cost | | | | | | (1.1 | ) |
|
| 687 |
+
| ------------------------- | --- | --- | --- | --- | --- | ------- | --- |
|
| 688 |
+
of revenue
|
| 689 |
+
Stock-based
|
| 690 |
+
| | (73.8 ) | (71.8 | ) (113.9 | ) | | | |
|
| 691 |
+
| --- | ----------- | ----- | ----------- | ---- | --- | --- | --- |
|
| 692 |
+
compensation
|
| 693 |
+
Amortization of acquired
|
| 694 |
+
| | | (21.5 | ) | (24.2 | ) | | |
|
| 695 |
+
| --- | --- | -------- | ---- | -------- | ---- | --- | --- |
|
| 696 |
+
intangibles
|
| 697 |
+
Impact of business
|
| 698 |
+
| | | | | | 3.5 | | |
|
| 699 |
+
| --- | --- | --- | --- | --- | ------ | ---- | --- |
|
| 700 |
+
reorganization
|
| 701 |
+
Acquisition related
|
| 702 |
+
| | | (1.0 | ) (10.6 | ) | | 11.5 | |
|
| 703 |
+
| --- | --- | ------- | ---------- | ---- | --- | ------- | --- |
|
| 704 |
+
expenses
|
| 705 |
+
| Other | | | | | | (1.4 | ) |
|
| 706 |
+
| ----- | --- | --- | --- | --- | --- | ------- | --- |
|
| 707 |
+
| | | | | | | | |
|
| 708 |
+
|
| 709 |
+
Cost of revenue -
|
| 710 |
+
Nine Months Ended Cost of revenue - Cost of revenue - Cost of revenue Cost of revenue -
|
| 711 |
+
| | Net revenue | | | | | Software development | |
|
| 712 |
+
| --- | ----------- | --- | --- | --- | --- | --------------------- | --- |
|
| 713 |
+
December 31, 2024 Product costs Game intangibles - Licenses Internal royalties
|
| 714 |
+
costs and royalties
|
| 715 |
+
As reported $ 4,051.1 $ 616.0 $ 508.0 $ 241.1 $ 249.3 $ 177.8
|
| 716 |
+
Net effect from deferred
|
| 717 |
+
revenue and related cost 15.5 0.3 1.7 (0.5 )
|
| 718 |
+
of revenue
|
| 719 |
+
Stock-based
|
| 720 |
+
| | | | | | | (8.6 | ) |
|
| 721 |
+
| --- | --- | --- | --- | --- | --- | ------- | --- |
|
| 722 |
+
compensation
|
| 723 |
+
Amortization and
|
| 724 |
+
| impairment of acquired | | (2.4 | ) (508.0 | ) | | | |
|
| 725 |
+
| ---------------------- | --- | ------- | ----------- | ---- | --- | --- | --- |
|
| 726 |
+
intangibles
|
| 727 |
+
| | | | | | | | |
|
| 728 |
+
| --- | --- | --- | --- | --- | --- | --- | --- |
|
| 729 |
+
Depreciation
|
| 730 |
+
Nine Months Ended Selling and Research and General and Business
|
| 731 |
+
| | | | | and | | Interest and other, net | |
|
| 732 |
+
| --- | --- | --- | --- | ---- | --- | ------------------------ | --- |
|
| 733 |
+
December 31, 2024 marketing development administrative reorganization
|
| 734 |
+
amortization
|
| 735 |
+
As reported $ 1,281.6 $ 707.4 $ 653.1 $ 141.6 $ 89.4 $ (75.2 )
|
| 736 |
+
Net effect from deferred
|
| 737 |
+
| revenue and related cost | | | | | | 2.0 | |
|
| 738 |
+
| ------------------------- | --- | --- | --- | --- | --- | ------ | --- |
|
| 739 |
+
of revenue
|
| 740 |
+
Stock-based
|
| 741 |
+
| | (68.1 ) | (75.5 | ) (92.2 | ) | | | |
|
| 742 |
+
| --- | ----------- | ----- | ---------- | ---- | --- | --- | --- |
|
| 743 |
+
compensation
|
| 744 |
+
Amortization and
|
| 745 |
+
impairment of acquired (4.1 ) (21.5 ) (27.4 )
|
| 746 |
+
intangibles
|
| 747 |
+
Impact of business
|
| 748 |
+
| | | | | | (89.4 | ) | |
|
| 749 |
+
| --- | --- | --- | --- | --- | -------- | ---- | --- |
|
| 750 |
+
reorganization
|
| 751 |
+
Acquisition related
|
| 752 |
+
| | (0.3 ) | (1.5 | ) (61.9 | ) | | 8.2 | |
|
| 753 |
+
| --- | ---------- | ---- | ---------- | ---- | --- | ------ | --- |
|
| 754 |
+
expenses
|
| 755 |
+
| Other | | | | | | 13.8 | |
|
| 756 |
+
| ----- | --- | --- | --- | --- | --- | ------- | --- |
|
| 757 |
+
|
| 758 |
+
| TAKE-TWO INTERACTIVE SOFTWARE, INC. and SUBSIDIARIES | | | | | | | |
|
| 759 |
+
| ---------------------------------------------------- | --- | --- | --- | --- | --- | --- | --- |
|
| 760 |
+
RECONCILIATION OF GAAP TO NON-GAAP MEASURE
|
| 761 |
+
| (in millions) | | | | | | | |
|
| 762 |
+
| ------------- | --- | --- | --- | --- | --- | --- | --- |
|
| 763 |
+
Three Months Ended December 31, Nine Months Ended December 31,
|
| 764 |
+
| | | 2025 | 2024 | 2025 | 2024 | | |
|
| 765 |
+
| -------- | --- | -------- | ------------ | ----------- | ------------ | --- | --- |
|
| 766 |
+
| Net loss | | $ (92.9 | ) $ (125.2 | ) $ (238.7 | ) $ (752.7 | ) | |
|
| 767 |
+
|
| 768 |
+
Provision for (benefit from) for income taxes 37.1 (27.7 ) 53.6 63.3
|
| 769 |
+
| Interest expense | 13.6 | 12.2 | 52.7 | 50.0 | |
|
| 770 |
+
| ---------------- | ------- | ---------- | --------- | ---------- | --- |
|
| 771 |
+
Depreciation and amortization 49.1 49.5 148.3 141.6
|
| 772 |
+
Amortization of acquired intangibles 167.9 180.0 501.0 536.0
|
| 773 |
+
| EBITDA | $ 174.8 | $ 88.8 | $ 516.9 | $ 38.2 | |
|
| 774 |
+
| -------------------------------------- | -------- | ---------- | ---------- | ---------- | --- |
|
| 775 |
+
| Outlook | | | | | |
|
| 776 |
+
| Fiscal Year Ending March 31, 2026 | | | | | |
|
| 777 |
+
| Net loss $(369) to $(338) | | | | | |
|
| 778 |
+
| Provision for income taxes $82 to $75 | | | | | |
|
| 779 |
+
| Interest expense $70 | | | | | |
|
| 780 |
+
| Depreciation $166 | | | | | |
|
| 781 |
+
Amortization of acquired intangibles $708
|
| 782 |
+
| EBITDA $657 to $681 | | | | | |
|
| 783 |
+
| -------------------------------------- | --- | --- | --- | --- | --- |
|
| 784 |
+
| Outlook | | | | | |
|
| 785 |
+
| Three Months Ended March 31, 2026 | | | | | |
|
| 786 |
+
| Net loss $(129) to $(99) | | | | | |
|
| 787 |
+
| Provision for income taxes $28 to $21 | | | | | |
|
| 788 |
+
| Interest expense $20 | | | | | |
|
| 789 |
+
| Depreciation $41 | | | | | |
|
| 790 |
+
Amortization of acquired intangibles $178
|
| 791 |
+
| EBITDA $138 to $161 | | | | | |
|
| 792 |
+
| -------------------- | --- | --- | --- | --- | --- |
|
| 793 |
+
|
| 794 |
+
View source version on businesswire.com: https://www.businesswire.com/news/home/20260203145448/en/
|
| 795 |
+
(Investor Relations)
|
| 796 |
+
Nicole Shevins
|
| 797 |
+
Senior Vice President
|
| 798 |
+
Investor Relations & Corporate Communications
|
| 799 |
+
Take-Two Interactive Software, Inc.
|
| 800 |
+
(646) 536-3005
|
| 801 |
+
Nicole.Shevins@take2games.com
|
| 802 |
+
(Corporate Press)
|
| 803 |
+
Alan Lewis
|
| 804 |
+
|
| 805 |
+
Head of Global Corporate Communications
|
| 806 |
+
Take-Two Interactive Software, Inc.
|
| 807 |
+
(646) 536-2983
|
| 808 |
+
Alan.Lewis@take2games.com
|
| 809 |
+
Source: Take-Two Interactive
|
q107/random_k2/question.json
CHANGED
|
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|
|
| 15 |
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|
| 16 |
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|
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|
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| 19 |
+
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|
| 20 |
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| 21 |
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| 22 |
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|
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|
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q107/random_k2/random_2.md
CHANGED
|
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q107/random_k4/question.json
CHANGED
|
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|
| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
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| 20 |
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|
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|
| 22 |
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|
| 23 |
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|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
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|
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|
| 17 |
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|
| 18 |
"original_filenames": [
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| 20 |
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| 21 |
+
"resize_r2_17.pdf",
|
| 22 |
+
"arxiv_1909.02164.pdf",
|
| 23 |
+
"resize_r2_24.pdf"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
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Ensure social goals
|
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solve challenges
|
| 51 |
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| 52 |
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| 53 |
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| 54 |
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|
| 55 |
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|
| 56 |
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determine exactly what your objectives should be. For guidance, look to the
|
| 57 |
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|
| 58 |
-
challenges before you.
|
| 59 |
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|
| 60 |
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• Has website traffic dipped?
|
| 61 |
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|
| 62 |
-
• Is customer loyalty low?
|
| 63 |
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|
| 64 |
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• Do you need to do a better job of building a positive brand reputation?
|
| 65 |
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|
| 66 |
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• Do you just need to make people aware that your product exists?
|
| 67 |
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|
| 68 |
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A smart social media marketing campaign can answer each of these questions.
|
| 69 |
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|
| 70 |
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Prove your team’s worth by tackling them head on. To get you started, we pulled
|
| 71 |
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|
| 72 |
-
together a few common business obstacles and social objectives that can help
|
| 73 |
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|
| 74 |
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brands overcome them.
|
| 75 |
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|
| 76 |
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Challenge: Low website traffic
|
| 77 |
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|
| 78 |
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The world is online. A brand’s website, therefore, is one of its most important
|
| 79 |
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|
| 80 |
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marketing tools. Low website traffic can mean fewer customers and lower profits.
|
| 81 |
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|
| 82 |
-
To combat this challenge, your social team should focus its goals on creating links
|
| 83 |
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|
| 84 |
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directly to the website (whether they’re from your own social posts or influencers’).
|
| 85 |
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|
| 86 |
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Link to useful content, subpages and company images to position your website
|
| 87 |
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|
| 88 |
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and your brand as a resource rather than just another cog in the corporate wheel.
|
| 89 |
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| 90 |
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This traffic should increase leads and, in the long run, revenues.
|
| 91 |
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| 92 |
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02
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| 93 |
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| 94 |
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Challenge: Decreasing customer retention
|
| 95 |
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|
| 96 |
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According to The Chartered Institute of Marketing, it costs four to ten times more
|
| 97 |
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|
| 98 |
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to acquire a customer than to retain one. To keep your customers around, use
|
| 99 |
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|
| 100 |
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social as a tool to support, communicate and engage. A good social relationship
|
| 101 |
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|
| 102 |
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with your customers should translate into a better perception and offline
|
| 103 |
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|
| 104 |
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relationship with your brand. By developing a strong social bond, customers will
|
| 105 |
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|
| 106 |
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be more likely to stick with your brand time and time again.
|
| 107 |
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|
| 108 |
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Challenge: Poor customer service
|
| 109 |
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|
| 110 |
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People turn to social to engage with businesses. Therefore, it is important for your
|
| 111 |
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|
| 112 |
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brand to be ready to help customers on any channel they can contact you
|
| 113 |
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| 114 |
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through. Arm your social media team with the materials, education and authority
|
| 115 |
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|
| 116 |
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to respond to customer questions and issues. When you do so, you’ll be equipped
|
| 117 |
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| 118 |
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to respond to your customers in a timely and accurate way, regardless of how they
|
| 119 |
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|
| 120 |
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reach out to you.
|
| 121 |
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| 122 |
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Challenge: Weak brand awareness
|
| 123 |
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|
| 124 |
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Social allows you to reach a broad audience. But honing and perfecting that
|
| 125 |
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|
| 126 |
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message takes brain power and time. To create authentic and lasting brand
|
| 127 |
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|
| 128 |
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awareness, avoid a slew of promotional messages; instead, focus on creating
|
| 129 |
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|
| 130 |
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meaningful content and a strong brand personality through your social channels.
|
| 131 |
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|
| 132 |
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Determine relevant hashtags and industry influencers you can engage with, and
|
| 133 |
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|
| 134 |
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tap into those resources to extend your brand’s overall awareness.
|
| 135 |
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| 136 |
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What are your social media goals?
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| 137 |
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|
| 138 |
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(cid:31) Increase brand awareness
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| 139 |
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| 140 |
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(cid:31) Drive website traffic
|
| 141 |
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|
| 142 |
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(cid:31) Improve customer
|
| 143 |
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service and retention
|
| 144 |
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| 145 |
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(cid:31) Gather quality leads
|
| 146 |
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| 147 |
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(cid:31) Source job candidates
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| 149 |
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03
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| 150 |
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02
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| 152 |
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Extend efforts throughout
|
| 153 |
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your organization
|
| 154 |
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|
| 155 |
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Social has long lived within the marketing department, but that doesn’t mean it
|
| 156 |
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|
| 157 |
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can’t (and shouldn’t) have a hand in nearly every business function, from human
|
| 158 |
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|
| 159 |
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resources to research and development. To create a fully integrated social media
|
| 160 |
-
|
| 161 |
-
marketing campaign, you’ll need to involve and integrate multiple departments,
|
| 162 |
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|
| 163 |
-
especially if your goals have a direct impact on them. Work with all your teams to
|
| 164 |
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|
| 165 |
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determine how you can best support their goals and what key performance
|
| 166 |
-
|
| 167 |
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indicators are important to them (we’ve outlined some ideas on both below).
|
| 168 |
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|
| 169 |
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Sales
|
| 170 |
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|
| 171 |
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Social selling is a term that has grown in popularity since the rise of social
|
| 172 |
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|
| 173 |
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marketing. By searching for sales opportunities and then engaging in a helpful
|
| 174 |
-
|
| 175 |
-
and authentic manner, social media can be a great way to prime the sales funnel
|
| 176 |
-
|
| 177 |
-
and find new leads.
|
| 178 |
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|
| 179 |
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04
|
| 180 |
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|
| 181 |
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Customer service
|
| 182 |
-
|
| 183 |
-
Social media is quickly becoming one of the most important channels through
|
| 184 |
-
|
| 185 |
-
which companies interact with their current customers. Social is an easy and very
|
| 186 |
-
|
| 187 |
-
public way for customers to air their grievances with your brand. If you aren’t
|
| 188 |
-
|
| 189 |
-
responding, it can hurt your reputation and customer relationship.
|
| 190 |
-
|
| 191 |
-
Building great relationships on social is about more than responding to
|
| 192 |
-
|
| 193 |
-
complaints. For example, Seamless does a wonderful job of Retweeting positive
|
| 194 |
-
|
| 195 |
-
posts from satisfied customers and regularly engaging with all kinds of mentions.
|
| 196 |
-
|
| 197 |
-
Human resources
|
| 198 |
-
|
| 199 |
-
While the HR team probably spends a good amount of its time on social media
|
| 200 |
-
|
| 201 |
-
looking through the profiles of applicants, it can also use social as a way to
|
| 202 |
-
|
| 203 |
-
increase overall application numbers. Showcase job postings on social media and
|
| 204 |
-
|
| 205 |
-
encourage your employees to share them to their networks as well. Beyond just
|
| 206 |
-
|
| 207 |
-
05
|
| 208 |
-
|
| 209 |
-
job postings, social is a useful tool in showcasing your company culture to the
|
| 210 |
-
|
| 211 |
-
world. Highlight some behind-the-scenes images of what it is like to work for your
|
| 212 |
-
|
| 213 |
-
company so you can improve the perception of your brand among candidates.
|
| 214 |
-
|
| 215 |
-
Research and Development
|
| 216 |
-
|
| 217 |
-
Your brand’s social audience represents a group that is highly engaged, invested
|
| 218 |
-
|
| 219 |
-
and interested in your product or service. Why not leverage that to serve as an
|
| 220 |
-
|
| 221 |
-
online focus group for your company? Asking for and listening to customer
|
| 222 |
-
|
| 223 |
-
feedback on social media is a nimble and easy way to get instant feedback.
|
| 224 |
-
|
| 225 |
-
Additionally, social media can help expose gaps in a product or service.
|
| 226 |
-
|
| 227 |
-
Marketing
|
| 228 |
-
|
| 229 |
-
The marketing department, specifically advertising and PR, traditionally has a
|
| 230 |
-
|
| 231 |
-
strong role in the social media strategy. But there are always new ways to ensure
|
| 232 |
-
|
| 233 |
-
people are aware of and excited about your brand through social. Whether you’re
|
| 234 |
-
|
| 235 |
-
debuting a product, ad campaign or initiative, ensure that social has a strong hand
|
| 236 |
-
|
| 237 |
-
in spreading the word.
|
| 238 |
-
|
| 239 |
-
Customer service
|
| 240 |
-
|
| 241 |
-
Social media is quickly becoming one of the most important channels through
|
| 242 |
-
|
| 243 |
-
which companies interact with their current customers. Social is an easy and very
|
| 244 |
-
|
| 245 |
-
public way for customers to air their grievances with your brand. If you aren’t
|
| 246 |
-
|
| 247 |
-
responding, it can hurt your reputation and customer relationship.
|
| 248 |
-
|
| 249 |
-
Building great relationships on social is about more than responding to
|
| 250 |
-
|
| 251 |
-
complaints. For example, Seamless does a wonderful job of Retweeting positive
|
| 252 |
-
|
| 253 |
-
posts from satisfied customers and regularly engaging with all kinds of mentions.
|
| 254 |
-
|
| 255 |
-
Human resources
|
| 256 |
-
|
| 257 |
-
While the HR team probably spends a good amount of its time on social media
|
| 258 |
-
|
| 259 |
-
looking through the profiles of applicants, it can also use social as a way to
|
| 260 |
-
|
| 261 |
-
increase overall application numbers. Showcase job postings on social media and
|
| 262 |
-
|
| 263 |
-
encourage your employees to share them to their networks as well. Beyond just
|
| 264 |
-
|
| 265 |
-
job postings, social is a useful tool in showcasing your company culture to the
|
| 266 |
-
|
| 267 |
-
world. Highlight some behind-the-scenes images of what it is like to work for your
|
| 268 |
-
|
| 269 |
-
company so you can improve the perception of your brand among candidates.
|
| 270 |
-
|
| 271 |
-
Research and Development
|
| 272 |
-
|
| 273 |
-
Your brand’s social audience represents a group that is highly engaged, invested
|
| 274 |
-
|
| 275 |
-
and interested in your product or service. Why not leverage that to serve as an
|
| 276 |
-
|
| 277 |
-
online focus group for your company? Asking for and listening to customer
|
| 278 |
-
|
| 279 |
-
feedback on social media is a nimble and easy way to get instant feedback.
|
| 280 |
-
|
| 281 |
-
Additionally, social media can help expose gaps in a product or service.
|
| 282 |
-
|
| 283 |
-
Marketing
|
| 284 |
-
|
| 285 |
-
The marketing department, specifically advertising and PR, traditionally has a
|
| 286 |
-
|
| 287 |
-
strong role in the social media strategy. But there are always new ways to ensure
|
| 288 |
-
|
| 289 |
-
people are aware of and excited about your brand through social. Whether you’re
|
| 290 |
-
|
| 291 |
-
debuting a product, ad campaign or initiative, ensure that social has a strong hand
|
| 292 |
-
|
| 293 |
-
in spreading the word.
|
| 294 |
-
|
| 295 |
-
What teams are active on social?
|
| 296 |
-
|
| 297 |
-
(cid:31) Sales
|
| 298 |
-
|
| 299 |
-
(cid:31) Marketing
|
| 300 |
-
|
| 301 |
-
(cid:31) Advertising
|
| 302 |
-
|
| 303 |
-
(cid:31) Public relations
|
| 304 |
-
|
| 305 |
-
(cid:31) Customer service
|
| 306 |
-
|
| 307 |
-
(cid:31) Human resources
|
| 308 |
-
|
| 309 |
-
(cid:31) Research and
|
| 310 |
-
development
|
| 311 |
-
|
| 312 |
-
06
|
| 313 |
-
|
| 314 |
-
03
|
| 315 |
-
Focus on networks
|
| 316 |
-
that add value
|
| 317 |
-
|
| 318 |
-
Just because a network has billions of users doesn’t mean it will have a direct
|
| 319 |
-
|
| 320 |
-
contribution to your brand’s objectives. Instead of trying to be everything to
|
| 321 |
-
|
| 322 |
-
everybody, focus your efforts on networks that hold the key to your target
|
| 323 |
-
|
| 324 |
-
audience and objectives.
|
| 325 |
-
|
| 326 |
-
Each network has its own strengths and weaknesses, and each social media
|
| 327 |
-
|
| 328 |
-
marketer should carefully pick and choose which networks they want to take
|
| 329 |
-
|
| 330 |
-
advantage of. Here are some of the most popular networks as well as what they’re
|
| 331 |
-
|
| 332 |
-
best at.
|
| 333 |
-
|
| 334 |
-
Facebook
|
| 335 |
-
|
| 336 |
-
With an audience of 2.32 billion monthly active users, Facebook offers an
|
| 337 |
-
|
| 338 |
-
opportunity to reach a broad range of customers and potential customers. The
|
| 339 |
-
|
| 340 |
-
chart below breaks down Facebook’s demographic representation—your target
|
| 341 |
-
|
| 342 |
-
audience is most likely represented in some way.
|
| 343 |
-
|
| 344 |
-
07
|
| 345 |
-
|
| 346 |
-
But how can Facebook contribute to your overall goals? Because Facebook’s
|
| 347 |
-
|
| 348 |
-
News Feed is a very visible place for social posts, it’s one of the best places for
|
| 349 |
-
|
| 350 |
-
you to distribute your content in order to increase brand awareness, drive website
|
| 351 |
-
|
| 352 |
-
traffic and distinguish yourself as a thought leader. This strategy is even more
|
| 353 |
-
|
| 354 |
-
effective when you take advantage of Facebook’s targeting capabilities that allow
|
| 355 |
-
|
| 356 |
-
you to tailor your messages to users with certain interests.
|
| 357 |
-
|
| 358 |
-
Twitter
|
| 359 |
-
|
| 360 |
-
Where Facebook has the volume of users, Twitter has the volume of messages. In
|
| 361 |
-
|
| 362 |
-
fact, there are over 500 million Tweets sent every day. With all those social
|
| 363 |
-
|
| 364 |
-
messages, there is a great chance that someone is either mentioning your
|
| 365 |
-
|
| 366 |
-
company or starting a conversation that you would be interested in joining.
|
| 367 |
-
|
| 368 |
-
That’s why Twitter is best to use as a customer service and business development
|
| 369 |
-
|
| 370 |
-
channel. Monitor the network for inbound messages from dissatisfied customers,
|
| 371 |
-
|
| 372 |
-
and quickly turn them into happy interactions. At the same time, look for
|
| 373 |
-
|
| 374 |
-
prospective customers.
|
| 375 |
-
|
| 376 |
-
LinkedIn
|
| 377 |
-
|
| 378 |
-
LinkedIn has a robust network of over 500 million users, most of whom frequent
|
| 379 |
-
|
| 380 |
-
the site with a “working” mindset. The advantage with this is that LinkedIn is an
|
| 381 |
-
|
| 382 |
-
amazing network for B2B social media marketers. Whereas sites like Twitter and
|
| 383 |
-
|
| 384 |
-
Facebook catch users more or less on their personal time, LinkedIn gives you
|
| 385 |
-
|
| 386 |
-
access to customers when they’re at their professional best. Use this to build
|
| 387 |
-
|
| 388 |
-
relationships with future customers.
|
| 389 |
-
|
| 390 |
-
Which networks align with your business strategy?
|
| 391 |
-
|
| 392 |
-
(cid:31) Facebook
|
| 393 |
-
|
| 394 |
-
(cid:31) Twitter
|
| 395 |
-
|
| 396 |
-
(cid:31) Instagram
|
| 397 |
-
|
| 398 |
-
(cid:31) LinkedIn
|
| 399 |
-
|
| 400 |
-
(cid:31) Pinterest
|
| 401 |
-
|
| 402 |
-
(cid:31) YouTube
|
| 403 |
-
|
| 404 |
-
(cid:31) Snapchat
|
| 405 |
-
|
| 406 |
-
08
|
| 407 |
-
|
| 408 |
-
04
|
| 409 |
-
Create engaging content
|
| 410 |
-
|
| 411 |
-
Once you’ve involved the right stakeholders, department and networks, it’s time to
|
| 412 |
-
|
| 413 |
-
start building engaging content for your social channels. This content—whether a
|
| 414 |
-
|
| 415 |
-
video, tip sheet or simple Tweet—should all ladder up into your business
|
| 416 |
-
|
| 417 |
-
objectives.
|
| 418 |
-
|
| 419 |
-
Videos
|
| 420 |
-
• How-to videos can be a proactive approach to social customer care—answer
|
| 421 |
-
|
| 422 |
-
your customers’ questions before they’re asked.
|
| 423 |
-
|
| 424 |
-
• Behind-the-scenes videos give your audience a sense of your company culture
|
| 425 |
-
|
| 426 |
-
and brand personality.
|
| 427 |
-
|
| 428 |
-
Guides
|
| 429 |
-
• Position your organization as a thought leader and elevate your brand by
|
| 430 |
-
|
| 431 |
-
developing engaging content that speaks to your customers.
|
| 432 |
-
|
| 433 |
-
• Guides should cater to your target audience, ensuring you’re adding value.
|
| 434 |
-
|
| 435 |
-
09
|
| 436 |
-
|
| 437 |
-
Infographics
|
| 438 |
-
• Internal or external data can be turned into a beautiful, insightful infographic.
|
| 439 |
-
|
| 440 |
-
• When done right, infographics can be some of the most socially shared pieces
|
| 441 |
-
|
| 442 |
-
of content, so make them engaging and resourceful.
|
| 443 |
|
| 444 |
-
|
| 445 |
-
and frequency?
|
| 446 |
|
| 447 |
-
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(
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Engage instead of ignore
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all
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Track, improve and market
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presentations.
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Advocacy & Analytics Solutions
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J
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]
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L
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s
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c
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[
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X
|
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r
|
| 38 |
+
a
|
| 39 |
+
|
| 40 |
+
Published as a conference paper at ICLR 2020
|
| 41 |
+
|
| 42 |
+
TABFACT: A LARGE-SCALE DATASET FOR TABLE-
|
| 43 |
+
BASED FACT VERIFICATION
|
| 44 |
+
|
| 45 |
+
Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang,
|
| 46 |
+
Shiyang Li, Xiyou Zhou, William Yang Wang
|
| 47 |
+
University of California, Santa Barbara, CA, USA
|
| 48 |
+
Tencent AI Lab, Bellevue, WA, USA
|
| 49 |
+
{wenhuchen,hongmin wang,yunkai zhang,hongwang600,william}@ucsb.edu
|
| 50 |
+
{shiyangli,xiyou}@cs.ucsb.edu jianshuchen@tencent.com
|
| 51 |
+
|
| 52 |
+
ABSTRACT
|
| 53 |
+
|
| 54 |
+
The problem of verifying whether a textual hypothesis holds based on the given
|
| 55 |
+
evidence, also known as fact verification, plays an important role in the study of
|
| 56 |
+
natural language understanding and semantic representation. However, existing
|
| 57 |
+
studies are mainly restricted to dealing with unstructured evidence (e.g., natu-
|
| 58 |
+
ral language sentences and documents, news, etc), while verification under struc-
|
| 59 |
+
tured evidence, such as tables, graphs, and databases, remains under-explored.
|
| 60 |
+
This paper specifically aims to study the fact verification given semi-structured
|
| 61 |
+
data as evidence. To this end, we construct a large-scale dataset called TabFact
|
| 62 |
+
with 16k Wikipedia tables as the evidence for 118k human-annotated natural lan-
|
| 63 |
+
guage statements, which are labeled as either ENTAILED or REFUTED. TabFact
|
| 64 |
+
is challenging since it involves both soft linguistic reasoning and hard symbolic
|
| 65 |
+
reasoning. To address these reasoning challenges, we design two different mod-
|
| 66 |
+
els: Table-BERT and Latent Program Algorithm (LPA). Table-BERT leverages
|
| 67 |
+
the state-of-the-art pre-trained language model to encode the linearized tables
|
| 68 |
+
and statements into continuous vectors for verification. LPA parses statements
|
| 69 |
+
into programs and executes them against the tables to obtain the returned binary
|
| 70 |
+
value for verification. Both methods achieve similar accuracy but still lag far be-
|
| 71 |
+
hind human performance. We also perform a comprehensive analysis to demon-
|
| 72 |
+
strate great future opportunities. The data and code of the dataset are provided in
|
| 73 |
+
https://github.com/wenhuchen/Table-Fact-Checking.
|
| 74 |
+
|
| 75 |
+
1
|
| 76 |
+
|
| 77 |
+
INTRODUCTION
|
| 78 |
+
|
| 79 |
+
Verifying whether a textual hypothesis is entailed or refuted by the given evidence is a fundamental
|
| 80 |
+
problem in natural language understanding (Katz & Fodor, 1963; Van Benthem et al., 2008). It
|
| 81 |
+
can benefit many downstream applications like misinformation detection, fake news detection, etc.
|
| 82 |
+
Recently, the first-ever end-to-end fact-checking system has been designed and proposed in Hassan
|
| 83 |
+
et al. (2017). The verification problem has been extensively studied under different natural language
|
| 84 |
+
tasks such as recognizing textual entailment (RTE) (Dagan et al., 2005), natural language inference
|
| 85 |
+
(NLI) (Bowman et al., 2015), claim verification (Popat et al., 2017; Hanselowski et al., 2018; Thorne
|
| 86 |
+
et al., 2018) and multimodal language reasoning (NLVR/NLVR2) (Suhr et al., 2017; 2019). RTE
|
| 87 |
+
and NLI view a premise sentence as the evidence, claim verification views passage collection like
|
| 88 |
+
Wikipedia1 as the evidence, NLVR/NLVR2 views images as the evidence. These problems have
|
| 89 |
+
been previously addressed using a variety of techniques including logic rules, knowledge bases, and
|
| 90 |
+
neural networks. Recently large-scale pre-trained language models (Devlin et al., 2019; Peters et al.,
|
| 91 |
+
2018; Yang et al., 2019; Liu et al., 2019) have surged to dominate the other algorithms to approach
|
| 92 |
+
human performance on several textual entailment tasks (Wang et al., 2018; 2019).
|
| 93 |
+
|
| 94 |
+
However, existing studies are restricted to dealing with unstructured text as the evidence, which
|
| 95 |
+
would not generalize to the cases where the evidence has a highly structured format. Since such
|
| 96 |
+
structured evidence (graphs, tables, or databases) are also ubiquitous in real-world applications like
|
| 97 |
+
|
| 98 |
+
1https://www.wikipedia.org/
|
| 99 |
+
|
| 100 |
+
1
|
| 101 |
+
|
| 102 |
+
Published as a conference paper at ICLR 2020
|
| 103 |
+
|
| 104 |
+
Figure 1: Examples from the TABFACT dataset. The top table contains the semi-structured knowl-
|
| 105 |
+
edge facts with caption ”United...”. The left and right boxes below provide several entailed and
|
| 106 |
+
refuted statements. The error parts are highlighted with red font.
|
| 107 |
+
|
| 108 |
+
database systems, dialog systems, commercial management systems, social networks, etc, we argue
|
| 109 |
+
that the fact verification under structured evidence forms is an equivalently important yet under-
|
| 110 |
+
explored problem. Therefore, in this paper, we are specifically interested in studying fact verification
|
| 111 |
+
with semi-structured Wikipedia tables (Bhagavatula et al., 2013)2 as evidence owing to its structured
|
| 112 |
+
and ubiquitous nature (Jauhar et al., 2016; Zhong et al., 2017; Pasupat & Liang, 2015). To this end,
|
| 113 |
+
we introduce a large-scale dataset called TABFACT, which consists of 118K manually annotated
|
| 114 |
+
statements with regard to 16K Wikipedia tables, their relations are classified as ENTAILED and
|
| 115 |
+
REFUTED3. The entailed and refuted statements are both annotated by human workers. With some
|
| 116 |
+
examples in Figure 1, we can clearly observe that unlike the previous verification related problems,
|
| 117 |
+
TABFACT combines two different forms of reasoning in the statements, (i) Linguistic Reasoning:
|
| 118 |
+
the verification requires semantic-level understanding. For example, “John J. Mcfall failed to be
|
| 119 |
+
re-elected though being unopposed.” requires understanding over the phrase “lost renomination ...”
|
| 120 |
+
in the table to correctly classify the entailment relation. Unlike the existing QA datasets (Zhong
|
| 121 |
+
et al., 2017; Pasupat & Liang, 2015), where the linguistic reasoning is dominated by paraphrasing,
|
| 122 |
+
TABFACT requires more linguistic inference or common sense. (ii) Symbolic Reasoning: the verifi-
|
| 123 |
+
cation requires symbolic execution on the table structure. For example, the phrase “There are three
|
| 124 |
+
Democrats incumbents” requires both condition operation (where condition) and arithmetic oper-
|
| 125 |
+
ation (count). Unlike question answering, a statement could contain compound facts, all of these
|
| 126 |
+
facts need to be verified to predict the verdict. For example, the ”There are ...” in Figure 1 requires
|
| 127 |
+
verifying three QA pairs (total count=5, democratic count=2, republic count=3). The two forms of
|
| 128 |
+
reasoning are interleaved across the statements making it challenging for existing models.
|
| 129 |
+
|
| 130 |
+
In this paper, we particularly propose two approaches to deal with such mixed-reasoning challenge:
|
| 131 |
+
(i) Table-BERT, this model views the verification task completely as an NLI problem by linearizing a
|
| 132 |
+
table as a premise sentence p, and applies state-of-the-art language understanding pre-trained model
|
| 133 |
+
to encode both the table and statements h into distributed representation for classification. This
|
| 134 |
+
model excels at linguistic reasoning like paraphrasing and inference but lacks symbolic reasoning
|
| 135 |
+
skills. (ii) Latent Program Algorithm, this model applies lexical matching to find linked entities and
|
| 136 |
+
triggers to filter pre-defined APIs (e.g. argmax, argmin, count, etc). We adopt bread-first-search
|
| 137 |
+
with memorization to construct the potential program candidates, a discriminator is further utilized
|
| 138 |
+
to select the most “consistent” latent programs. This model excels at the symbolic reasoning aspects
|
| 139 |
+
by executing database queries, which also provides better interpretability by laying out the decision
|
| 140 |
+
rationale. We perform extensive experiments to investigate their performances: the best-achieved
|
| 141 |
+
accuracy of both models are reasonable, but far below human performance. Thus, we believe that
|
| 142 |
+
the proposed table-based fact verification task can serve as an important new benchmark towards the
|
| 143 |
+
goal of building powerful AI that can reason over both soft linguistic form and hard symbolic forms.
|
| 144 |
+
To facilitate future research, we released all the data, code with the intermediate results.
|
| 145 |
+
|
| 146 |
+
2In contrast to the database tables, where each column has strong type constraint, the cell records in our
|
| 147 |
+
|
| 148 |
+
semi-structured tables can be string/data/integer/floating/phrase/sentences.
|
| 149 |
+
|
| 150 |
+
3we leave out NEUTRAL due to its low inter-worker agreement, which is easily confused with REFUTED.
|
| 151 |
+
|
| 152 |
+
2
|
| 153 |
+
|
| 154 |
+
DistrictIncumbentPartyResultCandidatesCalifornia 3John E. Mossdemocraticre-electedJohn E. Moss (d) 69.9% John Rakus(r) 30.1%California 5Phillip Burtondemocraticre-electedPhillip Burton (d) 81.8% EdloE. Powell (r) 18.2%California 8George Paul Millerdemocraticlost renominationdemocratic holdPeteStark(d) 52.9% Lew M. Warden, Jr. (r) 47.1%California 14Jerome R. Waldierepublicanre-electedJeromeR. Waldie(d) 77.6% FloydE. Sims(r) 22.4%California 15John J. Mcfallrepublicanre-electedJohn J. Mcfall(d) unopposed1.John E. Moss and Phillip Burton are both re-elected in the house of representative election.2.John J. Mcfallis unopposed during the re-election.3.There are three different incumbents from democratic.1.John E. Moss and George Paul Miller are both re-electedin the house of representative election.2.John J. Mcfallfailed to be re-elected though being unopposed.3.There are five candidates in total, two of them are democrats and three of them are republicans.United States House of Representatives Elections, 1972Entailed StatementRefuted StatementPublished as a conference paper at ICLR 2020
|
| 155 |
+
|
| 156 |
+
2 TABLE FACT VERIFICATION DATASET
|
| 157 |
+
|
| 158 |
+
First, we follow the previous Table-based Q&A datasets (Pasupat & Liang, 2015; Zhong et al., 2017)
|
| 159 |
+
to extract web tables (Bhagavatula et al., 2013) with captions from WikiTables4. Here we filter out
|
| 160 |
+
overly complicated and huge tables (e.g. multirows, multicolumns, latex symbol) and obtain 18K
|
| 161 |
+
relatively clean tables with less than 50 rows and 10 columns.
|
| 162 |
+
|
| 163 |
+
For crowd-sourcing jobs, we follow the human subject research protocols5 to pay Amazon Mechani-
|
| 164 |
+
cal Turk6 workers from the native English-speaking countries “US, GB, NZ, CA, AU” with approval
|
| 165 |
+
rates higher than 95% and more than 500 accepted HITs. Following WikiTableQuestion (Pasupat &
|
| 166 |
+
Liang, 2015), we provide the annotators with the corresponding table captions to help them better
|
| 167 |
+
understand the background. To ensure the annotation quality, we develop a pipeline of “positive
|
| 168 |
+
two-channel annotation” → ���negative statement rewriting” → “verification”, as described below.
|
| 169 |
+
|
| 170 |
+
2.1 POSITIVE TWO-CHANNEL COLLECTION & NEGATIVE REWRITING STRATEGY
|
| 171 |
+
|
| 172 |
+
To harvest statements of different difficulty levels, we design a two-channel collection process:
|
| 173 |
+
Low-Reward Simple Channel: the workers are paid 0.45 USD for annotating one Human Intel-
|
| 174 |
+
ligent Task (HIT) that requires writing five statements. The workers are encouraged to produce
|
| 175 |
+
plain statements meeting the requirements: (i) corresponding to a single row/record in the table with
|
| 176 |
+
unary fact without involving compound logical inference. (ii) mention the cell values without dra-
|
| 177 |
+
matic modification or paraphrasing. The average annotation time of a HIT is 4.2 min.
|
| 178 |
+
High-Reward Complex Channel: the workers are paid 0.75 USD for annotating a HIT (five state-
|
| 179 |
+
ments). They are guided to produce more sophisticated statements to meet the requirements: (i)
|
| 180 |
+
involving multiple rows in the tables with higher-order semantics like argmax, argmin, count, differ-
|
| 181 |
+
ence, average, summarize, etc. (ii) rephrase the table records to involve more semantic understand-
|
| 182 |
+
ing. The average annotation time of a HIT is 6.8 min. The data obtained from the complex channel
|
| 183 |
+
are harder in terms of both linguistic and symbolic reasoning, the goal of the two-channel split is to
|
| 184 |
+
help us understand the proposed models can reach under different levels of difficulty.
|
| 185 |
+
|
| 186 |
+
As suggested in (Zellers et al., 2018), there might be annotation artifacts and conditional stylistic
|
| 187 |
+
patterns such as length and word-preference biases, which can allow shallow models (e.g. bag-of-
|
| 188 |
+
words) to obtain artificially high performance. Therefore, we design a negative rewriting strategy to
|
| 189 |
+
minimize such linguistic cues or patterns. Instead of letting the annotators write negative statements
|
| 190 |
+
from scratch, we let them rewrite the collected entailed statements. During the annotation, the
|
| 191 |
+
workers are explicitly guided to modify the words, phrases or sentence structures but retain the
|
| 192 |
+
sentence style/length to prevent artificial cues. We disallow naive negations by adding “not, never,
|
| 193 |
+
etc” to revert the statement polarity in case of obvious linguistic patterns.
|
| 194 |
+
|
| 195 |
+
2.2 QUALITY CONTROL
|
| 196 |
+
|
| 197 |
+
To control the quality of the annotation process, we review a randomly sampled statement from each
|
| 198 |
+
HIT to decide whether the whole annotation job should be rejected during the annotation process.
|
| 199 |
+
Specifically, a HIT must satisfy the following criteria to be accepted: (i) the statements should
|
| 200 |
+
contain neither typos nor grammatical errors. (ii) the statements do not contain vague claims like
|
| 201 |
+
might, few, etc. (iii) the claims should be explicitly supported or contradicted by the table without
|
| 202 |
+
requiring the additional knowledge, no middle ground is permitted. After the data collection, we
|
| 203 |
+
re-distribute all the annotated samples to further filter erroneous statements, the workers are paid
|
| 204 |
+
0.05 USD per statement to decide whether the statement should be rejected. The criteria we apply
|
| 205 |
+
are similar: no ambiguity, no typos, explicitly supported or contradictory. Through the post-filtering
|
| 206 |
+
process, roughly 18% entailed and 27% refuted instances are further abandoned due to poor quality.
|
| 207 |
+
|
| 208 |
+
4http://websail-fe.cs.northwestern.edu/wikiTables/about/
|
| 209 |
+
5https://en.wikipedia.org/wiki/Minimum_wage_in_the_United_States
|
| 210 |
+
6https://www.mturk.com/
|
| 211 |
+
|
| 212 |
+
3
|
| 213 |
+
|
| 214 |
+
Published as a conference paper at ICLR 2020
|
| 215 |
+
|
| 216 |
+
Figure 2: Proportion of different higher-order operations from the simple/complex channels.
|
| 217 |
+
|
| 218 |
+
Channel
|
| 219 |
+
|
| 220 |
+
#Sentence
|
| 221 |
+
|
| 222 |
+
#Table
|
| 223 |
+
|
| 224 |
+
Len(Ent)
|
| 225 |
+
|
| 226 |
+
Len(Ref)
|
| 227 |
+
|
| 228 |
+
Split
|
| 229 |
+
|
| 230 |
+
#Sentence
|
| 231 |
+
|
| 232 |
+
Table
|
| 233 |
+
|
| 234 |
+
Row Col
|
| 235 |
+
|
| 236 |
+
Simple
|
| 237 |
+
Complex
|
| 238 |
+
Total
|
| 239 |
+
|
| 240 |
+
50,244
|
| 241 |
+
68,031
|
| 242 |
+
118,275
|
| 243 |
+
|
| 244 |
+
9,189
|
| 245 |
+
7,392
|
| 246 |
+
16,573
|
| 247 |
+
|
| 248 |
+
13.2
|
| 249 |
+
14.2
|
| 250 |
+
13.8
|
| 251 |
+
|
| 252 |
+
13.1
|
| 253 |
+
14.2
|
| 254 |
+
13.8
|
| 255 |
+
|
| 256 |
+
Train
|
| 257 |
+
Val
|
| 258 |
+
Test
|
| 259 |
+
|
| 260 |
+
92,283
|
| 261 |
+
12,792
|
| 262 |
+
12,779
|
| 263 |
+
|
| 264 |
+
13,182
|
| 265 |
+
1,696
|
| 266 |
+
1,695
|
| 267 |
+
|
| 268 |
+
14.1
|
| 269 |
+
14.0
|
| 270 |
+
14.2
|
| 271 |
+
|
| 272 |
+
5.5
|
| 273 |
+
5.4
|
| 274 |
+
5.4
|
| 275 |
+
|
| 276 |
+
Table 1: Basic statistics of the data collected from the simple/complex channel and the division of
|
| 277 |
+
Train/Val/Test Split in the dataset, where “Len” denotes the averaged sentence length.
|
| 278 |
+
|
| 279 |
+
2.3 DATASET STATISTICS
|
| 280 |
+
|
| 281 |
+
Inter-Annotator Agreement: After the data collection pipeline, we merged the instances from two
|
| 282 |
+
different channels to obtain a diverse yet clean dataset for table-based fact verification. We sample
|
| 283 |
+
1000 annotated (table, statement) pairs and re-distribute each to 5 individual workers to re-label them
|
| 284 |
+
as either ENTAILED or REFUTED. We follow the previous works (Thorne et al., 2018; Bowman
|
| 285 |
+
et al., 2015) to adopt the Fleiss Kappa (Fleiss, 1971) as an indicator, where Fleiss κ = ¯pc− ¯pe
|
| 286 |
+
is
|
| 287 |
+
1− ¯pe
|
| 288 |
+
computed from from the observed agreement ¯pc and the agreement by chance ¯pe. We obtain a Fleiss
|
| 289 |
+
κ = 0.75, which indicates strong inter-annotator agreement and good-quality.
|
| 290 |
+
|
| 291 |
+
Dataset Statistics: As shown in Table 1, the amount of data harvested via the complex channel
|
| 292 |
+
slightly outnumbers the simple channel, the averaged length of both the positive and negative sam-
|
| 293 |
+
ples are indistinguishable. More specifically, to analyze to which extent the higher-order operations
|
| 294 |
+
are included in two channels, we group the common higher-order operations into 8 different cate-
|
| 295 |
+
gories. As shown in Figure 2, we sample 200 sentences from two different channels to visualize
|
| 296 |
+
their distribution. We can see that the complex channel overwhelms the simple channel in terms
|
| 297 |
+
of the higher-order logic, among which, count and superlatives are the most frequent. We split
|
| 298 |
+
the whole data roughly with 8:1:1 into train, validation7, and test splits and shows their statistics
|
| 299 |
+
in Table 1. Each table with an average of 14 rows and 5-6 columns corresponds to 2-20 different
|
| 300 |
+
statements, while each cell has an average of 2.1 words. In the training split, the positive instances
|
| 301 |
+
slightly outnumber the negative instances, while the validation and test split both have rather bal-
|
| 302 |
+
anced distributions over positive and negative instances.
|
| 303 |
+
|
| 304 |
+
3 MODELS
|
| 305 |
+
|
| 306 |
+
With the collected dataset, we now formally define the table-based fact verification task: the dataset
|
| 307 |
+
is comprised of triple instances (T, S, L) consisting of a table T, a natural language statement
|
| 308 |
+
S = s1, · · · , sn and a verification label L ∈ {0, 1}. The table T = {Ti,j|i ≤ RT , j ≤ CT } has
|
| 309 |
+
RT rows and CT columns with the Tij being the content in the (i, j)-th cell. Tij could be a word,
|
| 310 |
+
a number, a phrase, or even a natural language sentence. The statement S describes a fact to be
|
| 311 |
+
verified against the content in the table T. If it is entailed by T, then L = 1, otherwise the label
|
| 312 |
+
L = 0. Figure 1 shows some entailed and refuted examples. During training, the model and the
|
| 313 |
+
learning algorithm are presented with K instances like (T, S, L)K
|
| 314 |
+
k=1 from the training split. In the
|
| 315 |
+
testing stage, the model is presented with (T, S)K(cid:48)
|
| 316 |
+
k=1 and supposed to predict the label as ˆL. We
|
| 317 |
+
I( ˆLk = Lk) on the test set.
|
| 318 |
+
measure the performance by the prediction accuracy Acc = 1
|
| 319 |
+
K(cid:48)
|
| 320 |
+
Before building the model, we first perform entity linking to detect all the entities in the statements.
|
| 321 |
+
Briefly, we first lemmatize the words and search for the longest sub-string matching pairs between
|
| 322 |
+
statements and table cells/captions, where the matched phrases are denoted as the linked entities. To
|
| 323 |
+
focus on statement verification against the table, we do not feed the caption to the model and simply
|
| 324 |
+
|
| 325 |
+
(cid:80)K(cid:48)
|
| 326 |
+
1
|
| 327 |
+
|
| 328 |
+
7We filter roughly 400 sentences from abnormal tables including hyperlinks, math symbols, etc
|
| 329 |
+
|
| 330 |
+
4
|
| 331 |
+
|
| 332 |
+
02040AGGREGATIONNEGATESUPERLATIVECOUNTCOMPATIVEORDINALUNIQUEALLPercentProportion of different Higher-order OperationsSimpleComplexOverallPublished as a conference paper at ICLR 2020
|
| 333 |
+
|
| 334 |
+
mask the phrases in the statements which link to the caption with placeholders. The details of the
|
| 335 |
+
entity linker are listed in the Appendix. We describe our two proposed models as follows.
|
| 336 |
+
|
| 337 |
+
3.1 LATENT PROGRAM ALGORITHM (LPA)
|
| 338 |
+
|
| 339 |
+
In this approach, we formulate the table fact verification as a program synthesis problem, where the
|
| 340 |
+
latent program algorithm is not given in TABFACT. Thus, it can be seen as a weakly supervised
|
| 341 |
+
learning problem as discussed in Liang et al. (2017); Lao et al. (2011). Under such a setting, we
|
| 342 |
+
propose to break down the verification into two stages: (i) latent program search, (ii) discriminator
|
| 343 |
+
ranking. In the first program synthesis step, we aim to parse the statement into programs to represent
|
| 344 |
+
its semantics. We define the plausible API set to include roughly 50 different functions like min, max,
|
| 345 |
+
count, average, filter, and and realize their interpreter with Python-Pandas. Each API is defined to
|
| 346 |
+
take arguments of specific types (number, string, bool, and view (e.g sub-table)) to output specific-
|
| 347 |
+
type variables. During the program execution, we store the generated intermediate variables to
|
| 348 |
+
different-typed caches N , R, B, V (Num, Str, Bool, View). At each execution step, the program can
|
| 349 |
+
fetch the intermediate variable from the caches to achieve semantic compositionality. In order to
|
| 350 |
+
shrink the search space, we follow NSM (Liang et al., 2017) to use trigger words to prune the API
|
| 351 |
+
set and accelerate the search speed. The definitions of all API, trigger words can be found in the
|
| 352 |
+
Appendix. The comprehensive the latent program search procedure is summarized in Algorithm 1,
|
| 353 |
+
|
| 354 |
+
while (P, N , R, B, V) = Q.pop() do:
|
| 355 |
+
|
| 356 |
+
while loop over function set f ∈ F do:
|
| 357 |
+
|
| 358 |
+
if arguments of f are in the caches then
|
| 359 |
+
|
| 360 |
+
Pop out the required arguments arg1, arg2, · · · , argn for different cachess.
|
| 361 |
+
Execute A = f (arg1, · · · , argn) and concatenate the program trace P .
|
| 362 |
+
if Type(A)=Bool then
|
| 363 |
+
|
| 364 |
+
Algorithm 1 Latent Program Search with Comments
|
| 365 |
+
1: Initialize Number Cache N , String Cache R, Bool Cache B, View Cache V → ∅
|
| 366 |
+
2: Push linked numbers, strings from the given statement S into N , R, and push T into V
|
| 367 |
+
3: Initialize the result collector P → ∅ and an empty program trace P = ∅
|
| 368 |
+
4: Initialize the Queue Q = [(P, N , R, B, V)], we use Q to store the intermediate states
|
| 369 |
+
5: Use trigger words to find plausible function set F, for example, more will trigger Greater function.
|
| 370 |
+
6: while loop over time t = 1 → MAXSTEP do:
|
| 371 |
+
7:
|
| 372 |
+
8:
|
| 373 |
+
9:
|
| 374 |
+
10:
|
| 375 |
+
11:
|
| 376 |
+
12:
|
| 377 |
+
13:
|
| 378 |
+
14:
|
| 379 |
+
15:
|
| 380 |
+
16:
|
| 381 |
+
17:
|
| 382 |
+
18:
|
| 383 |
+
19:
|
| 384 |
+
20:
|
| 385 |
+
21:
|
| 386 |
+
22:
|
| 387 |
+
23:
|
| 388 |
+
24:
|
| 389 |
+
25: Return the triple (T, S, P) # Return (Table, Statement, Program Set)
|
| 390 |
+
|
| 391 |
+
P.push((P, A)) # The program P is valid since it consumes all the variables.
|
| 392 |
+
P = ∅ # Collect the valid program P into set P and reset P
|
| 393 |
+
|
| 394 |
+
B.push(A) # The intermediate boolean value is added to the bool cache
|
| 395 |
+
Q.push((P, N , R, B, V)) # Add the refreshed state to the queue again
|
| 396 |
+
|
| 397 |
+
push A into N or S or V # Add the refreshed state to the queue for further search
|
| 398 |
+
Q.push((P, N , R, B, V))
|
| 399 |
+
|
| 400 |
+
P = ∅;break # The program ends without consuming the cache, throw it.
|
| 401 |
+
|
| 402 |
+
if Type(A) ∈ {Num, Str, View} then
|
| 403 |
+
|
| 404 |
+
if N = S = B = ∅ then
|
| 405 |
+
|
| 406 |
+
if N = S = B = ∅ then
|
| 407 |
+
|
| 408 |
+
else
|
| 409 |
+
|
| 410 |
+
else
|
| 411 |
+
|
| 412 |
+
and the searching procedure is illustrated in Figure 3.
|
| 413 |
+
|
| 414 |
+
After we collected all the potential program candidates P = {(P1, A1), · · · , (Pn, An)} for a given
|
| 415 |
+
statement S (where (Pi, Ai) refers to i-th candidate), we need to learn a discriminator to iden-
|
| 416 |
+
tify the “appropriate” traces from the set from many erroneous and spurious traces. Since we do
|
| 417 |
+
not have the ground truth label about such discriminator, we use a weakly supervised training al-
|
| 418 |
+
gorithm by viewing all the label-consistent programs as positive instances {Pi|(Pi, Ai); Ai = L}
|
| 419 |
+
and the label-inconsistent program as negative instances {Pi|(Pi, Ai); Ai (cid:54)= L} to minimize the
|
| 420 |
+
cross-entropy of discriminator pθ(S, P ) with the weakly supervised label. Specifically, we build
|
| 421 |
+
our discriminator with a Transformer-based two-way encoder (Vaswani et al., 2017), where the
|
| 422 |
+
statement encoder encodes the input statement S as a vector EncS(S) ∈ Rn×D with dimen-
|
| 423 |
+
sion D, while the program encoder encodes the program P = p1, · · · , pm as another vector
|
| 424 |
+
EncP (P ) ∈ Rm×D, we concatenate these two vectors and feed it into a linear projection layer
|
| 425 |
+
|
| 426 |
+
5
|
| 427 |
+
|
| 428 |
+
Published as a conference paper at ICLR 2020
|
| 429 |
+
|
| 430 |
+
Figure 3: The program synthesis procedure for the table in Figure 1. We link the entity (e.g. demo-
|
| 431 |
+
cratic, republican), and then composite functions on the fly to return the values from the table.
|
| 432 |
+
|
| 433 |
+
Figure 4: The diagram of Table-BERT with horizontal scan, two different linearizations are depicted.
|
| 434 |
+
|
| 435 |
+
to compute pθ(S, P ) = σ(vT
|
| 436 |
+
p [EncS(S); EncP (P )]) as the relevance between S and P with weight
|
| 437 |
+
vp ∈ RD. At test time, we use the discriminator pθ to assign confidence pθ(S, P ) to each candidate
|
| 438 |
+
P ∈ P, and then either aggregate the prediction from all hypothesis with the confidence weights or
|
| 439 |
+
rank the highest-confident hypothesis and use their outputs as the prediction.
|
| 440 |
+
|
| 441 |
+
3.2 TABLE-BERT
|
| 442 |
+
|
| 443 |
+
In this approach, we view the table verification problem as a two-sequence binary classification
|
| 444 |
+
problem like NLI or MPRC (Wang et al., 2018) by linearizing a table T into a sequence and treating
|
| 445 |
+
the statement as another sequence. Since the linearized table can be extremely long surpassing the
|
| 446 |
+
limit of sequence models like LSTM, Transformers, etc. We propose to shrink the sequence by only
|
| 447 |
+
retaining the columns containing entities linked to the statement to alleviate such a memory issue.
|
| 448 |
+
In order to encode such sub-table as a sequence, we propose two different linearization methods, as
|
| 449 |
+
is depicted in Figure 4. (i) Concatenation: we simply concatenate the table cells with [SEP] tokens
|
| 450 |
+
in between and restart position counter at the cell boundaries; the column name is fed as another
|
| 451 |
+
type embedding to the input layer. Such design retains the table information in its machine format.
|
| 452 |
+
(ii) Template: we adopt simple natural language templates to transform a table into a “somewhat
|
| 453 |
+
natural” sentence. Taking the horizontal scan as an example, we linearize a table as “row one’s
|
| 454 |
+
game is 51; the date is February; ..., the score is 3.4 (ot).
|
| 455 |
+
row 2 is ...”. The isolated cells are
|
| 456 |
+
connected with punctuations and copula verbs in a language-like format.
|
| 457 |
+
After obtaining the linearized sub-table ˜T, we concatenate it with the natural language state-
|
| 458 |
+
ment S and prefix a [CLS] token to the sentence to obtain the sequence-level representation
|
| 459 |
+
H = fBERT ([ ˜T, S]), with H ∈ R768 from pre-trained BERT (Devlin et al., 2019). The rep-
|
| 460 |
+
resentation is further fed into multi-layer perceptron fM LP to obtain the entailment probability
|
| 461 |
+
pθ( ˜T, S) = σ(fM LP (H)), where σ is the sigmoid function. We finetune the model θ (including the
|
| 462 |
+
parameters of BERT and MLP) to minimize the binary cross entropy L(pθ( ˜T, S), L) on the training
|
| 463 |
+
set. At test time, we use the trained BERT model to compute the matching probability between the
|
| 464 |
+
(table, statement) pair, and classify it as ENTAILED statement when pθ( ˜T, S) is greater than 0.5.
|
| 465 |
+
|
| 466 |
+
6
|
| 467 |
+
|
| 468 |
+
There are more democratsthan republicansin the election.incumbentdemocraticincumbentrepublicanV1=Filter(T, incumbent==democratic))Feature-based Entity LinkingV2=Filter(T, incumbent==republican))StringincumbentrepublicanSubV1SubV2SubV1Viewpop3=Count(V1)popCount3SubV1SubV2ViewNum2=Count(V2)Count2Count3NumGreater(3, 2)BoolTrueBoolpopTableLISP EngineEntailedSearchGameDateOpponentScore51February 3 , 2009Florida3-4 52February 4 , 2009Buffalo0-5 53February 7 , 2010Montreal5-2 TypePositionWordFebruary3,2009[SEP][CLS]51[SEP]10123400gameTOKdatedatedatedateTOKTOKTOK0[SEP]Floridaisplaying123SSS12-Layer BERT-Base Modelonegameis51;date[CLS]isFebruary32019;[SEP]123456708910111220PositionWordrowLabelFlorida13ConcatTemplatePublished as a conference paper at ICLR 2020
|
| 469 |
+
|
| 470 |
+
4 EXPERIMENTS
|
| 471 |
+
|
| 472 |
+
In this section, we aim to evaluate the proposed methods on TABFACT. Besides the standard valida-
|
| 473 |
+
tion and test sets, we also split the test set into a simple and a complex partition based on the channel
|
| 474 |
+
from which they were collected. This facilitates analyzing how well the model performs under dif-
|
| 475 |
+
ferent levels of difficulty. Additionally, we also hold out a small test set with 2K samples for human
|
| 476 |
+
evaluation, where we distribute each (table, statement) pair to 5 different workers to approximate
|
| 477 |
+
human judgments based on their majority voting, the results are reported in Table 2.
|
| 478 |
|
| 479 |
+
Model
|
| 480 |
|
| 481 |
+
BERT classifier w/o Table
|
| 482 |
|
| 483 |
+
Table-BERT-Horizontal-F+T-Concatenate
|
| 484 |
+
Table-BERT-Vertical-F+T-Template
|
| 485 |
+
Table-BERT-Vertical-T+F-Template
|
| 486 |
+
Table-BERT-Horizontal-F+T-Template
|
| 487 |
+
Table-BERT-Horizontal-T+F-Template
|
| 488 |
|
| 489 |
+
NSM w/ RL (Binary Reward)
|
| 490 |
+
NSM w/ LPA-guided ML + RL
|
| 491 |
+
LPA-Voting w/o Discriminator
|
| 492 |
+
LPA-Weighted-Voting
|
| 493 |
+
LPA-Ranking w/ Discriminator
|
| 494 |
+
LPA-Ranking w/ Discriminator (Caption)
|
| 495 |
|
| 496 |
+
Human Performance
|
| 497 |
|
| 498 |
+
Val
|
| 499 |
|
| 500 |
+
50.9
|
| 501 |
|
| 502 |
+
50.7
|
| 503 |
+
56.7
|
| 504 |
+
56.7
|
| 505 |
+
66.0
|
| 506 |
+
66.1
|
| 507 |
+
|
| 508 |
+
54.1
|
| 509 |
+
63.2
|
| 510 |
+
57.7
|
| 511 |
+
62.5
|
| 512 |
+
65.2
|
| 513 |
+
65.1
|
| 514 |
+
|
| 515 |
+
-
|
| 516 |
+
|
| 517 |
+
Test
|
| 518 |
+
|
| 519 |
+
50.5
|
| 520 |
+
|
| 521 |
+
50.4
|
| 522 |
+
56.2
|
| 523 |
+
57.0
|
| 524 |
+
65.1
|
| 525 |
+
65.1
|
| 526 |
+
|
| 527 |
+
54.1
|
| 528 |
+
63.5
|
| 529 |
+
58.2
|
| 530 |
+
63.1
|
| 531 |
+
65.0
|
| 532 |
+
65.3
|
| 533 |
+
|
| 534 |
+
-
|
| 535 |
+
|
| 536 |
+
Test (simple)
|
| 537 |
+
|
| 538 |
+
Test (complex)
|
| 539 |
+
|
| 540 |
+
Small Test
|
| 541 |
+
|
| 542 |
+
51.0
|
| 543 |
+
|
| 544 |
+
50.8
|
| 545 |
+
59.8
|
| 546 |
+
60.6
|
| 547 |
+
79.0
|
| 548 |
+
79.1
|
| 549 |
+
|
| 550 |
+
55.4
|
| 551 |
+
77.4
|
| 552 |
+
68.5
|
| 553 |
+
74.6
|
| 554 |
+
78.4
|
| 555 |
+
78.7
|
| 556 |
+
|
| 557 |
+
-
|
| 558 |
+
|
| 559 |
+
50.1
|
| 560 |
+
|
| 561 |
+
50.0
|
| 562 |
+
55.0
|
| 563 |
+
54.3
|
| 564 |
+
58.1
|
| 565 |
+
58.2
|
| 566 |
+
|
| 567 |
+
53.1
|
| 568 |
+
56.1
|
| 569 |
+
53.2
|
| 570 |
+
57.3
|
| 571 |
+
58.5
|
| 572 |
+
58.5
|
| 573 |
+
|
| 574 |
+
-
|
| 575 |
+
|
| 576 |
+
50.4
|
| 577 |
+
|
| 578 |
+
50.3
|
| 579 |
+
56.2
|
| 580 |
+
55.5
|
| 581 |
+
67.9
|
| 582 |
+
68.1
|
| 583 |
+
|
| 584 |
+
55.8
|
| 585 |
+
66.9
|
| 586 |
+
61.5
|
| 587 |
+
66.8
|
| 588 |
+
68.6
|
| 589 |
+
68.9
|
| 590 |
+
|
| 591 |
+
92.1
|
| 592 |
+
|
| 593 |
+
Table 2: The results of different models, the numbers are in percentage. T+F means table followed
|
| 594 |
+
by fact, while F+T means fact followed by table. NSM is modified from Liang et al. (2017).
|
| 595 |
+
|
| 596 |
+
NSM We follow Liang et al. (2017) to modify their approach to fit the setting of TABFACT. Specif-
|
| 597 |
+
ically, we adopt an LSTM as an encoder and another LSTM with copy mechanism as a decoder
|
| 598 |
+
to synthesize the program. However, without any ground truth annotation for the intermediate
|
| 599 |
+
programs, directly training with reinforcement learning is difficult as the binary reward is under-
|
| 600 |
+
specified, which is listed in Table 2 as ”NSM w/ RL”. Further, we use LPA as a teacher to search the
|
| 601 |
+
top programs for the NSM to bootstrap and then use reinforcement learning to finetune the model,
|
| 602 |
+
which achieves reasonable performance on our dataset listed as ”NSM w/ ML + RL”.
|
| 603 |
+
Table-BERT We build Table-BERT based on the open-source implementation of BERT8 using the
|
| 604 |
+
pre-trained model with 12-layer, 768-hidden, 12-heads, and 110M parameters trained in 104 lan-
|
| 605 |
+
guages. We use the standard BERT tokenizer to break the words in both statements and tables into
|
| 606 |
+
subwords and join the two sequences with a [SEP] token in between. The representation correspond-
|
| 607 |
+
ing to [CLS] is fed into an MLP layer to predict the verification label. We finetune the model on
|
| 608 |
+
a single TITAN X GPU with a mini-batch size of 6. The best performance is reached after about
|
| 609 |
+
3 hours of training (around 10K steps). We implement and compare the following variants of the
|
| 610 |
+
Table-BERT model including (i) Concatenation vs. Template: whether to use natural language tem-
|
| 611 |
+
plates during linearization. (ii) Horizontal vs. Vertical: scan direction in linearization.
|
| 612 |
+
LPA We run the latent program search in a distributed fashion on three 64-core machines to gener-
|
| 613 |
+
ate the latent programs. The search terminates once the buffer has more than 50 traces or the path
|
| 614 |
+
length is larger than 7. The average search time for each statement is about 2.5s. For the discrimina-
|
| 615 |
+
tor model, we design two transformer-based encoders (3 layers, 128-dimension hidden embedding,
|
| 616 |
+
and 4 heads at each layer) to encode the programs and statements, respectively. The variants of LPA
|
| 617 |
+
models considered include (i) Voting: assign each program with equal weight and vote without the
|
| 618 |
+
learned discriminator. (ii) Weighted-Voting: compute a weighted-sum to aggregate the predictions
|
| 619 |
+
of all latent programs with the discriminator confidence as the weights. (iii) Ranking: rank all the
|
| 620 |
+
hypotheses by the discriminator confidence and use the top-rated hypothesis as the output. (Caption)
|
| 621 |
+
means feeding the caption as a sequence of words to the discriminator during ranking.
|
| 622 |
+
Preliminary Evaluation In order to test whether our negative rewriting strategy eliminates the ar-
|
| 623 |
+
tifacts or shallow cues, we also fine-tune a pre-trained BERT (Devlin et al., 2019) to classify the
|
| 624 |
+
statement S without feeding in table information. The result is reported as “BERT classifier w/o
|
| 625 |
+
|
| 626 |
+
8https://github.com/huggingface/pytorch-pretrained-BERT
|
| 627 |
+
|
| 628 |
+
7
|
| 629 |
+
|
| 630 |
+
Published as a conference paper at ICLR 2020
|
| 631 |
+
|
| 632 |
+
Table” in Table 2, which is approximately the majority guess and reflects the effectiveness of the
|
| 633 |
+
rewriting strategy. Before presenting the experiment results, we first perform a preliminary study to
|
| 634 |
+
evaluate how well the entity linking system, program search, and the statement-program discrimi-
|
| 635 |
+
nator perform. Since we do not have the ground truth labels for these models, we randomly sample
|
| 636 |
+
100 samples from the dev set to perform the human study. For the entity linking, we evaluate its
|
| 637 |
+
accuracy as the number of correctly linked sentences / total sentences. For the latent program search,
|
| 638 |
+
we evaluate whether the “true” programs are included in the candidate set P as recall score.
|
| 639 |
+
|
| 640 |
+
Results We report the performance of different methods as well as human performance in Table 2.
|
| 641 |
+
First of all, we observe that the naive serialized model fails to learn anything effective (same as the
|
| 642 |
+
Majority Guess). It reveals the importance of template when using the pre-trained BERT (Devlin
|
| 643 |
+
et al., 2019) model: the “natural” connection words between individual cells is able to unleash the
|
| 644 |
+
power of the large pre-trained language model and enable it to perform reasoning on the structured
|
| 645 |
+
table form. Such behavior is understandable given the fact that BERT is pre-trained on purely natural
|
| 646 |
+
language corpora. In addition, we also observe that the horizontal scan excels in the vertical scan
|
| 647 |
+
because it better captures the convention of human expression. Among different LPA methods, we
|
| 648 |
+
found that LPA-Ranking performs the best since it can better suppress the spurious programs than
|
| 649 |
+
the voting-based algorithm. Overall, the LPA model is on par with Table-BERT on both simple
|
| 650 |
+
and test split without any pre-training on external corpus, which reflects the effectiveness of LPA to
|
| 651 |
+
leverage symbolic operations in the verification process.
|
| 652 |
+
|
| 653 |
+
Through our human evaluation, we found that only 58% of sentences have been correctly linked
|
| 654 |
+
without missing-link or over-link, while the systematic search has a recall of 51% under the cases
|
| 655 |
+
where the sentence is correctly linked. With that being said, the chance for LPA method to cover
|
| 656 |
+
the correct program (rationale) is roughly under 30%. After the discriminator’s re-ranking step,
|
| 657 |
+
the probability of selecting these particular oracle program is even much lower. However, we still
|
| 658 |
+
observe a final overall accuracy of 65%, which indicates that the spurious problem is quite severe in
|
| 659 |
+
LPA, where the correct label is predicted based on the wrong reason.
|
| 660 |
+
|
| 661 |
+
Through our human evaluation, we also observe that Table-BERT exhibits poor consistency as it can
|
| 662 |
+
misclassify simple cases but correctly-classify hard cases. These two major weaknesses are yet to
|
| 663 |
+
be solved in future studies. In contrast, LPA behaves much more consistently and provides a clear
|
| 664 |
+
latent rationale for its decision. But, such a pipeline system requires laborious handcrafting of API
|
| 665 |
+
operations and is also very sensitive to the entity linking accuracy. Both methods have pros and
|
| 666 |
+
cons; how to combine them still remains an open question.
|
| 667 |
+
|
| 668 |
+
Program Annotation To further promote the development of different models in our dataset, we
|
| 669 |
+
collect roughly 1400 human-annotated programs paired with the original statements. These state-
|
| 670 |
+
ments include the most popular logical operations like superlative, counting, comparison, unique,
|
| 671 |
+
etc. We provide these annotations in Github9, which can either be used to bootstrap the semantic
|
| 672 |
+
parsers or provide the rationale for NLI models.
|
| 673 |
+
|
| 674 |
+
5 RELATED WORK
|
| 675 |
+
|
| 676 |
+
Natural Language Inference & Reasoning: Modeling reasoning and inference in human language
|
| 677 |
+
is a fundamental and challenging problem towards true natural language understanding. There has
|
| 678 |
+
been extensive research on RTE in the early years (Dagan et al., 2005) and more recently shifted
|
| 679 |
+
to NLI (Bowman et al., 2015; Williams et al., 2017). NLI seeks to determine whether a natural
|
| 680 |
+
language hypothesis h can be inferred from a natural language premise p. With the surge of deep
|
| 681 |
+
learning, there have been many powerful algorithms like the Decomposed Model (Parikh et al.,
|
| 682 |
+
2016), Enhanced-LSTM (Chen et al., 2017) and BERT (Devlin et al., 2019). Besides the textual ev-
|
| 683 |
+
idence, NLVR (Suhr et al., 2017) and NLVR2 (Suhr et al., 2019) have been proposed to use images
|
| 684 |
+
as the evidence for statement verification on multi-modal setting. Our proposed fact verification task
|
| 685 |
+
is closely related to these inference tasks, where our semi-structured table can be seen as a collection
|
| 686 |
+
of “premises” exhibited in a semi-structured format. Our proposed problem hence could be viewed
|
| 687 |
+
as the generalization of NLI under the semi-structured domain.
|
| 688 |
+
Table Question Answering: Another line of research closely related to our task is the table-based
|
| 689 |
+
|
| 690 |
+
9https://github.com/wenhuchen/Table-Fact-Checking/tree/master/bootstrap
|
| 691 |
+
|
| 692 |
+
8
|
| 693 |
+
|
| 694 |
+
Published as a conference paper at ICLR 2020
|
| 695 |
+
|
| 696 |
+
Figure 5: The two uniqueness of Table-based fact verification against standard QA problems.
|
| 697 |
+
|
| 698 |
+
question answering, such as MCQ (Jauhar et al., 2016), WikiTableQuestion (Pasupat & Liang,
|
| 699 |
+
2015), Spider (Yu et al., 2018), Sequential Q&A (Iyyer et al., 2017), and WikiSQL (Zhong et al.,
|
| 700 |
+
2017), for which approaches have been extended to handle large-scale tables from Wikipedia (Bha-
|
| 701 |
+
gavatula et al., 2013). However, in these Q&A tasks, the question types typically provide strong
|
| 702 |
+
signals needed for identifying the type of answers, while TABFACT does not provide such speci-
|
| 703 |
+
ficity. The uniqueness of TABFACT lies in two folds: 1) a given fact is regarded as a false claim as
|
| 704 |
+
long as any part of the statement contains misinformation. Due to the conjunctive nature of verifica-
|
| 705 |
+
tion, a fact needs to be broken down into several sub-clauses or (Q, A) pairs to separate evaluate their
|
| 706 |
+
correctness. Such a compositional nature of the verification problem makes it more challenging than
|
| 707 |
+
a standard QA setting. On one hand, the model needs to recognize the multiple QA pairs and their
|
| 708 |
+
relationship. On the other hand, the multiple sub-clauses make the semantic form longer and logic
|
| 709 |
+
inference harder than the standard QA setting. 2) some facts cannot even be handled using semantic
|
| 710 |
+
forms, as they are driven by linguistic inference or common sense. In order to verify these state-
|
| 711 |
+
ments, more inference techniques have to be leveraged to enable robust verification. We visualize
|
| 712 |
+
the above two characteristics of TABFACT in Figure 5.
|
| 713 |
+
|
| 714 |
+
Program Synthesis & Semantic Parsing: There have also been great interests in using program
|
| 715 |
+
synthesis or logic forms to solve different natural language processing problems like question
|
| 716 |
+
answering (Liang et al., 2013; Berant et al., 2013; Berant & Liang, 2014), visual navigation (Artzi
|
| 717 |
+
et al., 2014; Artzi & Zettlemoyer, 2013), code generation (Yin & Neubig, 2017; Dong & Lapata,
|
| 718 |
+
2016), SQL synthesis (Yu et al., 2018), etc. The traditional semantic parsing papers (Artzi et al.,
|
| 719 |
+
2014; Artzi & Zettlemoyer, 2013; Zettlemoyer & Collins, 2005; Liang et al., 2013; Berant et al.,
|
| 720 |
+
2013) greatly rely on rules, lexicon to parse natural language sentences into different forms like
|
| 721 |
+
lambda calculus, DCS, etc. More recently, researchers strive to propose neural models to directly
|
| 722 |
+
perform end-to-end formal reasoning like Theory Prover (Riedel et al., 2017; Rockt¨aschel & Riedel,
|
| 723 |
+
2017), Neural Turing Machine (Graves et al., 2014), Neural Programmer (Neelakantan et al.,
|
| 724 |
+
2016; 2017) and Neural-Symbolic Machines (Liang et al., 2017; 2018; Agarwal et al., 2019). The
|
| 725 |
+
proposed TABFACT serves as a great benchmark to evaluate the reasoning ability of different neural
|
| 726 |
+
reasoning models. Specifically, TABFACT poses the following challenges: 1) spurious programs
|
| 727 |
+
(i.e., wrong programs with the true returned answers): since the program output is only a binary
|
| 728 |
+
label, which can cause serious spurious problems and misguide the reinforcement learning with the
|
| 729 |
+
under-specified binary rewards. 2) decomposition: the model needs to decompose the statement
|
| 730 |
+
into sub-clauses and verify the sub-clauses one by one, which normally requires the longer logic in-
|
| 731 |
+
ference chains to infer the statement verdict. 3) linguistic reasoning like inference and paraphrasing.
|
| 732 |
+
|
| 733 |
+
Fact Checking The problem of verifying claims and hypotheses on the web has drawn significant at-
|
| 734 |
+
tention recently due to its high social influence. Different fact-checking pioneering studies have been
|
| 735 |
+
|
| 736 |
+
9
|
| 737 |
+
|
| 738 |
+
DistrictIncumbentPartyResultCandidatesCalifornia 3John E. Mossdemocraticre-electedJohn E. Moss (d) 69.9% John Rakus(r) 30.1%California 5Phillip Burtondemocraticre-electedPhillip Burton (d) 81.8% EdloE. Powell (r) 18.2%California 8George Paul Millerdemocraticlost renominationdemocratic holdPeteStark(d) 52.9% Lew M. Warden, Jr. (r) 47.1%California 14Jerome R. Waldierepublicanre-electedJeromeR. Waldie(d) 77.6% FloydE. Sims(r) 22.4%California 15John J. Mcfallrepublicanre-electedJohn J. Mcfall(d) unopposedUnited States House of Representatives Elections, 1972There are five candidates in total, two of them are democrats and three of them are republicans.Question: How many of candidates in total?Answer: 5Question: How many democrats are there?Answer: 2Question: How many republicans are there?Answer: 3∧∧ConjunctiveEq(Count(T), 5)=TEq(Count(Filter(T, party=‘dem..’)), 2)=FEq(Count(Filter(T, party=‘rep..’)), 3)=F∧∧outcomedatetournamentsurfacepartneropponents in the finalscore in the finalrunner -up1985bologna , italyclayalberto touspaolocanèsimonecolombo5 -7 , 4 -6winner1986bordeaux , franceclaydavid de miguelronald agénor mansour bahrami7 -5 , 6 -4winner1989prague , czechoslovakiaclayhorst skoffpetr korda tomáš šmíd6 -4 , 6 -4Jordi Arreseachieves better score in 1986 than in 1985.Jordi ArreseJordi Arresewon both of the final games in 1986.1986: Winner1986: Runner-upLinguistic Inference7 -5 , 6 -4Mathematic Inference(2)(1)Published as a conference paper at ICLR 2020
|
| 739 |
+
|
| 740 |
+
performed including LIAR (Wang, 2017), PolitiFact (Vlachos & Riedel, 2014), FEVER (Thorne
|
| 741 |
+
et al., 2018) and AggChecker (Jo et al., 2019), etc. The former three studies are mainly based on
|
| 742 |
+
textual evidence on social media or Wikipedia, while AggChecker is closest to ours in using re-
|
| 743 |
+
lational databases as the evidence. Compared to AggChecker, our paper proposes a much larger
|
| 744 |
+
dataset to benchmark the progress in this direction.
|
| 745 |
+
|
| 746 |
+
6 CONCLUSION
|
| 747 |
+
|
| 748 |
+
This paper investigates a very important yet previously under-explored research problem: semi-
|
| 749 |
+
structured fact verification. We construct a large-scale dataset and proposed two methods, Table-
|
| 750 |
+
BERT and LPA, based on the state-of-the-art pre-trained natural language inference model and pro-
|
| 751 |
+
gram synthesis. In the future, we plan to push forward this research direction by inspiring more
|
| 752 |
+
sophisticated architectures that can perform both linguistic and symbolic reasoning.
|
| 753 |
+
|
| 754 |
+
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|
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+
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+
13
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| 978 |
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Published as a conference paper at ICLR 2020
|
| 980 |
|
| 981 |
+
A APPENDIX
|
| 982 |
|
| 983 |
+
A.1 FUNCTION DESCRIPTION
|
| 984 |
|
| 985 |
+
We list the detailed function description in Figure 6. We also visualize the functionality of the most
|
| 986 |
|
| 987 |
+
Figure 6: The function definition used in TabFact.
|
| 988 |
|
| 989 |
+
typical functions and their input/output examples in Figure 7.
|
|
|
|
| 990 |
|
| 991 |
+
Figure 7: The visualization of different functions.
|
| 992 |
|
| 993 |
+
14
|
| 994 |
|
| 995 |
+
NameArgumentsOutputCommentCountViewNumberReturnthe number of rows in the ViewWithinView, Header String, Cell String/NumberBoolReturn whetherthe cell string/number exists under the Header Column of the given viewWithoutView, Header String, Cell String/NumberBoolReturn whetherthe cell string/number does not exist under the Header Column of the given viewNoneStringBoolWhether the string representsNone, like “None”, “No”, “-”, “No information provided”Before/AfterRow, RowRowReturnswhether row1 is before/after row2First/Second/Third/FourthView, RowBoolReturns whether the rowis in the first/second/third position of the viewAverage/Sum/Max/MinView, HeaderStringNumberReturns theaverage/summation/max/min value under the Header Column of the given viewArgmin/ArgmaxView, Header StringRowReturns the row with the maximum/minimum value under the Header Column of thegiven viewHopRow,Header StringNumber/StringReturns thecell value under the Header Column of the given rowDiff/AddNumber, NumberNumberPerform arithmetic operations on twonumbersGreater/LessNumber, NumberBoolReturns whetherthe first number is greater/less than the second numberEqual/UnequalString, String/Number,NumberBoolComparetwo numbers or strings to see whether they are the sameFilter_eq/Filter_greater/Filter_less/Filter_greater_or_equal/Filter_less_or_equalView, HeaderString, NumberViewReturnsthe subviewof the given with the cell values under the Header column greater/less/eq/…against the given numberAll_eq/All_greater/All_less/All_greater_or_equal/All_less_or_equalView, HeaderString, NumberBoolReturnsthe whether all of the cell values under the Header column are greater/less/eq/…against the given numberAnd/OrBool, BoolBoolReturns the Booleanoperation results of two inputsCountNameAge()=2within(, Name, A)=𝑇𝑟𝑢𝑒NameAgeABwithout(, Name, A)=𝐹𝑎𝑙𝑠𝑒NameAgeABNone() =𝑇𝑟𝑢𝑒-/Not Given/NABeforeNameAgeA()=𝑇𝑟𝑢𝑒NameAgeBFirstNameAgeA() =𝑇𝑟𝑢𝑒Avg(, Age)=3NameAgeA2B4Argmin(, Age)=NameAgeA2B4NameAgeA2Filter_eq(, Age, 2)=NameAgeA2B4NameAgeA2All_eq(, Age, 2)=TrueNameAgeA2B2HopNameAgeA(, Name)=𝐴Diff(2, 1)=1Greater(2, 1)=𝑇𝑟𝑢𝑒Equal(2, 2)=𝑇𝑟𝑢𝑒, Published as a conference paper at ICLR 2020
|
| 996 |
|
| 997 |
+
We list all the trigger words for different functions in Figure 8
|
| 998 |
|
| 999 |
+
Figure 8: The trigger words used to shrink the search space.
|
| 1000 |
|
| 1001 |
+
B HIGHER-ORDER OPERATIONS
|
| 1002 |
|
| 1003 |
+
1. Aggregation: the aggregation operation refers to sentences like “the averaged age of all
|
| 1004 |
|
| 1005 |
+
....”, “the total amount of scores obtained in ...”, etc.
|
| 1006 |
|
| 1007 |
+
2. Negation: the negation operation refers to sentences like “xxx did not get the best score”,
|
| 1008 |
|
| 1009 |
+
“xxx has never obtained a score higher than 5”.
|
| 1010 |
|
| 1011 |
+
3. Superlative: the superlative operation refers to sentences like “xxx achieves the highest
|
| 1012 |
|
| 1013 |
+
score in”, “xxx is the lowest player in the team”.
|
| 1014 |
|
| 1015 |
+
4. Comparative: the comparative operation refers to sentences like “xxx has a higher score
|
| 1016 |
|
| 1017 |
+
than yyy”.
|
|
|
|
| 1018 |
|
| 1019 |
+
5. Ordinal: the ordinal operation refers to sentences like “the first country to achieve xxx is
|
|
|
|
|
|
|
| 1020 |
|
| 1021 |
+
xxx”, “xxx is the second oldest person in the country”.
|
| 1022 |
|
| 1023 |
+
6. Unique: the unique operation refers to sentences like “there are 5 different nations in the
|
| 1024 |
|
| 1025 |
+
tournament, ”, “there are no two different players from U.S”
|
| 1026 |
|
| 1027 |
+
7. All:
|
| 1028 |
|
| 1029 |
+
the for all operation refers to sentences like “all of the trains are departing in the
|
| 1030 |
|
| 1031 |
+
morning”, “none of the people are older than 25.”
|
| 1032 |
|
| 1033 |
+
8. None: the sentences which do not involve higher-order operations like “xxx achieves 2
|
| 1034 |
|
| 1035 |
+
points in xxx game”, “xxx player is from xxx country”.
|
| 1036 |
|
| 1037 |
+
C ERROR ANALYSIS
|
| 1038 |
|
| 1039 |
+
Before we quantitatively demonstrate the error analysis of the two methods, we first theoretically
|
| 1040 |
+
analyze the bottlenecks of the two methods as follows:
|
| 1041 |
|
| 1042 |
+
Symbolic We first provide a case in which the symbolic execution can not deal with theoretically
|
| 1043 |
+
in Figure 9. The failure cases of symbolic are either due to the entity link problem or function
|
| 1044 |
+
coverage problem. For example, in the given statement below, there is no explicit mention of ”7-5,
|
| 1045 |
+
6-4” cell. Therefore, the entity linking model fails to link to this cell content. Furthermore, even
|
| 1046 |
|
| 1047 |
+
15
|
| 1048 |
|
| 1049 |
+
TriggerFunction'average'average'difference', 'gap', 'than', 'separate'diff'sum', 'summation', 'combine', 'combined', 'total', 'add', 'all', 'there are'ddd, sum'not', 'no', 'never', "didn't", "won't", "wasn't", "isn't,"haven't", "weren't", "won't", 'neither', 'none', 'unable,'fail', 'different', 'outside', 'unable', 'fail'not_eq, not_within,Filter_not_eq,none'not', 'no', 'none'none'first', 'top', 'latest', 'most'first'last', 'bottom', 'latest', 'most'last'RBR', 'JJR', 'more', 'than', 'above', 'after'filter_greater,greater'RBR', 'JJR', 'less', 'than', 'below', 'under'filter_less, less'all', 'every', 'each'all_eq, all_less, all_greater, ['all', 'every', 'each'], ['not', 'no', 'never', "didn't", "won't", "wasn't"]all_not_eq'at most', 'than'all_less_eq, all_greater_eq'RBR', 'RBS', 'JJR', 'JJS'max, min'JJR', 'JJS', 'RBR', 'RBS', 'top', 'first'argmax, argmin'within', 'one', 'of', 'among'within'follow', 'following', 'followed', 'after', 'before', 'above', 'precede'before'follow', 'following', 'followed', 'after', 'before', 'above', 'precede'after’most’most_freqordinalFirst, second,third, fourthPublished as a conference paper at ICLR 2020
|
| 1050 |
|
| 1051 |
+
though we can successfully link to this string, there is no defined function to parse ”7-5, 6-5” as ”won
|
| 1052 |
+
two games” because it requires linguistic/mathematical inference to understand the implication from
|
| 1053 |
+
the string. Such cases are the weakness of symbolic reasoning models.
|
| 1054 |
|
| 1055 |
+
Figure 9: The error case of symbolic reasoning model
|
| 1056 |
|
| 1057 |
+
BERT In contrast, Table-BERT model seems to have no coverage problem as long as it can feed
|
| 1058 |
+
the whole table content. However, due to the template linearization, the table is unfolded into a long
|
| 1059 |
+
sequence as depicted in Figure 10. The useful information, ”clay” are separated in a very long span
|
| 1060 |
+
of unrelated words. How to grasp such a long dependency and memorize the history information
|
| 1061 |
+
poses a great challenge to the Table-BERT model.
|
| 1062 |
|
| 1063 |
+
Figure 10: The error case of BERT NLI model
|
| 1064 |
|
| 1065 |
+
Statistics Here we pick 200 samples from the validation set which only involve single semantic
|
| 1066 |
+
and divide them into different categories. We denote the above-mentioned cases as ”linguistic in-
|
| 1067 |
+
ference”, and the sentences which only describe information from one row as ”Trivial”, the rest are
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based on their logic operation like Aggregation, Superlative, Count, etc. We visualize the accuracy
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of LPA and Table-BERT in Figure 11. From which we can observe that the statements with linguis-
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tic inference are much better handled with the BERT model, while LPA achieves an accuracy barely
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higher than a random guess. The BERT model can deal with trivial cases well as it uses a horizontal
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scan order. In contrast, the LPA model outperforms BERT on higher-order logic cases, especially
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when the statement involves operations like Count and Superlative.
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16
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outcomedatetournamentsurfacepartneropponents in the finalscore in the finalrunner -up1985Bologna , ItalyclayAlberto TousPaolo CanèSimone Colombo5 -7 , 4 -6winner1986Bordeaux , FranceclayDavid De MiguelRonald AgénorMansour Bahrami7 -5 , 6 -4winner1989Prague , CzechoslovakiaclayHorst SkoffPetr KordaTomáššmíd6 -4 , 6 -4Jordi Arreseachieves better score in 1986 than in 1985.Jordi ArreseJordi Arresewon both of the final games in 1986.1986: Winner1986: Runner-upLinguistic Inference7 -5 , 6 -4Mathematic Inferenceoutcomedatetournamentsurfacepartneropponents in the finalscore in the finalrunner -up1985Bologna , ItalyclayAlberto TousPaolo CanèSimone Colombo5 -7 , 4 -6winner1986Bordeaux , FranceclayDavid De MiguelRonald AgénorMansour Bahrami7 -5 , 6 -4winner1989Prague , CzechoslovakiaclayHorst SkoffPetr KordaTomáššmíd6 -4 , 6 -4Jordi ArreseJordi Arreseplayed all of his games on clay surface.Given the table titled “Jordi Arrese”, in row one, the outcome is runner-up, the date is 1985, … , the surface is clay…. …… , In row two, the outcome is … , the surface is clay. In row three, the outcome is …, … the surface is clay.TemplateLong DependencyThe three “Clay” are separated by more over 20 wordsPublished as a conference paper at ICLR 2020
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Figure 11: The error analysis of two different models
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D REASONING DEPTH
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Given that our LPA has the breadth to cover a large semantic space. Here we also show the reasoning
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depth in terms of how many logic inference steps are required to tackle verify the given claims. We
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visualize the histogram in Figure 12 and observe that the reasoning steps are concentrated between
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4 to 7. Such statistics indicate the difficulty of fact verification in our TABFACT dataset.
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Figure 12: The histogram of reasoning steps required to verify the claims
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E WHETHER TO KEEP WIKIPEDIA CONTEXT
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Before crowd-sourcing the annotation for the tables, we observed that the previous WikiTableQues-
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tion Pasupat & Liang (2015) provides context (Wikipedia title) during annotation while the Wik-
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iSQL Zhong et al. (2017) does not. Therefore, we particularly design ablation annotation tasks to
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compare the annotation quality between w/ and w/o Wikipedia title as context. We demonstrate a
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typical example in Figure 13, where a Wiki table10 aims to describe the achievements of a tennis
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player named Dennis, but itself does not provide any explicit hint about “Tennis Player Dennis”.
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Unsurprisingly, the sentence fluency and coherence significantly drop without such information.
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Actually, a great portion of these Wikipedia tables requires background knowledge (like sports,
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celebrity, music, etc) to understand. We perform a small user study to measure the fluency of an-
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notated statements. Specifically, we collected 50 sentences from both annotation w/ and w/o title
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context and randomly shuffle them as pairs, which are distributed to the 8 experts without telling
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them their source to compare the language fluency. It turns out that the experts ubiquitously agree
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that the statements with Wikipedia titles are more human-readable. Therefore, we argue that such
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a context is necessary for annotators to understand the background knowledge to write more flu-
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ent sentences. On the other end, we also hope to minimize the influence of the textual context in
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the table-based verification task, therefore, we design an annotation criterion: the Wikipedia title
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10https://en.wikipedia.org/wiki/Dennis_Ralston
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17
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4550556065707580LinguisticTrivialAggregationSuperlativeCountCompareNegationError Analysis of LPA/Table-BERTTable-BERTLPA050000100000150000200000250000300000350000400000450000Reasoning Depth Statistics in LPA1234567Published as a conference paper at ICLR 2020
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is provided to the workers during the annotation, but they are explicitly banned from bringing any
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unrelated background information other than the title into the annotation. As illustrated in Figure 13,
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the title only acts as a placeholder in the statements to make it sound more natural.
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Figure 13: Comparison of worker annotation w/ and w/o Wikipedia title as context
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F ENTITY LINKING
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Here we propose to use the longest string match to find all the candidate entities in the table, when
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multiple candidates coexist, we select the one with the minimum edit distances. The visualization is
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demonstrated in Figure 14.
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Figure 14: Entity Linking System.
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G THE PROGRAM CANDIDATES
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Here we demonstrate some program candidates in Figure 15, and show how our proposed discrimi-
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nator is designed to compute the matching probability between the statement and program. Specif-
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ically, we employ two transformer-based encoder Vaswani et al. (2017), the left one is aimed to
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encode the program sequence and the right one is aimed to encode the statement sequence. Their
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output from [CLS] position is concatenated and fed into an MLP to classify the verification label.
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H HIT INTERFACE
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We provide the human intelligent task interface on AMT in the following. Very detailed instructions
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on what are trivial statements and what are non-trivial statements. Comprehensive examples have
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been given to guide the Turkers to write well-formed while logically plausible statements. In order
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to harvest fake statements without statistical cues, we also provide detailed instructions on how to
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re-write the ”fake” statements. During the annotation, we hire 8 experts to perform sanity checks on
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each of the HIT to make sure that the annotated dataset is clean and meets our requirements.
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18
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Context(Title)Richard Dennis Ralston(born July 27, 1942, an American formertennisplayerNo Informationis providedAnnotateFrom 1960 to 1969, Ralston won five major double championships.Winner is on the grass surface.Rafael Osuna is partner in the Wimbeldonoutcomeyearchampionshipsurfacepartnerwinner1960Wimbledon championshipsgrassRafael Osunawinner1961US ChampionshipsgrassChuck Mckinleyrunner -up1962US ChampionshipsgrassChuck Mckinleywinner1963US Championships (2)grassChuck MckinleyDistrictIncumbentPartyResultCandidatesCalifornia 3John E. Mossdemocraticre-electedJohn E. Moss (d) 69.9% John Rakus(r) 30.1%California 5Phillip Burtondemocraticre-electedPhillip Burton (d) 81.8% EdloE. Powell (r) 18.2%california8George Paul Millerdemocraticlost renomination democratic holdPeteStark(d) 52.9% Lew M. Warden, Jr. (r) 47.1%California 14Jerome R. Waldierepublicanre-electedJeromeR. Waldie(d) 77.6% FloydE. Sims(r) 22.4%California 15John J. Mcfallrepublicanre-electedJohn J. Mcfall(d) unopposedStatement: John E. Mossis a democratic who is from California 3 districtJohnJohn E. Moss (d) 69.9% johnrakus(r) 30.1%John E. MossJohn J. McfallJohnE. MossJohn E. Moss (d) 69.9% johnrakus(r) 30.1%John E. MossisPublished as a conference paper at ICLR 2020
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Figure 15: We demonstrate the top program candidates and use the discriminator to rank them.
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19
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Statement: There are more democraticthan republicanin the election. Less(Count(Filter(incumbent==democratic)), Count(Filter(incumbent==republican)))=FalseLess(Count(Filter(incumbent==republican)), Count(Filter(incumbent==democratic)))=TrueGreater(Count(Filter(incumbent==republican)), Count(Filter(incumbent==democratic)))=FalseGreater(Count(Filter(incumbent==democratic)),Count(Filter(incumbent==republican)))=TrueWithin((Filter(incumbent==democratic), incumbent, republican)=FalseWithin((Filter(incumbent==republican), incumbent, democratic)=FalseAnd(Same(all_rows, incumbent, democratic), Same(all_rows, incumbent, republican))=TrueOr(Same(all_rows, incumbent, democratic), Same(all_rows, incumbent, republican))=TrueEq(Count(Filter(incumbent==republican)), Count(Filter(incumbent==democratic)))=FalseProgram EncoderStatement EncoderLabel11/8/2019HIThttps://s3.amazonaws.com/mturk_bulk/hits/370501562/uNGk1Dz1zM48BZI6mALfxA.html1/4Survey Instructions (Click to expand)You are given a table with its wikipedia source, your job is to compose non-trivial statements supportedby the table.- "Trivial": the sentence can be easily generated by looking only a certain row without understanding thetable.- "Non-trivial": the sentence requires reading multiple rows of the table and understanding of the tablecontent. For example, the sentences which include summarization, comparative, negation, relational,inclusion, superlative, aggregational, rephrase or combinations of them are non-trivial. But non-trvial is notlimited to these types, any statement involving understanding and reasoning is accepted. We list two examples below to help you understand, you are encouraged to open the table wikipedia link tounderstand the context of the table. (Everything in the table is lower-cased, you are free to use lower or uppercase in your sentence):Table Wikipedia Link: Road_Rules_Challenge:_The_Island(https://en.wikipedia.org/wiki/Real_World/Road_Rules_Challenge:_The_Island)playeroriginal seasongendereliminatedplacingderrick kosinskirr : x - trememalewinnerwinnerevelyn smithfresh meatfemalewinnerwinnerjohnny devenanziorw : key westmalewinnerwinnerkenny santuccifresh meatmalewinnerwinnerjenn grijalvarw : denverfemaleepisode 8runner - uppaula meronekrw : key westfemaleepisode 8runner - uprobin hibbardrw : san diegofemaleepisode 8runner - upryan kehoefresh meatmaleepisode 8runner - updunbar merrillrw : sydneymaleepisode 89th placejohanna bottarw : austinfemaleepisode 810th placekellyanne juddrw : sydneyfemaleepisode 811th placedan walshrr : viewers' revengemaleepisode 812th placecolie edisonrw : denverfemaleepisode 713th placecohutta grindstaffrw : sydneymaleepisode 614th placetyrie ballardrw : denvermaleepisode 515th placeashli robsonrw : sydneyfemaleepisode 416th placerachel robinsonrr : campus crawlfemaleepisode 317th placeabram boiserr : south pacificmaleepisode 218th placedave malinoskyrw : hollywoodmaleepisode 2 (quit)19th placeRejected ("Trivial") examples:1. In the TV series "The Island", Derrick Kosinski is a male character. (Easy! You can simply look into firstrow to produce this sentence.)2. Derrick Kosinski has the placing of winner in the TV series.3. Kenny Santucci is from original season of "Fresh Meat".11/8/2019HIThttps://s3.amazonaws.com/mturk_bulk/hits/370501562/uNGk1Dz1zM48BZI6mALfxA.html2/4Table Wikipedia Link: AFC_Champions_League (https://en.wikipedia.org/wiki/AFC_Champions_League) Tips1: We set minimum length to 9, and sentences with more complicated grammar structures arepreferred. Tips2: Do not limited to only one type of description like superlative or relative. Tips3: Copying the records from the table is encouraged, which can help avoid typos and mis-spelling asmuch as possible, . Tips4: Do not vague words like "maybe", "perhaps", "good", "excellent", "most", etc. 4. Jenn Grijalva is Runner-Up of the challenge.Accepted ("Non-Trivial") examples: (Superlative): In the TV series "The Island", Evelyn Smith is the highest ranked female. (Comparitive): In the TV series "The Island", Jenn Grijalva appears later than Colie Edison in the series.(Relational): Ashli Robson appears one episode later than Rachel Robinson in the TV series.(Summarization): there are three male winners in the challenge.(Rephrase): Evelyn Smith never eliminated in any episode in the TV series.(Combination): Derrick Kosinski is the winner and Jenn Grijalva is Runner-Up of the challenge.(Negation): jenn grijalva is not the female winning the challenge. (Inclusion): Evelyn smith is one of the four winner for the challenge.rankmember associationpointsgroup stageplay - offafc cup1saudi arabia860.54002qatar838.24003iran813.53104uae750.22205uzbekistan680.81006india106.40027jordan128.7002Rejected ("Trivial") examples:1. In the rank, it has 0 play - off.2. ratar is in rank 2.3. When member association is india, the points is 106.4.Accepted ("Non-Trivial") examples: (Negation): iran is one of the two countries getting into the 4th stage. (Average): uae and qatar have anaverage of 1 play - off during the champion league. (Algorithmic): saudi arabia achieves 22.3 more points than qatar. (Comparison): india got lower points than jordan in the league. (Summarization): there are two team which have won the afc cup twice.(Superlative): In the Champions League, saudi arabia achieves the highest points. (Combination): saudi arabia is the group stage 4 while iran is in group stage 3.11/8/2019HIThttps://s3.amazonaws.com/mturk_bulk/hits/370501562/uNGk1Dz1zM48BZI6mALfxA.html3/4First Read the following table, then write five diverse non-trivial facts for this given table:Table Source: athletics at the 1952 summer olympics - men 's pole vault(https://en.wikipedia.org/wiki/Athletics_at_the_1952_Summer_Olympics_%E2%80%93_Men%27s_pole_vault)athletenationality3.603.803.95resultbob richardsunited states--o4.55 ordon lazunited states--o4.50ragnar lundbergsweden--o4.40petro denysenkosoviet union--o4.40valto oleniusfinland---4.30bunkichi sawadajapan-oxxo4.20volodymyr brazhnyksoviet union-oo4.20viktor knyazevsoviet union-oo4.20george mattosunited states--o4.20erkki katajafinland--o4.10tamás homonnaysweden-oo4.10lennart lindhungary-oo4.10milan milakovyugoslavia-oxo4.10rigas efstathiadisgreece-oo3.95torfy bryngeirssoniceland-oo3.95erling kaasnorway-oxxx3.80theodosios balafasgreeceooxxx3.80jukka piironenfinland-xoxx3.80zeno dragomirromania-xoxx3.80Please write a non-trivial statement, minimum 9 wordsPlease write a non-trivial statement, minimum 9 wordsPlease write a non-trivial statement, minimum 9 wordsPlease write a non-trivial statement, minimum 9 wordsPlease write a non-trivial statement, minimum 9 words11/8/2019HIThttps://s3.amazonaws.com/mturk_bulk/hits/391922557/v_5b2TrRmw9TnD5hSI_CnA.html1/3Survey Instructions (Click to expand)Please first read a table to understand its content, an example is shown below, which contains theleaderboard of a competition.PlayerOriginal SeasonGenderEliminatedPlacingDerrick KosinskiRR: X-TremeMaleWinnerWinnerEvelyn SmithFresh MeatFemaleWinnerWinnerJohnny DevenanzioRW: Key WestMaleWinnerWinnerKenny SantucciFresh MeatMaleWinnerWinnerJenn GrijalvaRW: DenverFemaleEpisode 8Runner-UpPaula MeronekRW: Key WestFemaleEpisode 8Runner-UpRobin HibbardRW: San DiegoFemaleEpisode 8Runner-UpRyan KehoeFresh MeatMaleEpisode 8Runner-UpDunbar MerrillRW: SydneyMaleEpisode 89th PlaceJohanna BottaRW: AustinFemaleEpisode 810th PlaceKellyAnne JuddRW: SydneyFemaleEpisode 811th PlaceDan WalshRR: Viewers' RevengeMaleEpisode 812th PlaceColie EdisonRW: DenverFemaleEpisode 713th PlaceCohutta GrindstaffRW: SydneyMaleEpisode 614th PlaceTyrie BallardRW: DenverMaleEpisode 515th PlaceAshli RobsonRW: SydneyFemaleEpisode 416th PlaceRachel RobinsonRR: Campus CrawlFemaleEpisode 317th PlaceAbram BoiseRR: South PacificMaleEpisode 218th PlaceDave MalinoskyRW: HollywoodMaleEpisode 2 (quit)19th PlaceTonya CooleyRW: ChicagoFemaleEpisode 120th PlaceYou are given a sentence to describe a fact in the table, please follow the following two cases to finish thejob:* If the given sentence is fluent and consistent with the table, then please re-write it to make it"fake" based on the following criteria:1. Contradictory: it should still be a fluent and coherent, but it needs be explicitly contrdictory to thefacts in the table.2. Do not simply add NOT to revert the sentence meaning.3. Do not write neutral or non-verifiable sentences, you need to confirm it in the table.3. The fake statement needs to be clear, explicit and natural, do not use vague or ambiguous words like"bad", "good", "many", etc.4. try to use diverse fake types during annotatoin.Example 1. Given statement: Ashli Robson was eliminated in episode 4.Good Faking: Ashli Robson survives through episode 1 to episode 5.Good Faking: Ashli Robson is not the only one eliminated in episode 4.Bad Faking (Simply add not): Ashli Robson was not eliminated on episode 4.11/8/2019HIThttps://s3.amazonaws.com/mturk_bulk/hits/391922557/v_5b2TrRmw9TnD5hSI_CnA.html2/3Bad Faking (Ambiguous, who is Ashli?): Ashli was not eliminated on episode 4.Bad Faking (Irrelevant): Ashli was born in Mexico.Bad Faking (Too subjective, what do you mean by "early"): AshlDerrick Kosinski lost the game very early.Bad Faking (Not verifiable): AshlDerrick Kosinski was the most popular player.Example 2. Given statement: Tonya Cooley is in the 20th place.Good Faking: Tonya Cooley is not the last in placing.Good Faking: Tonya Cooley is eliminated in episode 1 but not the last in placing.Bad Faking: (There is nothing larger than 20th) Tonya Cooley is after the 20th place.Bad Faking: (Half Wrong/half Right) When the gneder is female, the player is Tonya Colley.Bad Faking (Introduce values outside the table): Tonya Cooley is in the 43th place. Bad Faking (Typo): Tonya Cooler is in the 20th palace. * If the given statement is erroneous (see following), please type in N/A in the input box.1. critical grammar error like missing verbs, nouns, etc. Do not count small errors like tense,singular/plural, case errors.2. serious typo, misspelling.3. the described fact is contradictory to the table.You can use the highlight button to help you find the mentions in the table, you can use eitherupper or lower case, not important11/8/2019HIThttps://s3.amazonaws.com/mturk_bulk/hits/391922557/v_5b2TrRmw9TnD5hSI_CnA.html3/3SubmitFirst Read the given tables, then rewrite the statements to make them fake:Table Source: 2003 - 04 isu junior grand prix(https://en.wikipedia.org/wiki/2003%E2%80%9304_ISU_Junior_Grand_Prix)ranknationgoldsilverbronzetotal1russia10148322united states967223canada4210164japan454135hungary40266czech republic21146ukraine13046italy01347sweden12038israel11029finland00119france0101Hightlight Mentions, Click Me!Given Statement: russia won the most silver medals in the grand prixPlease rewrite a sentence which is contradictory to the tableHightlight Mentions, Click Me!Given Statement: france and finland won the least medals in the grand prixPlease rewrite a sentence which is contradictory to the tableHightlight Mentions, Click Me!Given Statement: hungary and finland were the only countries that idd not win any silver medalsPlease rewrite a sentence which is contradictory to the tableHightlight Mentions, Click Me!Given Statement: the united states won more gold medals than canadaPlease rewrite a sentence which is contradictory to the tableHightlight Mentions, Click Me!Given Statement: canada won the most bronze medals in the grand prixPlease rewrite a sentence which is contradictory to the table
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OREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)IntroductionClimate & Health Vulnerability AssessmentPURPOSEThis vulnerability assessment is intended to inform public health professionals and community partners engaged in climate change adaptation and resilience planning. It focuses specifically on social vulnerability as a way to integrate the concepts of social determinants of health and environmental justice into climate change planning.PROCESSThe Climate and Health Program developed this assessment in consultation with other grantees of the CDC’s Climate Ready States and Cities Initiative. The assessment is based on associations identified in research literature, which are summarized in the 2014 Oregon Climate and Health Profile Report.The Climate and Health Program envisions this assessment being updated and expanded as our knowledge grows and conditions change. This first edition, published in Fall 2015, is limited to measures of population sensitivity. In the future, we anticipate adding measures of hazard exposure such as extreme heat, and adaptive capacity, such as access to air conditioning. Additionally, we hope to expand the composite vulnerability index in subsequent assessments to incorporate more measures of vulnerability, and we hope to add context by analyzing the key drivers in each community.We acknowledge that maps of social and demographic characteristics do not tell the whole story. For example, there may be strengths that enable some communities to readily overcome vulnerabilities. This assessment is just one of many pieces of information that can help Oregon’s public health system prepare for the impacts of climate change.FOR MORE INFORMATIONContact:Climate and Health Programbrendon.haggerty@state.or.us(971) 673-0335Or visit:healthoregon.org/climateOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivitySocial vulnerabilityABOUT THIS INDICATORThis index is a combination eleven indicators of social vulnerability including measures of demographics, socioeconomic status, and health. The indicators are drawn from US Census data and health statistics from the Oregon Health Authority. Each indicator is equally weighted, and the index is relative to other census tracts in the state. Census tracts shaded dark blue represent areas with higher social vulnerability. These tracts are distributed in many parts of the state, and largely overlap with broad indicators of socioeconomic status such as educational attainment.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYIndexes such as this one are based on the work of Susan Cutter (1), which established associations between natural hazards and indicators of social vulnerability. They are used to help understand vulnerability to climate impacts in many jurisdictions (2, 3).DATA SOURCESOregon Climate & Health Program, Public Health Division, Oregon Health Authority. July 2015.See bibliography for references.For more information, visit healthoregon.org/climateComposite vulnerability indexCensus TractsLowMediumHighCounty borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityBirth outcomesABOUT THIS INDICATORThe percentage of births that are pre-term is an indicator of risks for infants calculated from birth certificate records. While darker blue represents a larger percent of preterm births, counties are mostly similar on this metric, varying between about 6% and 11%.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYPreterm births are associated with extreme heat (1) and air pollution (2). Moreover, adverse birth outcomes like preterm birth or low birth weight are associated with problems during early childhood (3) as well as long term health effects including risk of cardiovascular disease (4). Existing illness such as those linked to adverse birth outcomes result in greater vulnerability to negative health impacts of climate change.DATA SOURCESBirth Risk Factors: Oregon Birth Certificates, Center for Health Statistics, Center for Public Health Practice, Public Health Divsion, Oregon Health Authority.See bibliography for references.For more information, visit healthoregon.org/climatePercent of infants born <36 weeks of pregnancyCounties6.2% - 7.4%7.5% - 8.1%8.2% - 10.5%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityChildrenABOUT THIS INDICATORThe population of the youngest Oregon residents is unevenly distributed, as reflected in the above map showing the percent of the population within under age 18. Darker blue tracts indicate higher concentrations of children. Statewide, 22% of the population is under 18 years of age.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYInfants and children are vulnerable to multiple climate impacts. Young children are more susceptible to extreme heat (1). Children are more vulnerable to environmental toxins of all types, since the same dose given to an adult is lower in proportion to body size (2). This makes children more sensitive to contaminated food, water, and air resulting from impacts of climate change. One study estimated that 88% of the additional burden of disease due to climate change falls upon children (3).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of population aged less than 18 yearsCensus tracts0% - 19.2%19.3% - 24.2%24.3% - 38.1%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityChronic DiseaseABOUT THIS INDICATORBody Mass Index (BMI) is a population-level indicator of obesity levels. The estimates in the map above are derived from de-identified driver license data, adjusted for age, and averaged over whole census tracts. BMI is indicative of chronic illness, since it is closely associated with diseases such as diabetes, cardiovascular disease, and depression.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYPeople with existing illness are more vulnerable to climate change impacts because the changing climate has potential to exacerbate many conditions. For example, extreme heat increases the risk of heat-related death for those with diabetes (1), and air quality issues arising from heat or wildfire can worsen asthma symptoms (2). Moreover, extreme weather events such as floods and landslides can disrupt care and access to needed medication (3).DATA SOURCESOregon Environmental Public Health Tracking. 2015.[data files]. Available at www.epht.oregon.govSee bibliography for references.For more information, visit healthoregon.org/climateCensus tracts0.0 - 26.226.3 - 27.127.2 - 30.4County borders05010025MilesAge-adjusted mean body mass indexOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityEducational AttainmentABOUT THIS INDICATORThe percent of adults aged 25 years or over without a high school diploma is a common measure of educational attainment collected by the US Census Bureau. In other jurisdictions, this indicator was found to be a primary driver of social vulnerability (1). This map displays the percentage of adults in each census tract who do not have a high school diploma or equivalent. Dark blue census tracts reflect higher percentages of adults with low educational attainment.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYLow educational attainment is associated with greater vulnerability to heat related illness (2, 3, 4) and exposure to air pollution (5,6). As noted in the Oregon Climate and Health Profile Report, exposure to these hazards is likely to increase in Oregon as a result of climate change.DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of adults aged 25+ without a high school diplomaCensus tracts0% - 6.7%6.8% - 12%12.1% - 56.3%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityForeign-born populationABOUT THIS INDICATORThis indicator is a partial substitute for indicators of vulnerability used in other assessments (1). The percent of the population born outside the US is indicative of potential linguistic isolation or citizenship status. In this map, areas of darkest blue represent the highest percentages of people born outside the US. These tracts are found primarily in the Willamette Valley and Columbia River Gorge.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYThis indicator is suggests linguistic isolation, limited capacity to access resources, and potential difficulty asserting labor and housing rights. Together, these traits are associated with vulnerability to a range of climate-related hazards, including heat related illness, extreme weather, and occupational exposures (2).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of population born outside of the United StatesCensus tracts0% - 4.6%4.7% - 10.1%10.2% - 44.7%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityIsolated older adultsABOUT THIS INDICATORThe percent of households that are single-person aged 65 years or older indicates the co-occurrence of two types of vulnerability: advanced age and social isolation. Social isolation can take many forms, but this indicator from the census is among the most readily available. The map above shows high percentages of single-person older adult households in dark blue. Unlike the percent of adults aged 65 or older, the percentage of single-person older householders shows a less distinct spatial pattern.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYSocial isolation can result in a lack of supportive contact networks that can be relied upon in extreme conditions. This indicator is associated with greater vulnerability to extreme heat (1, 2).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of households that are single-person aged 65 years or olderCensus tracts0% - 7%7.1% - 11.1%11.2% - 40.3%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityOlder adultsABOUT THIS INDICATORIn the above map, dark blue represents areas with higher percentages of older adults. A very clear pattern is present: there are higher percentages of older adults in rural areas. The lowest percentages are found in the state’s urban areas in the Willamette Valley, Central Oregon, and near Medford.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYOlder adults are more vulnerable to multiple hazards, especially extreme heat (1, 2, 3). This is partly because of the decreased ability to regulate body temperature that normally comes with age. Risk is elevated for many older adults because of medications or chronic conditions such as diabetes or cardiovascular disease. As a result, older adults have the highest rates of heat-related illness and heat-related death. Older adults are also more vulnerable to poor air quality and infectious diseases related to climate change (4).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of population aged 65 years or olderCensus tracts0% - 11%11.1% - 17.1%17.2% - 46%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityRace and ethnicityABOUT THIS INDICATORThis indicator measures the proportion of the population who identifies as a race or ethnicity other than non-Hispanic white. Greater percentages are represented by darker shades of blue. Diverse communities are found across Oregon, with some greater concentrations in the lower Willamette Valley, North Central area, and parts of Eastern and Southern Oregon.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYOregon’s communities of color are already disproportionately burdened by illness and lack of access to health-supportive resources (1). Research suggests ways communities of color are more vulnerable to certain climate hazards, including: greater sensitivity and exposure to air pollutants (2, 3), fewer resources for recovery from extreme weather events (4), and inadequacy of existing warning systems (5).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent identifying as a race other than non-Hispanic whiteCensus tracts0% - 15.9%16% - 27.2%27.3% - 97.2%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivitySocioeconomic statusABOUT THIS INDICATORThe percent of households earning less than 200% of the federal poverty level is an indicator of socioeconomic status at the census tract level. In 2015, the poverty level for a family of 4 was about $24,000. Low-income households are part of communities throughout Oregon.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYLow-income households have few resources to cope with climate-related health impacts. Compared to wealthier households, disasters have a greater impact on low-income populations as a result of geographic isolation, type of residence and social exclusion (1). Lower income households are more likely to live in urban heat islands, have higher exposure to air pollutants, and are less likely to be able to afford protective measures like air conditioning (2, 3, 4).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of households with incomes <200% of Federal Poverty LevelCensus tracts0% - 29.1%29.2% - 42.2%42.3% - 91.7%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityTenureABOUT THIS INDICATORThe US Census Bureau provides estimates of the proportion of occupied housing units that are occupied by renters. In this map, dark blue tracts represent areas with a high proportion of renters. While it may appear to be a small number of tracts, they are overwhelmingly concentrated in urban areas with greater density. The dark blue tracts represent 1/3 of Oregon’s population.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYRenters are less able to mitigate climate threats by investing time, labor, and equipment in protective measures. This is attributed to financial barriers and lack of incentive to engage in protective maintenance (e.g. removing trees that elevate fire risk) (1).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of housing occupants occupied by rentersCensus tracts0% - 27.2%27.3% - 42%42.1% - 100%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Population sensitivityUnemploymentABOUT THIS INDICATOREmployment status is commonly included in measures of vulnerability (1). The American Community Survey provides estimates of the percent of the population age 16 years or older who are unemployed. On the above map, darker shades of blue represent greater unemployment rates. Tracts with high unemployment are distributed throughout the state.HOW THIS INDICATOR IS RELATED TO CLIMATE VULNERABILITYLike other indicators of socioeconomic status, the percentage of adults who are unemployed helps to illustrate peoples’ capacity to cope with climate stressors. This indicator also provides a baseline by which we can judge whether changes to the economy resulting from climate instability are affecting workers. Additionally, there is evidence that employment status shapes migration patterns (2).DATA SOURCES2009-2013 American Community Survey 5-year estimates. US Census Bureau.See bibliography for references.For more information, visit healthoregon.org/climatePercent of population aged 16 years or older who are unemployedCensus tracts0% - 9%9.1% - 12.8%12.9% - 32.6%County borders05010025MilesOREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)BibliographyBIRTH OUTCOMES1. Basu R., Malig B., Ostro B. (2010) High Ambient Temperature and the Risk of Preterm Delivery. American Journal of Epidemiology,172:1108–172. Fleischer, N.L., Merialdi, M., van Donkelaar, A., Vadillo-Ortega, F., Martin, R.V., Betran, A. P., & Souza, J. P. (2014). Outdoor air pollution, preterm birth, and low birth weight: analysis of the world health organization global survey on maternal and perinatal health. Environmental Health Perspectives, 122(4), 425.3. Kramer, M.S., Demissie, K., Yang, H., Platt, R.W., Sauvé, R., & Liston, R. (2000). The contribution of mild and moderate preterm birth to infant mortality. Journal of the American Medical Association, 284(7), 843-849.4. Rogers, L. K., & Velten, M. (2011). Maternal inflammation, growth retardation, and preterm birth: insights into adult cardiovascular disease. Life Sciences,89(13), 417-421.CHILDREN1. Sheffield P.E., Knowlton K., Carr J.L., Kinney P.L. (2011). Modeling of regional climate change effects on ground-level ozone and childhood asthma. American Journal of Preventive Medicine, 41:251–72. Basu, R. (2009). High ambient temperature and mortality: a review of epidemiologic studies from 2001 to 2008. Environmental Health, 8(1), 40.3. U.S. Environmental Protection Agency. America’s Children and the Environment [Internet]. (2000). Available from: http://yosemite.epa.gov/ochp/ochpweb.nsf/content/ACE-Report.htm/$File/ ACE-Report.pdfCHRONIC DISEASE1. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Diez-Roux, A.V., Brown, D.G., & Schwartz, J.D. (2009). Mapping community determinants of heat vulnerability. Environmental Health Perspectives, 117(11):1730-1736 2. Gent J.F., Triche E.W., Holford T.R., Belanger K., Bracken M.B., Beckett W.S., et al. Association of low-level ozone and fine particles with respiratory symptoms in children with asthma. Journal of the American Medical Association. 2003;290:1859– 67.3. Kessler R.C. (2007).Hurricane Katrina’s impact on the care of survivors with chronic medical conditions. Journal of General Internal Medicine, 22:1225–30.EDUCATIONAL ATTAINMENT1. Cooley, H., & Pacifica Institute. (2012). Social vulnerability to climate change in California. California Energy Commission.2. O’Neill, M. S., Zanobetti, A., & Schwartz, J. (2003). Modifiers of the temperature and mortality association in seven US cities. American Journal of Epidemiology, 157(12), 1074-1082.3. Basu, R. (2009). High ambient temperature and mortality: a review of epidemiologic studies from 2001 to 2008. Environmental Health, 8(1), 40.4. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Diez-Roux, A.V., Brown, D.G., & Schwartz, J.D. (2009). Mapping community determinants of heat vulnerability. Environmental Health Perspectives, 117(11):1730-1736 5. Krewski, D., R. T. Burnett, et al. (2000). Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of Particulate Air Pollution and Mortality. Boston, Massachusetts: Health Effects Institute.6. Pope III, C. A., & Dockery, D. W. (2006). Health effects of fine particulate air pollution: lines that connect. Journal of the Air & Waste Management Association, 56(6), 709-742FOREIGN-BORN POPULATION1. Cooley, H., & Pacifica Institute. (2012). Social vulnerability to climate change in California. California Energy Commission.2. Shonkoff, S. B., Morello-Frosch, R., Pastor, M., & Sadd, J. (2011). The climate gap: environmental health and equity implications of climate change and mitigation policies in California—a review of the literature. Climatic Change,109(1), 485-503.ISOLATED OLDER ADULTS1. McGeehin, M. A., & Mirabelli, M. (2001). The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States. Environmental health perspectives, 109(Suppl 2), 185.2. English, P. B., Sinclair, A. H., Ross, Z., Anderson, H., Boothe, V., Davis, C., Ebi, K., Kagey, B., Malecki, K., Shultz, R.m & Simms, E. (2009). Environmental health indicators of climate change for the United States: findings from the State Environmental Health Indicator Collaborative. Environmental Health Perspectives, 117(11), 1673-81.OLDER ADULTS1. Knowlton, K., Rotkin-Ellman, M., King, G., Margolis, H.G., Smith, D., Solomon, G., Trent R., & English, P. (2009). The 2006 California heat wave: impacts on hospitalizations and emergency department visits. Environmental Health Perspectives,117(1), 61-67.2. Basu, R., & Ostro, B. D. (2008). A multicounty analysis identifying the populations vulnerable to mortality associated with high ambient temperature in California. American Journal of Epidemiology, 168(6), 632-637.3. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Diez-Roux, A.V., Brown, D.G., & Schwartz, J.D. (2009). Mapping community determinants of heat vulnerability. Environmental Health Perspectives, 117(11):1730-1736 4. Gamble, J. L., Hurley, B. J., Schultz, P. A., Jaglom, W. S., Krishnan, N., & Harris, M. (2013). Climate change and older Americans: state of the science. Environmental Health Perspectives, 121(1), 15-22.OREGON HEALTH AUTHORITY | CLIMATE AND HEALTH PROGRAM OHA (10.15)Bibliography - continuedRACE AND ETHNICITY1. Oregon Health Authority. State of Equity Report [Internet]. 2013. Available from: http://www.oregon.gov/ oha/oei/Pages/soe.aspx2. Gwynn R.C., Thurston G.D. (2001). The burden of air pollution: impacts among racial minorities. Environmental Health Perspectives,109 Suppl 501–6.3. Medina-Ramón M., Schwartz J. (2008). Who is more vulnerable to die from ozone air pollution? Epidemiology,19:672–9.4. Toldson I.A., Ray K., Hatcher S.S., Louis L.S. (2011). Examining the long-term racial disparities in health and economic conditions among Hurricane Katrina survivors: Policy implications for Gulf Coast recovery. Journal of Black Studies, 42:360–78.5. Hayden M.H., Drobot S., Radil S., Benight C., Gruntfest E.C., Barnes L.R. (2007). Information sources for flash flood warnings in Denver, CO and Austin, TX. Environmental Hazards, 7:211SOCIAL VULNERABILITY1. Cutter, S.L., Boruff, B.J., & Shirley, W.L. (2003). Social vulnerability to environmental hazards. Social Science Quarterly, 84(2), 242-261.2. Cooley, H., & Pacifica Institute. (2012). Social vulnerability to climate change in California. California Energy Commission.3. Minnesota Department of Health. 2014. Minnesota Climate Change Vulnerability Assessment 2014. October 2014, Saint Paul, MNSOCIOECONOMIC STATUS1. Fothergill A, Peek LA. (2004). Poverty and Disasters in the United States: A Review of Recent Sociological Findings. Natural Hazards, 32:89–1102. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Diez-Roux, A.V., Brown, D.G., & Schwartz, J.D. (2009). Mapping community determinants of heat vulnerability. Environmental Health Perspectives, 117(11):1730-1736 3. Basu, R., & Ostro, B.D. (2008). A multicounty analysis identifying the populations vulnerable to mortality associated with high ambient temperature in California. American Journal of Epidemiology, 168(6), 632-637.4. Harlan S.L., Brazel A.J., Prashad L., Stefanov W.L., Larsen L. (2006). Neighborhood microclimates and vulnerability to heat stress. Social Science and Medicine, 63:2847–63.TENURE1.Collins, Timothy W., & Bolin, B. (2009). Situating hazard vulnerability: people’s negotiations with wildfire environments in the US Southwest. Environmental Management, 44.3: 441-455.UNEMPLOYMENT1. Cutter, S.L., Boruff, B.J., & Shirley, W L. (2003). Social vulnerability to environmental hazards. Social Science Quarterly, 84(2), 242-261.2. Reuveny, R. (2007). Climate change-induced migration and violent conflict. Political Geography, 26(6), 656-673.
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| 1 |
+
DOI: 10.1111/polp.12517
|
| 2 |
+
|
| 3 |
+
O R I G I N A L A R T I C L E
|
| 4 |
+
|
| 5 |
+
The fluid voter: Exploring independent voting patterns
|
| 6 |
+
over time
|
| 7 |
+
|
| 8 |
+
Thom Reilly1
|
| 9 |
+
|
| 10 |
+
| Dan Hunting2
|
| 11 |
+
|
| 12 |
+
1School of Public Affairs, Arizona State
|
| 13 |
+
University, Phoenix, Arizona, USA
|
| 14 |
+
|
| 15 |
+
2Lodestar Center for Philanthropy and
|
| 16 |
+
Nonprofit Innovation, Arizona State
|
| 17 |
+
University, Phoenix, Arizona, USA
|
| 18 |
+
|
| 19 |
+
Correspondence
|
| 20 |
+
|
| 21 |
+
Thom Reilly, School of Public Affairs, Arizona
|
| 22 |
+
State University, 411 N Central Ave. Office 422K,
|
| 23 |
+
Mail Code 3720, Phoenix, AZ 85005, USA.
|
| 24 |
+
Email: thom.reilly@asu.edu
|
| 25 |
+
|
| 26 |
+
Abstract
|
| 27 |
+
Independents remain hard to categorize because they are, by
|
| 28 |
+
their choice of self-identification, resisting the standard cate-
|
| 29 |
+
gories of political classification. Despite the growth in inde-
|
| 30 |
+
pendent voter identity, many political strategists still view
|
| 31 |
+
independents as partisans. In this article, we contribute to the
|
| 32 |
+
academic literature on independent voting behavior by explor-
|
| 33 |
+
ing whether those who identify as politically independent
|
| 34 |
+
function as true independents by accounting for their voting
|
| 35 |
+
patterns over time. We do this by analyzing data produced by
|
| 36 |
+
the American National Election Studies (ANES) on political
|
| 37 |
+
identification and voting choices from 1972 to 2020 on each
|
| 38 |
+
of the three ANES measures of party affiliation. Our findings
|
| 39 |
+
show when tracking independent voting behavior over more
|
| 40 |
+
than one election, there is a significant volatility in voting
|
| 41 |
+
loyalty and independents as a group are distinct from parti-
|
| 42 |
+
sans. This volatility was observed in all three measures of party
|
| 43 |
+
affiliation used by the ANES survey data. The research also
|
| 44 |
+
finds evidence that a sizeable number of independents move
|
| 45 |
+
in and out of independent status from one election to another.
|
| 46 |
+
|
| 47 |
+
K E Y W O R D S
|
| 48 |
+
ANES, elections, fluid voter, independent voter, over time, partisanship,
|
| 49 |
+
political behavior, political parties, United States, volatility, voter identifi-
|
| 50 |
+
cation, voting behavior, voting loyalty
|
| 51 |
+
|
| 52 |
+
Related Articles
|
| 53 |
+
Grossmann, Matt. 2014. “The Varied Effects of Policy Cues
|
| 54 |
+
on Partisan Opinions.” Politics & Policy 42(6): 881–904.
|
| 55 |
+
https://doi.org/10.1111/polp.12102.
|
| 56 |
+
Reilly, Thom, and E. C. Hedberg. 2022. “Social Networks
|
| 57 |
+
of Independents and Partisans: Are Independents a Moder-
|
| 58 |
+
ating Forcer?” Politics & Policy 50(2): 225–43. https://doi.
|
| 59 |
+
org/10.1111/polp.12460.
|
| 60 |
+
Saeki, Manabu. 2019. “Anatomy of Party Sorting: Parti-
|
| 61 |
+
san Polarization of Voters and Party Switching.” Politics &
|
| 62 |
+
Policy 47(4): 699–747. https://doi.org/10.1111/polp.12318.
|
| 63 |
+
|
| 64 |
+
Politics & Policy. 2023;00:1–22.
|
| 65 |
+
|
| 66 |
+
wileyonlinelibrary.com/journal/polp
|
| 67 |
+
|
| 68 |
+
1
|
| 69 |
+
|
| 70 |
+
© 2023 Policy Studies Organization.
|
| 71 |
+
2
|
| 72 |
+
|
| 73 |
+
THE FLUID VOTER
|
| 74 |
+
|
| 75 |
+
Americans are increasingly declaring independence from the political parties. The rise in political
|
| 76 |
+
independence is likely an outgrowth of Americans' record or near-record negative views of the
|
| 77 |
+
U.S. two-party system (Ingraham, 2021) and their low level of trust in government (PEW, 2022).
|
| 78 |
+
Self-defined independent voters now number between 40% and 46% of the U.S. electorate
|
| 79 |
+
(Gallup, 2022) and currently constitute either the largest or second-largest group of registered
|
| 80 |
+
voters in half the states (Gruber & Opdycke, 2020). Despite the historical increase in independ-
|
| 81 |
+
ent voter identification, many political strategists still view independents as partisans (Magleby
|
| 82 |
+
et al., 2011; Petrocik, 2009) and contend that the overwhelming majority of Americans who say
|
| 83 |
+
they are “independent” really lean toward one party or the other. However, other scholars have
|
| 84 |
+
disputed the findings that most independents are leaners and suggest that there is no conclusive
|
| 85 |
+
evidence for this position (Abrams & Fiorina, 2011).
|
| 86 |
+
|
| 87 |
+
Our study seeks to contribute to the academic literature by exploring whether those who are
|
| 88 |
+
identified as politically independent function as true independents by accounting for their voting
|
| 89 |
+
patterns over time. We are interested in determining whether independents move in and out of
|
| 90 |
+
independent status. We do this by reviewing the voting behavior of Democrats, Republicans,
|
| 91 |
+
and independents over multiple election cycles. Our research seeks to address the following three
|
| 92 |
+
questions:
|
| 93 |
+
|
| 94 |
+
1. Does political identification change across time?
|
| 95 |
+
2. How do respondents allocate their votes across parties?
|
| 96 |
+
3. Do voting choices change over time?
|
| 97 |
+
|
| 98 |
+
LITERATURE REVIEW
|
| 99 |
+
|
| 100 |
+
The classification of voters as independent dates back to the seminal work of Angus Campbell
|
| 101 |
+
and his colleagues, who first published The American Voter in 1960 (Campbell et al., 1960).
|
| 102 |
+
Analyzing data collected under the University of Michigan Survey Research Center (and later
|
| 103 |
+
aggregated by the American National Election Studies; ANES Data Center, 2021), the authors
|
| 104 |
+
describe the identity of party affiliation as a central characteristic explaining voting behavior
|
| 105 |
+
and other political attitudes and behaviors. The surveys that The American Voter analyzed have
|
| 106 |
+
been considered by many to be the gold standard in the field. Though officially founded in 1978,
|
| 107 |
+
the American National Election Studies (ANES) program has continuous survey data on the
|
| 108 |
+
electorate since 1948. The survey is usually administered every other year, but occasionally every
|
| 109 |
+
fourth year. ANES is a comprehensive survey which provides much information on respondents'
|
| 110 |
+
background and political attitude.
|
| 111 |
+
|
| 112 |
+
The American Voter authors acknowledged that some kind of “independent” existed but
|
| 113 |
+
characterized the independent as having little interest in campaigns and outcomes and suggested
|
| 114 |
+
their choice between competing candidates is uninformed. Most of what we know about inde-
|
| 115 |
+
pendents comes from survey data, and most surveys predispose the majority of independents as
|
| 116 |
+
leaners toward either of the two political parties. Since 1952, when individuals identified them-
|
| 117 |
+
selves as an independent, researchers and pollsters have asked a follow-up question on whether
|
| 118 |
+
respondents prefer one party over the other if they had to vote then and there.
|
| 119 |
+
|
| 120 |
+
In addition to asking respondents to identify themselves from a three-point scale: Democrat,
|
| 121 |
+
Republican, and independent, respondents were asked to self-identify on the ANES seven-point
|
| 122 |
+
political spectrum (ANES Data Center, 2015):
|
| 123 |
+
|
| 124 |
+
1. Strong Democrat
|
| 125 |
+
2. Democrat
|
| 126 |
+
3. Independent, leans Democrat
|
| 127 |
+
4. Independent
|
| 128 |
+
|
| 129 |
+
REILLY anD HUnTInG
|
| 130 |
+
|
| 131 |
+
3
|
| 132 |
+
|
| 133 |
+
5. Independent, leans Republican
|
| 134 |
+
6. Republican
|
| 135 |
+
7. Strong Republican
|
| 136 |
+
|
| 137 |
+
Since the seven-point measure was introduced in the 1952 survey, researchers accessing the ANES
|
| 138 |
+
data were able to use several measures. They could use the seven-point measure, a five-point
|
| 139 |
+
measure by collapsing the three independent categories into one (as the authors of the Amer-
|
| 140 |
+
ican Voter did), a three-point measure with leaners classed as independents, or a three-point
|
| 141 |
+
measure with leaners classified as partisans. Researchers used any or all of these measures often
|
| 142 |
+
depending on which coding decision gave them big enough cell sizes for analysis by re-coding the
|
| 143 |
+
data or not (DeBell, 2010).
|
| 144 |
+
|
| 145 |
+
Viewing the majority of independents as partisans originates from the formative research
|
| 146 |
+
popularized in The Myth of the Independent Voter (Keith et al., 1992), which claimed that the
|
| 147 |
+
ANES' “Seven-Point Scale” should only include three actual categories (Democrat, Repub-
|
| 148 |
+
lican, and Independent). After the Petrocik (2009) and Keith and others' (1992) articles, it
|
| 149 |
+
became more common to use a five-point or three-point measure with leaners classified as
|
| 150 |
+
independents.
|
| 151 |
+
|
| 152 |
+
Most independents indicated a lean toward one of the two major political parties' candi-
|
| 153 |
+
dates. Political scientists have labeled these individuals as “independent leaners” and have argued
|
| 154 |
+
that the number of pure independents is actually quite small—below 10%. This percentage has
|
| 155 |
+
remained constant since the 1950s (Mayer, 2008; PEW, 2019; Sides, 2013), and many political
|
| 156 |
+
scientists assert that the overwhelming majority of Americans who say there are “independent”
|
| 157 |
+
lean toward one party or the other (Teixiera, 2012).
|
| 158 |
+
|
| 159 |
+
Klar and Krupnikov (2016) have recently added some important research on the independent
|
| 160 |
+
voter. They explored the social significance of the growth in people refusing to identify them-
|
| 161 |
+
selves with a political party and suggested that independents and partisans differ psychologically
|
| 162 |
+
(Klar & Krupnikov, 2016). They do not dispute the notion that independents may be “closet
|
| 163 |
+
partisans” (they call them “undercover partisans”); but they do dispute the bias that independ-
|
| 164 |
+
ents are not politically engaged, stating that “engagement levels are comparable across independ-
|
| 165 |
+
ents and partisans” (Klar, 2014). They assert that many Americans are embarrassed by their
|
| 166 |
+
political party and do not wish to be associated with either side. Instead, they intentionally mask
|
| 167 |
+
their party preference, especially in social situations (Klar & Krupnikov, 2016). Nonetheless, they
|
| 168 |
+
contend that the refusal to publicly identify with a party must be revealing something important.
|
| 169 |
+
And they believe the predictors of independent political engagement differ substantially from
|
| 170 |
+
partisans.
|
| 171 |
+
|
| 172 |
+
However, there are some researchers that disagree with the assertion that independents
|
| 173 |
+
are leaners and suggest there is more volatility in their voter patterns, and that a sizeable
|
| 174 |
+
number of independents move in and out of independent status in ways that impact inde-
|
| 175 |
+
pendent voting over time (Abrams & Fiorina, 2011; Fiorina, 1977, 2016; Jackson, 1975;
|
| 176 |
+
Page & Jones, 1979). Their identification may depend on specific candidates or issues on the
|
| 177 |
+
ballot (Reilly et al., 2023) or may derive from short-term interest rather than a long-standing
|
| 178 |
+
loyalty (Miller, 1991). Fiorina (2017), professor of political science at Stanford University and
|
| 179 |
+
former chairman of the board of the ANES, contends that following independent leaners
|
| 180 |
+
over several elections is key to understanding their voting patterns. Along with his colleague
|
| 181 |
+
Samuel J. Abrams, they conducted such an analysis and found that, following independent
|
| 182 |
+
leaners across multiple elections, their partisan stability is closer to pure independents than
|
| 183 |
+
weak partisans (Fiorina, 2017). They also noted that “classifying all leaners as weak partisans
|
| 184 |
+
mis-characterizes the partisanship of Americans and overestimates the rate of party voting”
|
| 185 |
+
(Abrams & Fiorina, 2011). Other researchers have argued that responses to survey question
|
| 186 |
+
probes asking independents if they lean toward the Democratic or Republican Party are
|
| 187 |
+
significantly contaminated by short-term electoral elements operating in the campaign, such
|
| 188 |
+
|
| 189 |
+
4
|
| 190 |
+
|
| 191 |
+
THE FLUID VOTER
|
| 192 |
+
|
| 193 |
+
as the candidates and specific issues (Abrams & Fiorina, 2011; Brody, 1978, 1991; Brody &
|
| 194 |
+
Rothenberg, 1988; Miller, 1991).
|
| 195 |
+
|
| 196 |
+
Finally, given the lack of data on voting patterns of independents in state races and
|
| 197 |
+
down-ballot (other than for president, governor, and Congress), there is growing interest in
|
| 198 |
+
examining the characteristics and attitudes of unaffiliated or independent voters as they
|
| 199 |
+
compare to voters from the two major parties. Bitzer and others (2022) researched down-ballot
|
| 200 |
+
voters in North Carolina and found unaffiliated voters were not simply shadow partisans but
|
| 201 |
+
varied from Democrats and Republicans in terms of demographics, political behavior, and polit-
|
| 202 |
+
ical attitudes.
|
| 203 |
+
|
| 204 |
+
OUR EXPECTATIONS
|
| 205 |
+
|
| 206 |
+
Our study seeks to contribute to the academic literature by exploring whether those who are
|
| 207 |
+
identified as politically independent function as true independents by accounting for their voting
|
| 208 |
+
patterns over time. The study also explores whether independents move in and out of independ-
|
| 209 |
+
ent status.
|
| 210 |
+
|
| 211 |
+
We begin with a description of ANES data and the three measures of party affiliation used
|
| 212 |
+
by the survey. Analysis then begins with a look at how the political identification of voters
|
| 213 |
+
changes over multiple survey waves using each of the three ANES scales to be described in the
|
| 214 |
+
next section. This analysis includes a parallel review of respondents who voted in both waves and
|
| 215 |
+
those who voted in neither wave. We next investigate how frequently respondents to the ANES
|
| 216 |
+
vote “straight tickets”—always choosing candidates from the same party—or “mixed tickets”
|
| 217 |
+
where some Republican and some Democrat candidates are chosen. It is expected that those
|
| 218 |
+
identifying as Democrat or Republican will mostly choose candidates from their own party,
|
| 219 |
+
while independents will show more variety in their choices. These results will also be reported on
|
| 220 |
+
each of the three political identification scales discussed below. Finally, we explore the degree to
|
| 221 |
+
which individuals change their voting choices over time.
|
| 222 |
+
|
| 223 |
+
METHODOLOGY
|
| 224 |
+
|
| 225 |
+
The ANES Cumulative Data File (CDF) is used to examine political identification and voting
|
| 226 |
+
choices from 1972 to 2020 (ANES Data Center, n.d.). Although the CDF contains data dating
|
| 227 |
+
back to 1948, restricting the analysis to data from 1972 onward provided the best balance of: (a)
|
| 228 |
+
providing a large enough sample to be useful and (b) capturing attitudes and trends that are rele-
|
| 229 |
+
vant in the current social and political climate. There have been substantial demographic changes
|
| 230 |
+
in the United States over the 72 years of ANES data. Additionally, prior to the passage of the
|
| 231 |
+
Voting Rights Act of 1965, large portions of the population were effectively disenfranchised.
|
| 232 |
+
These changes become evident when pre-1972 ANES data are compared to 1972–2020 data.
|
| 233 |
+
Prior to 1972, 6.4% of ANES respondents who reported voting were non-White, but the figure
|
| 234 |
+
jumps to 22.4% when looking at voters between 1972 and 2020. This percentage is much more in
|
| 235 |
+
line with current voter profiles. Smaller, but still important, changes are evident in the age distri-
|
| 236 |
+
bution and gender of respondents across the two time periods. Eighteen- to twenty-year-olds
|
| 237 |
+
made up 1.5% of the pre-1972 respondents and 5.9% after that. Females made up 52.4% of
|
| 238 |
+
the pre-1972 respondents and 53.8% from 1972 to 2020. The 1972–2020 data are more closely
|
| 239 |
+
aligned with current voter demographics, making this analysis more applicable to today's voters.
|
| 240 |
+
This dataset includes political identification information for respondents and self-reported
|
| 241 |
+
voting choices for president, Senate, Congress, and governor races. Since the ANES does not
|
| 242 |
+
show 2020 election preference data in the CDF, these data were linked to the CDF using the
|
| 243 |
+
Respondent ID from the ANES 2020 timeseries file. The resulting file was then formatted so that
|
| 244 |
+
|
| 245 |
+
REILLY anD HUnTInG
|
| 246 |
+
|
| 247 |
+
5
|
| 248 |
+
|
| 249 |
+
each record represented a unique respondent, capturing party identification on three scales and
|
| 250 |
+
reported voting choices for all survey waves that each respondent answered.
|
| 251 |
+
|
| 252 |
+
We examine three questions, looking at each on three different political identification scales:
|
| 253 |
+
|
| 254 |
+
1. Does political identification change across time?
|
| 255 |
+
2. How do respondents allocate their votes across parties?
|
| 256 |
+
3. Do voting choices change over time?
|
| 257 |
+
|
| 258 |
+
To probe these areas, we look at political identification with three different scales commonly used
|
| 259 |
+
by the ANES. First, with the initial party identification queried in question VCF0302, which
|
| 260 |
+
asks, “Generally speaking, do you usually think of yourself as a Democrat, a Republican, an
|
| 261 |
+
Independent, or what?” This “Initial Party ID Response” gives a three-point scale with Demo-
|
| 262 |
+
crats and Republicans, and all minor-party and independent respondents grouped under the
|
| 263 |
+
independent umbrella. Second, we use the ANES Seven-Point Scale (VCF0301, “Seven Point
|
| 264 |
+
Scale”) that divides Democrats and Republicans into “strong” and “weak” supporters of their
|
| 265 |
+
parties, and divides independents into Democrat-leaners, Republican-leaners, and true independ-
|
| 266 |
+
ents. Finally, we use the modified three-point scale from VCF0303 “Summary 3-Category.” The
|
| 267 |
+
Summary 3-Category measure collapses the Seven-Point Scale by counting Democrat-leaning
|
| 268 |
+
independents as Democrats and Republican-leaning independents as Republicans. This leaves
|
| 269 |
+
only a small fraction of the respondents as independents.
|
| 270 |
+
|
| 271 |
+
American National Election Studies Survey
|
| 272 |
+
|
| 273 |
+
The CDF was downloaded in SPSS format and filtered to include responses from 1972 to 2020.
|
| 274 |
+
Since 2020 post-election voting information is not currently in the CDF, data from the 2020
|
| 275 |
+
time-series file were joined to the CDF to provide complete information on the 2016–2020 panel.
|
| 276 |
+
The resulting file contains responses from 43,423 individuals, of whom 27,832 voted in at least
|
| 277 |
+
one election (Table 1).
|
| 278 |
+
|
| 279 |
+
The ANES contains data on how respondents reported voting on four different contests,
|
| 280 |
+
giving the party choice for president, Congress, Senate, and governor. Respondents do not neces-
|
| 281 |
+
sarily vote in each of these races due to the timing of elections. Choices for a total of 77,729
|
| 282 |
+
contests are recorded for the 27,832 voters in the data. For each election cycle, the total number
|
| 283 |
+
of votes for Democratic, Republican, and third-party candidates were totaled for each respond-
|
| 284 |
+
ent, along with their party identification at that time. The survey has also included time-series
|
| 285 |
+
panel data from time to time, where respondents are contacted multiple times over the years. For
|
| 286 |
+
respondents that appeared in multiple waves of the survey, their votes and party identification
|
| 287 |
+
were tallied at each survey point.
|
| 288 |
+
|
| 289 |
+
Since 1970, there have been seven panels as shown in Table 2, each covering a single presi-
|
| 290 |
+
dential election. Of the 13,399 respondents to the survey in these panels, 4770 voted in all waves
|
| 291 |
+
available to them. These voters reported their voting choice on a total of 25,024 races for pres-
|
| 292 |
+
ident, Congress, Senate, and governor. Due to the timing of election cycles, not all respondents
|
| 293 |
+
reported voting in each of these races in each wave of the survey.
|
| 294 |
+
|
| 295 |
+
Party identification on three scales
|
| 296 |
+
|
| 297 |
+
ANES CDF classifies the political identification of respondents according to their answers to
|
| 298 |
+
questions VCF0302, VCF0301, and VCF0303.
|
| 299 |
+
|
| 300 |
+
VCF0302 is the initial party identification response and asks:
|
| 301 |
+
|
| 302 |
+
6
|
| 303 |
+
|
| 304 |
+
THE FLUID VOTER
|
| 305 |
+
|
| 306 |
+
T A B L E 1 ANES respondents by year
|
| 307 |
+
|
| 308 |
+
Total respondents
|
| 309 |
+
|
| 310 |
+
Respondents who voted
|
| 311 |
+
|
| 312 |
+
Total votes tallied
|
| 313 |
+
|
| 314 |
+
Year
|
| 315 |
+
|
| 316 |
+
1972
|
| 317 |
+
|
| 318 |
+
1974
|
| 319 |
+
|
| 320 |
+
1976
|
| 321 |
+
|
| 322 |
+
1978
|
| 323 |
+
|
| 324 |
+
1980
|
| 325 |
+
|
| 326 |
+
1982
|
| 327 |
+
|
| 328 |
+
1984
|
| 329 |
+
|
| 330 |
+
1986
|
| 331 |
+
|
| 332 |
+
1988
|
| 333 |
+
|
| 334 |
+
1990
|
| 335 |
+
|
| 336 |
+
1992
|
| 337 |
+
|
| 338 |
+
1994
|
| 339 |
+
|
| 340 |
+
1996
|
| 341 |
+
|
| 342 |
+
1998
|
| 343 |
+
|
| 344 |
+
2000
|
| 345 |
+
|
| 346 |
+
2002
|
| 347 |
+
|
| 348 |
+
2004
|
| 349 |
+
|
| 350 |
+
2008
|
| 351 |
+
|
| 352 |
+
2012
|
| 353 |
+
|
| 354 |
+
2016
|
| 355 |
+
|
| 356 |
+
2020
|
| 357 |
+
|
| 358 |
+
2705
|
| 359 |
+
|
| 360 |
+
475
|
| 361 |
+
|
| 362 |
+
1323
|
| 363 |
+
|
| 364 |
+
2304
|
| 365 |
+
|
| 366 |
+
1614
|
| 367 |
+
|
| 368 |
+
1418
|
| 369 |
+
|
| 370 |
+
2257
|
| 371 |
+
|
| 372 |
+
2176
|
| 373 |
+
|
| 374 |
+
2040
|
| 375 |
+
|
| 376 |
+
1980
|
| 377 |
+
|
| 378 |
+
1126
|
| 379 |
+
|
| 380 |
+
1036
|
| 381 |
+
|
| 382 |
+
398
|
| 383 |
+
|
| 384 |
+
1281
|
| 385 |
+
|
| 386 |
+
1807
|
| 387 |
+
|
| 388 |
+
324
|
| 389 |
+
|
| 390 |
+
1212
|
| 391 |
+
|
| 392 |
+
2322
|
| 393 |
+
|
| 394 |
+
5914
|
| 395 |
+
|
| 396 |
+
4270
|
| 397 |
+
|
| 398 |
+
5441
|
| 399 |
+
|
| 400 |
+
1718
|
| 401 |
+
|
| 402 |
+
237
|
| 403 |
+
|
| 404 |
+
691
|
| 405 |
+
|
| 406 |
+
1167
|
| 407 |
+
|
| 408 |
+
989
|
| 409 |
+
|
| 410 |
+
798
|
| 411 |
+
|
| 412 |
+
1427
|
| 413 |
+
|
| 414 |
+
1087
|
| 415 |
+
|
| 416 |
+
1226
|
| 417 |
+
|
| 418 |
+
1236
|
| 419 |
+
|
| 420 |
+
807
|
| 421 |
+
|
| 422 |
+
693
|
| 423 |
+
|
| 424 |
+
239
|
| 425 |
+
|
| 426 |
+
648
|
| 427 |
+
|
| 428 |
+
1240
|
| 429 |
+
|
| 430 |
+
160
|
| 431 |
+
|
| 432 |
+
829
|
| 433 |
+
|
| 434 |
+
1580
|
| 435 |
+
|
| 436 |
+
4355
|
| 437 |
+
|
| 438 |
+
3124
|
| 439 |
+
|
| 440 |
+
3581
|
| 441 |
+
|
| 442 |
+
7215
|
| 443 |
+
|
| 444 |
+
760
|
| 445 |
+
|
| 446 |
+
1731
|
| 447 |
+
|
| 448 |
+
2463
|
| 449 |
+
|
| 450 |
+
2572
|
| 451 |
+
|
| 452 |
+
1860
|
| 453 |
+
|
| 454 |
+
3314
|
| 455 |
+
|
| 456 |
+
2549
|
| 457 |
+
|
| 458 |
+
3104
|
| 459 |
+
|
| 460 |
+
4294
|
| 461 |
+
|
| 462 |
+
3888
|
| 463 |
+
|
| 464 |
+
2575
|
| 465 |
+
|
| 466 |
+
562
|
| 467 |
+
|
| 468 |
+
1509
|
| 469 |
+
|
| 470 |
+
3838
|
| 471 |
+
|
| 472 |
+
247
|
| 473 |
+
|
| 474 |
+
2058
|
| 475 |
+
|
| 476 |
+
3624
|
| 477 |
+
|
| 478 |
+
11,322
|
| 479 |
+
|
| 480 |
+
12,981
|
| 481 |
+
|
| 482 |
+
5263
|
| 483 |
+
|
| 484 |
+
77,729
|
| 485 |
+
|
| 486 |
+
Total
|
| 487 |
+
|
| 488 |
+
43,423
|
| 489 |
+
|
| 490 |
+
27,832
|
| 491 |
+
|
| 492 |
+
T A B L E 2 Multiple-wave voters in ANES data, 1972–2000
|
| 493 |
+
|
| 494 |
+
Year of 1st wave
|
| 495 |
+
|
| 496 |
+
Year of 2nd wave
|
| 497 |
+
|
| 498 |
+
Total respondents
|
| 499 |
+
|
| 500 |
+
Voted in both waves
|
| 501 |
+
|
| 502 |
+
Total votes in
|
| 503 |
+
Wave 1
|
| 504 |
+
|
| 505 |
+
Total votes
|
| 506 |
+
in Wave 2
|
| 507 |
+
|
| 508 |
+
1972
|
| 509 |
+
|
| 510 |
+
1974
|
| 511 |
+
|
| 512 |
+
1990
|
| 513 |
+
|
| 514 |
+
1992
|
| 515 |
+
|
| 516 |
+
1994
|
| 517 |
+
|
| 518 |
+
2000
|
| 519 |
+
|
| 520 |
+
2016
|
| 521 |
+
|
| 522 |
+
Grand total
|
| 523 |
+
|
| 524 |
+
1974
|
| 525 |
+
|
| 526 |
+
1976
|
| 527 |
+
|
| 528 |
+
1992
|
| 529 |
+
|
| 530 |
+
1994
|
| 531 |
+
|
| 532 |
+
1996
|
| 533 |
+
|
| 534 |
+
2002
|
| 535 |
+
|
| 536 |
+
2020
|
| 537 |
+
|
| 538 |
+
2705
|
| 539 |
+
|
| 540 |
+
475
|
| 541 |
+
|
| 542 |
+
1980
|
| 543 |
+
|
| 544 |
+
1126
|
| 545 |
+
|
| 546 |
+
1036
|
| 547 |
+
|
| 548 |
+
1807
|
| 549 |
+
|
| 550 |
+
4270
|
| 551 |
+
|
| 552 |
+
13,399
|
| 553 |
+
|
| 554 |
+
658
|
| 555 |
+
|
| 556 |
+
83
|
| 557 |
+
|
| 558 |
+
582
|
| 559 |
+
|
| 560 |
+
444
|
| 561 |
+
|
| 562 |
+
367
|
| 563 |
+
|
| 564 |
+
604
|
| 565 |
+
|
| 566 |
+
2032
|
| 567 |
+
|
| 568 |
+
4770
|
| 569 |
+
|
| 570 |
+
1644
|
| 571 |
+
|
| 572 |
+
189
|
| 573 |
+
|
| 574 |
+
902
|
| 575 |
+
|
| 576 |
+
763
|
| 577 |
+
|
| 578 |
+
560
|
| 579 |
+
|
| 580 |
+
1171
|
| 581 |
+
|
| 582 |
+
2858
|
| 583 |
+
|
| 584 |
+
8087
|
| 585 |
+
|
| 586 |
+
701
|
| 587 |
+
|
| 588 |
+
131
|
| 589 |
+
|
| 590 |
+
916
|
| 591 |
+
|
| 592 |
+
463
|
| 593 |
+
|
| 594 |
+
500
|
| 595 |
+
|
| 596 |
+
673
|
| 597 |
+
|
| 598 |
+
2298
|
| 599 |
+
|
| 600 |
+
5682
|
| 601 |
+
|
| 602 |
+
Generally speaking, do you usually think of yourself as a Democrat, a Republican,
|
| 603 |
+
an Independent, or what?
|
| 604 |
+
|
| 605 |
+
VCF0301 is party identification on a Seven-Point Scale and is constructed by combining the
|
| 606 |
+
VCF0302 question with one of two follow-up questions. Respondents who identify as either
|
| 607 |
+
Republicans or Democrats in their initial response are asked a follow-up question:
|
| 608 |
+
|
| 609 |
+
REILLY anD HUnTInG
|
| 610 |
+
|
| 611 |
+
7
|
| 612 |
+
|
| 613 |
+
Would you call yourself a strong [Democrat/Republican] or a not very strong
|
| 614 |
+
[Democrat/Republican]?
|
| 615 |
+
|
| 616 |
+
These responses form the two ends of the Seven-Point Scale, with Strong Democrats coded as 1,
|
| 617 |
+
Weak Democrats coded as 2, Weak Republicans coded as 6, and Strong Republicans as 7. A small
|
| 618 |
+
number (92) of those who expressed partisan affiliation in VCF0302 were coded as DK, NA,
|
| 619 |
+
Other at this point in the survey.
|
| 620 |
+
|
| 621 |
+
Those who did not identify as either Democrats or Republicans are given this follow-up
|
| 622 |
+
|
| 623 |
+
question:
|
| 624 |
+
|
| 625 |
+
Do you think of yourself as closer to the Republican Party or to the Democratic
|
| 626 |
+
Party?
|
| 627 |
+
|
| 628 |
+
These responses are used to construct the middle three categories of the Seven-Point Scale. Those
|
| 629 |
+
answering “Democratic” are assigned to Independent-Democrats (3), with “Republican” coded as
|
| 630 |
+
Independent-Republican (5). Respondents who choose “Neither” are Independent-Independents at
|
| 631 |
+
scale point 4. Note that although the above question is asked in the ANES time series surveys,
|
| 632 |
+
it does not appear in the CDF data. The results of this question are captured in CDF item
|
| 633 |
+
VCF0301. Also note that a small number of respondents answered “do not know” or refused
|
| 634 |
+
to answer VCF0302 but indicated a party preference in the follow-up. These were moved to the
|
| 635 |
+
Independent-Republican and Independent-Democrat categories for VCF0301.
|
| 636 |
+
|
| 637 |
+
Finally, the Seven-Point Scale of VCF0301 is collapsed to three categories for VCF0303.
|
| 638 |
+
This is done by combining the strong and weak Democrats with Independent-Democrats under
|
| 639 |
+
Democrats (including leaners) and ANES political identification data on 43,423 respondents
|
| 640 |
+
from 1972 through 2020 is shown on these three scales in Table 3. Independents make up 36%
|
| 641 |
+
of the total respondents over these surveys, with 13% identified as having no party leaning or
|
| 642 |
+
Independent-Independents.
|
| 643 |
+
|
| 644 |
+
RESULTS
|
| 645 |
+
|
| 646 |
+
Change in political identification over time—voters
|
| 647 |
+
|
| 648 |
+
We now use ANES data from multiple waves to look at how political identification changes for
|
| 649 |
+
voters over time. Between 1972 and 2020, ANES has data on 4770 respondents who voted in
|
| 650 |
+
two consecutive waves of the survey (Table 2). The following section looks at how these voters
|
| 651 |
+
changed their party identification from one survey cycle to the next. A small portion of this
|
| 652 |
+
number did not report party identification on one of the three scales analyzed below.
|
| 653 |
+
|
| 654 |
+
Initial Party ID Response (VCF0302)
|
| 655 |
+
|
| 656 |
+
Of the 4745 respondents shown in Figure 1, 22% changed their initial-response party ID from
|
| 657 |
+
one wave to another. Independents were more fluid on this metric than party-affiliated respond-
|
| 658 |
+
ents: 16% of both Democrats and Republicans were changed at the second survey wave, while
|
| 659 |
+
36% of Independents changed.
|
| 660 |
+
|
| 661 |
+
In each major party, 13% of the wave-one respondents changed their position and identi-
|
| 662 |
+
fied as independents at wave two, while 3% went to the opposite party. Independents saw 17%
|
| 663 |
+
of the wave-one respondents move to Democrat and 19% move to Republican. The absolute
|
| 664 |
+
number of voters switching from party-affiliated to independent (426) and from independent to
|
| 665 |
+
party-affiliated (520) are similar, but the percentage of independents becoming party-affiliated
|
| 666 |
+
|
| 667 |
+
8
|
| 668 |
+
|
| 669 |
+
THE FLUID VOTER
|
| 670 |
+
|
| 671 |
+
T A B L E 3 Three political ID scales: 1972–2020 ANES data
|
| 672 |
+
|
| 673 |
+
Democrat
|
| 674 |
+
|
| 675 |
+
Republican
|
| 676 |
+
|
| 677 |
+
Independent
|
| 678 |
+
|
| 679 |
+
Other
|
| 680 |
+
|
| 681 |
+
DK/NA Total
|
| 682 |
+
|
| 683 |
+
VCF0302 (initial
|
| 684 |
+
response)
|
| 685 |
+
|
| 686 |
+
Percent
|
| 687 |
+
|
| 688 |
+
16,263
|
| 689 |
+
|
| 690 |
+
37%
|
| 691 |
+
|
| 692 |
+
10,976
|
| 693 |
+
|
| 694 |
+
25%
|
| 695 |
+
|
| 696 |
+
VCF0301 (7-Point
|
| 697 |
+
|
| 698 |
+
Scale)
|
| 699 |
+
|
| 700 |
+
Strong
|
| 701 |
+
Dem
|
| 702 |
+
|
| 703 |
+
Weak
|
| 704 |
+
|
| 705 |
+
Weak
|
| 706 |
+
|
| 707 |
+
Dem
|
| 708 |
+
|
| 709 |
+
Rep
|
| 710 |
+
|
| 711 |
+
Strong
|
| 712 |
+
Rep
|
| 713 |
+
|
| 714 |
+
12,772
|
| 715 |
+
|
| 716 |
+
29%
|
| 717 |
+
|
| 718 |
+
3085
|
| 719 |
+
|
| 720 |
+
7%
|
| 721 |
+
|
| 722 |
+
327
|
| 723 |
+
|
| 724 |
+
1%
|
| 725 |
+
|
| 726 |
+
43,423
|
| 727 |
+
|
| 728 |
+
Ind-Dem Ind-Ind Ind-Rep DK/NA Total
|
| 729 |
+
|
| 730 |
+
Percent
|
| 731 |
+
|
| 732 |
+
VCF0303
|
| 733 |
+
|
| 734 |
+
(Summary
|
| 735 |
+
3-Category)
|
| 736 |
+
|
| 737 |
+
Percent
|
| 738 |
+
|
| 739 |
+
8523
|
| 740 |
+
|
| 741 |
+
20%
|
| 742 |
+
|
| 743 |
+
7677
|
| 744 |
+
|
| 745 |
+
18%
|
| 746 |
+
|
| 747 |
+
5354
|
| 748 |
+
|
| 749 |
+
12%
|
| 750 |
+
|
| 751 |
+
5592
|
| 752 |
+
|
| 753 |
+
13%
|
| 754 |
+
|
| 755 |
+
5515
|
| 756 |
+
|
| 757 |
+
13%
|
| 758 |
+
|
| 759 |
+
5677
|
| 760 |
+
|
| 761 |
+
13%
|
| 762 |
+
|
| 763 |
+
4726
|
| 764 |
+
|
| 765 |
+
11%
|
| 766 |
+
|
| 767 |
+
359
|
| 768 |
+
|
| 769 |
+
1%
|
| 770 |
+
|
| 771 |
+
43,423
|
| 772 |
+
|
| 773 |
+
100%
|
| 774 |
+
|
| 775 |
+
Democrat (incl.
|
| 776 |
+
leaners)
|
| 777 |
+
|
| 778 |
+
21,715
|
| 779 |
+
|
| 780 |
+
50%
|
| 781 |
+
|
| 782 |
+
Republican (incl.
|
| 783 |
+
|
| 784 |
+
Independent
|
| 785 |
+
|
| 786 |
+
DK/NA Total
|
| 787 |
+
|
| 788 |
+
leaners)
|
| 789 |
+
|
| 790 |
+
15,672
|
| 791 |
+
|
| 792 |
+
36%
|
| 793 |
+
|
| 794 |
+
5677
|
| 795 |
+
|
| 796 |
+
13%
|
| 797 |
+
|
| 798 |
+
359
|
| 799 |
+
|
| 800 |
+
1%
|
| 801 |
+
|
| 802 |
+
43,423
|
| 803 |
+
|
| 804 |
+
100%
|
| 805 |
+
|
| 806 |
+
F I G U R E 1 Change in initial response (VCF0302) voters, 1972–2020
|
| 807 |
+
|
| 808 |
+
is nearly three times that of party-affiliates becoming independent. Respondents coded as Inde-
|
| 809 |
+
pendent, No Preference, and Other are included in the independent category. This flow is illus-
|
| 810 |
+
trated in Figure 1.
|
| 811 |
+
|
| 812 |
+
Seven-Point Scale (VCF0301)
|
| 813 |
+
|
| 814 |
+
When the Seven-Point Scale of variable VCF0301 is analyzed across two survey waves, more
|
| 815 |
+
fluidity in political identification becomes apparent. Of the 4735 respondents who voted in two
|
| 816 |
+
waves of the survey and recorded scores on this scale in both waves, 43% changed their identifi-
|
| 817 |
+
cation at the second wave. This is nearly double the 22% rate seen in the initial response variable
|
| 818 |
+
above.
|
| 819 |
+
|
| 820 |
+
Partisan respondents at the extremes of the scale were more consistent in their identification,
|
| 821 |
+
with 21% of Strong Democrats and 22% of Strong Republicans changing at the second wave.
|
| 822 |
+
Fifty-seven percent of Weak Democrats and 55% of Weak Republicans changed their identifica-
|
| 823 |
+
tion at wave two. Overall, 36% of Democrats and 36% of Republicans changed their party iden-
|
| 824 |
+
tification by at least one point on this scale between wave one and wave two; this is substantially
|
| 825 |
+
higher than the 36% of party-identified respondents who changed their position.
|
| 826 |
+
|
| 827 |
+
REILLY anD HUnTInG
|
| 828 |
+
|
| 829 |
+
9
|
| 830 |
+
|
| 831 |
+
F I G U R E 2 Change in 7-point scale (VCF0301) voters, 1972–2020
|
| 832 |
+
|
| 833 |
+
The complex flow of the three independent classifications is shown in Figure 2. As noted
|
| 834 |
+
above, 36% of those reporting to be independent at the first wave interview were identifying with
|
| 835 |
+
one of the two parties at the second wave. In addition, another 22% of independents remained
|
| 836 |
+
independent at wave two, but shifted their position within the three independent categories on
|
| 837 |
+
this scale. Overall, 57% of those in one of the three independent categories of the Seven-Point
|
| 838 |
+
Scale changed their identification at wave two. This flow is illustrated in Figure 2.
|
| 839 |
+
|
| 840 |
+
Summary 3-Category Scale (VCF0303)
|
| 841 |
+
|
| 842 |
+
The collapsed categories of the Summary 3-Category Scale presented in VCF0303 necessarily
|
| 843 |
+
suppress much of the change in party identification seen in the previous two scales. By this
|
| 844 |
+
measure, 10% of Democrats (including leaners) and 12% of Republicans (including leaners)
|
| 845 |
+
changed their identification between the two survey waves. The independents represent just 7%
|
| 846 |
+
of respondents on this scale, as those who identify as independent but leaning toward a party are
|
| 847 |
+
grouped with their respective parties. The 328 remaining “true” independents fractured nearly
|
| 848 |
+
in thirds when queried at the second wave: 36% remained Independent while 30% switched to
|
| 849 |
+
Democrat and 34% to Republican. A total of 64% of the Independents from wave one were clas-
|
| 850 |
+
sified as partisans at wave two. Among those classified as either Democrats or Republicans at
|
| 851 |
+
wave one, just 11% changed their identification on this scale at wave two (Figure 3).
|
| 852 |
+
|
| 853 |
+
10
|
| 854 |
+
|
| 855 |
+
THE FLUID VOTER
|
| 856 |
+
|
| 857 |
+
F I G U R E 3 Change in Summary 3-Category Scale (VCF0303) voters, 1972–2020
|
| 858 |
+
|
| 859 |
+
F I G U R E 4 Change in initial response (VCF0302) non-voters, 1972–2020
|
| 860 |
+
|
| 861 |
+
Change in political identification over time—Non-voters
|
| 862 |
+
|
| 863 |
+
ANES data 1972–2020 also contain information on political identification for respondents
|
| 864 |
+
who did not vote. In this section we examine changes in political identification in the 15,292
|
| 865 |
+
respondents who answered two consecutive waves of the survey but voted in neither election.
|
| 866 |
+
For the purposes of this article, we use the term non-voters to identify those respondents who
|
| 867 |
+
did not vote in either wave of this analysis. It is unknown what portion of this population votes
|
| 868 |
+
on occasion.
|
| 869 |
+
|
| 870 |
+
Initial party response (VCF0302)
|
| 871 |
+
|
| 872 |
+
Of the 15,592 respondents shown in Figure 4, 60% changed their initial response party identifi-
|
| 873 |
+
cation from one wave to the next. This is nearly three times the 22% rate seen among those who
|
| 874 |
+
voted in both waves. Fifty-seven percent of the non-voting Democrat-identified respondents and
|
| 875 |
+
|
| 876 |
+
REILLY anD HUnTInG
|
| 877 |
+
|
| 878 |
+
11
|
| 879 |
+
|
| 880 |
+
69% of Republicans changed their identification. Taken together, 62% of the party-identified
|
| 881 |
+
non-voters changed their identification at wave two. This compares with 59% of the independ-
|
| 882 |
+
ents who changed.1
|
| 883 |
+
|
| 884 |
+
Of the 5201 who identified with Democrats at wave one, just 43% identified as such at wave
|
| 885 |
+
two, with 34% now seeing themselves as independents, and 23% crossing over to be Republicans.
|
| 886 |
+
This contrasts with just three percent of voting Democrats crossing over to the other party at
|
| 887 |
+
wave two. Non-voting Republicans showed even more fluidity between the two survey waves.
|
| 888 |
+
Just 31% of those who said they were Republican at wave one maintained that identification
|
| 889 |
+
at wave two, with a third of the respondents switching to Democratic identification and 36%
|
| 890 |
+
now calling themselves Independent. Non-voting independents switched to Democrat in 36% of
|
| 891 |
+
the cases, and to Republican 23%, with 41% remaining independent. This flow is illustrated in
|
| 892 |
+
Figure 4.
|
| 893 |
+
|
| 894 |
+
Seven-Point Scale (VCF0301)
|
| 895 |
+
|
| 896 |
+
Non-voting respondents to ANES changed their political identification on the Seven-Point Scale
|
| 897 |
+
between wave one and wave two in 81% of the cases. This fluidity was relatively consistent across
|
| 898 |
+
the scale, ranging from 76% of Strong Democrats changing identification by at least one scale
|
| 899 |
+
point to 87% of Independent-Republicans.
|
| 900 |
+
|
| 901 |
+
Changes in party identification for the three independent categories are shown in Figure 5.
|
| 902 |
+
A total of 5923 (83%) of those who identified as one of the three independent categories at wave
|
| 903 |
+
one had moved by at least one scale point at wave two. Of this amount, 1722 (29%) remained
|
| 904 |
+
within the independent domain while 4201 (81%) moved to one of the parties. Changes in inde-
|
| 905 |
+
pendent non-voter identification are shown in Figure 5.
|
| 906 |
+
|
| 907 |
+
Summary 3-Category Scale (VCF0303)
|
| 908 |
+
|
| 909 |
+
When non-voting ANES respondents are examined on the summary 3-category scale of
|
| 910 |
+
VCF0303, 58% are seen to change categories. Democrats (including leaners) moved to another
|
| 911 |
+
point on the scale 46% of the time, with 32% identifying as Republicans at wave 2 and 13%
|
| 912 |
+
as independents. Well over half (60%) of the non-voters identified as Republicans at wave one
|
| 913 |
+
changed identification at wave two, with 47% later identifying as Democrat and 13% as inde-
|
| 914 |
+
pendent. Independent non-voters changed identification 81% of the time, with 48% moving to
|
| 915 |
+
Democrat at wave two and 33% to Republican. These flows are illustrated in Figure 6.
|
| 916 |
+
|
| 917 |
+
Voting patterns: Straight and split-ticket voters
|
| 918 |
+
|
| 919 |
+
ANES asks respondents to state how they voted in four contests: president, Congress, Senate7,
|
| 920 |
+
and governor. Respondents may not have the opportunity to vote in each of these races, depend-
|
| 921 |
+
ing on the timing of the election cycle. There are 27,832 respondents in the ANES data that said
|
| 922 |
+
they voted in at least one election, and these respondents give us information on a total of 77,729
|
| 923 |
+
races.
|
| 924 |
+
|
| 925 |
+
Of the ANES respondents who reported voting from 1972 to 2010, Figure 7 shows that 20,521
|
| 926 |
+
(73.7%) always voted a straight ticket for either Democrats (11,638 respondents) or Republicans
|
| 927 |
+
(8883). Conversely, 9316 respondents never voted for a Democrat and 12,201 never voted Repub-
|
| 928 |
+
|
| 929 |
+
1 Z-test for proportions <.01.
|
| 930 |
+
|
| 931 |
+
12
|
| 932 |
+
|
| 933 |
+
THE FLUID VOTER
|
| 934 |
+
|
| 935 |
+
F I G U R E 5 Change in 7-Point Scale (VCF0301) non-voters, 1972–2020
|
| 936 |
+
|
| 937 |
+
lican (Figure 7) in the races surveyed. Note that the 0% and 100% columns do not exactly mirror
|
| 938 |
+
each other due to the number of votes for minor parties.
|
| 939 |
+
|
| 940 |
+
The great majority of voters surveyed by ANES exclusively vote for one of the major parties,
|
| 941 |
+
with only a small percentage splitting their votes between Republicans and Democrats. The
|
| 942 |
+
40%–59% bracket in Figure 7 shows that 4655 people (16.7%) divided their votes evenly between
|
| 943 |
+
the two parties. Considering both the small number of election contests available for analysis
|
| 944 |
+
and the polarized nature of voting noted above, further analysis divides voters into three groups:
|
| 945 |
+
those who voted for Democrats in 100% of the contests, those who voted for Republicans in
|
| 946 |
+
100% of the contests, and those who voted for some mix of Democrats and Republicans. With
|
| 947 |
+
this information, we can see what portion of the sample consistently vote for one party and what
|
| 948 |
+
portion switch their votes between parties (Figure 7).
|
| 949 |
+
|
| 950 |
+
Initial Party ID Response (VCF0302)
|
| 951 |
+
|
| 952 |
+
As expected, Democrats generally vote a straight ticket for Democrats, at a rate of 74% while 71%
|
| 953 |
+
of Republicans, 5678 of the total 7990 Republican voters, always vote Republican (Figure 8).
|
| 954 |
+
Incongruously, 5% of Democrats and 5% of Republicans report that they always vote for the
|
| 955 |
+
opposite party.
|
| 956 |
+
|
| 957 |
+
Independents are much more evenly divided in their vote choices. A significant portion still
|
| 958 |
+
vote straight tickets for one party or the other, with 34.8% always voting for Democrats and
|
| 959 |
+
30% always voting Republican. A plurality of independents (35.2%) split their votes between
|
| 960 |
+
Democrats and Republicans at least occasionally. This compares with the combined figures for
|
| 961 |
+
|
| 962 |
+
REILLY anD HUnTInG
|
| 963 |
+
|
| 964 |
+
13
|
| 965 |
+
|
| 966 |
+
F I G U R E 6 Change in Summary 3-Category Scale (VCF0303) non-voters, 1972–2020
|
| 967 |
+
|
| 968 |
+
12,000
|
| 969 |
+
|
| 970 |
+
12,101
|
| 971 |
+
|
| 972 |
+
10,000
|
| 973 |
+
|
| 974 |
+
9,316
|
| 975 |
+
|
| 976 |
+
11,638
|
| 977 |
+
|
| 978 |
+
8,883
|
| 979 |
+
|
| 980 |
+
s
|
| 981 |
+
t
|
| 982 |
+
n
|
| 983 |
+
e
|
| 984 |
+
d
|
| 985 |
+
n
|
| 986 |
+
o
|
| 987 |
+
p
|
| 988 |
+
s
|
| 989 |
+
e
|
| 990 |
+
R
|
| 991 |
+
S
|
| 992 |
+
E
|
| 993 |
+
N
|
| 994 |
+
A
|
| 995 |
+
|
| 996 |
+
8,000
|
| 997 |
+
|
| 998 |
+
6,000
|
| 999 |
+
|
| 1000 |
+
4,000
|
| 1001 |
+
|
| 1002 |
+
2,000
|
| 1003 |
+
|
| 1004 |
+
-
|
| 1005 |
+
|
| 1006 |
+
1,882
|
| 1007 |
+
|
| 1008 |
+
2,086
|
| 1009 |
+
|
| 1010 |
+
2,327
|
| 1011 |
+
|
| 1012 |
+
2,328
|
| 1013 |
+
|
| 1014 |
+
2,061
|
| 1015 |
+
|
| 1016 |
+
1,869
|
| 1017 |
+
|
| 1018 |
+
165
|
| 1019 |
+
|
| 1020 |
+
191
|
| 1021 |
+
|
| 1022 |
+
443
|
| 1023 |
+
|
| 1024 |
+
374
|
| 1025 |
+
|
| 1026 |
+
0%
|
| 1027 |
+
|
| 1028 |
+
1%-19% 20%-39% 40%-59% 60%-79% 80%-99%
|
| 1029 |
+
|
| 1030 |
+
100%
|
| 1031 |
+
|
| 1032 |
+
Dem Votes
|
| 1033 |
+
|
| 1034 |
+
Rep Votes
|
| 1035 |
+
|
| 1036 |
+
F I G U R E 7 Percent of each respondent's votes by party, 1972–2020
|
| 1037 |
+
|
| 1038 |
+
Democrats and Republicans showing that 22% of the party-identified voters voted a mixed ticket
|
| 1039 |
+
at least once.2 Respondents coded as Independent, No Preference, and Other are included in the
|
| 1040 |
+
Independent category (Figure 8).
|
| 1041 |
+
|
| 1042 |
+
Seven-Point Scale (VCF0301)
|
| 1043 |
+
|
| 1044 |
+
With the Independent-Democrats and Independent-Republicans broken out on the
|
| 1045 |
+
7-Point Scale of VCF0301, we see a steady progression from left-to-right, with decreas-
|
| 1046 |
+
ing Democratic straight-ticket voting and increasing Republican support (Figure 9). The
|
| 1047 |
+
Independent-Independents at the middle of the scale have truly mixed voting choices: 31% only
|
| 1048 |
+
voting for Democrats, 27% on voting for Republicans, and 43% choosing a mixture of Democrat
|
| 1049 |
+
and Republican candidates. The votes reported by Independent-Independents represent 8% of
|
| 1050 |
+
the 27,704 reported to ANES by respondents (Figure 9).
|
| 1051 |
+
|
| 1052 |
+
2 Z-test for proportions <.01.
|
| 1053 |
+
|
| 1054 |
+
14
|
| 1055 |
+
|
| 1056 |
+
THE FLUID VOTER
|
| 1057 |
+
|
| 1058 |
+
8,160
|
| 1059 |
+
|
| 1060 |
+
s
|
| 1061 |
+
t
|
| 1062 |
+
n
|
| 1063 |
+
e
|
| 1064 |
+
d
|
| 1065 |
+
n
|
| 1066 |
+
o
|
| 1067 |
+
p
|
| 1068 |
+
s
|
| 1069 |
+
e
|
| 1070 |
+
R
|
| 1071 |
+
S
|
| 1072 |
+
E
|
| 1073 |
+
N
|
| 1074 |
+
A
|
| 1075 |
+
|
| 1076 |
+
9,000
|
| 1077 |
+
|
| 1078 |
+
8,000
|
| 1079 |
+
|
| 1080 |
+
7,000
|
| 1081 |
+
|
| 1082 |
+
6,000
|
| 1083 |
+
|
| 1084 |
+
5,000
|
| 1085 |
+
|
| 1086 |
+
4,000
|
| 1087 |
+
|
| 1088 |
+
3,000
|
| 1089 |
+
|
| 1090 |
+
2,000
|
| 1091 |
+
|
| 1092 |
+
1,000
|
| 1093 |
+
|
| 1094 |
+
-
|
| 1095 |
+
|
| 1096 |
+
5,678
|
| 1097 |
+
|
| 1098 |
+
3,026
|
| 1099 |
+
|
| 1100 |
+
3,056
|
| 1101 |
+
|
| 1102 |
+
2,610
|
| 1103 |
+
|
| 1104 |
+
2,324
|
| 1105 |
+
|
| 1106 |
+
1,906
|
| 1107 |
+
|
| 1108 |
+
560
|
| 1109 |
+
|
| 1110 |
+
406
|
| 1111 |
+
|
| 1112 |
+
Democrat
|
| 1113 |
+
|
| 1114 |
+
Republican
|
| 1115 |
+
|
| 1116 |
+
Independent
|
| 1117 |
+
|
| 1118 |
+
Always Votes DEM
|
| 1119 |
+
|
| 1120 |
+
Mixed Votes
|
| 1121 |
+
|
| 1122 |
+
Always Votes REP
|
| 1123 |
+
|
| 1124 |
+
F I G U R E 8
|
| 1125 |
+
|
| 1126 |
+
Straight-ticket and mixed voting by Initial Party ID Response, 1972–2020
|
| 1127 |
+
|
| 1128 |
+
s
|
| 1129 |
+
t
|
| 1130 |
+
n
|
| 1131 |
+
e
|
| 1132 |
+
d
|
| 1133 |
+
n
|
| 1134 |
+
o
|
| 1135 |
+
p
|
| 1136 |
+
s
|
| 1137 |
+
e
|
| 1138 |
+
R
|
| 1139 |
+
S
|
| 1140 |
+
E
|
| 1141 |
+
N
|
| 1142 |
+
A
|
| 1143 |
+
|
| 1144 |
+
6,000
|
| 1145 |
+
|
| 1146 |
+
5,000
|
| 1147 |
+
|
| 1148 |
+
4,000
|
| 1149 |
+
|
| 1150 |
+
3,000
|
| 1151 |
+
|
| 1152 |
+
2,000
|
| 1153 |
+
|
| 1154 |
+
1,000
|
| 1155 |
+
|
| 1156 |
+
-
|
| 1157 |
+
|
| 1158 |
+
Strong Dem Weak Dem Ind-Dem
|
| 1159 |
+
|
| 1160 |
+
Ind-Ind
|
| 1161 |
+
|
| 1162 |
+
Ind-Rep Weak Rep Strong Rep
|
| 1163 |
+
|
| 1164 |
+
Always vote DEM
|
| 1165 |
+
|
| 1166 |
+
Mixed Votes
|
| 1167 |
+
|
| 1168 |
+
Always vote REP
|
| 1169 |
+
|
| 1170 |
+
F I G U R E 9
|
| 1171 |
+
|
| 1172 |
+
Straight-ticket and mixed voting by 7-point scale, 1972–2010
|
| 1173 |
+
|
| 1174 |
+
Interestingly, Independent-Democrats show a higher percentage of straight-ticket support of
|
| 1175 |
+
Democratic candidates (63%) than the Weak Democrats who explicitly declare support for the
|
| 1176 |
+
party (60%).3
|
| 1177 |
+
|
| 1178 |
+
Summary 3-Category Scale (VCF0303)
|
| 1179 |
+
|
| 1180 |
+
With the Independent-Democrats and Independent-Republicans of VCF0301 included as “lean-
|
| 1181 |
+
ers” in their respective partisan buckets for VCF0303, the Independent-Independents are high-
|
| 1182 |
+
lighted (Figure 10). Combining the straight-ticket Democrat and Republican votes shows that
|
| 1183 |
+
|
| 1184 |
+
3 Z-test for proportions p < .05.
|
| 1185 |
+
|
| 1186 |
+
REILLY anD HUnTInG
|
| 1187 |
+
|
| 1188 |
+
15
|
| 1189 |
+
|
| 1190 |
+
s
|
| 1191 |
+
t
|
| 1192 |
+
n
|
| 1193 |
+
e
|
| 1194 |
+
d
|
| 1195 |
+
n
|
| 1196 |
+
o
|
| 1197 |
+
p
|
| 1198 |
+
s
|
| 1199 |
+
e
|
| 1200 |
+
R
|
| 1201 |
+
S
|
| 1202 |
+
E
|
| 1203 |
+
N
|
| 1204 |
+
A
|
| 1205 |
+
|
| 1206 |
+
12,000
|
| 1207 |
+
|
| 1208 |
+
10,000
|
| 1209 |
+
|
| 1210 |
+
8,000
|
| 1211 |
+
|
| 1212 |
+
6,000
|
| 1213 |
+
|
| 1214 |
+
4,000
|
| 1215 |
+
|
| 1216 |
+
2,000
|
| 1217 |
+
|
| 1218 |
+
-
|
| 1219 |
+
|
| 1220 |
+
10,207
|
| 1221 |
+
|
| 1222 |
+
7,412
|
| 1223 |
+
|
| 1224 |
+
3,284
|
| 1225 |
+
|
| 1226 |
+
3,019
|
| 1227 |
+
|
| 1228 |
+
817
|
| 1229 |
+
|
| 1230 |
+
665
|
| 1231 |
+
|
| 1232 |
+
705
|
| 1233 |
+
|
| 1234 |
+
984
|
| 1235 |
+
|
| 1236 |
+
611
|
| 1237 |
+
|
| 1238 |
+
Democrat (incl. leaners)
|
| 1239 |
+
|
| 1240 |
+
Republican (incl. leaners)
|
| 1241 |
+
|
| 1242 |
+
Independent
|
| 1243 |
+
|
| 1244 |
+
Always Votes DEM
|
| 1245 |
+
|
| 1246 |
+
Mixed Votes
|
| 1247 |
+
|
| 1248 |
+
Always Votes REP
|
| 1249 |
+
|
| 1250 |
+
F I G U R E 1 0
|
| 1251 |
+
|
| 1252 |
+
Straight-ticket and mixed voting by Summary 3-Category scale, 1972–2010
|
| 1253 |
+
|
| 1254 |
+
77% of the Democrat (including leaners) category always votes a straight ticket, 73% of Repub-
|
| 1255 |
+
licans (including leaners), and 57% of independents (Figure 10).
|
| 1256 |
+
|
| 1257 |
+
Voting change over time
|
| 1258 |
+
|
| 1259 |
+
Changes in voting behavior for ANES two-wave voters are summarized in Table 4. The 1464
|
| 1260 |
+
respondents reported voting a straight Democrat ticket both the first and second time they were
|
| 1261 |
+
interviewed, with 1239 voting straight Republican both times, and 434 casting mixed votes at
|
| 1262 |
+
each wave. This total of 3137 represents 66% of the total 4770 who voted in two waves of the
|
| 1263 |
+
survey. This leaves 34% who altered their behavior across the election cycles.
|
| 1264 |
+
|
| 1265 |
+
The 4754 respondents who voted in two waves of the ANES survey and stated their political
|
| 1266 |
+
identification are summarized in Table 5.4 Respondents who identified as Republicans or Demo-
|
| 1267 |
+
crats as their Initial Party ID Response for VCF0302 are grouped together as Party Affiliated in
|
| 1268 |
+
this table, for comparison to independent voters. Respondents coded as Independent, No Prefer-
|
| 1269 |
+
ence, and Other are included in the independent category.
|
| 1270 |
+
|
| 1271 |
+
Party-affiliated voters exhibited the same voting behavior, either straight-ticket or mixed
|
| 1272 |
+
voting in each wave, in 70% of the cases. For Independents, this percentage drops to 57%.
|
| 1273 |
+
Conversely, 30% of party affiliates changed their voting patterns across two elections, while 43%
|
| 1274 |
+
of Independents changed.
|
| 1275 |
+
|
| 1276 |
+
Party-affiliated voters voted a straight ticket for the same party at a rate of 62%. Independ-
|
| 1277 |
+
ents, while still voting consistently for a single party at a significant rate (44%), were still more
|
| 1278 |
+
likely to change their voting behavior at the second wave of the survey. A small number of voters
|
| 1279 |
+
voted a straight ticket for one party at Wave 1 and then switched to the other party at Wave 2.
|
| 1280 |
+
Here we see that independents were twice as likely to make this large shift than party affiliates.
|
| 1281 |
+
There is a small difference between the two groups on percentages that went from straight ticket
|
| 1282 |
+
at Wave 1 to mixed at Wave 2. Independents were more likely to go from mixed to straight voting
|
| 1283 |
+
and much more likely to vote for a mix of the two parties in both waves.
|
| 1284 |
+
|
| 1285 |
+
4 Sixteen of the 4770 ANES respondents who reported voting in two waves of the survey are coded as DK or NA, refused in VCF0302,
|
| 1286 |
+
leaving 4754 who could have their political identification classified.
|
| 1287 |
+
|
| 1288 |
+
16
|
| 1289 |
+
|
| 1290 |
+
THE FLUID VOTER
|
| 1291 |
+
|
| 1292 |
+
T A B L E 4 Changes in voting behavior, all respondents
|
| 1293 |
+
|
| 1294 |
+
Wave 2
|
| 1295 |
+
|
| 1296 |
+
Wave 1
|
| 1297 |
+
|
| 1298 |
+
Straight REP
|
| 1299 |
+
|
| 1300 |
+
Mixed vote
|
| 1301 |
+
|
| 1302 |
+
Straight DEM
|
| 1303 |
+
|
| 1304 |
+
Total
|
| 1305 |
+
|
| 1306 |
+
Straight REP
|
| 1307 |
+
|
| 1308 |
+
Mixed Vote
|
| 1309 |
+
|
| 1310 |
+
Straight DEM
|
| 1311 |
+
|
| 1312 |
+
1239
|
| 1313 |
+
|
| 1314 |
+
399
|
| 1315 |
+
|
| 1316 |
+
55
|
| 1317 |
+
|
| 1318 |
+
1693
|
| 1319 |
+
|
| 1320 |
+
285
|
| 1321 |
+
|
| 1322 |
+
434
|
| 1323 |
+
|
| 1324 |
+
264
|
| 1325 |
+
|
| 1326 |
+
983
|
| 1327 |
+
|
| 1328 |
+
123
|
| 1329 |
+
|
| 1330 |
+
507
|
| 1331 |
+
|
| 1332 |
+
1464
|
| 1333 |
+
|
| 1334 |
+
2094
|
| 1335 |
+
|
| 1336 |
+
T A B L E 5 Voting changes over two waves of ANES data
|
| 1337 |
+
|
| 1338 |
+
Party affiliated
|
| 1339 |
+
|
| 1340 |
+
Independent
|
| 1341 |
+
|
| 1342 |
+
Initial Party ID Response (VCF0302)
|
| 1343 |
+
|
| 1344 |
+
Straight ticket Wave 1 & Wave 2: same party both waves*
|
| 1345 |
+
|
| 1346 |
+
Mixed ticket, both Wave 1 & Wave 2*
|
| 1347 |
+
|
| 1348 |
+
Subtotal: Same voting behavior in Wave 1 & 2*
|
| 1349 |
+
|
| 1350 |
+
Straight ticket Wave 1 & Wave 2: switched parties*
|
| 1351 |
+
|
| 1352 |
+
Straight ticket in Wave 1, mixed ticket in Wave 2**
|
| 1353 |
+
|
| 1354 |
+
Mixed ticket in Wave 1, straight ticket in Wave 2*
|
| 1355 |
+
|
| 1356 |
+
Subtotal: Different voting behavior in Wave 1 & 2*
|
| 1357 |
+
|
| 1358 |
+
n
|
| 1359 |
+
|
| 1360 |
+
2056
|
| 1361 |
+
|
| 1362 |
+
237
|
| 1363 |
+
|
| 1364 |
+
2293
|
| 1365 |
+
|
| 1366 |
+
96
|
| 1367 |
+
|
| 1368 |
+
355
|
| 1369 |
+
|
| 1370 |
+
547
|
| 1371 |
+
|
| 1372 |
+
998
|
| 1373 |
+
|
| 1374 |
+
%
|
| 1375 |
+
|
| 1376 |
+
62%
|
| 1377 |
+
|
| 1378 |
+
7%
|
| 1379 |
+
|
| 1380 |
+
70%
|
| 1381 |
+
|
| 1382 |
+
3%
|
| 1383 |
+
|
| 1384 |
+
11%
|
| 1385 |
+
|
| 1386 |
+
17%
|
| 1387 |
+
|
| 1388 |
+
30%
|
| 1389 |
+
|
| 1390 |
+
n
|
| 1391 |
+
|
| 1392 |
+
640
|
| 1393 |
+
|
| 1394 |
+
196
|
| 1395 |
+
|
| 1396 |
+
836
|
| 1397 |
+
|
| 1398 |
+
81
|
| 1399 |
+
|
| 1400 |
+
191
|
| 1401 |
+
|
| 1402 |
+
355
|
| 1403 |
+
|
| 1404 |
+
627
|
| 1405 |
+
|
| 1406 |
+
Total
|
| 1407 |
+
|
| 1408 |
+
1647
|
| 1409 |
+
|
| 1410 |
+
1340
|
| 1411 |
+
|
| 1412 |
+
1783
|
| 1413 |
+
|
| 1414 |
+
4770
|
| 1415 |
+
|
| 1416 |
+
%
|
| 1417 |
+
|
| 1418 |
+
44%
|
| 1419 |
+
|
| 1420 |
+
13%
|
| 1421 |
+
|
| 1422 |
+
57%
|
| 1423 |
+
|
| 1424 |
+
6%
|
| 1425 |
+
|
| 1426 |
+
13%
|
| 1427 |
+
|
| 1428 |
+
24%
|
| 1429 |
+
|
| 1430 |
+
43%
|
| 1431 |
+
|
| 1432 |
+
Total
|
| 1433 |
+
|
| 1434 |
+
*Z-test for proportions p < .01.
|
| 1435 |
+
**Z-test for proportions p < .05.
|
| 1436 |
+
|
| 1437 |
+
Initial Party ID Response (VCF0302)
|
| 1438 |
+
|
| 1439 |
+
3291
|
| 1440 |
+
|
| 1441 |
+
100%
|
| 1442 |
+
|
| 1443 |
+
1463
|
| 1444 |
+
|
| 1445 |
+
100%
|
| 1446 |
+
|
| 1447 |
+
When the party-affiliated category shown in Table 5 is broken out to show the two parties, we see
|
| 1448 |
+
the results are largely the same. Democrats continued their pattern from Wave 1, either voting
|
| 1449 |
+
a straight ticket for a particular party or voting a mixed ticket, in 71% of the cases. This left
|
| 1450 |
+
29% of self-identified Democrats changing their voting behavior in some fashion, with 32% of
|
| 1451 |
+
Republicans exhibiting changed behavior. The p-value for a comparison of these percentages is
|
| 1452 |
+
.176, suggesting that there is little meaningful difference between Democrats and Republicans on
|
| 1453 |
+
this measure.
|
| 1454 |
+
|
| 1455 |
+
As noted above, 43% of independents showed changed behavior between Wave 1 and Wave 2,
|
| 1456 |
+
|
| 1457 |
+
with a p-value of <.01 compared to party-affiliated respondents (Table 6).
|
| 1458 |
+
|
| 1459 |
+
Seven-Point Scale (VCF0301)
|
| 1460 |
+
|
| 1461 |
+
When this same measure of voting change over time is applied to the Seven-Point Scale of
|
| 1462 |
+
VCF0301, we see that, unsurprisingly, the Strong Democrats and Strong Republicans are most
|
| 1463 |
+
consistent in their behavior, with less than a quarter of these groups changing their voting profile
|
| 1464 |
+
from one wave to the next (Table 7). Independent-Independents were the most likely to change their
|
| 1465 |
+
voting profile at 48%, followed by Independent-Republicans at 45%. Independent-Democrats
|
| 1466 |
+
again seem to be as committed to Democratic candidates as the Weak Democrats with the party
|
| 1467 |
+
in the question posed in VCF0301. Weak Democrats voted for a straight Democratic ticked at a
|
| 1468 |
+
|
| 1469 |
+
REILLY anD HUnTInG
|
| 1470 |
+
|
| 1471 |
+
T A B L E 6 Changes in voting behavior by Initial Party ID Response
|
| 1472 |
+
|
| 1473 |
+
VCF0302
|
| 1474 |
+
|
| 1475 |
+
Democrat
|
| 1476 |
+
|
| 1477 |
+
Republican
|
| 1478 |
+
|
| 1479 |
+
Subtotal: Party-identified
|
| 1480 |
+
|
| 1481 |
+
Independent, Other, No Pref.
|
| 1482 |
+
|
| 1483 |
+
Total
|
| 1484 |
+
|
| 1485 |
+
Voted in two waves
|
| 1486 |
+
|
| 1487 |
+
Percent that changed voting behavior
|
| 1488 |
+
|
| 1489 |
+
1803
|
| 1490 |
+
|
| 1491 |
+
1488
|
| 1492 |
+
|
| 1493 |
+
3291
|
| 1494 |
+
|
| 1495 |
+
1463
|
| 1496 |
+
|
| 1497 |
+
4754
|
| 1498 |
+
|
| 1499 |
+
29%
|
| 1500 |
+
|
| 1501 |
+
32%
|
| 1502 |
+
|
| 1503 |
+
30%
|
| 1504 |
+
|
| 1505 |
+
43%
|
| 1506 |
+
|
| 1507 |
+
34%
|
| 1508 |
+
|
| 1509 |
+
17
|
| 1510 |
+
|
| 1511 |
+
Percent that
|
| 1512 |
+
did not change
|
| 1513 |
+
|
| 1514 |
+
71%
|
| 1515 |
+
|
| 1516 |
+
68%
|
| 1517 |
+
|
| 1518 |
+
70%
|
| 1519 |
+
|
| 1520 |
+
57%
|
| 1521 |
+
|
| 1522 |
+
66%
|
| 1523 |
+
|
| 1524 |
+
T A B L E 7 Changes in voting behavior by 7-Point Scale
|
| 1525 |
+
|
| 1526 |
+
VCF0301
|
| 1527 |
+
|
| 1528 |
+
Voted in two waves
|
| 1529 |
+
|
| 1530 |
+
Percent that changed voting behavior
|
| 1531 |
+
|
| 1532 |
+
Percent that did not change
|
| 1533 |
+
|
| 1534 |
+
Strong Democrat
|
| 1535 |
+
|
| 1536 |
+
1045
|
| 1537 |
+
|
| 1538 |
+
Weak Democrat
|
| 1539 |
+
|
| 1540 |
+
Independent-Democrat
|
| 1541 |
+
|
| 1542 |
+
Independent-Independent
|
| 1543 |
+
|
| 1544 |
+
Independent-Republican
|
| 1545 |
+
|
| 1546 |
+
Weak Republican
|
| 1547 |
+
|
| 1548 |
+
Strong Republican
|
| 1549 |
+
|
| 1550 |
+
Total
|
| 1551 |
+
|
| 1552 |
+
757
|
| 1553 |
+
|
| 1554 |
+
547
|
| 1555 |
+
|
| 1556 |
+
332
|
| 1557 |
+
|
| 1558 |
+
588
|
| 1559 |
+
|
| 1560 |
+
637
|
| 1561 |
+
|
| 1562 |
+
850
|
| 1563 |
+
|
| 1564 |
+
4756
|
| 1565 |
+
|
| 1566 |
+
22%
|
| 1567 |
+
|
| 1568 |
+
40%
|
| 1569 |
+
|
| 1570 |
+
38%
|
| 1571 |
+
|
| 1572 |
+
48%
|
| 1573 |
+
|
| 1574 |
+
45%
|
| 1575 |
+
|
| 1576 |
+
42%
|
| 1577 |
+
|
| 1578 |
+
24%
|
| 1579 |
+
|
| 1580 |
+
34%
|
| 1581 |
+
|
| 1582 |
+
78%
|
| 1583 |
+
|
| 1584 |
+
60%
|
| 1585 |
+
|
| 1586 |
+
62%
|
| 1587 |
+
|
| 1588 |
+
52%
|
| 1589 |
+
|
| 1590 |
+
55%
|
| 1591 |
+
|
| 1592 |
+
58%
|
| 1593 |
+
|
| 1594 |
+
76%
|
| 1595 |
+
|
| 1596 |
+
66%
|
| 1597 |
+
|
| 1598 |
+
rate of 45%, while Independent-Democrats did so at a rate of 47% with a p-value of .472 between
|
| 1599 |
+
the two rates, indicating little actual difference between the two groups.
|
| 1600 |
+
|
| 1601 |
+
Summary 3-Category Scale (VCF0303)
|
| 1602 |
+
|
| 1603 |
+
The Summary 3-Category Scale once again shrinks the size of the independent category but
|
| 1604 |
+
maximizes its difference from the enlarged party-identified categories. Democrats (including
|
| 1605 |
+
leaners) were slightly less likely to change their behavior (31%) than Republicans (including lean-
|
| 1606 |
+
ers) at 35%.5 True independents, as above, changed their voting profile 48% of the time between
|
| 1607 |
+
the first and second survey waves (Table 8).
|
| 1608 |
+
|
| 1609 |
+
DISCUSSION
|
| 1610 |
+
|
| 1611 |
+
Analyzing each of the three ANES measures of party affiliation (Initial Party ID, Seven-Point
|
| 1612 |
+
Scale, and Summary 3 Category) over multiple elections provides some important findings on
|
| 1613 |
+
the voting patterns of independents. We find evidence that, when tracking independent voting
|
| 1614 |
+
behavior over more than one election, there is a significant volatility in voting loyalty and as
|
| 1615 |
+
a group, independents are distinct from partisans. The research also confirms that a sizeable
|
| 1616 |
+
number of independents move in and out of independent status from one election to another.
|
| 1617 |
+
|
| 1618 |
+
In the first analysis on how political identification of voters changes over multiple survey
|
| 1619 |
+
waves, we explored how these respondents changed their party identification from one survey
|
| 1620 |
+
cycle to the next. The Initial Party ID scale found that independents were more fluid on this metric
|
| 1621 |
+
than party-affiliated respondents with the percent of independents changing at the second wave
|
| 1622 |
+
|
| 1623 |
+
5 Z-test for proportions <.01.
|
| 1624 |
+
|
| 1625 |
+
18
|
| 1626 |
+
|
| 1627 |
+
THE FLUID VOTER
|
| 1628 |
+
|
| 1629 |
+
T A B L E 8 Changes in voting behavior by Summary 3-Category Scale
|
| 1630 |
+
|
| 1631 |
+
VCF0303
|
| 1632 |
+
|
| 1633 |
+
Voted in two waves
|
| 1634 |
+
|
| 1635 |
+
Percent that changed voting behavior
|
| 1636 |
+
|
| 1637 |
+
Democrat (including leaners)
|
| 1638 |
+
|
| 1639 |
+
Republican (including leaners)
|
| 1640 |
+
|
| 1641 |
+
Subtotal: Party-Identified
|
| 1642 |
+
|
| 1643 |
+
Independent
|
| 1644 |
+
|
| 1645 |
+
Total
|
| 1646 |
+
|
| 1647 |
+
2349
|
| 1648 |
+
|
| 1649 |
+
2075
|
| 1650 |
+
|
| 1651 |
+
4424
|
| 1652 |
+
|
| 1653 |
+
332
|
| 1654 |
+
|
| 1655 |
+
4756
|
| 1656 |
+
|
| 1657 |
+
31%
|
| 1658 |
+
|
| 1659 |
+
35%
|
| 1660 |
+
|
| 1661 |
+
33%
|
| 1662 |
+
|
| 1663 |
+
48%
|
| 1664 |
+
|
| 1665 |
+
34%
|
| 1666 |
+
|
| 1667 |
+
Percent that
|
| 1668 |
+
did not change
|
| 1669 |
+
|
| 1670 |
+
69%
|
| 1671 |
+
|
| 1672 |
+
65%
|
| 1673 |
+
|
| 1674 |
+
67%
|
| 1675 |
+
|
| 1676 |
+
52%
|
| 1677 |
+
|
| 1678 |
+
66%
|
| 1679 |
+
|
| 1680 |
+
by more than double that of partisans. Additionally, the percentage of independents becoming
|
| 1681 |
+
party affiliated was nearly three times that of party affiliates becoming independent. Moving to
|
| 1682 |
+
the analysis of the Seven-Point Scale, even more fluidity was found with an overall 57% of those
|
| 1683 |
+
in one of the three independent categories of the Seven-Point Scale changing their identification
|
| 1684 |
+
at wave two. The last analysis collapsed categories of the Summary 3-Category Scale in party
|
| 1685 |
+
identification seen in the previous two scales and resulted in a significantly reduced (7%) number
|
| 1686 |
+
of independent respondents. Despite this small percentage of independent respondents, almost
|
| 1687 |
+
two-thirds or 64% of the independents changed classification to partisans at Wave 2.
|
| 1688 |
+
|
| 1689 |
+
ANES participants who responded to two consecutive waves of the survey but voted in
|
| 1690 |
+
neither of the corresponding elections showed much greater fluidity in their political identifica-
|
| 1691 |
+
tion between waves. Overall, 60% of respondents changed their Initial Party Identification. In
|
| 1692 |
+
contrast with the voting respondents, non-voting Independents were substantially the same as
|
| 1693 |
+
party affiliates, 59% making a switch to party affiliation. Non-voting independents were more
|
| 1694 |
+
likely to move by at least one point on the Seven-Point Scale (64%) than either Democrats (50%)
|
| 1695 |
+
or Republicans (49%). Thirty-nine percent of non-voters who identified as Independent in the
|
| 1696 |
+
first survey wave chose party affiliation at wave two. When the Summary 3-Category Scale is
|
| 1697 |
+
analyzed, we see that 81% of the non-voting independents identified with one of the major
|
| 1698 |
+
parties at wave two, compared with 58% of all respondents.
|
| 1699 |
+
|
| 1700 |
+
Our analysis on how independent voters and non-voters changed their party identification
|
| 1701 |
+
from one cycle to the next showed a significant amount of fluidity with non-voters being espe-
|
| 1702 |
+
cially unpredictable. On all three political identification scales, independent respondents changed
|
| 1703 |
+
their political identification over time more often than partisans (ranging from 36% to 64% for
|
| 1704 |
+
voters and 59% to 83% for non-voters) with the exception of non-voting Republicans on the
|
| 1705 |
+
Initial Party ID Scale. These findings suggest that independent voters and non-voters who iden-
|
| 1706 |
+
tify in one political classification in one election are less likely to identify themselves in the same
|
| 1707 |
+
manner in the next election. Their identification may depend on specific candidates or issues on
|
| 1708 |
+
the ballot (Reilly et al., 2023) or may derive from short-term interest rather than a long-standing
|
| 1709 |
+
loyalty (Miller, 1991). This finding supports Fiorina's (2016) assertion about independent voting
|
| 1710 |
+
behavior: “whatever they are, they are an important component of the electoral instability that
|
| 1711 |
+
characterizes the contemporary era. Their critical contribution to contemporary elections lies in
|
| 1712 |
+
their volatility” (p. 10).
|
| 1713 |
+
|
| 1714 |
+
We next investigated how frequently respondents to the ANES scales vote “straight tickets,”
|
| 1715 |
+
always choosing candidates from the same party or “mixed tickets” where some Republican
|
| 1716 |
+
and some Democrat candidates are chosen. Our expectation that those identifying as Demo-
|
| 1717 |
+
crat or Republican would mostly choose candidates from their own party was confirmed, while
|
| 1718 |
+
independents demonstrated more variety in their choices. For the Initial Party ID scale, over
|
| 1719 |
+
70% of partisans voted straight ticket, while 65% of independent respondents did, with the
|
| 1720 |
+
independent straight-ticket voters divided; 35% voting for Democrats and 30% for Republi-
|
| 1721 |
+
cans. While the Seven-Point Scale showed similar results, Independent-Democrats showed a
|
| 1722 |
+
|
| 1723 |
+
REILLY anD HUnTInG
|
| 1724 |
+
|
| 1725 |
+
19
|
| 1726 |
+
|
| 1727 |
+
higher percentage of straight-ticket support of Democratic candidates than the Weak Demo-
|
| 1728 |
+
crats, while Independent Republicans were slightly less likely to vote a straight ticket than Weak
|
| 1729 |
+
Republicans.
|
| 1730 |
+
|
| 1731 |
+
Finally, we explored the degree to which individuals change their voting choices over time
|
| 1732 |
+
(two-wave voters). Partisan voters exhibited the same voting behavior, either straight-ticket
|
| 1733 |
+
or mixed voting in each wave, in 70% of the cases. For independents, this percentage drops
|
| 1734 |
+
to 57%. The Initial Party ID analysis found that approximately 30% of partisans changed
|
| 1735 |
+
between waves compared to 43% of independents; while the Seven-Point Scale showed
|
| 1736 |
+
Independent-Independents were the most likely to change their voting profile at 48%, followed
|
| 1737 |
+
by Independent-Republicans at 45%. Weak Democrats voted for a straight Democratic ticket at
|
| 1738 |
+
a rate of 45%, while Independent-Democrats did so at a rate of 47%. Independents were more
|
| 1739 |
+
likely to go from mixed to straight voting and much more likely to vote for a mix of the two
|
| 1740 |
+
parties in both waves. For the Summary 3-Category, approximately a third of partisans changed
|
| 1741 |
+
their voting patterns over the two waves compared to 48% of independents.
|
| 1742 |
+
|
| 1743 |
+
Our research on independent voting behavior included analyses of voting patterns over time.
|
| 1744 |
+
The findings confirm that independents do indeed move in and out of independent status when
|
| 1745 |
+
tracked over multiple elections. Further, this study lends support to the notion that there is a
|
| 1746 |
+
good deal more fluidity in voting patterns of independents. This was the case when analyzing
|
| 1747 |
+
data across all three ANES scales. Our analysis of the ANES Seven-Point Scale showed that
|
| 1748 |
+
Independent-Republicans and Weak-Republicans resembled each other's voting patterns on
|
| 1749 |
+
straight/split ticket and voting change over time analyses (Mayer, 2008; Petrocik, 2009; Smith
|
| 1750 |
+
et al., 1995); however, this was not the case with Independent-Democrats and Weak-Democrats.
|
| 1751 |
+
Independent-Democrats, who did not affiliate with any party in the Initial Party Response ID
|
| 1752 |
+
question, were more likely to vote only for Democrats than Weak-Democrats that specifically
|
| 1753 |
+
identified as Democrat. Similarly, Independent-Republicans were as likely to vote a straight
|
| 1754 |
+
Republican ticket in both waves than Weak Republicans. Respondents who were coded as either
|
| 1755 |
+
5 (Independent-Republican) or 6 (Weak Republican) showed essentially the same voting behav-
|
| 1756 |
+
ior, while those coded as 3 (Independent-Democrat) were more Democratic in their behavior
|
| 1757 |
+
than the supposedly more liberal Weak Democrats at scale point 2. This indicates that caution
|
| 1758 |
+
needs to be exercised when treating the Seven-Point Scale (VCF0301) as a continuous variable.
|
| 1759 |
+
|
| 1760 |
+
It may be that traditional ways of measuring voter identification do not capture the independ-
|
| 1761 |
+
ent voter due to voter composition of the electorate and our hyperpolarized political environ-
|
| 1762 |
+
ment. Due to the research of Keith and others (1992), it became most common for researchers
|
| 1763 |
+
with the ANES to utilize a three-point or five-point scale that classified independent-leaning
|
| 1764 |
+
Democrats, or independent-leaning Republicans, as partisans (VCF0302, Initial Party ID
|
| 1765 |
+
response). This resulted in a significant reduction in the number of self-described independ-
|
| 1766 |
+
ents. Reilly and Hedberg (2022) have argued that in light of the more recent work of Klar and
|
| 1767 |
+
Krupnikov (2016) and Zschirnt (2011), which showed the importance of the independent iden-
|
| 1768 |
+
tity, classifying self-identified independents as partisans seems counterproductive in examining
|
| 1769 |
+
their influence on partisans, especially when respondents elected to self-identify as leaners. The
|
| 1770 |
+
authors collapsed three groups—respondents who selected option 3, 4, or 5—as independ-
|
| 1771 |
+
ent, thus treating leaners as Independents (VCF0303, Summary 3-category scale). Similarly,
|
| 1772 |
+
Fiorina (2016) has long been an opponent of classifying leaning independents as partisans and
|
| 1773 |
+
leaving pure independents in the middle ID category arguing that “We can think of no other case
|
| 1774 |
+
in political science where analysts change a respondent's explicit response to a survey item on
|
| 1775 |
+
the basis of information from other items—especially one generally used as the dependent varia-
|
| 1776 |
+
ble” (Abrams & Fiorina, 2011, p. 5). Perhaps it is time to develop new explanatory constructs to
|
| 1777 |
+
capture independent voter classification.
|
| 1778 |
+
|
| 1779 |
+
20
|
| 1780 |
+
|
| 1781 |
+
CONCLUSION
|
| 1782 |
+
|
| 1783 |
+
THE FLUID VOTER
|
| 1784 |
+
|
| 1785 |
+
Our study contributes to previous literature on the independent voter by showing their voting
|
| 1786 |
+
patterns are volatile, unpredictable, and distinct from partisans. Additionally, when analyz-
|
| 1787 |
+
ing voting behavior over time, our research confirmed that a sizeable number of independ-
|
| 1788 |
+
ents move in and out of independent status from one election to another. This volatility was
|
| 1789 |
+
observed in all three measures of party affiliation used by the ANES survey data. When inde-
|
| 1790 |
+
pendents are followed over multiple elections, they have been found to have no firm partisan
|
| 1791 |
+
loyalties.
|
| 1792 |
+
|
| 1793 |
+
Despite our contributions, our study has several limitations. First, as with any survey, the
|
| 1794 |
+
voting classification and behavior details are all based on self-reports, which are suspectable to
|
| 1795 |
+
response bias. Second, although ANES is a rich dataset with a long history to draw from, it does
|
| 1796 |
+
have limitations for this sort of analysis. There is limited information about voter choices in the
|
| 1797 |
+
data. The survey asks for party choices on just four races: president, Congress, Senate, and gover-
|
| 1798 |
+
nor. With the survey waves spaced two years apart (except for the 2016–2020 waves), respondents
|
| 1799 |
+
will not be able to provide answers to presidential, senatorial, and most governor's races in both
|
| 1800 |
+
waves, which limits the data available for analysis. These four races, especially at the presidential
|
| 1801 |
+
level, are susceptible to a “celebrity effect” where a high-profile candidate's perceived charm
|
| 1802 |
+
(or repulsiveness) may overwhelm a voter's policy-based preferences when selecting a candidate.
|
| 1803 |
+
Data that included more frequent and down-ballot races would provide a better picture of the
|
| 1804 |
+
relationship between the stated political identification of voters and their voting choices (Bitzer
|
| 1805 |
+
et al., 2021). Finally, it is also difficult to draw solid conclusions about the behavior of non-voters
|
| 1806 |
+
from these data. These non-voters may be latent voters who generally lie dormant but turn out
|
| 1807 |
+
at the polls when there is an issue or candidate that particularly motivates them. Without a very
|
| 1808 |
+
long time-series survey, it is difficult to say with what frequency these latent voters are activated
|
| 1809 |
+
or what motivates changes in their political identification.
|
| 1810 |
+
|
| 1811 |
+
There is a lot that still needs to be learned about this emerging group of voters. Future
|
| 1812 |
+
research should explore the fluidity of Black and Latino voters as well as the increasing genera-
|
| 1813 |
+
tional divide. Most importantly, there is a need to continue to track independent voting behavior
|
| 1814 |
+
over time and more analysis on the voting patterns of independents is needed down ballot at the
|
| 1815 |
+
state and local level.
|
| 1816 |
+
|
| 1817 |
+
ORCID
|
| 1818 |
+
Thom Reilly
|
| 1819 |
+
|
| 1820 |
+
https://orcid.org/0000-0001-8614-0482
|
| 1821 |
+
|
| 1822 |
+
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Challenge of Democracy: Explorations in the Analysis of Public Opinion and Political Particiaption, edited by Paul
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M. Sniderman and Benjamin Highton, pp. 238–63. Princeton, NJ: Princeton University Press.
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Mayer, William G. 2008. The Swing Voter in American Politics. Washington, DC: Brookings Institution Press.
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Miller, Warren E. 1991. “Party Identification, Realignment and Party Voting: Back to Basics.” American Political Science
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Petrocik, John R. 2009. “Measuring Party Support: Leaners Are Not Independents.” Electoral Studies 28(4): 562–72.
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PEW Research Center. 2022. Americans’ Views of Government: Decades of Distrust, Enduring Support for Its Role U.S.
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Politics & Policy. https://www.pewresearch.org/politics/2022/06/06/americans-views-of-government-decades-of-dist
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rust-enduring-support-for-its-role/.
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Reilly, Thom, and E. C. Hedberg. 2022. “Social Networks of Independents and Partisans: Are Independents a Moderat-
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ing Force?” Politics & Policy 50(2): 225–43. https://doi.org/10.1111/polp.12460.
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+
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Reilly, Thom, Jacqueline S. Salit, and Omar H. Ali. 2023. The Independent Voter. London: Routledge.
|
| 1935 |
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Sides, John. 2013. “Three Myths about Political Independents.” The Monkey Cage. https://themonkeycage.org/2009/12/
|
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three_myths_about_political_in/.
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Smith, Andrew E., Alfred J. Tuchfarber, Eric W. Rademacher, and Stephen E. Bennett. 1995. “Partisan Leaners Are NOT
|
| 1940 |
+
|
| 1941 |
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Independents.” The Public Perspective. https://ropercenter.cornell.edu/sites/default/files/2018-07/66009.pdf.
|
| 1942 |
+
|
| 1943 |
+
Teixiera, Ruy. 2012. “The Great Illusion.” The New Republic. https://newrepublic.com/article/100799/swing-vote-untapp
|
| 1944 |
+
|
| 1945 |
+
ed-power-independents-linda-killian.
|
| 1946 |
+
|
| 1947 |
+
Zschirnt, Simon. 2011. “The Origins & Meaning of Liberal/Conservative Self-Identifications Revisited.” Political Behav-
|
| 1948 |
+
|
| 1949 |
+
ior 33(4): 685–701. https://doi.org/10.1007/s11109-010-9145-6.
|
| 1950 |
+
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| 1951 |
+
22
|
| 1952 |
+
|
| 1953 |
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THE FLUID VOTER
|
| 1954 |
+
|
| 1955 |
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AUT HOR BI OG RAP HIES
|
| 1956 |
+
|
| 1957 |
+
Thom Reilly is a Professor and Co-Director for the Center for an Independent and Sustaina-
|
| 1958 |
+
ble Democracy in the School of Public Affairs at Arizona State University. He is the former
|
| 1959 |
+
Chancellor of the Nevada System of Higher Education and County Manager for Clark
|
| 1960 |
+
County, Nevada. Reilly's research focuses on public pay and benefit schemes, nonpartisan
|
| 1961 |
+
governance, the independent voter, and child welfare. He is the author of several books
|
| 1962 |
+
including The Independent Voter (Routledge Press, 2023) with co-authors Jacqueline Salit and
|
| 1963 |
+
Omar Ali, The Failure of Governance in Bell, California (Lexington Press, 2016), and Rethink-
|
| 1964 |
+
ing Public Sector Compensation (M.E. Sharpe, 2012).
|
| 1965 |
+
|
| 1966 |
+
Dan Hunting is Senior Researcher at Arizona State University's Lodestar Center for Philan-
|
| 1967 |
+
thropy & Nonprofit Innovation. His research interests include economic impacts of the
|
| 1968 |
+
nonprofit sector, voter dynamics, workforce development, education funding, and urban
|
| 1969 |
+
growth. Hunting has authored several foundational works that have informed Arizona policy
|
| 1970 |
+
discussions including Finding & Keeping: Educators for Arizona's Classrooms an analysis
|
| 1971 |
+
of the state's teacher shortage, and Sun Corridor: A Competitive Mindset (co-authored with
|
| 1972 |
+
Grady Gammage, Jr.) which described the complex connections between the economies of
|
| 1973 |
+
Phoenix and Tucson.
|
| 1974 |
+
|
| 1975 |
+
How to cite this article: Reilly, Thom, and Dan Hunting. 2023. “The fluid voter:
|
| 1976 |
+
Exploring independent voting patterns over time.” Politics & Policy 00: 1–22. https://doi.
|
| 1977 |
+
org/10.1111/polp.12517.
|
| 1978 |
+
|
q130/random_k2/question.json
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],
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"original_filenames": [
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],
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"modality": "markdown"
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],
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"original_filenames": [
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"Campaign_038_Introducing_AC_Whitepaper_v5e.pdf",
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"web_419331e34a19dd26.pdf",
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+
"web_040fe479bf878a27.pdf"
|
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],
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"modality": "markdown"
|
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}
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q130/random_k2/random_1.md
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September 2014
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Investing in People &
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Technology
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to Enhance In-Store
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Experiences ............................... 4
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Cross-Channel Consistency ....... 6
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into Actionable Messaging ........ 9
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Store Technologies .................. 10
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How to Engage and Convert Consumers with Great
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In-Store Retail Experiences
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years. In particular, the ascendance of multichannel e-commerce platforms has
|
| 47 |
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challenged brands to reimagine how they interact with consumers. As a result, today’s
|
| 48 |
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connected consumers have access to a whole host of digital shopping tools, including
|
| 49 |
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interactive websites with high-definition images and mobile-optimized web and email.
|
| 50 |
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E-commerce offers variety, convenience, and information, empowering consumers to
|
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engage with retailers when, where, and how they please.
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The Department of Commerce estimates that e-commerce accounted for approximately
|
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6.5% of all retail sales in the U.S. during the second quarter of 2014. Although this
|
| 56 |
-
reaffirms that physical stores remain retailers’ most prominent sources of revenue, it
|
| 57 |
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also suggests that there are great opportunities for synergy between a brand’s physical
|
| 58 |
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locations and its e-commerce platform.
|
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sales have turned out to be great assets to retailers. Mobile devices enable businesses
|
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to send extremely relevant and timely messages to consumers by using location-based
|
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services and Bluetooth Low Energy (BLE) beacons. Loyalty programs deployed across
|
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channels encourage repeat business both in-store and online. QR codes and interactive
|
| 65 |
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displays offer customers new ways to engage with and learn about products and
|
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services. Omnichannel initiatives (e.g., an option for the consumer to buy online and
|
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pick up in-store) promote interchannel traffic. Because of these innovations, today’s
|
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consumers begin shopping before they walk into the store and continue shopping after
|
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they leave, making their in-store experiences the unifying element.
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it has been influenced in large part by technological innovation and new consumer
|
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insights. The most successful retail stores not only leverage new technologies to drive
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in-store conversions, but they also enhance the shopping experience, collect actionable
|
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customer data, and serve as a physical extension of the brand. This is the store of the
|
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future: a connected showroom that fuses together multichannel experiences to convert
|
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and engage customers while also learning from them.
|
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retailers are creating in their stores. The analysis is based on survey data collected from
|
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retail executives and professionals in a variety of industries. This data was collected on-site
|
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at the 2014 Future Stores Conference and through an online survey. The findings are
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based on the insights and practices of some of the world’s leading retailers and brands.
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the future will create seamless shopping
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experiences and integrate with other
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technologies and services.
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In-store retail technology is constantly evolving.
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Although many new technologies will arise over the next 2-5 years,
|
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not all of those tools will help businesses improve their conversions and
|
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experiences. Retailers will need to critically sort through the multitude
|
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of solutions and only implement those that enhance conversions while
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providing customers with effortless, engaging experiences.
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Customer Experience Strategist
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and Designer, Storyminers
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driving consumer loyalty and engagement through innovative interactions and inventive
|
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campaigns. Stores are also a burgeoning source of data that can be turned into rich insights
|
| 148 |
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into shoppers’ tendencies and preferences. Add in customers’ lofty expectations for shopping
|
| 149 |
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experiences and the value of the modern store becomes undeniable. With few exceptions,
|
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stores continue to be the backbone of retail businesses, even in today’s world of e-commerce
|
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and digital interconnectedness.
|
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|
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they are constantly updating designs, technology, and personnel to get the most out of
|
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each location. Creating a store of the future means seamlessly integrating cutting-edge
|
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technology with tried and true designs and tactics, providing a strong balance of analog
|
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and digital elements that help deliver to customers higher value outcomes that are easier
|
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to achieve. When it comes to technology, electronic point of sale (EPOS) tools have
|
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become extremely common, with over three quarters of survey respondents indicating
|
| 160 |
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that they are already utilizing the capability. A robust 72% are leveraging mobile devices
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and tablets in stores, and 60% are making use of digital displays or kiosks.
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Associates to Be Their Greatest In-Store Assets
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most to improve in-store conversions?
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Technology and Sales Associate Training to Drive
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In-Store Conversions
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| 223 |
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Enhance In-Store Experiences
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“The tools are all there
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| 249 |
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to integrate these
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| 250 |
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experiences, they just
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| 251 |
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aren’t always being
|
| 252 |
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implemented. There is
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| 253 |
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a resistance to change,
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| 254 |
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because making changes
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| 255 |
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costs a lot of time and
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| 256 |
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money.”
|
| 257 |
-
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| 258 |
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- Jack Shaw, VP North American
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| 259 |
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Sales, Adaequare Inc.
|
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The Challenge of Cross-Channel Consistency
|
| 262 |
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|
| 263 |
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Advances in technology – particularly mobile technology – over the past decade have
|
| 264 |
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resulted in a rapid expansion in the variety of commercial tools available to consumers.
|
| 265 |
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Today, consumers are increasingly engaging with brands across a variety of diverse media.
|
| 266 |
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The customer journey has become expansive, dynamic, and multilayered; it permeates
|
| 267 |
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desktop websites, mobile-optimized sites and apps, social networks, and retail stores
|
| 268 |
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themselves. For retailers, this has meant a multiplication of consumer touch points and
|
| 269 |
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an unprecedented demand for innovative digital shopping tools. However, the challenge
|
| 270 |
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for retailers is not just to develop spectacular omnichannel shopping capabilities but also
|
| 271 |
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to deliver outstanding experiences across all channels. When it comes to omnichannel
|
| 272 |
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customer experiences, consistency is key.
|
| 273 |
-
|
| 274 |
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Delivering consistently great customer experiences in-store and online can be a profound
|
| 275 |
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challenge for retail businesses. In this study, only 16% of respondents said that their
|
| 276 |
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customer experiences are very consistent between their stores and online presence.
|
| 277 |
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The majority (60%) of those surveyed noted that their experiences are only somewhat
|
| 278 |
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consistent. In their quest to provide a great customer experience, these retailers are facing
|
| 279 |
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many complex challenges, including creating consistency across channels, personalizing
|
| 280 |
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the experience, capturing and applying relevant customer data, and the implementation
|
| 281 |
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of customer experience initiatives across store locations.
|
| 282 |
-
|
| 283 |
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Although the retailer perspective is an important indicator of the state of shopping
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| 284 |
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experiences, an even more critical measure is how consumers perceive those experiences.
|
| 285 |
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Unfortunately, the way retailers view their shopping experience can differ greatly from
|
| 286 |
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consumers’ perspectives. For instance, in a Bain & Co. customer experience survey,
|
| 287 |
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80% of companies stated that they were delivering a “superior experience” to their
|
| 288 |
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customers. However, consumers in the survey said that only 8% of companies were
|
| 289 |
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actually delivering high-quality experiences. This discrepancy underlines how critical it is
|
| 290 |
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for retailers to listen to their customers, especially when it comes to experiences.
|
| 291 |
-
|
| 292 |
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Without a doubt, modern retail businesses must have an omnichannel vision in order
|
| 293 |
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to adapt to the changes in consumer shopping patterns brought on by technological
|
| 294 |
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advances. In part, a successful omnichannel strategy demands that retailers understand
|
| 295 |
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the key actions that consumers take during their shopping experiences, and retailers
|
| 296 |
-
must then make those actions available across multiple channels. Enabling consumers to
|
| 297 |
-
engage with multiple platforms en route to a purchase not only improves the shopping
|
| 298 |
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experience but also increases conversion rates and reduces cart abandonment.
|
| 299 |
-
|
| 300 |
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Two notable omnichannel shopping practices include showrooming and “buy online, pick
|
| 301 |
-
up in store” options. Showrooming, the practice of evaluating products in a store before
|
| 302 |
-
buying them online, poses a clear threat to traditional retailers, which are susceptible to
|
| 303 |
-
customers using mobile devices to compare prices while in the store. Despite the threat,
|
| 304 |
-
nearly three quarters of respondents reported that they have not seen any sort of impact
|
| 305 |
-
from showrooming. In fact, 19% noted that showrooming has had a positive impact on
|
| 306 |
-
their businesses. This is likely because omnichannel shoppers have been shown to spend
|
| 307 |
-
significantly more than single-channel shoppers. Similarly, “buy online, pick up in store”
|
| 308 |
-
options, which offer the convenience of an online transaction alongside the satisfaction
|
| 309 |
-
of instantly picking up an item, are expanding although only 26% of respondents
|
| 310 |
-
currently have fully-deployed programs.
|
| 311 |
|
| 312 |
-
|
| 313 |
|
| 314 |
-
|
| 315 |
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between in-store and online?
|
| 316 |
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| 317 |
-
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| 318 |
|
| 319 |
-
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| 320 |
|
| 321 |
-
|
| 322 |
|
| 323 |
-
|
| 324 |
-
Online Experiences Are Somewhat Consistent
|
| 325 |
|
| 326 |
-
|
| 327 |
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great customer experience?
|
| 328 |
|
| 329 |
-
|
| 330 |
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experiences across
|
| 331 |
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channels
|
| 332 |
|
| 333 |
-
|
| 334 |
|
| 335 |
-
|
| 336 |
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experiences
|
| 337 |
|
| 338 |
-
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| 339 |
|
| 340 |
-
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| 341 |
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customer data
|
| 342 |
|
| 343 |
-
|
| 344 |
|
| 345 |
-
|
| 346 |
-
initiatives across
|
| 347 |
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stores
|
| 348 |
|
| 349 |
-
|
| 350 |
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Customer Experience, with No Single Obstacle
|
| 351 |
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Standing Out Above the Rest
|
| 352 |
|
| 353 |
-
|
| 354 |
|
| 355 |
-
|
| 356 |
|
| 357 |
-
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| 358 |
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| 359 |
-
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| 360 |
|
| 361 |
-
|
| 362 |
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change
|
| 363 |
|
| 364 |
-
|
| 365 |
|
| 366 |
-
|
| 367 |
-
are leveraging it to
|
| 368 |
-
drive sales
|
| 369 |
|
| 370 |
-
|
| 371 |
-
hurting our sales
|
| 372 |
|
| 373 |
-
|
| 374 |
-
Yet Felt the Effects of Showrooming
|
| 375 |
|
| 376 |
-
|
| 377 |
-
in store” option?
|
| 378 |
|
| 379 |
-
|
| 380 |
|
| 381 |
-
|
| 382 |
-
deployed program
|
| 383 |
|
| 384 |
-
|
| 385 |
|
| 386 |
-
|
|
|
|
| 387 |
|
| 388 |
-
|
| 389 |
-
Currently Offer Some Sort of Option to Buy
|
| 390 |
-
Products Online and Pick Them Up In-Store
|
| 391 |
|
| 392 |
8
|
| 393 |
|
| 394 |
-
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|
| 395 |
|
| 396 |
-
|
| 397 |
|
| 398 |
-
|
| 399 |
-
collected in their stores. Using BLE beacons, location-based mobile services, loyalty programs,
|
| 400 |
-
promotions, and sales trends, merchants can uncover valuable data on the in-store customer
|
| 401 |
-
experience. This data can then help them track traffic patterns, evaluate how customers are
|
| 402 |
-
interacting with displays, and determine which promotions and marketing messages are
|
| 403 |
-
having the greatest impact. In other words, these insights lead to optimized stores, improved
|
| 404 |
-
marketing campaigns, and more effective omnichannel commerce interfaces.
|
| 405 |
|
| 406 |
-
|
| 407 |
-
|
| 408 |
-
|
| 409 |
-
|
| 410 |
-
personalization indicates that most retailers are missing major opportunities to reap the many
|
| 411 |
-
benefits of in-store data insights.
|
| 412 |
|
| 413 |
-
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| 414 |
-
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| 415 |
-
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| 416 |
-
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| 417 |
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| 420 |
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| 421 |
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| 422 |
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| 423 |
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| 424 |
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| 426 |
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|
| 427 |
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| 428 |
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| 429 |
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| 430 |
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| 431 |
-
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| 432 |
-
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|
| 433 |
|
| 434 |
9
|
| 435 |
|
| 436 |
-
|
| 437 |
-
|
| 438 |
-
|
| 439 |
-
|
| 440 |
-
|
| 441 |
-
shopping is where the
|
| 442 |
-
real opportunity lies for
|
| 443 |
-
retailers to make their
|
| 444 |
-
store a better place to
|
| 445 |
-
shop. It is gradually
|
| 446 |
-
becoming clear: the
|
| 447 |
-
stores that make proper
|
| 448 |
-
use of mobile wallets
|
| 449 |
-
are the ones who will
|
| 450 |
-
come out on top in the
|
| 451 |
-
modern retail era.”
|
| 452 |
|
| 453 |
-
|
| 454 |
-
Retail
|
| 455 |
|
| 456 |
-
|
| 457 |
-
targeting of your current marketing activities?
|
| 458 |
|
| 459 |
-
|
| 460 |
|
| 461 |
-
and
|
| 462 |
|
| 463 |
-
|
| 464 |
-
personalized
|
| 465 |
|
| 466 |
-
|
| 467 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 468 |
|
| 469 |
-
|
| 470 |
|
| 471 |
-
|
| 472 |
-
Targeting Their Marketing Messages, but There
|
| 473 |
-
Is Still Room for Improvement
|
| 474 |
|
| 475 |
-
|
| 476 |
|
| 477 |
-
|
| 478 |
-
omnichannel execution has become the bedrock of modern retail strategy. In fact, the
|
| 479 |
-
intersections between physical and digital retail channels have become so extensive that
|
| 480 |
-
many companies are no longer differentiating between sales made in stores and those
|
| 481 |
-
made digitally. As Saks Inc. CEO Stephen Sadove has said, “There is so much integration
|
| 482 |
-
between store and online sales that we can’t report the numbers separately. [That just
|
| 483 |
-
doesn’t] make sense, because we are moving inventory from one to another all the time.”
|
| 484 |
|
| 485 |
-
|
| 486 |
-
New devices, online offerings, and digital touch points are the engines of retail growth
|
| 487 |
-
because they streamline shopping experiences across channels and engage consumers on
|
| 488 |
-
their own terms. Novel technologies also enable businesses to gather a massive amount
|
| 489 |
-
of customer data, which can then be used to personalize marketing messages and shift
|
| 490 |
-
inventory to the right places. However, given the abundance of tools and technologies
|
| 491 |
-
available, choosing the right solutions can prove challenging. The best brands are those
|
| 492 |
-
that cut through unessential capabilities and focus only on those that add significant
|
| 493 |
-
value to the customer experience.
|
| 494 |
|
| 495 |
-
|
| 496 |
-
collect data in stores will inevitably change over time. As a result, which capabilities will
|
| 497 |
-
be at the center of the stores of the future? Despite the relatively wide utilization of QR
|
| 498 |
-
codes in retail stores, 61% of those surveyed said that they believe that QR codes will
|
| 499 |
-
disappear on the next 2-5 years. In contrast, 71% of respondents indicated anticipation
|
| 500 |
-
that mobile wallet capabilities will become standard over the same time period. In many
|
| 501 |
-
cases, the utilization of a given capability will not just depend on how sophisticated a
|
| 502 |
-
technology is but also on how that technology can be leveraged during a customer’s
|
| 503 |
|
| 504 |
-
|
| 505 |
|
| 506 |
-
|
| 507 |
|
| 508 |
-
|
| 509 |
-
process and mitigate one possible obstacle to a purchase while also enhancing customer
|
| 510 |
-
loyalty programs by capturing more data and improving incentives.
|
| 511 |
|
| 512 |
-
|
| 513 |
-
Mike Wittenstein, Retail Customer Experience Strategist and Designer, Storyminers, some
|
| 514 |
-
of the most successful retail technologies are the least intrusive and most intuitive for
|
| 515 |
-
consumers to interact with. This is the principle of Invisible Design: the less intrusive and
|
| 516 |
-
more streamlined a technology is, the more likely it is to become widely adopted.
|
| 517 |
|
| 518 |
-
|
| 519 |
-
next 2-5 years?
|
| 520 |
|
| 521 |
-
|
| 522 |
|
| 523 |
-
|
| 524 |
|
| 525 |
-
|
| 526 |
|
| 527 |
-
|
| 528 |
|
| 529 |
-
|
| 530 |
|
| 531 |
-
|
| 532 |
|
| 533 |
-
|
| 534 |
|
| 535 |
-
|
| 536 |
|
| 537 |
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| 538 |
-
|
| 539 |
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|
| 540 |
-
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|
| 541 |
|
| 542 |
-
|
| 543 |
|
| 544 |
-
|
| 545 |
|
| 546 |
-
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|
| 547 |
|
| 548 |
-
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|
| 549 |
|
| 550 |
-
|
|
|
|
| 551 |
|
| 552 |
-
|
|
|
|
| 553 |
|
| 554 |
-
|
| 555 |
|
| 556 |
-
|
| 557 |
-
standard practice in the next 2-5 years?
|
| 558 |
|
| 559 |
-
|
| 560 |
|
| 561 |
-
|
|
|
|
| 562 |
|
| 563 |
-
|
| 564 |
|
| 565 |
-
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|
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|
|
| 566 |
|
| 567 |
-
|
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|
|
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|
|
| 568 |
|
| 569 |
-
|
| 570 |
-
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|
|
|
|
| 571 |
|
| 572 |
-
|
|
|
|
|
|
|
| 573 |
|
| 574 |
-
|
|
|
|
| 575 |
|
| 576 |
-
|
| 577 |
-
70
|
| 578 |
-
50
|
| 579 |
-
Becoming Standard over the next 2-5 Years
|
| 580 |
|
| 581 |
-
|
| 582 |
|
| 583 |
-
|
| 584 |
|
| 585 |
-
|
|
|
|
|
|
|
| 586 |
|
| 587 |
-
|
| 588 |
|
| 589 |
-
|
| 590 |
|
| 591 |
-
|
| 592 |
|
| 593 |
-
|
| 594 |
|
| 595 |
-
|
| 596 |
|
| 597 |
-
|
| 598 |
-
Which retailers do you believe are providing the
|
| 599 |
-
most exceptional in-store experiences?
|
| 600 |
|
| 601 |
1
|
| 602 |
|
|
@@ -604,283 +493,476 @@ most exceptional in-store experiences?
|
|
| 604 |
|
| 605 |
3
|
| 606 |
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|
| 607 |
4
|
| 608 |
|
| 609 |
-
|
| 610 |
|
| 611 |
-
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|
| 612 |
|
| 613 |
-
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|
| 614 |
|
| 615 |
-
|
| 616 |
|
| 617 |
-
|
| 618 |
|
| 619 |
-
|
|
|
|
| 620 |
|
| 621 |
-
|
| 622 |
-
Retailers Providing Exceptional In-Store
|
| 623 |
-
Experiences
|
| 624 |
|
| 625 |
-
|
|
|
|
|
|
|
| 626 |
|
| 627 |
-
|
|
|
|
| 628 |
|
| 629 |
-
|
| 630 |
-
|
| 631 |
-
|
| 632 |
-
sales asset than associates.
|
| 633 |
|
| 634 |
-
|
| 635 |
-
|
| 636 |
-
As those tools become more sophisticated, they may eventually supersede sales
|
| 637 |
-
associates as the greatest in-store revenue drivers.
|
| 638 |
|
| 639 |
-
|
| 640 |
-
|
| 641 |
-
|
| 642 |
-
|
| 643 |
-
|
| 644 |
|
| 645 |
-
|
| 646 |
-
|
| 647 |
-
for information, goods, and services on an ongoing basis) and time of awareness to
|
| 648 |
-
time of satisfaction (i.e., how long it takes for a customer to acquire a good or service
|
| 649 |
-
from the time they become aware of it). Improving involvement and shortening the
|
| 650 |
-
time of awareness to time of satisfaction are becoming central objectives for businesses.
|
| 651 |
|
| 652 |
-
|
| 653 |
-
how well businesses are learning from and
|
| 654 |
-
listening to customers.
|
| 655 |
|
| 656 |
-
|
| 657 |
-
|
| 658 |
-
source of these inputs, which enable organizations to optimize their offerings and
|
| 659 |
-
create personalized marketing messages.
|
| 660 |
|
| 661 |
-
|
| 662 |
-
the
|
| 663 |
-
|
| 664 |
-
|
| 665 |
-
|
| 666 |
-
without detracting from the overall experience. Many retailers are struggling with this
|
| 667 |
-
cross-channel consistency, highlighting the need for them to critically evaluate how they
|
| 668 |
-
interact with customers on different media.
|
| 669 |
|
| 670 |
-
|
| 671 |
-
|
| 672 |
-
out anachronistic elements.
|
| 673 |
|
| 674 |
-
|
| 675 |
-
revenue, companies must replace outmoded elements with the right technologies,
|
| 676 |
-
particularly digital tools that enhance product interactions and capture key data points.
|
| 677 |
-
This requires constant re-evaluation and, occasionally, reinvention of store components
|
| 678 |
|
| 679 |
-
|
|
|
|
| 680 |
|
| 681 |
-
|
| 682 |
|
| 683 |
-
|
| 684 |
-
For this report, Worldwide Business Research conducted in person and online surveys
|
| 685 |
-
of 104 store, operations, IT, cross-channel, and retail customer experience executives
|
| 686 |
-
representing 14 industries (see Appendix B for demographic information). Survey
|
| 687 |
-
participants included decision-makers and executives with responsibility for their
|
| 688 |
-
businesses’ in-store and digital experiences and performance. In-person surveys and
|
| 689 |
-
interviews were conducted on-site at the 2014 Future Stores Conference. Data was
|
| 690 |
-
collected in June of 2014.
|
| 691 |
|
| 692 |
-
|
| 693 |
|
| 694 |
-
|
| 695 |
|
| 696 |
-
|
| 697 |
|
| 698 |
-
|
| 699 |
|
| 700 |
-
|
| 701 |
|
| 702 |
-
|
| 703 |
|
| 704 |
-
|
| 705 |
|
| 706 |
-
|
| 707 |
|
| 708 |
-
|
| 709 |
|
| 710 |
-
|
| 711 |
|
| 712 |
-
|
| 713 |
-
Appliances
|
| 714 |
|
| 715 |
-
|
| 716 |
|
| 717 |
-
|
| 718 |
|
| 719 |
-
|
| 720 |
|
| 721 |
-
|
| 722 |
|
| 723 |
-
|
| 724 |
|
| 725 |
-
|
| 726 |
|
| 727 |
-
|
| 728 |
|
| 729 |
-
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|
|
|
|
| 730 |
|
| 731 |
-
|
| 732 |
|
| 733 |
-
|
| 734 |
|
| 735 |
-
|
| 736 |
|
| 737 |
-
|
| 738 |
|
| 739 |
-
|
| 740 |
|
| 741 |
-
|
| 742 |
|
| 743 |
-
|
| 744 |
|
| 745 |
-
|
| 746 |
|
| 747 |
-
|
| 748 |
|
| 749 |
-
|
| 750 |
-
Experience
|
| 751 |
|
| 752 |
-
|
| 753 |
|
| 754 |
-
|
| 755 |
|
| 756 |
-
|
| 757 |
|
| 758 |
-
|
| 759 |
|
| 760 |
-
|
| 761 |
|
| 762 |
-
|
| 763 |
|
| 764 |
-
|
| 765 |
|
| 766 |
-
|
| 767 |
|
| 768 |
-
|
| 769 |
|
| 770 |
-
|
| 771 |
|
| 772 |
-
|
| 773 |
|
| 774 |
-
|
| 775 |
|
| 776 |
-
|
| 777 |
|
| 778 |
-
|
| 779 |
|
| 780 |
-
|
| 781 |
|
| 782 |
-
|
| 783 |
-
It was very well executed,
|
| 784 |
-
and I have taken a lot
|
| 785 |
-
of information from the
|
| 786 |
-
event that we will be
|
| 787 |
-
working to implement in
|
| 788 |
-
our stores.”
|
| 789 |
|
| 790 |
-
|
| 791 |
-
Merchandiser, Coastal.com
|
| 792 |
|
| 793 |
-
|
| 794 |
|
| 795 |
-
|
| 796 |
-
strategies. From omnichannel marketing and customer analytics to retail technology
|
| 797 |
-
and store operations, Future Stores will show you how to design and implement
|
| 798 |
-
winning in-store strategies to beat the competition and boost customer loyalty.
|
| 799 |
|
| 800 |
-
|
| 801 |
-
and customer experience executives to bridge the gap between the store experience
|
| 802 |
-
and the digital experience. Future Stores provides tactical strategies for brick and
|
| 803 |
-
mortar retailers to improve and increase conversion rates in-store as well as make the
|
| 804 |
-
store and cross-channel shopping experiences as seamless and easy as they are online.
|
| 805 |
|
| 806 |
-
|
| 807 |
|
| 808 |
-
|
| 809 |
-
CFI Group provides a technology platform that leverages the science of the American
|
| 810 |
-
Customer Satisfaction Index (ACSI). This platform continuously measures the customer
|
| 811 |
-
experience across multiple channels, benchmarks performance, and prioritizes
|
| 812 |
-
improvements for maximum impact.
|
| 813 |
|
| 814 |
-
|
| 815 |
-
global clients from a network of offices worldwide. Our clients span a variety of
|
| 816 |
-
industries, including financial services, hospitality, manufacturing, telecom, retail, and
|
| 817 |
-
government. Regardless of your industry, we can put the power of our technology and
|
| 818 |
-
the science of the ACSI methodology to work for you.
|
| 819 |
|
| 820 |
-
|
| 821 |
-
625 Avis Drive
|
| 822 |
-
Ann Arbor, MI 48108
|
| 823 |
-
(734) 930-9090
|
| 824 |
-
Askcfi@cfigroup.com
|
| 825 |
|
| 826 |
-
|
|
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|
|
|
|
| 827 |
|
| 828 |
-
|
| 829 |
-
|
|
|
|
|
|
|
| 830 |
|
| 831 |
-
|
| 832 |
-
|
| 833 |
-
|
| 834 |
-
competitors on the quality of the events we produce and the relationships we nurture
|
| 835 |
-
with both attendees and sponsors.
|
| 836 |
|
| 837 |
-
|
| 838 |
-
|
| 839 |
-
|
| 840 |
-
|
| 841 |
-
|
| 842 |
|
| 843 |
-
|
| 844 |
-
division, WBR Digital, connects solutions providers to their target audiences with
|
| 845 |
-
digital branding and engagement services and lead generation campaigns. WBR’s
|
| 846 |
-
marketers act as an extension of your team, relieving strain on your internal resources
|
| 847 |
-
while engaging with customers and prospects on your brand and solutions. Solutions
|
| 848 |
-
providers can target identified accounts or relevant industry/function segments of WBR’s
|
| 849 |
-
global database of senior-level decision makers.
|
| 850 |
|
| 851 |
-
|
| 852 |
-
Andrew Cole
|
| 853 |
-
Digital Content Manager
|
| 854 |
-
646-200-7541
|
| 855 |
-
Andrew.Cole@wbresearch.com
|
| 856 |
|
| 857 |
-
|
| 858 |
-
Future Stores Conference
|
| 859 |
|
| 860 |
-
|
| 861 |
|
| 862 |
-
|
| 863 |
|
| 864 |
-
|
| 865 |
-
1.888.482.6012, or email us at futurestores@wbresearch.com
|
| 866 |
|
| 867 |
-
|
| 868 |
|
| 869 |
-
|
| 870 |
|
| 871 |
-
|
| 872 |
-
action rapidly, is the ultimate competitive advantage.” - Jack Welch
|
| 873 |
|
| 874 |
-
|
| 875 |
-
|
| 876 |
-
|
| 877 |
-
content team and helps us to improve.
|
| 878 |
|
| 879 |
-
|
| 880 |
-
|
| 881 |
|
| 882 |
-
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|
| 883 |
|
| 884 |
18
|
| 885 |
|
| 886 |
-
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|
|
| 1 |
+
Becoming a
|
| 2 |
+
data-driven
|
| 3 |
+
organization
|
| 4 |
|
| 5 |
+
The what, why and how
|
|
|
|
| 6 |
|
| 7 |
+
Ongoing digitization is turning everything into data, forcing
|
| 8 |
|
| 9 |
+
Technological advancements in data analytics are, however,
|
| 10 |
|
| 11 |
+
companies to become more data-driven. While the benefits of
|
| 12 |
|
| 13 |
+
making it possible for any type of company in every industry to
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
|
| 15 |
+
the data-driven organisation are clear (improved performance,
|
|
|
|
| 16 |
|
| 17 |
+
become data-driven.
|
|
|
|
| 18 |
|
| 19 |
+
more profitability, stronger innovations), there are still some
|
|
|
|
| 20 |
|
| 21 |
+
Discover the basic do’s and don’ts in ‘Becoming a data-driven
|
| 22 |
|
| 23 |
+
technical and business challenges to overcome.
|
| 24 |
|
| 25 |
+
organisation: the what, why and how’.
|
| 26 |
|
| 27 |
+
Table of contents
|
| 28 |
|
| 29 |
+
1
|
| 30 |
|
| 31 |
+
Why become
|
| 32 |
+
data-driven?
|
| 33 |
|
| 34 |
+
You may not have noticed, but everything around us has
|
|
|
|
|
|
|
| 35 |
|
| 36 |
+
turned into data. Not just our cars or mobile phones, a
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 37 |
|
| 38 |
+
growing number of other appliances, machines and ‘things’
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 39 |
|
| 40 |
+
are generating a constant flux of data. Where we are and
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 41 |
|
| 42 |
+
what we do is used for marketing purposes. Sensors in
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 43 |
|
| 44 |
+
machines tell companies how to improve their output.
|
|
|
|
|
|
|
|
|
|
|
|
|
| 45 |
|
| 46 |
+
This flood of data is transforming our world. Companies that
|
| 47 |
+
|
| 48 |
+
want to stay ahead must become data-driven.
|
| 49 |
+
|
| 50 |
+
The rise of the data-driven organisation
|
| 51 |
+
|
| 52 |
+
Many organisations worry about staying competitive in the midst of Big
|
| 53 |
+
Data, Artificial Intelligence (AI), Machine Learning or the Internet of Things
|
| 54 |
+
(IoT). Especially as many of these concepts are already generating value
|
| 55 |
+
for many companies. The glue that binds all of these together is data.
|
| 56 |
+
|
| 57 |
+
What is being data-driven all about?
|
| 58 |
+
|
| 59 |
+
Data-driven organisations process and use ever more data
|
| 60 |
+
|
| 61 |
+
As consultancy firm McKinsey says:
|
| 62 |
+
|
| 63 |
+
to improve and speed up their decision-making. The goal of
|
| 64 |
+
|
| 65 |
+
having superior analytics is having superior insights. In data-
|
| 66 |
|
| 67 |
+
driven organisations, decisions that aren’t supported by data,
|
| 68 |
+
|
| 69 |
+
are considered suspicious. Smarter analytics technologies
|
| 70 |
+
|
| 71 |
+
now enable every company to become more data-driven.
|
| 72 |
+
|
| 73 |
+
“Businesses no longer have to go on gut instinct;
|
| 74 |
+
they can use data and analytics to make faster
|
| 75 |
+
decisions and more accurate forecasts supported
|
| 76 |
+
by a mountain of evidence.”
|
| 77 |
+
|
| 78 |
+
Becoming a data-driven organization
|
| 79 |
+
|
| 80 |
+
4
|
| 81 |
+
|
| 82 |
+
Data-driven organisations
|
| 83 |
+
use analytics to become smarter:
|
| 84 |
+
|
| 85 |
+
1
|
| 86 |
+
|
| 87 |
+
They perform
|
| 88 |
+
better
|
| 89 |
+
|
| 90 |
+
The data shows where
|
| 91 |
+
they can streamline
|
| 92 |
+
their processes.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 93 |
|
| 94 |
3
|
| 95 |
|
| 96 |
+
They are more
|
| 97 |
+
profitable
|
| 98 |
+
|
| 99 |
+
Constant improvements
|
| 100 |
+
and better predictions
|
| 101 |
+
help to outsmart the
|
| 102 |
+
competition and
|
| 103 |
+
improve innovation.
|
| 104 |
|
| 105 |
+
2
|
|
|
|
|
|
|
| 106 |
|
| 107 |
+
They are
|
| 108 |
+
operationally
|
| 109 |
+
more predictable
|
| 110 |
|
| 111 |
+
Data insights fuel
|
| 112 |
+
current and future
|
| 113 |
+
decision-making.
|
| 114 |
|
| 115 |
+
These advantages make an organisation more shock-resistant and less
|
| 116 |
+
likely to be surprised by the next economy - or technology disruption.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 117 |
|
| 118 |
+
Gut feeling no longer makes the difference
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 119 |
|
| 120 |
+
Gut feeling is not good enough anymore to differentiate yourself from
|
| 121 |
+
your competitors. To be truly competitive, you will need data. Lots of
|
| 122 |
+
relevant data. Luckily, any organisation can set out on the journey to
|
| 123 |
+
become data-driven. You no longer need to be a data scientist to work
|
| 124 |
+
with data. Citizen Data Scientists are not your professional statistician or
|
| 125 |
+
trained analyst, nor your maths wizard or computer scientist, but rather
|
| 126 |
+
regular business users who create and use advanced analytical models.
|
| 127 |
|
| 128 |
+
Citizen Data Scientists are part of the ongoing wave of democratization
|
| 129 |
+
of analytics in every department. These business people have the right
|
| 130 |
+
attitude – curious, adventurous, determined – to research and improve
|
| 131 |
+
things in your organisation. They want to get their hands on the data
|
| 132 |
+
themselves and find new ways to get answers. They’re willing to learn
|
| 133 |
+
new methods and use new tools. They often think, “I don’t want to ask a
|
| 134 |
+
statistician. I want to try it myself.”
|
| 135 |
|
| 136 |
+
Becoming a data-driven organization
|
| 137 |
|
| 138 |
+
5
|
| 139 |
|
| 140 |
+
2,500 PB
|
| 141 |
|
| 142 |
+
Every day, the world creates 2,500
|
| 143 |
+
petabytes of data. In the past two years,
|
| 144 |
+
mankind has generated more data than
|
| 145 |
+
in the preceding 5,000 years combined.
|
| 146 |
|
| 147 |
+
Source: IFL Science
|
|
|
|
| 148 |
|
| 149 |
+
ZOOM-IN ON
|
| 150 |
+
SWISSCOM
|
| 151 |
|
| 152 |
+
SWITZERLAND | TELECOM | CUSTOMER SERVICE
|
| 153 |
|
| 154 |
+
7 x FASTER
|
|
|
|
| 155 |
|
| 156 |
+
CUSTOMER SERVICE DATA IS NOW PROCESSED 7X FASTER
|
| 157 |
+
MAKING IT FAR MORE USEFUL IN ISSUE SOLVING.
|
| 158 |
|
| 159 |
+
Swisscom, Switzerland’s biggest telecom operator, found that the analysis
|
| 160 |
+
of their customer service data was too slow and required too much
|
| 161 |
+
manual work. As such, it did not really help to improve customer service.
|
| 162 |
+
Through smarter text analytics, however, relationships and possible
|
| 163 |
+
solutions were shown much faster, often almost simultaneously as the
|
| 164 |
+
ongoing call center documentation evolved. Reports are now sent daily
|
| 165 |
+
instead of weekly or even monthly.
|
| 166 |
|
| 167 |
+
“We are able to create fully automated daily reports, which
|
| 168 |
+
has a direct positive effect on service quality and customer
|
| 169 |
+
satisfaction.”
|
| 170 |
|
| 171 |
+
Albert Labermeier
|
| 172 |
+
Senior Marketing Analyst at Swisscom
|
| 173 |
|
| 174 |
+
Becoming a data-driven organization
|
| 175 |
|
| 176 |
+
6
|
| 177 |
|
| 178 |
+
2
|
|
|
|
|
|
|
| 179 |
|
| 180 |
+
The road to
|
| 181 |
+
becoming
|
| 182 |
+
data-driven
|
| 183 |
|
| 184 |
+
While the benefits of becoming more data-driven are
|
| 185 |
|
| 186 |
+
apparent, in our experience, many companies are still faced
|
| 187 |
|
| 188 |
+
with a few bumps in the road. Luckily, technical advances are
|
| 189 |
|
| 190 |
+
bringing data analytics within reach of a growing number of
|
| 191 |
|
| 192 |
+
organisations.
|
| 193 |
|
| 194 |
+
Changing mindsets
|
| 195 |
|
| 196 |
+
On the road to becoming data-driven, it’s crucial for people to change
|
| 197 |
+
their mindset and organisations to change their processes. Doing so, will
|
| 198 |
+
help overcome some of these hurdles:
|
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|
| 199 |
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| 200 |
+
1
|
| 201 |
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+
2
|
| 203 |
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+
3
|
| 205 |
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+
4
|
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|
| 208 |
+
UNSTRUCTURED DATA
|
| 209 |
|
| 210 |
+
UNCONNECTED SYSTEMS
|
| 211 |
|
| 212 |
+
LOW DATA QUALITY OR
|
| 213 |
+
UNAVAILABLE DATA
|
| 214 |
|
| 215 |
+
MISALIGNMENT WITH IT
|
| 216 |
|
| 217 |
+
Data that is not predefined or does
|
| 218 |
|
| 219 |
+
Organisations often use multiple
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|
| 220 |
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| 221 |
+
Sometimes, the data quality simply
|
| 222 |
|
| 223 |
+
Business units shouldn’t have to
|
|
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|
| 224 |
|
| 225 |
+
not fit the mould of traditional
|
| 226 |
|
| 227 |
+
information storage systems side by
|
| 228 |
|
| 229 |
+
isn’t good enough, because of poor
|
| 230 |
|
| 231 |
+
depend on IT for data analytics, they
|
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|
| 232 |
|
| 233 |
+
data models. This includes text
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|
| 234 |
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| 235 |
+
side with no or difficult connections
|
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|
| 236 |
|
| 237 |
+
data input or poorly implemented
|
| 238 |
|
| 239 |
+
should be able to run it themselves.
|
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|
| 240 |
|
| 241 |
+
documents, pictures, e-mails, sensor
|
| 242 |
|
| 243 |
+
between them. These systems may
|
|
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|
| 244 |
|
| 245 |
+
data connections. It is hard to get
|
| 246 |
|
| 247 |
+
With IT being under constant
|
|
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|
|
| 248 |
|
| 249 |
+
data, and much more. This data
|
|
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|
|
|
| 250 |
|
| 251 |
+
even offer conflicting information
|
| 252 |
|
| 253 |
+
good business intelligence from
|
| 254 |
|
| 255 |
+
pressure to keep delivering more
|
| 256 |
|
| 257 |
+
is hard to analyse for traditional
|
| 258 |
|
| 259 |
+
because they use different sources,
|
|
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|
| 260 |
|
| 261 |
+
poor – or plain wrong – data.
|
| 262 |
|
| 263 |
+
at lower costs, your data analytics
|
|
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|
|
|
|
| 264 |
|
| 265 |
+
analytics programs, although it
|
|
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|
| 266 |
|
| 267 |
+
processing methods or naming
|
|
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|
| 268 |
|
| 269 |
+
contains valuable information.
|
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|
| 270 |
|
| 271 |
+
conventions.
|
| 272 |
|
| 273 |
+
requests may end up at the bottom
|
|
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|
| 274 |
|
| 275 |
+
of their list.
|
| 276 |
|
| 277 |
+
But all of these challenges can be overcome by defining
|
| 278 |
+
a roadmap towards better data analytics.
|
| 279 |
|
| 280 |
+
Becoming a data-driven organization
|
|
|
|
|
|
|
| 281 |
|
| 282 |
8
|
| 283 |
|
| 284 |
+
ZOOM-IN ON
|
| 285 |
+
ASTRAZENECA
|
| 286 |
+
|
| 287 |
+
SWEDEN | HEALTHCARE | MANUFACTURING
|
| 288 |
+
|
| 289 |
+
VARIATIONS IN THE PRODUCTION PROCESS HAVE BEEN MINIMIZED.
|
| 290 |
|
| 291 |
+
THE CONTENT OF THE ANALYSES HAS BEEN GREATLY EXPANDED.
|
| 292 |
|
| 293 |
+
PRODUCTION CYCLES HAVE BECOME LEANER.
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
| 294 |
|
| 295 |
+
AstraZeneca, a global pharmaceutical company, wanted to make the
|
| 296 |
+
production process for its inhalers more cost-effective and qualitative by
|
| 297 |
+
better using the production data. Not an easy task, given the system’s 1,700
|
| 298 |
+
parameters and a total data growth of 1.5 million rows per week.
|
|
|
|
|
|
|
| 299 |
|
| 300 |
+
With the proper analytics system in place, automated data management
|
| 301 |
+
for each production batch has become possible, thus allowing for quick
|
| 302 |
+
analysis throughout the manufacturing process. Between 50 and 100
|
| 303 |
+
employees – as diverse as engineers, operators and managers – now create
|
| 304 |
+
or receive reports from the system while knowledge sharing is greatly
|
| 305 |
+
facilitated.
|
| 306 |
|
| 307 |
+
“Due to the success of the program, several other products
|
| 308 |
+
from the same family which are produced in AstraZeneca’s
|
| 309 |
+
Swedish operations have now been included under the
|
| 310 |
+
system. We plan to use the same system for completely
|
| 311 |
+
different product groups as well.”
|
| 312 |
|
| 313 |
+
Henrik Åkerblom
|
| 314 |
+
Process Engineer at AstraZeneca
|
| 315 |
|
| 316 |
+
80%
|
| 317 |
|
| 318 |
+
Analysts at Gartner
|
| 319 |
+
estimate that 80% of all
|
| 320 |
+
enterprise data today is
|
| 321 |
+
unstructured
|
| 322 |
|
| 323 |
+
Source: Gartner
|
| 324 |
|
| 325 |
+
45%
|
| 326 |
+
|
| 327 |
+
According to an IDG
|
| 328 |
+
survey, 45% of business
|
| 329 |
+
leaders cite ‛unstructured
|
| 330 |
+
data’ as their single
|
| 331 |
+
biggest hurdle to
|
| 332 |
+
overcome in analytics.
|
| 333 |
+
|
| 334 |
+
Source: IDG
|
| 335 |
+
|
| 336 |
+
Becoming a data-driven organization
|
| 337 |
|
| 338 |
9
|
| 339 |
|
| 340 |
+
3
|
| 341 |
+
|
| 342 |
+
The three
|
| 343 |
+
foundations of
|
| 344 |
+
better analytics
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 345 |
|
| 346 |
+
Technological improvements within analytics platforms
|
|
|
|
| 347 |
|
| 348 |
+
enable more companies to become data-driven, as it
|
|
|
|
| 349 |
|
| 350 |
+
enables organisations to manage their data better, run more
|
| 351 |
|
| 352 |
+
complex analyses and visualize the outcome in a more
|
| 353 |
|
| 354 |
+
understandable manner. Getting the technical foundations
|
|
|
|
| 355 |
|
| 356 |
+
right puts you well on your way.
|
| 357 |
+
|
| 358 |
+
Laying the foundation
|
| 359 |
+
|
| 360 |
+
There are three foundations to becoming data-driven.
|
| 361 |
+
|
| 362 |
+
1
|
| 363 |
|
| 364 |
+
2
|
| 365 |
|
| 366 |
+
3
|
|
|
|
|
|
|
| 367 |
|
| 368 |
+
DATA MANAGEMENT
|
| 369 |
|
| 370 |
+
This is the data you use as input. A good analytics platform can process any combination of structured, semi-structured and unstructured data. Automated
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 371 |
|
| 372 |
+
connections between your analytics platform and other systems ensure that the most recent data is always available and used. While not every data point will
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 373 |
|
| 374 |
+
be crystal clear from the start, technical advances in Machine Learning and the like already automate data management, for the most part. Similarly, data inputs
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 375 |
|
| 376 |
+
and data comparisons can be automated, neatly breaking down the obstacle of handling semi- and unstructured data. By applying the right governance
|
| 377 |
|
| 378 |
+
structure, privacy rules can be applied to personally identifiable information.
|
| 379 |
|
| 380 |
+
ANALYTICS
|
|
|
|
|
|
|
| 381 |
|
| 382 |
+
Pouring over endless rows of figures and numbers is the heavy lifting of data science. By leaving this task to specialized software, you leave less room for
|
|
|
|
|
|
|
|
|
|
|
|
|
| 383 |
|
| 384 |
+
human error and create more room to actually start using the results of your analysis. Complex calculations can now be run by a click of a button, making it
|
|
|
|
| 385 |
|
| 386 |
+
available to any regular business user.
|
| 387 |
|
| 388 |
+
DATA VISUALIZATION
|
| 389 |
|
| 390 |
+
The end result of your analytical work should be smarter insights. By visualizing this in different types of graphics and charts, the outcomes become easily
|
| 391 |
|
| 392 |
+
understandable for everyone at a glance, while reports and dashboards can quickly be set up, thus opening up the insights to a growing number of people
|
| 393 |
|
| 394 |
+
across the whole organisation.
|
| 395 |
|
| 396 |
+
Becoming a data-driven organization
|
| 397 |
|
| 398 |
+
11
|
| 399 |
|
| 400 |
+
74%
|
| 401 |
|
| 402 |
+
According to a Forrester
|
| 403 |
+
study, 74% of all companies
|
| 404 |
+
would like to be more data-
|
| 405 |
+
driven, but only 29% claim
|
| 406 |
+
that they are actually good
|
| 407 |
+
at putting this idea into
|
| 408 |
+
action.
|
| 409 |
|
| 410 |
+
Source: Forrester
|
| 411 |
|
| 412 |
+
The power of analytics that everyone can use
|
| 413 |
|
| 414 |
+
These three solid foundations enable you to build an analytics platform
|
| 415 |
+
that works for everyone. This has major benefits that help eliminate the
|
| 416 |
+
obstacles on your data-driven journey.
|
| 417 |
|
| 418 |
+
You get clear, actionable results, even from imperfect or
|
| 419 |
+
unstructured data. Cleaning up your data and perfecting your input
|
| 420 |
+
models can come later.
|
| 421 |
|
| 422 |
+
Your intelligence is easy to view and understand with visuals that
|
| 423 |
+
are more captivating than any line of text could ever be.
|
| 424 |
|
| 425 |
+
Because the platform is easy to use, self-service reduces reliance on
|
| 426 |
+
IT. In turn, IT can focus more on its core business.
|
| 427 |
|
| 428 |
+
1
|
| 429 |
|
| 430 |
+
2
|
|
|
|
| 431 |
|
| 432 |
+
3
|
| 433 |
|
| 434 |
+
ZOOM-IN ON
|
| 435 |
+
RABOBANK
|
| 436 |
|
| 437 |
+
THE NETHERLANDS | BANKING | OPERATIONS
|
| 438 |
|
| 439 |
+
TRANSPARENCY THROUGHOUT THE ORGANISATION HAS
|
| 440 |
+
INCREASED. DATA VISUALIZATION ENABLES THE BANK TO PROVIDE
|
| 441 |
+
PERTINENT INFORMATION AND DIRECT CHAIN MANAGERS MORE
|
| 442 |
+
EFFECTIVELY.
|
| 443 |
|
| 444 |
+
The Rabobank Group, a leading global financial services provider serving
|
| 445 |
+
more than 10 million customers and headquartered in the Netherlands,
|
| 446 |
+
wanted to optimize its operations by improving the financial and
|
| 447 |
+
collaborative alignment across its chains. The company discovered that
|
| 448 |
+
there was a huge amount of data available from all groups of the bank’s
|
| 449 |
+
organisational chain such as departments, business units and local
|
| 450 |
+
branches, but there wasn’t one single system that could integrate and
|
| 451 |
+
structure all the information efficiently and provide the ability to share
|
| 452 |
+
results.
|
| 453 |
|
| 454 |
+
With data visualization, large amounts of data are presented visually. The
|
| 455 |
+
diverse pictorial or graphical options lead to new questions that weren’t
|
| 456 |
+
asked before. The bank is now much more flexible in its ability to provide
|
| 457 |
+
information and it can direct chain managers more effectively. At the
|
| 458 |
+
same time, employees have become more engaged because they can
|
| 459 |
+
quickly see the results of what they do.
|
| 460 |
|
| 461 |
+
“With the knowledge and access to all chain information,
|
| 462 |
+
we are able to let go of old business models and replace
|
| 463 |
+
them with more dynamic ones.”
|
| 464 |
|
| 465 |
+
John Lambrechts
|
| 466 |
+
Manager Concern Control at Rabobank
|
| 467 |
|
| 468 |
+
Becoming a data-driven organization
|
|
|
|
|
|
|
|
|
|
| 469 |
|
| 470 |
+
12
|
| 471 |
|
| 472 |
+
4
|
| 473 |
|
| 474 |
+
The
|
| 475 |
+
data-driven
|
| 476 |
+
journey
|
| 477 |
|
| 478 |
+
So where do you start your data-driven journey? Anywhere is
|
| 479 |
|
| 480 |
+
good, as long as it isn’t everywhere. A ‘big bang’ approach is
|
| 481 |
|
| 482 |
+
risky: it can overcomplicate things or may simply lack focus.
|
| 483 |
|
| 484 |
+
We recommend a step-by-step approach as the surest way
|
| 485 |
|
| 486 |
+
forward to success.
|
| 487 |
|
| 488 |
+
Plotting the course
|
|
|
|
|
|
|
| 489 |
|
| 490 |
1
|
| 491 |
|
|
|
|
| 493 |
|
| 494 |
3
|
| 495 |
|
| 496 |
+
Choose your starting point
|
| 497 |
+
|
| 498 |
+
The most important datasets have priority
|
| 499 |
+
|
| 500 |
+
Expand the reach of the platform
|
| 501 |
+
|
| 502 |
+
This can be a team (e.g. the marketing
|
| 503 |
+
department) or a specific data source. Consider
|
| 504 |
+
collecting data from your CRM system to get a
|
| 505 |
+
better insight into customer behavior, or begin
|
| 506 |
+
with productivity data from the shop-floor.
|
| 507 |
+
|
| 508 |
+
Recorded customer service calls or data from your
|
| 509 |
+
finance department could equally be your first
|
| 510 |
+
project. It is best if your starting-point is something
|
| 511 |
+
you’re already familiar with, and if you have a clear
|
| 512 |
+
goal in mind.
|
| 513 |
+
|
| 514 |
+
You must make a distinction between must-have
|
| 515 |
+
datasets that will work towards your goal and nice-
|
| 516 |
+
to-have datasets that are only loosely related.
|
| 517 |
+
|
| 518 |
+
Data may be a mix of structured, semi-structured
|
| 519 |
+
and unstructured data. Pour it all in and look at
|
| 520 |
+
what your analytics platform comes up with and
|
| 521 |
+
whether the results are actionable. Consider if
|
| 522 |
+
additional data management (e.g. data cleaning)
|
| 523 |
+
is needed or whether you can already continue
|
| 524 |
+
using the current datasets.
|
| 525 |
+
|
| 526 |
+
Once you have value-added results, you can start
|
| 527 |
+
expanding the reach of the platform within and
|
| 528 |
+
across teams. This can happen in a series of waves
|
| 529 |
+
that create more and more buy-in as the results
|
| 530 |
+
begin to show more and more benefits.
|
| 531 |
+
|
| 532 |
+
Becoming a data-driven organization
|
| 533 |
+
|
| 534 |
+
14
|
| 535 |
+
|
| 536 |
+
Start
|
| 537 |
+
|
| 538 |
+
expand
|
| 539 |
+
within the team
|
| 540 |
+
|
| 541 |
+
Scale
|
| 542 |
+
|
| 543 |
+
Grow
|
| 544 |
+
|
| 545 |
+
expand
|
| 546 |
+
beyond the team
|
| 547 |
+
|
| 548 |
+
get the entire
|
| 549 |
+
organization on-board
|
| 550 |
+
|
| 551 |
4
|
| 552 |
|
| 553 |
+
The data-driven organisation is born
|
| 554 |
|
| 555 |
+
Once you have moved from a limited number of data sources to an all-
|
| 556 |
+
encompassing data management flow; you’ve extended the reach of
|
| 557 |
+
data analytics from the few to the many and every key decision is backed
|
| 558 |
+
by data, you’ve truly become a data-driven organisation. You‘ll find that,
|
| 559 |
+
as you become better at analytics, you’ll move from hindsight to insight
|
| 560 |
|
| 561 |
+
to foresight. You’ll no longer simply look back at ‘what happened’, but
|
| 562 |
+
you’ll steer your gaze to the future. Not only can you track ROI on all
|
| 563 |
+
data-enabled projects, you can also run predictive analytics and simulate
|
| 564 |
+
‘what-if’ scenarios. The backbone of your business strategy is now
|
| 565 |
+
formed by undisputable facts.
|
| 566 |
|
| 567 |
+
Becoming a data-driven organization
|
| 568 |
|
| 569 |
+
15
|
| 570 |
|
| 571 |
+
ZOOM-IN ON
|
| 572 |
+
Eni
|
| 573 |
|
| 574 |
+
BELGIUM | ENERGY | MARKETING & OPERATIONS
|
|
|
|
|
|
|
| 575 |
|
| 576 |
+
a
|
| 577 |
+
360°
|
| 578 |
+
view
|
| 579 |
|
| 580 |
+
on your
|
| 581 |
+
customers
|
| 582 |
|
| 583 |
+
‛What-if’ scenarios, allowing them to assess the impact of strategic
|
| 584 |
+
decisions, such as changes in price or margin, reduced customer
|
| 585 |
+
churn and more.
|
|
|
|
| 586 |
|
| 587 |
+
User-friendly dashboards that help to keep an eye on the long-term
|
| 588 |
+
profitability of the entire customer base.
|
|
|
|
|
|
|
| 589 |
|
| 590 |
+
“We calculate how much the customer will spend with us
|
| 591 |
+
(revenues) and how long they will stay (retention). We also
|
| 592 |
+
predict when we might experience payment issues (credit
|
| 593 |
+
losses) with them and how much it will cost us to serve their
|
| 594 |
+
needs (service costs).”
|
| 595 |
|
| 596 |
+
Zdravka Jevtimov
|
| 597 |
+
Customer Insights Manager at Eni
|
|
|
|
|
|
|
|
|
|
|
|
|
| 598 |
|
| 599 |
+
CUSTOMER CHURN AND RETENTION CAN NOW BE PREDICTED.
|
|
|
|
|
|
|
| 600 |
|
| 601 |
+
FUTURE PROFITABILITY OF PRODUCTS, CHANNELS AND
|
| 602 |
+
SEGMENTS CAN BE BETTER EVALUATED UP FRONT.
|
|
|
|
|
|
|
| 603 |
|
| 604 |
+
Eni is an integrated energy company with operations on five continents.
|
| 605 |
+
In the highly competitive energy market, it’s crucial to build long-term
|
| 606 |
+
relationships with clients. That’s why the company continuously monitors
|
| 607 |
+
and analyses the behaviour of its entire client base throughout the
|
| 608 |
+
complete customer life cycle.
|
|
|
|
|
|
|
|
|
|
| 609 |
|
| 610 |
+
The company developed a solid and trustworthy prediction model using
|
| 611 |
+
more than 700 parameters offering Eni’s management:
|
|
|
|
| 612 |
|
| 613 |
+
Valuable information about customers
|
|
|
|
|
|
|
|
|
|
| 614 |
|
| 615 |
+
Help in evaluating the future profitability of the company’s product
|
| 616 |
+
portfolio, sales channels and customer segments
|
| 617 |
|
| 618 |
+
60%
|
| 619 |
|
| 620 |
+
56%
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 621 |
|
| 622 |
+
Analyst firm Gartner estimates that
|
| 623 |
|
| 624 |
+
According to CMO.com, best-in-
|
| 625 |
|
| 626 |
+
over half of Big Data projects at
|
| 627 |
|
| 628 |
+
class marketeers are 56% more likely
|
| 629 |
|
| 630 |
+
companies fail. One big reason for
|
| 631 |
|
| 632 |
+
to use data and analytics platforms.
|
| 633 |
|
| 634 |
+
this is that companies often want
|
| 635 |
|
| 636 |
+
However, only 19% of marketers fully
|
| 637 |
|
| 638 |
+
to do everything at once instead of
|
| 639 |
|
| 640 |
+
track all their marketing efforts with
|
| 641 |
|
| 642 |
+
focusing on smaller projects with a
|
|
|
|
| 643 |
|
| 644 |
+
data.
|
| 645 |
|
| 646 |
+
clear end goal or a quick win.
|
| 647 |
|
| 648 |
+
Source: CMO.com
|
| 649 |
|
| 650 |
+
Source: Gartner
|
| 651 |
|
| 652 |
+
Becoming a data-driven organization
|
| 653 |
|
| 654 |
+
16
|
| 655 |
|
| 656 |
+
5
|
| 657 |
|
| 658 |
+
The next level
|
| 659 |
+
in data-driven
|
| 660 |
+
work
|
| 661 |
|
| 662 |
+
Being data-driven is not an end-state. It’s the beginning of an exploration of exciting possibilities. As the pace of technology
|
| 663 |
|
| 664 |
+
innovation keeps accelerating, yesterday’s science fiction becomes today’s reality. Here are some of the elements that will fuel
|
| 665 |
|
| 666 |
+
the data-driven organisation of the future.
|
| 667 |
|
| 668 |
+
On the edge of Tomorrow
|
| 669 |
|
| 670 |
+
Edge analytics
|
| 671 |
|
| 672 |
+
Transparency
|
| 673 |
|
| 674 |
+
Security
|
| 675 |
|
| 676 |
+
IoT
|
| 677 |
|
| 678 |
+
AI
|
| 679 |
|
| 680 |
+
Supply chain
|
|
|
|
| 681 |
|
| 682 |
+
Real-time on site analytics
|
| 683 |
|
| 684 |
+
Why not be transparent with
|
| 685 |
|
| 686 |
+
Analytics can be put to work
|
| 687 |
|
| 688 |
+
With the wealth of data
|
| 689 |
|
| 690 |
+
Artificial intelligence (AI)
|
| 691 |
|
| 692 |
+
Experts can use Big Data to
|
| 693 |
|
| 694 |
+
can track consumers’ in-store
|
| 695 |
|
| 696 |
+
consumers about the huge
|
| 697 |
|
| 698 |
+
for data protection as well.
|
| 699 |
|
| 700 |
+
generated by machines, your
|
| 701 |
|
| 702 |
+
makes it possible for
|
| 703 |
|
| 704 |
+
further optimize logistics.
|
| 705 |
|
| 706 |
+
behavior and pair it with the
|
| 707 |
|
| 708 |
+
amounts of data that are
|
| 709 |
|
| 710 |
+
With advanced pattern
|
| 711 |
|
| 712 |
+
production lines could map
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 713 |
|
| 714 |
+
machines to learn from
|
|
|
|
| 715 |
|
| 716 |
+
By taking into account
|
| 717 |
|
| 718 |
+
right kind of offer bundles to
|
|
|
|
|
|
|
|
|
|
| 719 |
|
| 720 |
+
collected? Some information
|
|
|
|
|
|
|
|
|
|
|
|
|
| 721 |
|
| 722 |
+
recognition and correlating
|
| 723 |
|
| 724 |
+
out ways to become even
|
|
|
|
|
|
|
|
|
|
|
|
|
| 725 |
|
| 726 |
+
experience, adjust to new
|
|
|
|
|
|
|
|
|
|
|
|
|
| 727 |
|
| 728 |
+
circumstantial factors that
|
|
|
|
|
|
|
|
|
|
|
|
|
| 729 |
|
| 730 |
+
attract attention and capture
|
| 731 |
+
|
| 732 |
+
will always remain sensitive,
|
| 733 |
+
|
| 734 |
+
the needs of the individual.
|
| 735 |
+
|
| 736 |
+
but offering transparency
|
| 737 |
+
|
| 738 |
+
This effectively creates the
|
| 739 |
+
|
| 740 |
+
to your customers can be
|
| 741 |
+
|
| 742 |
+
segment of one.
|
| 743 |
+
|
| 744 |
+
a big win in the branding
|
| 745 |
+
|
| 746 |
+
department. According to
|
| 747 |
|
| 748 |
+
recent surveys, over 80%
|
| 749 |
+
of consumers say ethics
|
| 750 |
+
matter when they buy. With
|
| 751 |
+
the General Data Protection
|
| 752 |
|
| 753 |
+
Regulation (GDPR), adhering
|
| 754 |
+
to privacy rules has become
|
| 755 |
+
an absolute must.
|
|
|
|
|
|
|
| 756 |
|
| 757 |
+
behaviours, risks can be
|
| 758 |
+
assessed better and cyber
|
| 759 |
+
attacks or real-life security
|
| 760 |
+
threats can be prevented
|
| 761 |
+
before they even occur.
|
| 762 |
|
| 763 |
+
more productive, discover
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 764 |
|
| 765 |
+
inputs and perform human-
|
|
|
|
|
|
|
|
|
|
|
|
|
| 766 |
|
| 767 |
+
influence delivery speed and
|
|
|
|
| 768 |
|
| 769 |
+
hidden costs and unlikely
|
| 770 |
|
| 771 |
+
like tasks. AI relies heavily on
|
| 772 |
|
| 773 |
+
reliability (e.g. traffic flows,
|
|
|
|
| 774 |
|
| 775 |
+
sources of revenue. The
|
| 776 |
|
| 777 |
+
deep learning and natural
|
| 778 |
|
| 779 |
+
accidents, weather patterns,
|
|
|
|
| 780 |
|
| 781 |
+
Internet of Things (IoT) will
|
| 782 |
+
revolutionize production
|
| 783 |
+
as well as consumption
|
|
|
|
| 784 |
|
| 785 |
+
language processing.
|
| 786 |
+
Computers are ‘trained’ to
|
| 787 |
|
| 788 |
+
rain storms), smarter logistics
|
| 789 |
+
|
| 790 |
+
could even be used to
|
| 791 |
+
|
| 792 |
+
accomplish specific tasks by
|
| 793 |
+
|
| 794 |
+
operate more sustainably.
|
| 795 |
+
|
| 796 |
+
patterns. And it’s just around
|
| 797 |
+
|
| 798 |
+
processing large amounts
|
| 799 |
+
|
| 800 |
+
the corner.
|
| 801 |
+
|
| 802 |
+
of data and recognizing
|
| 803 |
+
|
| 804 |
+
patterns in that data.
|
| 805 |
+
|
| 806 |
+
Becoming a data-driven organization
|
| 807 |
|
| 808 |
18
|
| 809 |
|
| 810 |
+
ZOOM-IN ON
|
| 811 |
+
INTERAMERICAN
|
| 812 |
+
|
| 813 |
+
GREECE | INSURANCE | COMPLIANCE
|
| 814 |
+
|
| 815 |
+
BE FULLY GDPR-COMPLIANT.
|
| 816 |
+
MAKE A BIG STEP TOWARDS BECOMING A DIGITAL-ONLY INSURER.
|
| 817 |
+
|
| 818 |
+
For INTERAMERICAN, a leading insurance provider in Greece, trust
|
| 819 |
+
is crucial to retaining loyal customers. The company adopted a data
|
| 820 |
+
analytics platform to be fully compliant with the EU General Data
|
| 821 |
+
Protection Regulation (GDPR) while also supporting the company’s
|
| 822 |
+
strategic focus of transforming itself into a digital-only insurer.
|
| 823 |
+
|
| 824 |
+
Its data governance initiative improves the availability, completeness and
|
| 825 |
+
accuracy of the information and data being managed. Topics covered
|
| 826 |
+
are data ownership, data location, data access, data provenance, risk
|
| 827 |
+
assessments and proper recovery procedures in case of breaches. All vital
|
| 828 |
+
elements in helping give customers peace of mind that their personal
|
| 829 |
+
data will be safe.
|
| 830 |
+
|
| 831 |
+
“Our organisation is working to transition to the new digital
|
| 832 |
+
age and create long-term, trust-based relationships with our
|
| 833 |
+
customers. SAS for Data Protection helps us work towards
|
| 834 |
+
compliance with the requirements of the new regulation
|
| 835 |
+
and foster customer trust.”
|
| 836 |
+
|
| 837 |
+
Xenophon Liapakis
|
| 838 |
+
CIO at INTERAMERICAN
|
| 839 |
+
|
| 840 |
+
41%
|
| 841 |
+
|
| 842 |
+
According to a CFI Group
|
| 843 |
+
survey, 41% of all consumers
|
| 844 |
+
use mobile apps while
|
| 845 |
+
shopping. For Millennials, this
|
| 846 |
+
figure even rises to 67%. 51%
|
| 847 |
+
of those polled said they would
|
| 848 |
+
be likely to use apps if they
|
| 849 |
+
made the shopping experience
|
| 850 |
+
easier and faster.
|
| 851 |
+
|
| 852 |
+
Source: CFI Group
|
| 853 |
+
|
| 854 |
+
Over half of organisations
|
| 855 |
+
surveyed by IDG say that
|
| 856 |
+
they are already deploying
|
| 857 |
+
analytics to detect cyber
|
| 858 |
+
attacks, denial-of-service
|
| 859 |
+
attacks and phishing.
|
| 860 |
+
However, 59% among them
|
| 861 |
+
still said they have been
|
| 862 |
+
compromised at least once
|
| 863 |
+
per month “because they
|
| 864 |
+
were not able to keep up
|
| 865 |
+
and fully analyse the data.”
|
| 866 |
+
|
| 867 |
+
Source: IDG
|
| 868 |
+
|
| 869 |
+
According to Accenture
|
| 870 |
+
research, using Big Data
|
| 871 |
+
analytics had a net positive
|
| 872 |
+
impact on customer service
|
| 873 |
+
and demand fulfilment
|
| 874 |
+
for nearly half of all supply
|
| 875 |
+
chain experts polled.
|
| 876 |
+
Other advantages listed
|
| 877 |
+
included greater supply
|
| 878 |
+
chain integration (36%),
|
| 879 |
+
productivity improvements
|
| 880 |
+
(33%) and improved cost to
|
| 881 |
+
serve (28%).
|
| 882 |
+
|
| 883 |
+
Source: Accenture
|
| 884 |
+
|
| 885 |
+
46%
|
| 886 |
+
|
| 887 |
+
53%
|
| 888 |
+
|
| 889 |
+
Becoming a data-driven organization
|
| 890 |
+
|
| 891 |
+
19
|
| 892 |
+
|
| 893 |
+
6
|
| 894 |
+
|
| 895 |
+
Getting in
|
| 896 |
+
on the action
|
| 897 |
+
|
| 898 |
+
Becoming a data-driven organisation is now within reach
|
| 899 |
+
of every company. Cloud solutions have made access to
|
| 900 |
+
data analytics platforms much easier: software-as-a-service
|
| 901 |
+
(SaaS) enables organisations to no longer build and
|
| 902 |
+
maintain everything on premise but rent this for as long as
|
| 903 |
+
needed. And with Results-as-a-Service (RaaS), it becomes
|
| 904 |
+
even possible to completely ‘outsource’ your analytics.
|
| 905 |
+
If you do not have tools and expertise to turn data into
|
| 906 |
+
insights, you can still get results.
|
| 907 |
+
Your organization provides the data and the business
|
| 908 |
+
problem to be solved, and RaaS delivers results you can
|
| 909 |
+
act on.
|
| 910 |
+
|
| 911 |
+
By starting your data-driven journey in one specific area
|
| 912 |
+
of your company, clearly defining your path towards data
|
| 913 |
+
analytics, adopting the right mindset and technologies,
|
| 914 |
+
and gradually extending the reach and impact throughout
|
| 915 |
+
your company, you too can become the type of data-driven
|
| 916 |
+
company that is ready for tomorrow’s challenges.
|
| 917 |
+
Start your data-driven journey now and, in no time, you’ll
|
| 918 |
+
find yourself wondering: ‘How on earth did we run our
|
| 919 |
+
business without analytics?’
|
| 920 |
+
|
| 921 |
+
Becoming a data-driven organization
|
| 922 |
+
|
| 923 |
+
21
|
| 924 |
+
|
| 925 |
+
Learn more about the what, why and how of
|
| 926 |
+
becoming a data-driven organisation
|
| 927 |
+
|
| 928 |
+
Read more
|
| 929 |
+
|
| 930 |
+
Follow us:
|
| 931 |
+
|
| 932 |
+
For more information, contact us
|
| 933 |
+
|
| 934 |
+
SOURCES
|
| 935 |
+
|
| 936 |
+
https://www.cio.com/article/3204131/analytics/intelligent-analytics-fuels-faster-smarter-decision-making.html
|
| 937 |
+
|
| 938 |
+
http://www.gartner.com/newsroom/id/3130017
|
| 939 |
+
|
| 940 |
+
https://www.retailcustomerexperience.com/news/report-says-most-millennials-are-using-mobile-retail-apps/?utm_source=NetWorld%20Alliance&utm_
|
| 941 |
+
|
| 942 |
+
medium=email&utm_campaign=EMNARCE07022014
|
| 943 |
+
|
| 944 |
+
http://www.sustainablebrands.com/news_and_views/stakeholder_trends_insights/sustainable_brands/study_81_consumers_say_they_will_make_
|
| 945 |
+
|
| 946 |
+
http://www.cmo.com/features/articles/2016/5/31/15-mind-blowing-stats-about-data-driven-marketing.html#gs.uH3Iceg
|
| 947 |
+
|
| 948 |
+
https://www.csoonline.com/article/3139923/security/how-big-data-is-improving-cyber-security.html
|
| 949 |
+
|
| 950 |
+
https://www.forbes.com/sites/louiscolumbus/2015/07/13/ten-ways-big-data-is-revolutionizing-supply-chain-management/#53f4e2769f59
|
| 951 |
+
|
| 952 |
+
https://www.shopify.com/enterprise/94678726-the-need-for-speed-why-customer-service-needs-to-be-faster-than-ever
|
| 953 |
+
|
| 954 |
+
https://reprints.forrester.com/#/assets/2/202/’RES127061’/reports
|
| 955 |
+
|
| 956 |
+
https://www.sas.com/nl_nl/training/citizen-data-scientist.html
|
| 957 |
+
|
| 958 |
+
https://www.sas.com/en_us/insights/articles/analytics/how-to-find-and-equip-citizen-data-scientists.html
|
| 959 |
+
|
| 960 |
+
https://www.forbes.com/sites/forbestechcouncil/2017/06/05/the-big-unstructured-data-problem/#28e176dd493a
|
| 961 |
+
|
| 962 |
+
SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration.
|
| 963 |
+
Other brand and product names are trademarks of their respective companies. Copyright © 2017, SAS Institute Inc. All rights reserved. 109150_G66177.1117
|
| 964 |
+
|
| 965 |
+
Becoming a data-driven organization
|
| 966 |
+
|
| 967 |
+
22
|
| 968 |
+
|
q130/random_k2/random_2.md
CHANGED
|
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|
|
| 1 |
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|
| 2 |
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| 3 |
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|
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|
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Eight easy steps to develop your
|
| 6 |
-
social media presence
|
| 7 |
|
| 8 |
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|
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|
| 10 |
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|
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4
|
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5
|
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6
|
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7
|
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8
|
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-
|
| 38 |
-
8
|
| 39 |
|
| 40 |
-
|
| 41 |
|
| 42 |
-
|
|
|
|
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|
| 44 |
-
|
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|
| 46 |
-
2
|
| 47 |
|
| 48 |
-
|
| 49 |
|
| 50 |
-
|
| 51 |
-
that Really Matter—and
|
| 52 |
-
How to Track Them
|
| 53 |
|
| 54 |
-
|
| 55 |
|
| 56 |
-
|
| 57 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 58 |
|
| 59 |
-
The
|
| 60 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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audience by 50 new followers per week."
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track, it’s hard to prove their real value for your business. Instead, focus on
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get executive buy-in and investment.
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three social media goals.
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personas
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Learn everything you can about your audience
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if you’re not engaged in social media listening, you’re creating your business
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strategy with blinders on—and you’re missing out on mountains of actionable
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creating content that they will like, comment on, and share. This knowledge
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also critical for planning how to develop your social media fans into
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customers for your business.
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different personas based on demographics, buying motivations, common
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buying objections, and the emotional needs of each type of customer.
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might not respond to Facebook ads with sales. But they might respond to
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Facebook ads with exclusive in-store events to be the first to see a new line of
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clothing. With personas, you’ll have the customer insights you need to create
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campaigns that speak to the real desires and motivations of your buyers.
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valuable information about who your followers are, where they live, which
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languages they speak, and how they interact with your brand on social. These
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insights allow you to refine your strategy and better target your social ads.
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social listening
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Watch: How to set up
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social listening streams
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business page
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Create an Instagram
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business account
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Create a Twitter business
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account
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Create a Snapchat
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Create a LinkedIn
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Company Page
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Create a Pinterest
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business account
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you. Remember, it’s better to
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use fewer channels well than
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to stretch yourself thin trying
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to maintain a presence on
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every social network.
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reference guide for image
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sizes for every network.
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Set up accounts and improve existing profiles
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Decide which networks you’ll focus on, and then set up and optimize your
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accounts.
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Determine which networks to use (and how to use them)
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As you decide which social channels to use, you’ll also need to define your
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strategy for each network. For example, you might decide to use Twitter for
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customer service, Facebook for customer acquisition, and Instagram for
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engaging existing customers.
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It’s a good exercise to create mission statements for each network. These
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one-sentence declarations will help you focus on a very specific goal for
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each account on each social network.
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For example, you could decide that:
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•• Facebook is best for acquiring new customers via paid advertising.
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••
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Instagram is where you build brand affinity with existing customers.
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•• Twitter is where you engage press and industry influencers.
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•• LinkedIn is where you engage existing employees and attract new talent.
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•• YouTube is where you support existing customers with education and
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video help content.
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•• Snapchat is where you distribute content with the goal of building brand
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awareness with younger consumers.
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If you can’t create a solid mission statement for a particular social network,
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you may want to reconsider whether that network is worth it.
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Set up (and optimize) your accounts
|
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Once you’ve decided which networks to focus on, it’s time to create your
|
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profiles—or improve existing profiles so they align with your strategic plan.
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In general, make sure you fill out all profile fields, use keywords people will
|
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use to search for your business, and use images that are correctly sized for
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each network.
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readers, and generates profit
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•• One-third of your social content shares ideas and stories from thought
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leaders in your industry or like-minded businesses
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•• One-third of your social content involves personal interactions with your
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audience
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Once you have your calendar set, use scheduling tools or bulk scheduling to
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prepare your posting in advance rather than updating constantly throughout
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the day. This allows you to focus on crafting the language and format of your
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posts, rather than writing them on the fly whenever you have time.
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You can also use this information to test different posts, campaigns, and
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strategies against one another. Constant testing allows you to understand
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what works and what doesn’t, so you can refine your strategy in real time.
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Ask your social media followers, email list, and website visitors whether
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you’re meeting their needs and expectations on social media. You can even
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ask them what they’d like to see more of—and then make sure to deliver on
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what they tell you.
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|
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go through significant demographic shifts. Your business will go through
|
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periods of change as well. All this means that your social media strategy
|
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should be a living document that you look at regularly and adjust as needed.
|
| 505 |
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Refer to it often to keep you on track, but don’t be afraid to make changes
|
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so that it better reflects new goals, tools, or plans.
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social team know, so they can all work together to help your business make
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the most of your social media accounts.
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strategy template
|
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Does this all feel a little overwhelming? The truth is that building your social
|
| 519 |
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media strategy is a substantial job. It should be, since it’s such an important
|
| 520 |
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document for your business. But it doesn’t have to be complicated.
|
| 521 |
|
| 522 |
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|
| 523 |
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creating your social media marketing plan. Visit our blog to download it (plus
|
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six other social media templates that can save you hours of work).
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| 539 |
-
|
| 540 |
-
|
| 541 |
-
We’re the world’s most widely used platform for managing social media.
|
| 542 |
|
| 543 |
-
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| 544 |
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| 545 |
-
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| 546 |
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| 547 |
-
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| 548 |
-
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| 549 |
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| 550 |
-
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| 551 |
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| 552 |
-
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| 553 |
|
|
|
|
| 1 |
+
FOR PUBLICATION
|
| 2 |
|
| 3 |
+
UNITED STATES COURT OF APPEALS
|
| 4 |
+
FOR THE NINTH CIRCUIT
|
|
|
|
|
|
|
| 5 |
|
| 6 |
+
X CORP.,
|
| 7 |
|
| 8 |
+
Plaintiff - Appellant,
|
| 9 |
|
| 10 |
+
v.
|
| 11 |
|
| 12 |
+
ROBERT BONTA, in his official
|
| 13 |
+
capacity as Attorney General of
|
| 14 |
+
California,
|
| 15 |
|
| 16 |
+
Defendant - Appellee.
|
| 17 |
|
| 18 |
+
No. 24-271
|
| 19 |
|
| 20 |
+
D.C. No.
|
| 21 |
+
2:23-cv-01939-
|
| 22 |
+
WBS-AC
|
| 23 |
|
| 24 |
+
OPINION
|
| 25 |
|
| 26 |
+
Appeal from the United States District Court
|
| 27 |
+
for the Eastern District of California
|
| 28 |
+
William B. Shubb, District Judge, Presiding
|
| 29 |
|
| 30 |
+
Argued and Submitted July 17, 2024
|
| 31 |
+
San Francisco, California
|
|
|
|
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|
| 32 |
|
| 33 |
+
Filed September 4, 2024
|
| 34 |
|
| 35 |
+
Before: MILAN D. SMITH, JR., MARK J. BENNETT,
|
| 36 |
+
and ANTHONY D. JOHNSTONE, Circuit Judges.
|
| 37 |
|
| 38 |
+
Opinion by Judge Milan D. Smith, Jr.
|
| 39 |
|
| 40 |
+
2
|
| 41 |
|
| 42 |
+
X CORP. V. BONTA
|
| 43 |
|
| 44 |
+
SUMMARY*
|
|
|
|
|
|
|
| 45 |
|
| 46 |
+
First Amendment / Social Media Platforms
|
| 47 |
|
| 48 |
+
The panel reversed the district court’s order denying
|
| 49 |
+
social media platform owner X Corp.’s motion for a
|
| 50 |
+
preliminary injunction to enjoin enforcement of California
|
| 51 |
+
Assembly Bill AB 587 (AB 587), which requires large social
|
| 52 |
+
media companies to post their terms of service and to submit
|
| 53 |
+
reports to the Attorney General of California (the State)
|
| 54 |
+
about their terms of service and their content-moderation
|
| 55 |
+
policies and practices.
|
| 56 |
|
| 57 |
+
The Content Category Report provisions of AB 587
|
| 58 |
+
require social media companies to submit to the State a
|
| 59 |
+
semiannual report detailing whether and how they define six
|
| 60 |
+
categories of content: hate speech or racism, extremism or
|
| 61 |
+
radicalization,
|
| 62 |
+
or misinformation,
|
| 63 |
+
harassment, foreign political interference, and controlled
|
| 64 |
+
substance distribution.
|
| 65 |
|
| 66 |
+
disinformation
|
| 67 |
|
| 68 |
+
The panel held that X Corp. was likely to succeed on the
|
| 69 |
+
merits of its claim that the Content Category Report
|
| 70 |
+
provisions facially violate the First Amendment. A facial
|
| 71 |
+
challenge is permissible because the Content Category
|
| 72 |
+
Report provisions raise the same First Amendment issues for
|
| 73 |
+
every social media company. The Content Category Report
|
| 74 |
+
provisions compel non-commercial speech, and are subject
|
| 75 |
+
to strict scrutiny because the provisions are content-
|
| 76 |
+
based. The Content Category Report provisions likely fail
|
| 77 |
+
strict scrutiny because they are not narrowly tailored to serve
|
| 78 |
|
| 79 |
+
* This summary constitutes no part of the opinion of the court. It has
|
| 80 |
+
been prepared by court staff for the convenience of the reader.
|
| 81 |
|
| 82 |
+
X CORP. V. BONTA
|
|
|
|
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|
| 83 |
|
| 84 |
3
|
| 85 |
|
| 86 |
+
the State’s purported goal of requiring social media
|
| 87 |
+
companies to be transparent about their policies and
|
| 88 |
+
practices.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
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|
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|
|
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|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 89 |
|
| 90 |
+
The panel held that the remaining factors weighed in
|
| 91 |
|
| 92 |
+
favor of a preliminary injunction.
|
|
|
|
|
|
|
|
|
|
|
|
|
| 93 |
|
| 94 |
+
Accordingly, the panel reversed the district court’s
|
| 95 |
+
denial of a preliminary injunction, and remanded with
|
| 96 |
+
instructions to enter a preliminary injunction consistent with
|
| 97 |
+
the opinion and to determine whether the Content Category
|
| 98 |
+
Report provisions are severable from the remainder of AB
|
| 99 |
+
587 and, if so, which, if any, of the remaining challenged
|
| 100 |
+
provisions should also be enjoined.
|
| 101 |
|
| 102 |
+
COUNSEL
|
|
|
|
|
|
|
|
|
|
| 103 |
|
| 104 |
+
Joel L. Kurtzberg (argued), Floyd Abrams, Jason D.
|
| 105 |
+
Rozbruch, and Lisa J. Cole, Cahill Gordon & Reindel LLP,
|
| 106 |
+
New York, New York; William R. Warne and Meghan M.
|
| 107 |
+
Baker, Downey Brand LLP, Sacramento, California; for
|
| 108 |
+
Plaintiff-Appellant.
|
| 109 |
|
| 110 |
+
Gabrielle D. Boutin (argued), Deputy Attorney General;
|
| 111 |
+
Anthony R. Hakl, Supervising Deputy Attorney General;
|
| 112 |
+
Thomas S. Patterson, Senior Deputy Attorney General; Rob
|
| 113 |
+
Bonta, Attorney General of California; Office of the
|
| 114 |
+
California Attorney General, Sacramento, California; for
|
| 115 |
+
Defendant-Appellee.
|
| 116 |
|
| 117 |
+
Robert Corn-Revere and Joshua A. House, Foundation for
|
| 118 |
+
Individual Rights and Expression, Washington, D.C., for
|
| 119 |
+
Amicus Curiae Foundation for Individual Rights and
|
| 120 |
+
Expression.
|
| 121 |
|
| 122 |
+
4
|
|
|
|
| 123 |
|
| 124 |
+
X CORP. V. BONTA
|
| 125 |
|
| 126 |
+
Trenton H. Norris, Mark W. Brennan, J. Ryan Thompson,
|
| 127 |
+
Sophie Baum, and Alexander Tablan, Hogan Lovells LLP,
|
| 128 |
+
San Francisco, California; Cory L. Andrews and John M.
|
| 129 |
+
Masslon II, Washington Legal Foundation, Washington,
|
| 130 |
+
D.C.; for Amicus Curiae Washington Legal Foundation.
|
| 131 |
|
| 132 |
+
Gene C. Schaerr, Schaerr Jaffe LLP, Washington, D.C., for
|
| 133 |
+
Amici Curiae Professor Eugene Volokh and Protect the First
|
| 134 |
+
Foundation.
|
|
|
|
|
|
|
| 135 |
|
| 136 |
+
Megan L. Brown, Jeremy J. Broggi, and Boyd Garriott,
|
| 137 |
+
Wiley Rein LLP, Washington, D.C.; Jonathan D. Urick and
|
| 138 |
+
Maria C. Monaghan, United States Chamber Litigation
|
| 139 |
+
Center; Washington, D.C.; for Amicus Curiae United States
|
| 140 |
+
of America Chamber of Commerce.
|
| 141 |
|
| 142 |
+
Bruce D. Brown, Katie Townsend, Gabe Rottman, Grayson
|
| 143 |
+
Clary and Emily Hockett, Reporters Committee for Freedom
|
| 144 |
+
of the Press, Washington, D.C.; for Amicus Curiae Reporters
|
| 145 |
+
Committee for Freedom of the Press.
|
| 146 |
|
| 147 |
+
David A. Greene and Aaron Mackey, Electronic Frontier
|
| 148 |
+
Foundation, San Francisco, California, for Amicus Curiae
|
| 149 |
+
Electronic Frontier Foundation.
|
|
|
|
| 150 |
|
| 151 |
+
Jacob M. Karr, Technology Law and Policy Clinic at New
|
| 152 |
+
York University, New York, New York; G.S. Hans, Cornell
|
| 153 |
+
Law School, Ithaca, New York; for Amici Curiae First
|
| 154 |
+
Amendment and Internet Law Scholars.
|
| 155 |
|
| 156 |
+
Michelle Quist and Lauren D. Wigginton, Buchalter APC,
|
| 157 |
+
Salt Lake City, Utah; Jon M. Greenbaum, Edward G. Caspar,
|
| 158 |
+
and Marc P. Epstein, Lawyers' Committee for Civil Rights
|
| 159 |
+
Under Law, Washington, D.C.; for Amicus Curiae Lawyers'
|
| 160 |
+
Committee for Civil Rights Under Law.
|
| 161 |
|
| 162 |
+
X CORP. V. BONTA
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 163 |
|
| 164 |
5
|
| 165 |
|
| 166 |
+
Viviana M. Hanley and Nathanial I. Levy, Deputy Attorneys
|
| 167 |
+
General; Michael L. Zuckerman, Deputy Solicitor General;
|
| 168 |
+
Jeremy Feigenbaum, Solicitor General; Metthew J. Platkin,
|
| 169 |
+
Attorney General of New Jersey; Office of the New Jersey
|
| 170 |
+
Attorney General, Trenton, New Jersey; Kristin K. Mayes,
|
| 171 |
+
Attorney General of Arizona, Office of the Arizona Attorney
|
| 172 |
+
General, Phoenix, Arizona; Philip J. Weiser, Attorney
|
| 173 |
+
General of Colorado, Office of the Colorado Attorney
|
| 174 |
+
General, Denver, Colorado; William Tong, Attorney
|
| 175 |
+
General of Connecticut, Office of the Connecticut Attorney
|
| 176 |
+
General, Hartford, Connecticut; Kathleen
|
| 177 |
+
Jennings,
|
| 178 |
+
Attorney General of Delaware, Office of the Delaware
|
| 179 |
+
Attorney General, Wilmington, Delaware; Brian L.
|
| 180 |
+
Schwalb, Attorney General of the District of Columbia,
|
| 181 |
+
Office of the District of Columbia Attorney General,
|
| 182 |
+
Washington, D.C.; Kwame Raoul, Attorney General of
|
| 183 |
+
Illinois, Office of the Illinois Attorney General, Chicago,
|
| 184 |
+
Illinois; Aaron M. Frey, Attorney General of Maine, Office
|
| 185 |
+
of the Maine Attorney General, Augusta, Maine; Anthony
|
| 186 |
+
G. Brown, Attorney General of Maryland, Office of the
|
| 187 |
+
Maryland Attorney General, Baltimore, Maryland; Andrea
|
| 188 |
+
J. Campbell, Attorney General of Massachusetts, Office of
|
| 189 |
+
the Massachusetts
|
| 190 |
+
Boston,
|
| 191 |
+
Attorney
|
| 192 |
+
Massachusetts; Dana Nessel, Attorney General of Michigan,
|
| 193 |
+
Office of
|
| 194 |
+
the Michigan Attorney General, Lansing,
|
| 195 |
+
Michigan; Keith Ellison, Attorney General of Minnesota,
|
| 196 |
+
Office of the Minnesota Attorney General, St. Paul,
|
| 197 |
+
Minnesota; Aaron D. Ford, Attorney General of Nevada,
|
| 198 |
+
Office of the Nevada Attorney General, Carson City,
|
| 199 |
+
Nevada; Letitia James, Attorney General of New York,
|
| 200 |
+
Office of the New York Attorney General, New York, New
|
| 201 |
+
York; Ellen F. Rosenblum, Attorney General of Oregon,
|
| 202 |
+
Office of the Oregon Attorney General, Salem, Oregon;
|
| 203 |
+
|
| 204 |
+
General,
|
| 205 |
+
|
| 206 |
+
6
|
| 207 |
+
|
| 208 |
+
X CORP. V. BONTA
|
| 209 |
+
|
| 210 |
+
Michelle A. Henry, Attorney General of Pennsylvania,
|
| 211 |
+
Office of Harrisburg, Pennsylvania; Charity R. Clark,
|
| 212 |
+
Attorney General of Vermont, Office of the Vermont
|
| 213 |
+
Attorney General, Montpelier, Vermont; Robert M.
|
| 214 |
+
Ferguson, Attorney General of Washington, Office of the
|
| 215 |
+
Washington Attorney General, Olympia, Washington; for
|
| 216 |
+
Amici Curiae States of New Jersey, Arizona, Colorado,
|
| 217 |
+
Connecticut, Delaware, The District of Columbia, Illinois,
|
| 218 |
+
Maine, Maryland, Massachusetts, Michigan, Minnesota,
|
| 219 |
+
Nevada, New York, Oregon, Pennsylvania, Vermont, and
|
| 220 |
+
Washington.
|
| 221 |
+
|
| 222 |
+
Jason S. Harrow and Charles Gerstein, Gerstein Harrow
|
| 223 |
+
LLP, Los Angeles, California, for Amicus Curiae Institute
|
| 224 |
+
for Strategic Dialogue.
|
| 225 |
+
|
| 226 |
+
Megan Iorio and Schuyler Standley, Electronic Privacy
|
| 227 |
+
Information Center, Washington, D.C., for Amicus Curiae
|
| 228 |
+
Electronic Privacy Information Center.
|
| 229 |
+
|
| 230 |
+
Kristen G. Simplicio and Cort T. Carlson, Tycko & Zavareei
|
| 231 |
+
LLP, Washington, D.C.; John Yang, Niyati Shah, and Noah
|
| 232 |
+
Baron, Asian Americans Advancing Justice, Washington,
|
| 233 |
+
D.C.; for Amicus Curiae Asian Americans Advancing
|
| 234 |
+
Justice.
|
| 235 |
+
|
| 236 |
+
X CORP. V. BONTA
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 237 |
|
| 238 |
7
|
| 239 |
|
| 240 |
+
OPINION
|
| 241 |
+
|
| 242 |
+
M. SMITH, Circuit Judge:
|
| 243 |
+
|
| 244 |
+
The California State Legislature enacted Assembly Bill
|
| 245 |
+
587 (AB 587) in September 2022. Cal. Bus. & Prof. Code
|
| 246 |
+
§§ 22675–81.
|
| 247 |
+
The law requires large social media
|
| 248 |
+
companies to, inter alia, post their terms of service and to
|
| 249 |
+
submit, on a semiannual basis, reports to the Attorney
|
| 250 |
+
General of California (the State) about their terms of service
|
| 251 |
+
and content-moderation policies and practices. X Corp., the
|
| 252 |
+
owner of the large social media platform X (formerly known
|
| 253 |
+
as Twitter), moved for a preliminary injunction to enjoin
|
| 254 |
+
enforcement of AB 587 on free speech and federal
|
| 255 |
+
preemption grounds. The district court denied X Corp.’s
|
| 256 |
+
motion, finding that X Corp. failed to establish a likelihood
|
| 257 |
+
of success on the merits. X Corp. appeals. For the reasons
|
| 258 |
+
below, we reverse and remand to the district court for further
|
| 259 |
+
proceedings consistent with this opinion.
|
| 260 |
+
|
| 261 |
+
FACTUAL AND PROCEDURAL BACKGROUND
|
| 262 |
+
|
| 263 |
+
AB 587 has three primary elements: (1) a requirement
|
| 264 |
+
that social media companies 1 publicly post their terms of
|
| 265 |
+
service, including processes for flagging content and
|
| 266 |
+
potential actions that may be taken with respect to flagged
|
| 267 |
+
content (Terms of Service (TOS) Posting), see Cal. Bus. &
|
| 268 |
+
Prof. Code § 22676, (2) a requirement that social media
|
| 269 |
+
|
| 270 |
+
1 AB 587 does not apply to social media companies with gross annual
|
| 271 |
+
revenues of less than $100 million, Cal. Bus. & Prof. Code § 22680, nor
|
| 272 |
+
to “an internet-based service or application for which interactions
|
| 273 |
+
between users are limited to direct messages, commercial transactions,
|
| 274 |
+
consumer reviews of products, sellers, services, events, or places, or any
|
| 275 |
+
combination thereof,” id. § 22681.
|
| 276 |
+
|
| 277 |
+
8
|
| 278 |
+
|
| 279 |
+
X CORP. V. BONTA
|
| 280 |
+
|
| 281 |
+
racism;
|
| 282 |
+
|
| 283 |
+
(b) extremism or
|
| 284 |
+
|
| 285 |
+
companies submit to the State a semiannual report detailing
|
| 286 |
+
their TOS and content-moderation practices including, if at
|
| 287 |
+
all, how the terms of service define and address (a) hate
|
| 288 |
+
speech or
|
| 289 |
+
radicalization;
|
| 290 |
+
(c) disinformation or misinformation; (d) harassment; and
|
| 291 |
+
(e) foreign political interference, as well as statistics on
|
| 292 |
+
content that was flagged by the social media company as
|
| 293 |
+
belonging to any of the categories (TOS Report), see id.
|
| 294 |
+
§ 22677, 2 and (3) a penalty provision, whereby the social
|
| 295 |
+
media company may be sued in court for, inter alia,
|
| 296 |
+
materially omitting or misrepresenting required information
|
| 297 |
+
and may be liable to pay up to $15,000 per violation per day,
|
| 298 |
+
see id. § 22678.3
|
| 299 |
+
|
| 300 |
+
On September 8, 2023, X Corp. filed a complaint against
|
| 301 |
+
the State seeking declaratory relief and injunctive relief
|
| 302 |
+
barring the law’s enforcement. The complaint alleges three
|
| 303 |
+
causes of action challenging the TOS Posting, TOS Report,
|
| 304 |
+
and penalty provision of AB 587 as: (1) a violation of the
|
| 305 |
+
free speech clauses of the U.S. and California Constitutions;
|
| 306 |
+
(2) a violation of the Dormant Commerce Clause; and
|
| 307 |
+
(3) federally preempted pursuant to the Communications
|
| 308 |
+
Decency Act, 47 U.S.C. § 230(c). X Corp. filed a motion for
|
| 309 |
+
preliminary injunction based on its free speech and
|
| 310 |
+
|
| 311 |
+
2 AB 587 was subsequently amended to add to this list “[c]ontrolled
|
| 312 |
+
substance distribution.” 2023 Cal. Legis. Serv. 7680 (West).
|
| 313 |
+
|
| 314 |
+
3 In assessing the amount of any penalty, a court is to consider whether
|
| 315 |
+
the social media company has made a reasonable, good faith attempt to
|
| 316 |
+
comply with the provisions of the statute. Cal. Bus. & Prof. Code
|
| 317 |
+
§ 22678(a)(3).
|
| 318 |
+
|
| 319 |
+
X CORP. V. BONTA
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 320 |
|
| 321 |
9
|
| 322 |
|
| 323 |
+
preemption claims, seeking to enjoin the State from
|
| 324 |
+
enforcing the challenged provisions of AB 587.4
|
| 325 |
+
|
| 326 |
+
On December 28, 2023, the district court denied X
|
| 327 |
+
Corp.’s motion. The court began its analysis with X Corp.’s
|
| 328 |
+
First Amendment claim.5 The court held that X Corp. was
|
| 329 |
+
unlikely to prevail because the TOS Posting and TOS Report
|
| 330 |
+
requirements appeared constitutionally permissible in light
|
| 331 |
+
of Zauderer v. Office of Disciplinary Counsel of Supreme
|
| 332 |
+
Court of Ohio, 471 U.S. 626 (1985), the Supreme Court’s
|
| 333 |
+
test for compelled commercial speech. See X Corp. v. Bonta,
|
| 334 |
+
No. 23-cv-01939, 2023 WL 8948286, at *1–2 (E.D. Cal.
|
| 335 |
+
Dec. 28, 2023).
|
| 336 |
+
|
| 337 |
+
The court’s analysis of the TOS Report requirement
|
| 338 |
+
focused primarily on the provisions requiring that social
|
| 339 |
+
media companies report whether and how they define and
|
| 340 |
+
address certain enumerated content categories. Id. at *2.
|
| 341 |
+
The court acknowledged that such reports do “not so easily
|
| 342 |
+
fit the traditional definition of commercial speech” because
|
| 343 |
+
they “are not advertisements” and because “social media
|
| 344 |
+
companies have no particular economic motivation to
|
| 345 |
+
provide them.” Id. However, the court applied Zauderer to
|
| 346 |
+
those provisions nevertheless so as to “follow[] the lead of
|
| 347 |
+
the Fifth and Eleventh Circuits.” Id. (citing NetChoice, LLC
|
| 348 |
+
v. Paxton, 49 F.4th 439, 485 (5th Cir. 2022), rev’d on other
|
| 349 |
+
grounds sub nom. Moody v. NetChoice, LLC, 144 S. Ct. 2383
|
| 350 |
+
|
| 351 |
+
4 X Corp. did not seek a preliminary injunction based upon the Dormant
|
| 352 |
+
Commerce Clause.
|
| 353 |
+
|
| 354 |
+
5 The district court did not analyze X Corp.’s free speech claim under
|
| 355 |
+
Article I, Section 2, of the California Constitution, nor do the parties
|
| 356 |
+
meaningfully address this claim on appeal. Because we hold that X
|
| 357 |
+
Corp. is likely to succeed on its First Amendment claim, we do not reach
|
| 358 |
+
X Corp.’s free speech claim pursuant to the California Constitution.
|
| 359 |
+
|
| 360 |
+
10
|
| 361 |
+
|
| 362 |
+
X CORP. V. BONTA
|
| 363 |
+
|
| 364 |
+
to
|
| 365 |
+
|
| 366 |
+
(2024) (“NetChoice (Tex.)”), and NetChoice, LLC v. Att’y
|
| 367 |
+
Gen., Fla., 34 F.4th 1196, 1230 (11th Cir. 2022), rev’d on
|
| 368 |
+
other grounds sub nom. Moody, 144 S. Ct. 2383 (“NetChoice
|
| 369 |
+
(Fla.)”)). The court then concluded that the TOS Report
|
| 370 |
+
requirement satisfies Zauderer. Id. The court reasoned that
|
| 371 |
+
the provisions require speech that is “purely factual” and
|
| 372 |
+
“uncontroversial” because they “merely require[] social
|
| 373 |
+
media companies
|
| 374 |
+
their existing content
|
| 375 |
+
identify
|
| 376 |
+
moderation policies, if any, related to the specified
|
| 377 |
+
categories” and the “mere fact that the reports may be ‘tied
|
| 378 |
+
in some way to a controversial issue’ does not make the
|
| 379 |
+
reports themselves controversial.” Id. (quoting CTIA - The
|
| 380 |
+
Wireless Ass’n v. City of Berkeley, 928 F.3d 832, 845 (9th
|
| 381 |
+
Cir. 2019) (“CTIA II”)). The court rejected X Corp.’s
|
| 382 |
+
argument that the TOS Report requirement is “unduly
|
| 383 |
+
burdensome,” explaining that “AB 587 does not require that
|
| 384 |
+
a social media company adopt any of the specified
|
| 385 |
+
categories” of speech, and that in any event “Zauderer is
|
| 386 |
+
concerned not merely with logistical or economic burdens,
|
| 387 |
+
but burdens on speech.” Id. It further held that the TOS
|
| 388 |
+
Report requirement is “reasonably related to a substantial
|
| 389 |
+
government interest in requiring social media companies to
|
| 390 |
+
be transparent about their content moderation policies and
|
| 391 |
+
practices so that consumers can make informed decisions
|
| 392 |
+
about where they consume and disseminate news and
|
| 393 |
+
information.” Id.
|
| 394 |
+
|
| 395 |
+
The district court also determined that X Corp. had failed
|
| 396 |
+
to show a likelihood of success on its claim that AB 587 is
|
| 397 |
+
preempted by 47 U.S.C. § 230(c). Id. at *3. The court
|
| 398 |
+
observed that the purpose of section 230(c) “is to provide
|
| 399 |
+
‘protection for “Good Samaritan” blocking and screening of
|
| 400 |
+
offensive material’” so that a website may “self-regulate
|
| 401 |
+
offensive third party content without fear of liability.” Id.
|
| 402 |
+
|
| 403 |
+
X CORP. V. BONTA
|
| 404 |
+
|
| 405 |
+
11
|
| 406 |
|
| 407 |
+
(quoting Doe v. Internet Brands, Inc., 824 F.3d 846, 851–52
|
| 408 |
+
(9th Cir. 2016)). The court concluded that AB 587 is not
|
| 409 |
+
preempted because, under its plain language, it “does not
|
| 410 |
+
provide for any potential liability stemming from a
|
| 411 |
+
company’s content moderation activities per se,” only for
|
| 412 |
+
failing to make AB 587’s required disclosures. Id.
|
| 413 |
|
| 414 |
+
On January 12, 2024, X Corp. timely filed notice of its
|
| 415 |
+
appeal. The provision of AB 587 most relevant in this appeal
|
| 416 |
+
is section 22677(a), which reads in its entirety:
|
| 417 |
|
| 418 |
+
(a) On a semiannual basis in accordance with
|
| 419 |
+
subdivision (b), a social media company shall
|
| 420 |
+
submit to the Attorney General a terms of
|
| 421 |
+
service report. The terms of service report
|
| 422 |
+
shall include, for each social media platform
|
| 423 |
+
owned or operated by the company, all of the
|
| 424 |
+
following:
|
| 425 |
|
| 426 |
+
(1) The current version of the terms of service
|
| 427 |
+
of the social media platform.
|
| 428 |
|
| 429 |
+
(2) If a social media company has filed its
|
| 430 |
+
first
|
| 431 |
+
report, a complete and detailed
|
| 432 |
+
description of any changes to the terms of
|
| 433 |
+
service since the previous report.
|
| 434 |
|
| 435 |
+
(3) A statement of whether the current
|
| 436 |
+
version of the terms of service defines each
|
| 437 |
+
of the following categories of content, and, if
|
| 438 |
+
so,
|
| 439 |
+
those categories,
|
| 440 |
+
the definitions of
|
| 441 |
+
including any subcategories:
|
| 442 |
|
| 443 |
+
(A) Hate speech or racism.
|
|
|
|
|
|
|
|
|
|
| 444 |
|
| 445 |
+
(B) Extremism or radicalization.
|
|
|
|
|
|
|
|
|
|
|
|
|
| 446 |
|
| 447 |
+
(C) Disinformation or misinformation.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 448 |
|
| 449 |
+
12
|
|
|
|
|
|
|
| 450 |
|
| 451 |
+
X CORP. V. BONTA
|
| 452 |
|
| 453 |
+
(D) Harassment.
|
| 454 |
|
| 455 |
+
(E) Foreign political interference.
|
|
|
|
|
|
|
|
|
|
|
|
|
| 456 |
|
| 457 |
+
(F) Controlled substance distribution.6
|
|
|
|
|
|
|
| 458 |
|
| 459 |
+
(4) A detailed description of content
|
| 460 |
+
moderation practices used by the social
|
| 461 |
+
media company for that platform, including,
|
| 462 |
+
but not limited to, all of the following:
|
| 463 |
|
| 464 |
+
(A) Any existing policies intended to
|
| 465 |
+
address
|
| 466 |
+
the categories of content
|
| 467 |
+
described in paragraph (3).
|
| 468 |
|
| 469 |
+
(B) How automated content moderation
|
| 470 |
+
systems enforce terms of service of the
|
| 471 |
+
social media platform and when these
|
| 472 |
+
systems involve human review.
|
| 473 |
|
| 474 |
+
(C) How the social media company
|
| 475 |
+
responds to user reports of violations of
|
| 476 |
+
the terms of service.
|
| 477 |
|
| 478 |
+
(D) How the social media company
|
| 479 |
+
would remove
|
| 480 |
+
individual pieces of
|
| 481 |
+
content, users, or groups that violate the
|
| 482 |
+
terms of service, or take broader action
|
| 483 |
+
against individual users or against groups
|
| 484 |
+
of users that violate the terms of service.
|
| 485 |
+
|
| 486 |
+
(E) The languages in which the social
|
| 487 |
+
media platform does not make terms of
|
| 488 |
+
service available, but does offer product
|
| 489 |
|
| 490 |
+
6 As noted above, section 22677(a)(3)(F) was added subsequent to X
|
| 491 |
+
Corp. filing its lawsuit in the district court.
|
|
|
|
| 492 |
|
| 493 |
+
X CORP. V. BONTA
|
| 494 |
|
| 495 |
+
13
|
| 496 |
|
| 497 |
+
features, including, but not limited to,
|
| 498 |
+
menus and prompts.
|
| 499 |
|
| 500 |
+
(5) (A) Information on content that was
|
| 501 |
+
flagged by the social media company as
|
| 502 |
+
content belonging to any of the categories
|
| 503 |
+
described in paragraph (3), including all of
|
| 504 |
+
the following:
|
| 505 |
|
| 506 |
+
(i) The total number of flagged items of
|
| 507 |
+
content.
|
| 508 |
+
|
| 509 |
+
(ii) The total number of actioned items of
|
| 510 |
+
content.
|
| 511 |
+
|
| 512 |
+
(iii) The total number of actioned items of
|
| 513 |
+
content that resulted in action taken by
|
| 514 |
+
the social media company against the
|
| 515 |
+
user or group of users responsible for the
|
| 516 |
+
content.
|
| 517 |
+
|
| 518 |
+
(iv) The total number of actioned items of
|
| 519 |
+
content that were removed, demonetized,
|
| 520 |
+
or deprioritized by the social media
|
| 521 |
+
company.
|
| 522 |
+
|
| 523 |
+
(v) The number of times actioned items
|
| 524 |
+
of content were viewed by users.
|
| 525 |
+
|
| 526 |
+
(vi) The number of times actioned items
|
| 527 |
+
of content were shared, and the number of
|
| 528 |
+
users that viewed the content before it
|
| 529 |
+
was actioned.
|
| 530 |
+
|
| 531 |
+
(vii) The number of times users appealed
|
| 532 |
+
social media company actions taken on
|
| 533 |
+
that platform and the number of reversals
|
| 534 |
+
of social media company actions on
|
| 535 |
+
|
| 536 |
+
14
|
| 537 |
+
|
| 538 |
+
X CORP. V. BONTA
|
| 539 |
+
|
| 540 |
+
appeal disaggregated by each type of
|
| 541 |
+
action.
|
| 542 |
+
|
| 543 |
+
(B) All information required by subparagraph
|
| 544 |
+
(A) shall be disaggregated into the following
|
| 545 |
+
categories:
|
| 546 |
+
|
| 547 |
+
(i) The category of content, including any
|
| 548 |
+
relevant
|
| 549 |
+
in
|
| 550 |
+
paragraph (3).
|
| 551 |
+
|
| 552 |
+
categories
|
| 553 |
+
|
| 554 |
+
described
|
| 555 |
+
|
| 556 |
+
(ii) The type of content, including, but not
|
| 557 |
+
limited to, posts, comments, messages,
|
| 558 |
+
profiles of users, or groups of users.
|
| 559 |
+
|
| 560 |
+
(iii) The type of media of the content,
|
| 561 |
+
including, but not limited to, text, images,
|
| 562 |
+
and videos.
|
| 563 |
+
|
| 564 |
+
the content was flagged,
|
| 565 |
+
(iv) How
|
| 566 |
+
including, but not limited to, flagged by
|
| 567 |
+
company employees or contractors,
|
| 568 |
+
flagged by artificial intelligence software,
|
| 569 |
+
flagged by community moderators,
|
| 570 |
+
flagged by civil society partners, and
|
| 571 |
+
flagged by users.
|
| 572 |
+
|
| 573 |
+
(v) How
|
| 574 |
+
the content was actioned,
|
| 575 |
+
including, but not limited to, actioned by
|
| 576 |
+
company employees or contractors,
|
| 577 |
+
intelligence
|
| 578 |
+
actioned
|
| 579 |
+
software,
|
| 580 |
+
community
|
| 581 |
+
moderators, actioned by civil society
|
| 582 |
+
partners, and actioned by users.
|
| 583 |
+
|
| 584 |
+
by
|
| 585 |
+
actioned
|
| 586 |
+
|
| 587 |
+
artificial
|
| 588 |
+
by
|
| 589 |
+
|
| 590 |
+
X CORP. V. BONTA
|
| 591 |
+
|
| 592 |
+
15
|
| 593 |
+
|
| 594 |
+
JURISDICTION AND STANDARD OF REVIEW
|
| 595 |
+
|
| 596 |
+
We have jurisdiction pursuant to 28 U.S.C. § 1292(a)(1)
|
| 597 |
+
to review the denial of a preliminary injunction. Creech v.
|
| 598 |
+
Idaho Comm’n of Pardons & Parole, 94 F.4th 851, 854 (9th
|
| 599 |
+
Cir. 2024). We review the denial of a preliminary injunction
|
| 600 |
+
for abuse of discretion, but we review de novo the
|
| 601 |
+
underlying issues of law. Cal. Chamber of Com. v. Council
|
| 602 |
+
for Educ. & Rsch. on Toxics, 29 F.4th 468, 475 (9th Cir.
|
| 603 |
+
2022).
|
| 604 |
+
|
| 605 |
+
“The appropriate legal standard to analyze a preliminary
|
| 606 |
+
injunction motion requires a district court to determine
|
| 607 |
+
whether a movant has established that (1) [it] is likely to
|
| 608 |
+
succeed on the merits of [its] claim, (2) [it] is likely to suffer
|
| 609 |
+
irreparable harm absent the preliminary injunction, (3) the
|
| 610 |
+
balance of equities tips in [its] favor, and (4) a preliminary
|
| 611 |
+
injunction is in the public interest.” Baird v. Bonta, 81 F.4th
|
| 612 |
+
1036, 1040 (9th Cir. 2023); see Winter v. Nat. Res. Def.
|
| 613 |
+
Council, Inc., 555 U.S. 7, 20 (2008). Because “the party
|
| 614 |
+
opposing injunctive relief is a government entity” here, the
|
| 615 |
+
third and fourth factors “merge.” Fellowship of Christian
|
| 616 |
+
Athletes v. San Jose Unified Sch. Dist. Bd. of Educ., 82 F.4th
|
| 617 |
+
664, 695 (9th Cir. 2023) (en banc) (quoting Nken v. Holder,
|
| 618 |
+
556 U.S. 418, 435 (2009)).
|
| 619 |
+
|
| 620 |
+
ANALYSIS
|
| 621 |
+
|
| 622 |
+
On appeal, X Corp. challenges the district court’s ruling
|
| 623 |
+
on the TOS Report requirement and penalty provision as
|
| 624 |
+
applied to the TOS Report requirement. X Corp. does not
|
| 625 |
+
appeal the district court’s denial of a preliminary injunction
|
| 626 |
+
as to the TOS Posting requirement, Cal. Bus. & Prof. Code
|
| 627 |
+
§ 22676.
|
| 628 |
+
|
| 629 |
+
16
|
| 630 |
+
|
| 631 |
+
X CORP. V. BONTA
|
| 632 |
+
|
| 633 |
+
X Corp. argues that the district court erred by finding that
|
| 634 |
+
X Corp. did not establish a likelihood of success on the
|
| 635 |
+
merits because
|
| 636 |
+
is
|
| 637 |
+
(1) the TOS Report
|
| 638 |
+
compelled, non-commercial speech subject to strict scrutiny,
|
| 639 |
+
not the lower tier of scrutiny in Zauderer, (2) regardless, the
|
| 640 |
+
TOS Report requirement fails under any level of scrutiny,
|
| 641 |
+
and (3) section 230’s broad immunity precludes liability
|
| 642 |
+
under AB 587.
|
| 643 |
+
|
| 644 |
+
requirement
|
| 645 |
+
|
| 646 |
+
X Corp. seeks to reverse the district court’s ruling as to
|
| 647 |
+
the entirety of the TOS Report requirement. But the thrust
|
| 648 |
+
of the appeal concerns section 22677(a)(3), which requires
|
| 649 |
+
that social media companies report whether and how they
|
| 650 |
+
define six categories of content, and sections 22677(a)(4)(A)
|
| 651 |
+
and (a)(5), which directly incorporate section 22677(a)(3).
|
| 652 |
+
For ease of reference, we refer to these sections as the
|
| 653 |
+
Content Category Report provisions.
|
| 654 |
+
|
| 655 |
+
For the reasons below, we hold that the Content Category
|
| 656 |
+
Report provisions likely compel non-commercial speech and
|
| 657 |
+
are subject to strict scrutiny, under which they do not
|
| 658 |
+
survive. We reverse the district court on that basis. Because
|
| 659 |
+
we reverse on free speech grounds, we need not reach X
|
| 660 |
+
Corp.’s section 230 theory. We remand to the district court
|
| 661 |
+
to determine in the first instance whether the Content
|
| 662 |
+
Category Report provisions are severable from
|
| 663 |
+
the
|
| 664 |
+
remainder of AB 587, and if so, which, if any, of the
|
| 665 |
+
remaining challenged provisions should also be subject to
|
| 666 |
+
the preliminary injunction.7
|
| 667 |
+
|
| 668 |
+
7 We do not decide whether sections 22677(a)(1), (2), and (4)(B)–(E)—
|
| 669 |
+
which require that social media companies disclose the text of their TOS
|
| 670 |
+
and describe their enforcement mechanisms, without mention of specific
|
| 671 |
+
|
| 672 |
+
X CORP. V. BONTA
|
| 673 |
+
|
| 674 |
+
17
|
| 675 |
+
|
| 676 |
+
I. X Corp. is likely to succeed in showing that the
|
| 677 |
+
Content Category Report provisions facially violate
|
| 678 |
+
the First Amendment.
|
| 679 |
+
|
| 680 |
+
“For a host of good reasons, courts usually handle
|
| 681 |
+
constitutional claims case by case, not en masse.” Moody,
|
| 682 |
+
144 S. Ct. at 2397. The Supreme Court “has therefore made
|
| 683 |
+
facial challenges hard to win.” Id. In a typical facial
|
| 684 |
+
challenge, a plaintiff cannot
|
| 685 |
+
succeed “unless he
|
| 686 |
+
‘establish[es] that no set of circumstances exists under which
|
| 687 |
+
the [law] would be valid,’ or he shows that the law lacks a
|
| 688 |
+
‘plainly legitimate sweep.’” Id. (alterations in original) (first
|
| 689 |
+
quoting United States v. Salerno, 481 U.S. 739, 745 (1987);
|
| 690 |
+
then quoting Wash. State Grange v. Wash. State Republican
|
| 691 |
+
Party, 552 U.S. 442, 449 (2008)).
|
| 692 |
+
|
| 693 |
+
less demanding
|
| 694 |
+
|
| 695 |
+
However, in First Amendment cases, the Supreme Court
|
| 696 |
+
“has lowered that very high bar.” Id. “To provide breathing
|
| 697 |
+
the Supreme Court has
|
| 698 |
+
room for free expression,”
|
| 699 |
+
“substituted a
|
| 700 |
+
though still rigorous
|
| 701 |
+
standard.” Id. (cleaned up) (quoting United States v.
|
| 702 |
+
Hansen, 599 U.S. 762, 769 (2023)); see also Tucson v. City
|
| 703 |
+
of Seattle, 91 F.4th 1318, 1327 (9th Cir. 2024). “[I]f the
|
| 704 |
+
law’s unconstitutional applications substantially outweigh
|
| 705 |
+
its constitutional ones,” then a court may sustain a facial
|
| 706 |
+
challenge to the law and strike it down. Moody, 144 S. Ct.
|
| 707 |
+
at 2397. As Moody clarified, a First Amendment facial
|
| 708 |
+
challenge has two parts: first, the courts must “assess the
|
| 709 |
+
state laws’ scope”; and second, the courts must “decide
|
| 710 |
+
|
| 711 |
+
content categories—are facially constitutional. Neither party—either
|
| 712 |
+
below or on appeal—briefed what should happen to the remainder of
|
| 713 |
+
section 22677 if the Content Category Report provisions were found to
|
| 714 |
+
be likely unconstitutional.
|
| 715 |
+
|
| 716 |
+
18
|
| 717 |
+
|
| 718 |
+
X CORP. V. BONTA
|
| 719 |
+
|
| 720 |
+
which of the laws’ applications violate the First Amendment,
|
| 721 |
+
and . . . measure them against the rest.” Id. at 2398.
|
| 722 |
+
|
| 723 |
+
“[N]o one has paid much attention to” the requirements
|
| 724 |
+
for a facial challenge so far in this case. Id. at 2397.
|
| 725 |
+
Nevertheless, we conclude that a facial challenge is
|
| 726 |
+
permissible here. That is because all aspects of the Content
|
| 727 |
+
Category Report, in every application to a covered social
|
| 728 |
+
media company, raise the same First Amendment issues. As
|
| 729 |
+
explained in further detail below, every Content Category
|
| 730 |
+
Report must detail the company’s policies and actions
|
| 731 |
+
concerning certain state-specified categories of content
|
| 732 |
+
(even if only to detail the company’s decision not to define
|
| 733 |
+
the enumerated categories of section 22677(a)(3)). In effect,
|
| 734 |
+
the Content Category Report provisions compel every
|
| 735 |
+
covered social media company to reveal its policy opinion
|
| 736 |
+
about contentious issues, such as what constitutes hate
|
| 737 |
+
speech or misinformation and whether to moderate such
|
| 738 |
+
expression.8
|
| 739 |
+
|
| 740 |
+
8 X Corp. cites legislative history and statements from the California
|
| 741 |
+
State Attorney General in describing the indirect chilling effects AB 587
|
| 742 |
+
may have by generating public controversy about the actions of social
|
| 743 |
+
media companies and thereby pressuring them to change their content
|
| 744 |
+
moderation policies. No matter how a social media company chooses to
|
| 745 |
+
moderate such content, the company will face backlash from its users
|
| 746 |
+
and the public. That is true even if the company decides not to define
|
| 747 |
+
the enumerated categories, because they will draw criticism for under-
|
| 748 |
+
moderating their community. While we account for these effects in our
|
| 749 |
+
analysis, whether State officials intended these effects plays no role in
|
| 750 |
+
our analysis of the merits of this facial challenge. See B & L Prods., Inc.
|
| 751 |
+
v. Newsom, 104 F.4th 108, 116 (9th Cir. 2024) (citing United States v.
|
| 752 |
+
O’Brien, 391 U.S. 367, 383 n.30 (1968)) (rejecting “the idea that
|
| 753 |
+
‘legislative motive’” of indirectly chilling speech “‘is a proper basis for
|
| 754 |
+
declaring a statute unconstitutional’”).
|
| 755 |
+
|
| 756 |
+
X CORP. V. BONTA
|
| 757 |
+
|
| 758 |
+
19
|
| 759 |
+
|
| 760 |
+
Thus, the Content Category Report provisions raise the
|
| 761 |
+
same First Amendment issues for every covered social
|
| 762 |
+
media company. That is true from the face of the law; we
|
| 763 |
+
need not “speculate about ‘hypothetical’ or ‘imaginary’
|
| 764 |
+
cases.” See Wash. State Grange, 552 U.S. at 450. We
|
| 765 |
+
therefore proceed to consider whether the Content Category
|
| 766 |
+
Report provisions are likely to survive X Corp.’s First
|
| 767 |
+
Amendment facial challenge.
|
| 768 |
+
|
| 769 |
+
A. The Content Category Report provisions compel
|
| 770 |
+
non-commercial speech and are subject to strict
|
| 771 |
+
scrutiny.
|
| 772 |
+
|
| 773 |
+
regulation
|
| 774 |
+
|
| 775 |
+
One of the First Amendment’s core purposes is “to
|
| 776 |
+
preserve an uninhibited marketplace of ideas in which truth
|
| 777 |
+
will ultimately prevail.” McCullen v. Coakley, 573 U.S. 464,
|
| 778 |
+
476 (2014) (quoting FCC v. League of Women Voters of
|
| 779 |
+
Cal., 468 U.S. 364, 377 (1984)). In evaluating whether a
|
| 780 |
+
regulation violates the First Amendment, courts “distinguish
|
| 781 |
+
between content-based and content-neutral regulations of
|
| 782 |
+
speech.” Vidal v. Elster, 602 U.S. 286, 292 (2024) (internal
|
| 783 |
+
quotation marks omitted) (quoting Nat’l Inst. of Fam. & Life
|
| 784 |
+
Advocs. v. Becerra, 585 U.S. 755, 766 (2018)). A content-
|
| 785 |
+
based
|
| 786 |
+
its
|
| 787 |
+
communicative content,” restricting discussion of a subject
|
| 788 |
+
matter or topic. Reed v. Town of Gilbert, 576 U.S. 155, 163
|
| 789 |
+
(2015). “As a general matter,” a content-based regulation is
|
| 790 |
+
“presumptively unconstitutional and may be justified only if
|
| 791 |
+
the government proves that [it is] narrowly tailored to serve
|
| 792 |
+
compelling state interests.” Nat’l Inst. of Fam. & Life
|
| 793 |
+
Advocs., 585 U.S. at 766 (quoting Reed, 576 U.S. at 163).
|
| 794 |
+
When a state “compel[s] individuals to speak a particular
|
| 795 |
+
message,” the state “alter[s] the content of their speech,” and
|
| 796 |
+
engages in content-based regulation. Id. (cleaned up)
|
| 797 |
+
(quoting Riley v. Nat’l Fed’n of the Blind of N.C., Inc., 487
|
| 798 |
+
|
| 799 |
+
speech based on
|
| 800 |
+
|
| 801 |
+
“target[s]
|
| 802 |
+
|
| 803 |
+
20
|
| 804 |
+
|
| 805 |
+
X CORP. V. BONTA
|
| 806 |
+
|
| 807 |
+
U.S. 781, 795 (1988)). The First Amendment’s guarantee of
|
| 808 |
+
freedom of speech makes no distinction of “constitutional
|
| 809 |
+
significance” “between compelled speech and compelled
|
| 810 |
+
silence.” Riley, 487 U.S. at 796–97.
|
| 811 |
+
|
| 812 |
+
In general, laws regulating commercial speech are
|
| 813 |
+
subject to a lesser standard of scrutiny. See Bolger v. Youngs
|
| 814 |
+
Drug Prods. Corp., 463 U.S. 60, 64–65 (1983) (discussing
|
| 815 |
+
recognition and evolution of commercial speech doctrine).
|
| 816 |
+
This holds true for both corporations and individuals alike.
|
| 817 |
+
See Pac. Gas & Elec. Co. v. Pub. Utils. Comm’n of Cal., 475
|
| 818 |
+
U.S. 1, 16 (1986). Commercial speech is “usually defined
|
| 819 |
+
as speech that does no more than propose a commercial
|
| 820 |
+
transaction.” United States v. United Foods, Inc., 533 U.S.
|
| 821 |
+
405, 409 (2001). “Courts view this definition as just a
|
| 822 |
+
starting point, however, and instead try to give effect to a
|
| 823 |
+
‘common-sense distinction’ between commercial speech
|
| 824 |
+
and other varieties of speech.” Ariix, LLC v. NutriSearch
|
| 825 |
+
Corp., 985 F.3d 1107, 1115 (9th Cir. 2021) (cleaned up)
|
| 826 |
+
(quoting Jordan v. Jewel Food Stores, Inc., 743 F.3d 509,
|
| 827 |
+
516–17 (7th Cir. 2014)). Indeed, the “commercial speech
|
| 828 |
+
analysis is fact-driven, due to the inherent difficulty of
|
| 829 |
+
drawing bright lines that will clearly cabin commercial
|
| 830 |
+
speech in a distinct category.” First Resort, Inc. v. Herrera,
|
| 831 |
+
860 F.3d 1263, 1272 (9th Cir. 2017) (internal quotation
|
| 832 |
+
marks omitted) (quoting Greater Balt. Ctr. for Pregnancy
|
| 833 |
+
Concerns, Inc. v. Mayor & City Council of Balt., 721 F.3d
|
| 834 |
+
264, 284 (4th Cir. 2013)).
|
| 835 |
+
|
| 836 |
+
Because of the difficulty of drawing clear lines between
|
| 837 |
+
commercial and non-commercial speech, the Supreme Court
|
| 838 |
+
in Bolger outlined three factors to consider. 463 U.S. at 64–
|
| 839 |
+
67. “Where the facts present a close question, ‘strong
|
| 840 |
+
support’ that the speech should be characterized as
|
| 841 |
+
commercial speech is found where [1] the speech is an
|
| 842 |
+
|
| 843 |
+
X CORP. V. BONTA
|
| 844 |
+
|
| 845 |
+
21
|
| 846 |
+
|
| 847 |
+
advertisement, [2] the speech refers to a particular product,
|
| 848 |
+
and [3] the speaker has an economic motivation.” Hunt v.
|
| 849 |
+
City of L.A., 638 F.3d 703, 715 (9th Cir. 2011) (citing
|
| 850 |
+
Bolger, 463 U.S. at 66–67). These so-called Bolger factors
|
| 851 |
+
are important guideposts, but they are not necessarily
|
| 852 |
+
dispositive. See Bolger, 463 U.S. at 67 n.14 (“Nor do we
|
| 853 |
+
mean to suggest that each of the characteristics present in
|
| 854 |
+
this case must necessarily be present in order for speech to
|
| 855 |
+
be commercial.”); Dex Media W., Inc. v. City of Seattle, 696
|
| 856 |
+
F.3d 952, 958 (9th Cir. 2012).
|
| 857 |
+
|
| 858 |
+
Commercial speech is generally subject to intermediate
|
| 859 |
+
scrutiny. Nat’l Ass’n of Wheat Growers v. Bonta, 85 F.4th
|
| 860 |
+
1263, 1266 (9th Cir. 2023). However, an exception applies
|
| 861 |
+
to compelled commercial speech that is “purely factual and
|
| 862 |
+
uncontroversial.” Id.; see Pac. Coast Horseshoeing Sch.,
|
| 863 |
+
Inc. v. Kirchmeyer, 961 F.3d 1062, 1074 (9th Cir. 2020)
|
| 864 |
+
(citing Zauderer as a variation in the treatment of speech
|
| 865 |
+
“within the class of commercial speech”). “In that scenario,
|
| 866 |
+
the government need only demonstrate the compelled speech
|
| 867 |
+
survives a lesser form of scrutiny akin to a rational basis
|
| 868 |
+
test.” Nat’l Wheat, 85 F.4th at 1266.
|
| 869 |
+
|
| 870 |
+
State legislatures do not have “freewheeling authority to
|
| 871 |
+
declare new categories of speech outside the scope of the
|
| 872 |
+
First Amendment.” United States v. Stevens, 559 U.S. 460,
|
| 873 |
+
472, (2010). Thus, “without persuasive evidence that a
|
| 874 |
+
novel restriction on content is part of a long (if heretofore
|
| 875 |
+
unrecognized) tradition of proscription, a legislature may not
|
| 876 |
+
revise the ‘judgment [of] the American people,’ embodied in
|
| 877 |
+
the First Amendment, ‘that the benefits of its restrictions on
|
| 878 |
+
the Government outweigh the costs.’” Brown v. Entm’t
|
| 879 |
+
Merchs. Ass’n, 564 U.S. 786, 792 (2011) (alteration in
|
| 880 |
+
original) (quoting Stevens, 559 U.S. at 470).
|
| 881 |
+
|
| 882 |
+
22
|
| 883 |
+
|
| 884 |
+
X CORP. V. BONTA
|
| 885 |
+
|
| 886 |
+
Here, the Content Category Reports are not commercial
|
| 887 |
+
speech. They require a company to recast its content-
|
| 888 |
+
moderation practices in language prescribed by the State,
|
| 889 |
+
implicitly opining on whether and how certain controversial
|
| 890 |
+
categories of content should be moderated. As a result, few
|
| 891 |
+
indicia of commercial speech are present in the Content
|
| 892 |
+
Category Reports.
|
| 893 |
+
|
| 894 |
+
First, the Content Category Reports do not satisfy the
|
| 895 |
+
“usual[] defin[ition]” of commercial speech—i.e., “speech
|
| 896 |
+
that does no more than propose a commercial transaction.”
|
| 897 |
+
See United Foods, Inc., 533 U.S. at 409; see also IMDb.com
|
| 898 |
+
Inc. v. Becerra, 962 F.3d 1111, 1122 (2020) (“Because
|
| 899 |
+
IMDb’s public profiles do not ‘propose a commercial
|
| 900 |
+
transaction,’ we need not reach the Bolger factors.”). The
|
| 901 |
+
State appears to concede as much in its answering brief.
|
| 902 |
+
|
| 903 |
+
To the extent our circuit has recognized exceptions to
|
| 904 |
+
that general rule, those exceptions are limited and are
|
| 905 |
+
inapplicable to the Content Category Reports here. For
|
| 906 |
+
example, as identified by the First Amendment and Internet
|
| 907 |
+
Law Scholars amici, we have characterized the following
|
| 908 |
+
speech as commercial even if not a clear fit with the Supreme
|
| 909 |
+
Court’s above articulation: (i) targeted, individualized
|
| 910 |
+
solicitations, see Nationwide Biweekly Admin., Inc. v. Owen,
|
| 911 |
+
873 F.3d. 716, 731–32 (9th Cir. 2017); contract negotiations,
|
| 912 |
+
see S.F. Apartment Ass’n v. San Francisco, 881 F.3d 1169,
|
| 913 |
+
1177–78 (9th Cir. 2018); and retail product warnings, see
|
| 914 |
+
CTIA II, 928 F.3d at 845. Though it does not directly or
|
| 915 |
+
exclusively propose a commercial transaction, all of this
|
| 916 |
+
speech communicates the terms of an actual or potential
|
| 917 |
+
transaction. But the Content Category Reports go further:
|
| 918 |
+
they express a view about those terms by conveying whether
|
| 919 |
+
a company believes certain categories should be defined and
|
| 920 |
+
proscribed.
|
| 921 |
+
|
| 922 |
+
X CORP. V. BONTA
|
| 923 |
+
|
| 924 |
+
23
|
| 925 |
+
|
| 926 |
+
Second, the Content Category Reports fail to satisfy at
|
| 927 |
+
least two of the three Bolger factors. The compelled
|
| 928 |
+
disclosures are not advertisements. See Hunt, 638 F.3d at
|
| 929 |
+
715. Nor do the Content Category Reports merely disclose
|
| 930 |
+
existing commercial speech, so a social media company has
|
| 931 |
+
no economic motivation in their content. See id. The district
|
| 932 |
+
court found the same. The State does not dispute the district
|
| 933 |
+
court’s finding on appeal. Although the Bolger factors are
|
| 934 |
+
not dispositive, they are “important guideposts” to the
|
| 935 |
+
analysis and, here, further support the conclusion that the
|
| 936 |
+
compelled speech is non-commercial. See Ariix, LLC, 985
|
| 937 |
+
F.3d at 1116.
|
| 938 |
+
|
| 939 |
+
topics,
|
| 940 |
+
|
| 941 |
+
Third, while a social media platform’s existing TOS and
|
| 942 |
+
content moderation policies may be commercial speech, its
|
| 943 |
+
opinions about and reasons for those policies are different in
|
| 944 |
+
character and kind. The Content Category Report provisions
|
| 945 |
+
would require 9 a social media company to convey the
|
| 946 |
+
company’s policy views on intensely debated and politically
|
| 947 |
+
fraught
|
| 948 |
+
racism,
|
| 949 |
+
misinformation, and radicalization, and also convey how the
|
| 950 |
+
company has applied its policies. The State suggests that
|
| 951 |
+
this requirement is subject to lower scrutiny because “it is
|
| 952 |
+
only a transparency measure” about the product. But even if
|
| 953 |
+
the Content Category Report provisions concern only
|
| 954 |
+
transparency, the relevant question here is: transparency into
|
| 955 |
+
what? Even a pure “transparency” measure, if it compels
|
| 956 |
+
non-commercial speech, is subject to strict scrutiny. See
|
| 957 |
+
|
| 958 |
+
including
|
| 959 |
+
|
| 960 |
+
speech,
|
| 961 |
+
|
| 962 |
+
hate
|
| 963 |
+
|
| 964 |
+
9 The State relies heavily on the fact that AB 587 does not affirmatively
|
| 965 |
+
require any social media company to opine on these topics, instead
|
| 966 |
+
requiring the company to convey its position only to the extent such a
|
| 967 |
+
policy already exists. That fact, however, is immaterial or at least non-
|
| 968 |
+
dispositive as to the nature of the speech being conveyed, which is
|
| 969 |
+
fundamentally non-commercial.
|
| 970 |
+
|
| 971 |
+
24
|
| 972 |
+
|
| 973 |
+
X CORP. V. BONTA
|
| 974 |
+
|
| 975 |
+
Riley, 487 U.S. at 796–97. That is true of the Content
|
| 976 |
+
Category Report provisions. Insight into whether a social
|
| 977 |
+
media company considers, for example, (1) a post citing
|
| 978 |
+
rhetoric from on-campus protests to constitute hate speech;
|
| 979 |
+
(2) reports about a seized laptop to constitute foreign
|
| 980 |
+
political interference; or (3) posts about election fraud to
|
| 981 |
+
constitute misinformation
|
| 982 |
+
is sensitive, constitutionally
|
| 983 |
+
protected speech that the State could not otherwise compel a
|
| 984 |
+
social media company to disclose without satisfying strict
|
| 985 |
+
scrutiny. The mere fact that those beliefs are memorialized
|
| 986 |
+
in the company’s content moderation policy does not, by
|
| 987 |
+
itself, convert expression about
|
| 988 |
+
into
|
| 989 |
+
commercial speech. As X Corp. argues in its reply brief,
|
| 990 |
+
such a rule would be untenable. It would mean that basically
|
| 991 |
+
any compelled disclosure by any business about its activities
|
| 992 |
+
would be commercial and subject to a lower tier of scrutiny,
|
| 993 |
+
no matter how political in nature. Protection under the First
|
| 994 |
+
Amendment cannot be vitiated so easily.10
|
| 995 |
+
|
| 996 |
+
those beliefs
|
| 997 |
+
|
| 998 |
+
The district court performed, essentially, no analysis on
|
| 999 |
+
this question. In fact, the district court acknowledged that
|
| 1000 |
+
the Content Category Reports “do not so easily fit the
|
| 1001 |
+
traditional definition of commercial speech” as they “are not
|
| 1002 |
+
advertisements, and social media companies have no
|
| 1003 |
+
|
| 1004 |
+
10 For substantially the same reason, nor can the test for whether speech
|
| 1005 |
+
is commercial or non-commercial turn on whether the speech is “directed
|
| 1006 |
+
to potential consumers and may presumably play a role in the decision
|
| 1007 |
+
of whether to use the platform,” as the district court seemed to suggest.
|
| 1008 |
+
Consider, for example, a state law that compels a social media company
|
| 1009 |
+
to disclose the political affiliations of its managers. That information
|
| 1010 |
+
could conceivably “play a role in the [potential consumer’s] decision of
|
| 1011 |
+
whether to use the platform”—i.e., if the consumer is concerned about
|
| 1012 |
+
the platform’s content being politically skewed. It could not be that such
|
| 1013 |
+
a law compels only commercial speech subject to a lower tier of scrutiny.
|
| 1014 |
+
|
| 1015 |
+
X CORP. V. BONTA
|
| 1016 |
+
|
| 1017 |
+
25
|
| 1018 |
+
|
| 1019 |
+
to provide
|
| 1020 |
+
|
| 1021 |
+
particular economic motivation
|
| 1022 |
+
them.”
|
| 1023 |
+
Nevertheless, the court applied Zauderer, suggesting the
|
| 1024 |
+
compelled speech is commercial. See Nat’l Wheat, 85 F.4th
|
| 1025 |
+
at 1275 (identifying Central Hudson Gas & Electric Corp.
|
| 1026 |
+
v. Public Service Commission of New York, 447 U.S. 557
|
| 1027 |
+
(1980), and Zauderer as “two levels of scrutiny governing
|
| 1028 |
+
compelled commercial speech” (emphasis added)); CTIA II,
|
| 1029 |
+
928 F.3d at 843 (endorsing proposition that Zauderer is
|
| 1030 |
+
merely the “exception to the general rule of Central
|
| 1031 |
+
Hudson”). The district court offered no reason for that
|
| 1032 |
+
decision except for wanting to “follow[] the lead of the Fifth
|
| 1033 |
+
and Eleventh Circuits.”
|
| 1034 |
+
|
| 1035 |
+
But neither the Fifth nor Eleventh Circuit dealt with
|
| 1036 |
+
speech similar to the Content Category Reports. Unlike
|
| 1037 |
+
Texas HB 20 or Florida SB 7072, the Content Category
|
| 1038 |
+
Report provisions compel social media companies to report
|
| 1039 |
+
whether and how they believe particular, controversial
|
| 1040 |
+
categories of content should be defined and regulated on
|
| 1041 |
+
their platforms. Neither the Texas nor Florida provisions at
|
| 1042 |
+
issue in the NetChoice cases require a company to disclose
|
| 1043 |
+
the existence or substance of its policies addressing such
|
| 1044 |
+
categories. See NetChoice (Tex.), 49 F.4th at 446 (requiring
|
| 1045 |
+
platforms to disclose “how they moderate and promote
|
| 1046 |
+
content” and provide “high-level statistics” about their
|
| 1047 |
+
moderation efforts without mention of controversial topics);
|
| 1048 |
+
NetChoice (Fla.), 34 F.4th at 1206–07 (requiring platforms
|
| 1049 |
+
to disclose information about their content-moderation
|
| 1050 |
+
“standards” and “rule changes” without regard to particular
|
| 1051 |
+
content categories). Though perhaps relevant to an analysis
|
| 1052 |
+
of sections 22677(a)(1), (2), and (4)(B)–(E), these cases are
|
| 1053 |
+
unhelpful on the issue of the Content Category Reports and
|
| 1054 |
+
offer no compelling reason to apply Zauderer.
|
| 1055 |
+
|
| 1056 |
+
26
|
| 1057 |
+
|
| 1058 |
+
X CORP. V. BONTA
|
| 1059 |
+
|
| 1060 |
+
For these reasons, we conclude that the Content
|
| 1061 |
+
Category Report provisions compel non-commercial speech.
|
| 1062 |
+
Because the provisions are content-based, which the State
|
| 1063 |
+
does not contest, they are subject to strict scrutiny. See Nat’l
|
| 1064 |
+
Inst. of Fam. & Life Advocs., 585 U.S. at 766.11
|
| 1065 |
+
|
| 1066 |
+
B. The Content Category Report provisions likely
|
| 1067 |
+
|
| 1068 |
+
fail strict scrutiny.
|
| 1069 |
+
|
| 1070 |
+
Strict scrutiny “is a demanding standard.” Brown v. Ent.
|
| 1071 |
+
Merchants Ass’n, 564 U.S. 786, 799 (2011). “It is rare that
|
| 1072 |
+
a regulation restricting speech because of its content will
|
| 1073 |
+
ever be permissible.” United States v. Playboy Ent. Grp.,
|
| 1074 |
+
Inc., 529 U.S. 803, 818 (2000). A state must show that the
|
| 1075 |
+
statute “furthers a compelling governmental interest and is
|
| 1076 |
+
narrowly tailored to that end.” Reed, 576 U.S. at 171. “If a
|
| 1077 |
+
less restrictive alternative would serve the [g]overnment’s
|
| 1078 |
+
purpose, the legislature must use that alternative.” Playboy
|
| 1079 |
+
Ent. Grp., Inc., 529 U.S. at 813.
|
| 1080 |
+
|
| 1081 |
+
At minimum, the Content Category Report provisions
|
| 1082 |
+
likely fail under strict scrutiny because they are not narrowly
|
| 1083 |
+
tailored. They are more extensive than necessary to serve
|
| 1084 |
+
the State’s purported goal of “requiring social media
|
| 1085 |
+
companies to be transparent about their content-moderation
|
| 1086 |
+
policies and practices so that consumers can make informed
|
| 1087 |
+
decisions about where they consume and disseminate news
|
| 1088 |
+
and information.” Consumers would still be meaningfully
|
| 1089 |
+
informed if, for example, a company disclosed whether it
|
| 1090 |
+
|
| 1091 |
+
11 X Corp. argues that strict scrutiny applies for the following additional
|
| 1092 |
+
reasons: because AB 587 is viewpoint discriminatory, interferes with a
|
| 1093 |
+
social media company’s constitutionally protected editorial judgment,
|
| 1094 |
+
and regulates “speech about speech.” Several of the amici raise similar
|
| 1095 |
+
arguments. Because we agree that strict scrutiny applies, we need not
|
| 1096 |
+
reach these arguments.
|
| 1097 |
+
|
| 1098 |
+
X CORP. V. BONTA
|
| 1099 |
+
|
| 1100 |
+
27
|
| 1101 |
+
|
| 1102 |
+
was moderating certain categories of speech without having
|
| 1103 |
+
to define those categories in a public report. Or, perhaps, a
|
| 1104 |
+
company could be compelled to disclose a sample of posts
|
| 1105 |
+
that have been removed without requiring the company to
|
| 1106 |
+
explain why or on what grounds.12
|
| 1107 |
+
|
| 1108 |
+
In any event, the State does not attempt to argue that the
|
| 1109 |
+
law survives strict scrutiny. For the reasons above, X Corp.
|
| 1110 |
+
has shown a likelihood of success on the merits of its First
|
| 1111 |
+
Amendment claim as to sections 22677(a)(3), (a)(4)(A), and
|
| 1112 |
+
(a)(5).
|
| 1113 |
+
|
| 1114 |
+
C. The remaining Winter factors weigh in favor of a
|
| 1115 |
+
|
| 1116 |
+
preliminary injunction.
|
| 1117 |
+
|
| 1118 |
+
With respect to the second factor, a loss of First
|
| 1119 |
+
Amendment freedoms constitutes an irreparable injury. See
|
| 1120 |
+
Fellowship of Christian Athletes, 82 F.4th at 694 (“It is
|
| 1121 |
+
axiomatic that ‘[t]he loss of First Amendment freedoms, for
|
| 1122 |
+
even minimal periods of time, unquestionably constitutes
|
| 1123 |
+
irreparable injury.’” (citation omitted)). Because X Corp.
|
| 1124 |
+
has a colorable First Amendment claim, it has demonstrated
|
| 1125 |
+
that it likely will suffer irreparable harm. See Am. Bev. Ass’n
|
| 1126 |
+
v. San Francisco, 916 F.3d 749, 758 (9th Cir. 2019) (en
|
| 1127 |
+
banc).
|
| 1128 |
+
|
| 1129 |
+
The third and fourth factors—balance of equities and
|
| 1130 |
+
public interest—also favor X Corp. “[I]t is always in the
|
| 1131 |
+
public interest to prevent the violation of a party’s
|
| 1132 |
+
constitutional rights.” Fellowship of Christian Athletes, 82
|
| 1133 |
+
F.4th at 695 (citation omitted). When a party “‘raise[s]
|
| 1134 |
+
serious First Amendment questions,’ that alone ‘compels a
|
| 1135 |
+
|
| 1136 |
+
12 We do not opine on whether such laws would survive constitutional
|
| 1137 |
+
scrutiny. They are offered only to illustrate that the Content Category
|
| 1138 |
+
Report provisions are not narrowly tailored to the State’s interest.
|
| 1139 |
+
|
| 1140 |
+
28
|
| 1141 |
+
|
| 1142 |
+
X CORP. V. BONTA
|
| 1143 |
+
|
| 1144 |
+
finding that the balance of hardships tips sharply in [its]
|
| 1145 |
+
favor.’” Id. (second alteration in original) (quoting Am. Bev.
|
| 1146 |
+
Ass’n, 916 F.3d at 758). The government reasonably has an
|
| 1147 |
+
interest in transparency by social media platforms. But even
|
| 1148 |
+
“undeniably admirable goals” “must yield” when they
|
| 1149 |
+
“collide with the . . . Constitution.” Id.
|
| 1150 |
+
|
| 1151 |
+
Because X Corp. has shown a likelihood of success on
|
| 1152 |
+
the merits of its First Amendment claim, and the remaining
|
| 1153 |
+
Winter factors weigh in favor of an injunction, we reverse
|
| 1154 |
+
the district court’s decision denying a preliminary injunction
|
| 1155 |
+
as to AB 587’s Content Category Report provisions.
|
| 1156 |
+
|
| 1157 |
+
II. We remand to the district court to determine whether
|
| 1158 |
+
the Content Category Report provisions are likely
|
| 1159 |
+
severable from the remainder of AB 587.
|
| 1160 |
+
|
| 1161 |
+
“Severability is . . . a matter of state law.” Sam Francis
|
| 1162 |
+
Found. v. Christies, Inc., 784 F.3d 1320, 1325 (9th Cir.
|
| 1163 |
+
2015) (en banc) (alteration in original) (quoting Leavitt v.
|
| 1164 |
+
Jane L., 518 U.S. 137, 139 (1996) (per curiam)). “In
|
| 1165 |
+
California, the presence of a severability clause in a statutory
|
| 1166 |
+
scheme that contains an invalid provision ‘normally calls for
|
| 1167 |
+
sustaining the valid part of the enactment.’” Garcia v. City
|
| 1168 |
+
of Los Angeles, 11 F.4th 1113, 1120 (9th Cir. 2021) (quoting
|
| 1169 |
+
Cal. Redevelopment Ass’n v. Matosantos, 267 P.3d 580, 607
|
| 1170 |
+
(Cal. 2011)).
|
| 1171 |
+
|
| 1172 |
+
The parties did not brief severability on appeal, and the
|
| 1173 |
+
severability arguments below appear to have been cursory.
|
| 1174 |
+
During oral argument, counsel for the State suggested that,
|
| 1175 |
+
were we to find that any part of the statute should be
|
| 1176 |
+
enjoined, the issue of severability should be remanded. We
|
| 1177 |
+
agree and leave it to the district court to determine in the first
|
| 1178 |
+
instance whether the likely unconstitutional provisions of
|
| 1179 |
+
AB 587, sections 22677(a)(3), (a)(4)(A), and (a)(5), are
|
| 1180 |
+
|
| 1181 |
+
X CORP. V. BONTA
|
| 1182 |
+
|
| 1183 |
+
29
|
| 1184 |
+
|
| 1185 |
+
severable from its remainder. See generally Detrich v. Ryan,
|
| 1186 |
+
740 F.3d 1237, 1248–49 (9th Cir. 2013) (en banc) (observing
|
| 1187 |
+
that it is “standard practice . . . to remand to the district court
|
| 1188 |
+
for a decision in the first instance without requiring any
|
| 1189 |
+
special justification for so doing”), overruled on other
|
| 1190 |
+
grounds by Shinn v. Ramirez, 596 U.S. 366 (2022).
|
| 1191 |
+
|
| 1192 |
+
CONCLUSION
|
| 1193 |
+
|
| 1194 |
+
For the foregoing reasons, we REVERSE the district
|
| 1195 |
+
court’s denial of a preliminary injunction as to California
|
| 1196 |
+
Business and Professions Code sections 22677(a)(3),
|
| 1197 |
+
(a)(4)(A), and (a)(5). We remand with instructions to enter
|
| 1198 |
+
a preliminary injunction consistent with this opinion and to
|
| 1199 |
+
determine whether these provisions are severable from the
|
| 1200 |
+
remainder of AB 587 and, if so, which, if any, of the
|
| 1201 |
+
remaining challenged provisions should also be enjoined.
|
| 1202 |
|
q130/random_k4/question.json
CHANGED
|
@@ -17,10 +17,10 @@
|
|
| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
"Campaign_038_Introducing_AC_Whitepaper_v5e.pdf",
|
| 20 |
-
"
|
| 21 |
-
"
|
| 22 |
-
"
|
| 23 |
-
"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
|
|
|
|
| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
"Campaign_038_Introducing_AC_Whitepaper_v5e.pdf",
|
| 20 |
+
"web_419331e34a19dd26.pdf",
|
| 21 |
+
"web_040fe479bf878a27.pdf",
|
| 22 |
+
"resize_r1_12.pdf",
|
| 23 |
+
"web_bfb031d3e591ca35.pdf"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
|
q130/random_k4/random_1.md
CHANGED
|
@@ -1,602 +1,491 @@
|
|
| 1 |
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| 2 |
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-
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-
September 2014
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-
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| 11 |
-
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| 13 |
-
|
| 14 |
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Investing in People &
|
| 15 |
-
Technology
|
| 16 |
-
to Enhance In-Store
|
| 17 |
-
Experiences ............................... 4
|
| 18 |
|
| 19 |
-
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Cross-Channel Consistency ....... 6
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| 22 |
-
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into Actionable Messaging ........ 9
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Store Technologies .................. 10
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| 40 |
|
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|
| 42 |
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How to Engage and Convert Consumers with Great
|
| 43 |
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In-Store Retail Experiences
|
| 44 |
|
| 45 |
-
|
| 46 |
-
years. In particular, the ascendance of multichannel e-commerce platforms has
|
| 47 |
-
challenged brands to reimagine how they interact with consumers. As a result, today’s
|
| 48 |
-
connected consumers have access to a whole host of digital shopping tools, including
|
| 49 |
-
interactive websites with high-definition images and mobile-optimized web and email.
|
| 50 |
-
E-commerce offers variety, convenience, and information, empowering consumers to
|
| 51 |
-
engage with retailers when, where, and how they please.
|
| 52 |
|
| 53 |
-
|
| 54 |
-
The Department of Commerce estimates that e-commerce accounted for approximately
|
| 55 |
-
6.5% of all retail sales in the U.S. during the second quarter of 2014. Although this
|
| 56 |
-
reaffirms that physical stores remain retailers’ most prominent sources of revenue, it
|
| 57 |
-
also suggests that there are great opportunities for synergy between a brand’s physical
|
| 58 |
-
locations and its e-commerce platform.
|
| 59 |
|
| 60 |
-
|
| 61 |
-
sales have turned out to be great assets to retailers. Mobile devices enable businesses
|
| 62 |
-
to send extremely relevant and timely messages to consumers by using location-based
|
| 63 |
-
services and Bluetooth Low Energy (BLE) beacons. Loyalty programs deployed across
|
| 64 |
-
channels encourage repeat business both in-store and online. QR codes and interactive
|
| 65 |
-
displays offer customers new ways to engage with and learn about products and
|
| 66 |
-
services. Omnichannel initiatives (e.g., an option for the consumer to buy online and
|
| 67 |
-
pick up in-store) promote interchannel traffic. Because of these innovations, today’s
|
| 68 |
-
consumers begin shopping before they walk into the store and continue shopping after
|
| 69 |
-
they leave, making their in-store experiences the unifying element.
|
| 70 |
|
| 71 |
-
|
| 72 |
-
it has been influenced in large part by technological innovation and new consumer
|
| 73 |
-
insights. The most successful retail stores not only leverage new technologies to drive
|
| 74 |
-
in-store conversions, but they also enhance the shopping experience, collect actionable
|
| 75 |
-
customer data, and serve as a physical extension of the brand. This is the store of the
|
| 76 |
-
future: a connected showroom that fuses together multichannel experiences to convert
|
| 77 |
-
and engage customers while also learning from them.
|
| 78 |
|
| 79 |
-
|
| 80 |
-
retailers are creating in their stores. The analysis is based on survey data collected from
|
| 81 |
-
retail executives and professionals in a variety of industries. This data was collected on-site
|
| 82 |
-
at the 2014 Future Stores Conference and through an online survey. The findings are
|
| 83 |
-
based on the insights and practices of some of the world’s leading retailers and brands.
|
| 84 |
|
| 85 |
-
|
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|
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|
| 88 |
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-
|
| 90 |
-
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-
|
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| 95 |
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| 96 |
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|
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| 100 |
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| 101 |
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| 102 |
-
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| 103 |
-
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| 104 |
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| 105 |
-
|
| 106 |
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-
|
| 109 |
-
|
| 110 |
-
|
| 111 |
-
|
| 112 |
-
|
| 113 |
-
the future will create seamless shopping
|
| 114 |
-
experiences and integrate with other
|
| 115 |
-
technologies and services.
|
| 116 |
-
|
| 117 |
-
In-store retail technology is constantly evolving.
|
| 118 |
-
Although many new technologies will arise over the next 2-5 years,
|
| 119 |
-
not all of those tools will help businesses improve their conversions and
|
| 120 |
-
experiences. Retailers will need to critically sort through the multitude
|
| 121 |
-
of solutions and only implement those that enhance conversions while
|
| 122 |
-
providing customers with effortless, engaging experiences.
|
| 123 |
|
| 124 |
3
|
| 125 |
|
| 126 |
-
|
| 127 |
-
|
| 128 |
-
|
| 129 |
-
|
| 130 |
-
|
| 131 |
-
|
| 132 |
-
|
| 133 |
-
|
| 134 |
|
| 135 |
-
|
| 136 |
-
Customer Experience Strategist
|
| 137 |
-
and Designer, Storyminers
|
| 138 |
|
| 139 |
-
|
|
|
|
|
|
|
| 140 |
|
| 141 |
-
|
| 142 |
-
|
|
|
|
| 143 |
|
| 144 |
-
|
| 145 |
-
|
| 146 |
-
driving consumer loyalty and engagement through innovative interactions and inventive
|
| 147 |
-
campaigns. Stores are also a burgeoning source of data that can be turned into rich insights
|
| 148 |
-
into shoppers’ tendencies and preferences. Add in customers’ lofty expectations for shopping
|
| 149 |
-
experiences and the value of the modern store becomes undeniable. With few exceptions,
|
| 150 |
-
stores continue to be the backbone of retail businesses, even in today’s world of e-commerce
|
| 151 |
-
and digital interconnectedness.
|
| 152 |
|
| 153 |
-
|
| 154 |
-
they are constantly updating designs, technology, and personnel to get the most out of
|
| 155 |
-
each location. Creating a store of the future means seamlessly integrating cutting-edge
|
| 156 |
-
technology with tried and true designs and tactics, providing a strong balance of analog
|
| 157 |
-
and digital elements that help deliver to customers higher value outcomes that are easier
|
| 158 |
-
to achieve. When it comes to technology, electronic point of sale (EPOS) tools have
|
| 159 |
-
become extremely common, with over three quarters of survey respondents indicating
|
| 160 |
-
that they are already utilizing the capability. A robust 72% are leveraging mobile devices
|
| 161 |
-
and tablets in stores, and 60% are making use of digital displays or kiosks.
|
| 162 |
|
| 163 |
-
|
| 164 |
-
|
| 165 |
-
|
| 166 |
-
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|
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|
| 167 |
|
| 168 |
-
|
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|
| 169 |
|
| 170 |
-
|
| 171 |
|
| 172 |
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|
| 173 |
|
| 174 |
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|
| 175 |
|
| 176 |
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|
| 177 |
-
|
| 178 |
-
|
|
|
|
| 179 |
|
| 180 |
-
|
| 181 |
-
Associates to Be Their Greatest In-Store Assets
|
| 182 |
|
| 183 |
-
|
|
|
|
| 184 |
|
| 185 |
-
|
| 186 |
|
| 187 |
-
|
| 188 |
-
most to improve in-store conversions?
|
| 189 |
|
| 190 |
-
|
|
|
|
| 191 |
|
| 192 |
-
|
| 193 |
-
|
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|
| 194 |
|
| 195 |
-
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|
| 196 |
|
| 197 |
-
|
| 198 |
-
|
| 199 |
|
| 200 |
-
|
| 201 |
|
| 202 |
-
|
| 203 |
|
| 204 |
-
|
| 205 |
-
Technology and Sales Associate Training to Drive
|
| 206 |
-
In-Store Conversions
|
| 207 |
|
| 208 |
-
|
| 209 |
-
|
|
|
|
| 210 |
|
| 211 |
-
|
| 212 |
|
| 213 |
-
|
| 214 |
|
| 215 |
-
|
| 216 |
|
| 217 |
-
|
| 218 |
|
| 219 |
-
|
| 220 |
|
| 221 |
-
|
| 222 |
|
| 223 |
-
|
| 224 |
-
|
| 225 |
-
|
| 226 |
-
Enhance In-Store Experiences
|
| 227 |
|
| 228 |
-
|
| 229 |
|
| 230 |
-
|
| 231 |
|
| 232 |
-
|
| 233 |
|
| 234 |
-
|
| 235 |
|
| 236 |
-
|
| 237 |
|
| 238 |
-
|
| 239 |
|
| 240 |
-
|
|
|
|
| 241 |
|
| 242 |
-
|
| 243 |
|
| 244 |
-
|
| 245 |
|
| 246 |
-
|
| 247 |
-
|
| 248 |
-
“The tools are all there
|
| 249 |
-
to integrate these
|
| 250 |
-
experiences, they just
|
| 251 |
-
aren’t always being
|
| 252 |
-
implemented. There is
|
| 253 |
-
a resistance to change,
|
| 254 |
-
because making changes
|
| 255 |
-
costs a lot of time and
|
| 256 |
-
money.”
|
| 257 |
-
|
| 258 |
-
- Jack Shaw, VP North American
|
| 259 |
-
Sales, Adaequare Inc.
|
| 260 |
-
|
| 261 |
-
The Challenge of Cross-Channel Consistency
|
| 262 |
-
|
| 263 |
-
Advances in technology – particularly mobile technology – over the past decade have
|
| 264 |
-
resulted in a rapid expansion in the variety of commercial tools available to consumers.
|
| 265 |
-
Today, consumers are increasingly engaging with brands across a variety of diverse media.
|
| 266 |
-
The customer journey has become expansive, dynamic, and multilayered; it permeates
|
| 267 |
-
desktop websites, mobile-optimized sites and apps, social networks, and retail stores
|
| 268 |
-
themselves. For retailers, this has meant a multiplication of consumer touch points and
|
| 269 |
-
an unprecedented demand for innovative digital shopping tools. However, the challenge
|
| 270 |
-
for retailers is not just to develop spectacular omnichannel shopping capabilities but also
|
| 271 |
-
to deliver outstanding experiences across all channels. When it comes to omnichannel
|
| 272 |
-
customer experiences, consistency is key.
|
| 273 |
-
|
| 274 |
-
Delivering consistently great customer experiences in-store and online can be a profound
|
| 275 |
-
challenge for retail businesses. In this study, only 16% of respondents said that their
|
| 276 |
-
customer experiences are very consistent between their stores and online presence.
|
| 277 |
-
The majority (60%) of those surveyed noted that their experiences are only somewhat
|
| 278 |
-
consistent. In their quest to provide a great customer experience, these retailers are facing
|
| 279 |
-
many complex challenges, including creating consistency across channels, personalizing
|
| 280 |
-
the experience, capturing and applying relevant customer data, and the implementation
|
| 281 |
-
of customer experience initiatives across store locations.
|
| 282 |
-
|
| 283 |
-
Although the retailer perspective is an important indicator of the state of shopping
|
| 284 |
-
experiences, an even more critical measure is how consumers perceive those experiences.
|
| 285 |
-
Unfortunately, the way retailers view their shopping experience can differ greatly from
|
| 286 |
-
consumers’ perspectives. For instance, in a Bain & Co. customer experience survey,
|
| 287 |
-
80% of companies stated that they were delivering a “superior experience” to their
|
| 288 |
-
customers. However, consumers in the survey said that only 8% of companies were
|
| 289 |
-
actually delivering high-quality experiences. This discrepancy underlines how critical it is
|
| 290 |
-
for retailers to listen to their customers, especially when it comes to experiences.
|
| 291 |
-
|
| 292 |
-
Without a doubt, modern retail businesses must have an omnichannel vision in order
|
| 293 |
-
to adapt to the changes in consumer shopping patterns brought on by technological
|
| 294 |
-
advances. In part, a successful omnichannel strategy demands that retailers understand
|
| 295 |
-
the key actions that consumers take during their shopping experiences, and retailers
|
| 296 |
-
must then make those actions available across multiple channels. Enabling consumers to
|
| 297 |
-
engage with multiple platforms en route to a purchase not only improves the shopping
|
| 298 |
-
experience but also increases conversion rates and reduces cart abandonment.
|
| 299 |
-
|
| 300 |
-
Two notable omnichannel shopping practices include showrooming and “buy online, pick
|
| 301 |
-
up in store” options. Showrooming, the practice of evaluating products in a store before
|
| 302 |
-
buying them online, poses a clear threat to traditional retailers, which are susceptible to
|
| 303 |
-
customers using mobile devices to compare prices while in the store. Despite the threat,
|
| 304 |
-
nearly three quarters of respondents reported that they have not seen any sort of impact
|
| 305 |
-
from showrooming. In fact, 19% noted that showrooming has had a positive impact on
|
| 306 |
-
their businesses. This is likely because omnichannel shoppers have been shown to spend
|
| 307 |
-
significantly more than single-channel shoppers. Similarly, “buy online, pick up in store”
|
| 308 |
-
options, which offer the convenience of an online transaction alongside the satisfaction
|
| 309 |
-
of instantly picking up an item, are expanding although only 26% of respondents
|
| 310 |
-
currently have fully-deployed programs.
|
| 311 |
|
| 312 |
-
|
| 313 |
|
| 314 |
-
|
| 315 |
-
between in-store and online?
|
| 316 |
|
| 317 |
-
|
| 318 |
|
| 319 |
-
|
| 320 |
|
| 321 |
-
|
| 322 |
|
| 323 |
-
|
| 324 |
-
Online Experiences Are Somewhat Consistent
|
| 325 |
|
| 326 |
-
|
| 327 |
-
great customer experience?
|
| 328 |
|
| 329 |
-
|
| 330 |
-
experiences across
|
| 331 |
-
channels
|
| 332 |
|
| 333 |
-
|
| 334 |
|
| 335 |
-
|
| 336 |
-
experiences
|
| 337 |
|
| 338 |
-
|
| 339 |
|
| 340 |
-
|
| 341 |
-
customer data
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| 342 |
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| 343 |
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| 344 |
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| 345 |
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| 346 |
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initiatives across
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| 347 |
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stores
|
| 348 |
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| 349 |
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| 350 |
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Customer Experience, with No Single Obstacle
|
| 351 |
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Standing Out Above the Rest
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| 352 |
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| 353 |
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| 354 |
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change
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| 365 |
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| 367 |
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are leveraging it to
|
| 368 |
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drive sales
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| 369 |
|
| 370 |
-
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| 371 |
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hurting our sales
|
| 372 |
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| 373 |
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| 374 |
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Yet Felt the Effects of Showrooming
|
| 375 |
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| 376 |
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| 377 |
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in store” option?
|
| 378 |
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| 379 |
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deployed program
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| 383 |
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| 387 |
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| 388 |
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| 389 |
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Currently Offer Some Sort of Option to Buy
|
| 390 |
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Products Online and Pick Them Up In-Store
|
| 391 |
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| 392 |
8
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| 395 |
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| 398 |
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|
| 399 |
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collected in their stores. Using BLE beacons, location-based mobile services, loyalty programs,
|
| 400 |
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promotions, and sales trends, merchants can uncover valuable data on the in-store customer
|
| 401 |
-
experience. This data can then help them track traffic patterns, evaluate how customers are
|
| 402 |
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interacting with displays, and determine which promotions and marketing messages are
|
| 403 |
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having the greatest impact. In other words, these insights lead to optimized stores, improved
|
| 404 |
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marketing campaigns, and more effective omnichannel commerce interfaces.
|
| 405 |
|
| 406 |
-
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| 407 |
-
|
| 408 |
-
|
| 409 |
-
|
| 410 |
-
personalization indicates that most retailers are missing major opportunities to reap the many
|
| 411 |
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benefits of in-store data insights.
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| 412 |
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9
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| 435 |
|
| 436 |
-
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| 437 |
-
|
| 438 |
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|
| 439 |
-
|
| 440 |
-
|
| 441 |
-
shopping is where the
|
| 442 |
-
real opportunity lies for
|
| 443 |
-
retailers to make their
|
| 444 |
-
store a better place to
|
| 445 |
-
shop. It is gradually
|
| 446 |
-
becoming clear: the
|
| 447 |
-
stores that make proper
|
| 448 |
-
use of mobile wallets
|
| 449 |
-
are the ones who will
|
| 450 |
-
come out on top in the
|
| 451 |
-
modern retail era.”
|
| 452 |
|
| 453 |
-
|
| 454 |
-
Retail
|
| 455 |
|
| 456 |
-
|
| 457 |
-
targeting of your current marketing activities?
|
| 458 |
|
| 459 |
-
|
| 460 |
|
| 461 |
-
and
|
| 462 |
|
| 463 |
-
|
| 464 |
-
personalized
|
| 465 |
|
| 466 |
-
|
| 467 |
-
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|
|
|
|
| 468 |
|
| 469 |
-
|
| 470 |
|
| 471 |
-
|
| 472 |
-
Targeting Their Marketing Messages, but There
|
| 473 |
-
Is Still Room for Improvement
|
| 474 |
|
| 475 |
-
|
| 476 |
|
| 477 |
-
|
| 478 |
-
omnichannel execution has become the bedrock of modern retail strategy. In fact, the
|
| 479 |
-
intersections between physical and digital retail channels have become so extensive that
|
| 480 |
-
many companies are no longer differentiating between sales made in stores and those
|
| 481 |
-
made digitally. As Saks Inc. CEO Stephen Sadove has said, “There is so much integration
|
| 482 |
-
between store and online sales that we can’t report the numbers separately. [That just
|
| 483 |
-
doesn’t] make sense, because we are moving inventory from one to another all the time.”
|
| 484 |
|
| 485 |
-
|
| 486 |
-
New devices, online offerings, and digital touch points are the engines of retail growth
|
| 487 |
-
because they streamline shopping experiences across channels and engage consumers on
|
| 488 |
-
their own terms. Novel technologies also enable businesses to gather a massive amount
|
| 489 |
-
of customer data, which can then be used to personalize marketing messages and shift
|
| 490 |
-
inventory to the right places. However, given the abundance of tools and technologies
|
| 491 |
-
available, choosing the right solutions can prove challenging. The best brands are those
|
| 492 |
-
that cut through unessential capabilities and focus only on those that add significant
|
| 493 |
-
value to the customer experience.
|
| 494 |
|
| 495 |
-
|
| 496 |
-
collect data in stores will inevitably change over time. As a result, which capabilities will
|
| 497 |
-
be at the center of the stores of the future? Despite the relatively wide utilization of QR
|
| 498 |
-
codes in retail stores, 61% of those surveyed said that they believe that QR codes will
|
| 499 |
-
disappear on the next 2-5 years. In contrast, 71% of respondents indicated anticipation
|
| 500 |
-
that mobile wallet capabilities will become standard over the same time period. In many
|
| 501 |
-
cases, the utilization of a given capability will not just depend on how sophisticated a
|
| 502 |
-
technology is but also on how that technology can be leveraged during a customer’s
|
| 503 |
|
| 504 |
-
|
| 505 |
|
| 506 |
-
|
| 507 |
|
| 508 |
-
|
| 509 |
-
process and mitigate one possible obstacle to a purchase while also enhancing customer
|
| 510 |
-
loyalty programs by capturing more data and improving incentives.
|
| 511 |
|
| 512 |
-
|
| 513 |
-
Mike Wittenstein, Retail Customer Experience Strategist and Designer, Storyminers, some
|
| 514 |
-
of the most successful retail technologies are the least intrusive and most intuitive for
|
| 515 |
-
consumers to interact with. This is the principle of Invisible Design: the less intrusive and
|
| 516 |
-
more streamlined a technology is, the more likely it is to become widely adopted.
|
| 517 |
|
| 518 |
-
|
| 519 |
-
next 2-5 years?
|
| 520 |
|
| 521 |
-
|
| 522 |
|
| 523 |
-
|
| 524 |
|
| 525 |
-
|
| 526 |
|
| 527 |
-
|
| 528 |
|
| 529 |
-
|
| 530 |
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| 531 |
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| 532 |
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| 533 |
-
|
| 534 |
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| 535 |
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|
| 536 |
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-
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| 547 |
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| 548 |
-
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|
| 549 |
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| 550 |
-
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|
| 551 |
|
| 552 |
-
|
|
|
|
| 553 |
|
| 554 |
-
|
| 555 |
|
| 556 |
-
|
| 557 |
-
standard practice in the next 2-5 years?
|
| 558 |
|
| 559 |
-
|
| 560 |
|
| 561 |
-
|
|
|
|
| 562 |
|
| 563 |
-
|
| 564 |
|
| 565 |
-
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|
| 566 |
|
| 567 |
-
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|
| 568 |
|
| 569 |
-
|
| 570 |
-
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|
| 571 |
|
| 572 |
-
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|
| 573 |
|
| 574 |
-
|
|
|
|
| 575 |
|
| 576 |
-
|
| 577 |
-
70
|
| 578 |
-
50
|
| 579 |
-
Becoming Standard over the next 2-5 Years
|
| 580 |
|
| 581 |
-
|
| 582 |
|
| 583 |
-
|
| 584 |
|
| 585 |
-
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|
| 586 |
|
| 587 |
-
|
| 588 |
|
| 589 |
-
|
| 590 |
|
| 591 |
-
|
| 592 |
|
| 593 |
-
|
| 594 |
|
| 595 |
-
|
| 596 |
|
| 597 |
-
|
| 598 |
-
Which retailers do you believe are providing the
|
| 599 |
-
most exceptional in-store experiences?
|
| 600 |
|
| 601 |
1
|
| 602 |
|
|
@@ -604,283 +493,476 @@ most exceptional in-store experiences?
|
|
| 604 |
|
| 605 |
3
|
| 606 |
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|
| 607 |
4
|
| 608 |
|
| 609 |
-
|
| 610 |
|
| 611 |
-
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|
| 612 |
|
| 613 |
-
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|
| 614 |
|
| 615 |
-
|
| 616 |
|
| 617 |
-
|
| 618 |
|
| 619 |
-
|
|
|
|
| 620 |
|
| 621 |
-
|
| 622 |
-
Retailers Providing Exceptional In-Store
|
| 623 |
-
Experiences
|
| 624 |
|
| 625 |
-
|
|
|
|
|
|
|
| 626 |
|
| 627 |
-
|
|
|
|
| 628 |
|
| 629 |
-
|
| 630 |
-
|
| 631 |
-
|
| 632 |
-
sales asset than associates.
|
| 633 |
|
| 634 |
-
|
| 635 |
-
|
| 636 |
-
As those tools become more sophisticated, they may eventually supersede sales
|
| 637 |
-
associates as the greatest in-store revenue drivers.
|
| 638 |
|
| 639 |
-
|
| 640 |
-
|
| 641 |
-
|
| 642 |
-
|
| 643 |
-
|
| 644 |
|
| 645 |
-
|
| 646 |
-
|
| 647 |
-
for information, goods, and services on an ongoing basis) and time of awareness to
|
| 648 |
-
time of satisfaction (i.e., how long it takes for a customer to acquire a good or service
|
| 649 |
-
from the time they become aware of it). Improving involvement and shortening the
|
| 650 |
-
time of awareness to time of satisfaction are becoming central objectives for businesses.
|
| 651 |
|
| 652 |
-
|
| 653 |
-
how well businesses are learning from and
|
| 654 |
-
listening to customers.
|
| 655 |
|
| 656 |
-
|
| 657 |
-
|
| 658 |
-
source of these inputs, which enable organizations to optimize their offerings and
|
| 659 |
-
create personalized marketing messages.
|
| 660 |
|
| 661 |
-
|
| 662 |
-
the
|
| 663 |
-
|
| 664 |
-
|
| 665 |
-
|
| 666 |
-
without detracting from the overall experience. Many retailers are struggling with this
|
| 667 |
-
cross-channel consistency, highlighting the need for them to critically evaluate how they
|
| 668 |
-
interact with customers on different media.
|
| 669 |
|
| 670 |
-
|
| 671 |
-
|
| 672 |
-
out anachronistic elements.
|
| 673 |
|
| 674 |
-
|
| 675 |
-
revenue, companies must replace outmoded elements with the right technologies,
|
| 676 |
-
particularly digital tools that enhance product interactions and capture key data points.
|
| 677 |
-
This requires constant re-evaluation and, occasionally, reinvention of store components
|
| 678 |
|
| 679 |
-
|
|
|
|
| 680 |
|
| 681 |
-
|
| 682 |
|
| 683 |
-
|
| 684 |
-
For this report, Worldwide Business Research conducted in person and online surveys
|
| 685 |
-
of 104 store, operations, IT, cross-channel, and retail customer experience executives
|
| 686 |
-
representing 14 industries (see Appendix B for demographic information). Survey
|
| 687 |
-
participants included decision-makers and executives with responsibility for their
|
| 688 |
-
businesses’ in-store and digital experiences and performance. In-person surveys and
|
| 689 |
-
interviews were conducted on-site at the 2014 Future Stores Conference. Data was
|
| 690 |
-
collected in June of 2014.
|
| 691 |
|
| 692 |
-
|
| 693 |
|
| 694 |
-
|
| 695 |
|
| 696 |
-
|
| 697 |
|
| 698 |
-
|
| 699 |
|
| 700 |
-
|
| 701 |
|
| 702 |
-
|
| 703 |
|
| 704 |
-
|
| 705 |
|
| 706 |
-
|
| 707 |
|
| 708 |
-
|
| 709 |
|
| 710 |
-
|
| 711 |
|
| 712 |
-
|
| 713 |
-
Appliances
|
| 714 |
|
| 715 |
-
|
| 716 |
|
| 717 |
-
|
| 718 |
|
| 719 |
-
|
| 720 |
|
| 721 |
-
|
| 722 |
|
| 723 |
-
|
| 724 |
|
| 725 |
-
|
| 726 |
|
| 727 |
-
|
| 728 |
|
| 729 |
-
|
|
|
|
|
|
|
| 730 |
|
| 731 |
-
|
| 732 |
|
| 733 |
-
|
| 734 |
|
| 735 |
-
|
| 736 |
|
| 737 |
-
|
| 738 |
|
| 739 |
-
|
| 740 |
|
| 741 |
-
|
| 742 |
|
| 743 |
-
|
| 744 |
|
| 745 |
-
|
| 746 |
|
| 747 |
-
|
| 748 |
|
| 749 |
-
|
| 750 |
-
Experience
|
| 751 |
|
| 752 |
-
|
| 753 |
|
| 754 |
-
|
| 755 |
|
| 756 |
-
|
| 757 |
|
| 758 |
-
|
| 759 |
|
| 760 |
-
|
| 761 |
|
| 762 |
-
|
| 763 |
|
| 764 |
-
|
| 765 |
|
| 766 |
-
|
| 767 |
|
| 768 |
-
|
| 769 |
|
| 770 |
-
|
| 771 |
|
| 772 |
-
|
| 773 |
|
| 774 |
-
|
| 775 |
|
| 776 |
-
|
| 777 |
|
| 778 |
-
|
| 779 |
|
| 780 |
-
|
| 781 |
|
| 782 |
-
|
| 783 |
-
It was very well executed,
|
| 784 |
-
and I have taken a lot
|
| 785 |
-
of information from the
|
| 786 |
-
event that we will be
|
| 787 |
-
working to implement in
|
| 788 |
-
our stores.”
|
| 789 |
|
| 790 |
-
|
| 791 |
-
Merchandiser, Coastal.com
|
| 792 |
|
| 793 |
-
|
| 794 |
|
| 795 |
-
|
| 796 |
-
strategies. From omnichannel marketing and customer analytics to retail technology
|
| 797 |
-
and store operations, Future Stores will show you how to design and implement
|
| 798 |
-
winning in-store strategies to beat the competition and boost customer loyalty.
|
| 799 |
|
| 800 |
-
|
| 801 |
-
and customer experience executives to bridge the gap between the store experience
|
| 802 |
-
and the digital experience. Future Stores provides tactical strategies for brick and
|
| 803 |
-
mortar retailers to improve and increase conversion rates in-store as well as make the
|
| 804 |
-
store and cross-channel shopping experiences as seamless and easy as they are online.
|
| 805 |
|
| 806 |
-
|
| 807 |
|
| 808 |
-
|
| 809 |
-
CFI Group provides a technology platform that leverages the science of the American
|
| 810 |
-
Customer Satisfaction Index (ACSI). This platform continuously measures the customer
|
| 811 |
-
experience across multiple channels, benchmarks performance, and prioritizes
|
| 812 |
-
improvements for maximum impact.
|
| 813 |
|
| 814 |
-
|
| 815 |
-
global clients from a network of offices worldwide. Our clients span a variety of
|
| 816 |
-
industries, including financial services, hospitality, manufacturing, telecom, retail, and
|
| 817 |
-
government. Regardless of your industry, we can put the power of our technology and
|
| 818 |
-
the science of the ACSI methodology to work for you.
|
| 819 |
|
| 820 |
-
|
| 821 |
-
625 Avis Drive
|
| 822 |
-
Ann Arbor, MI 48108
|
| 823 |
-
(734) 930-9090
|
| 824 |
-
Askcfi@cfigroup.com
|
| 825 |
|
| 826 |
-
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|
| 827 |
|
| 828 |
-
|
| 829 |
-
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|
|
|
|
| 830 |
|
| 831 |
-
|
| 832 |
-
|
| 833 |
-
|
| 834 |
-
competitors on the quality of the events we produce and the relationships we nurture
|
| 835 |
-
with both attendees and sponsors.
|
| 836 |
|
| 837 |
-
|
| 838 |
-
|
| 839 |
-
|
| 840 |
-
|
| 841 |
-
|
| 842 |
|
| 843 |
-
|
| 844 |
-
division, WBR Digital, connects solutions providers to their target audiences with
|
| 845 |
-
digital branding and engagement services and lead generation campaigns. WBR’s
|
| 846 |
-
marketers act as an extension of your team, relieving strain on your internal resources
|
| 847 |
-
while engaging with customers and prospects on your brand and solutions. Solutions
|
| 848 |
-
providers can target identified accounts or relevant industry/function segments of WBR’s
|
| 849 |
-
global database of senior-level decision makers.
|
| 850 |
|
| 851 |
-
|
| 852 |
-
Andrew Cole
|
| 853 |
-
Digital Content Manager
|
| 854 |
-
646-200-7541
|
| 855 |
-
Andrew.Cole@wbresearch.com
|
| 856 |
|
| 857 |
-
|
| 858 |
-
Future Stores Conference
|
| 859 |
|
| 860 |
-
|
| 861 |
|
| 862 |
-
|
| 863 |
|
| 864 |
-
|
| 865 |
-
1.888.482.6012, or email us at futurestores@wbresearch.com
|
| 866 |
|
| 867 |
-
|
| 868 |
|
| 869 |
-
|
| 870 |
|
| 871 |
-
|
| 872 |
-
action rapidly, is the ultimate competitive advantage.” - Jack Welch
|
| 873 |
|
| 874 |
-
|
| 875 |
-
|
| 876 |
-
|
| 877 |
-
content team and helps us to improve.
|
| 878 |
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| 879 |
-
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| 880 |
-
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| 881 |
|
| 882 |
-
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| 883 |
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| 884 |
18
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| 885 |
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| 886 |
-
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|
| 1 |
+
Becoming a
|
| 2 |
+
data-driven
|
| 3 |
+
organization
|
| 4 |
|
| 5 |
+
The what, why and how
|
|
|
|
| 6 |
|
| 7 |
+
Ongoing digitization is turning everything into data, forcing
|
| 8 |
|
| 9 |
+
Technological advancements in data analytics are, however,
|
| 10 |
|
| 11 |
+
companies to become more data-driven. While the benefits of
|
| 12 |
|
| 13 |
+
making it possible for any type of company in every industry to
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
|
| 15 |
+
the data-driven organisation are clear (improved performance,
|
|
|
|
| 16 |
|
| 17 |
+
become data-driven.
|
|
|
|
| 18 |
|
| 19 |
+
more profitability, stronger innovations), there are still some
|
|
|
|
| 20 |
|
| 21 |
+
Discover the basic do’s and don’ts in ‘Becoming a data-driven
|
| 22 |
|
| 23 |
+
technical and business challenges to overcome.
|
| 24 |
|
| 25 |
+
organisation: the what, why and how’.
|
| 26 |
|
| 27 |
+
Table of contents
|
| 28 |
|
| 29 |
+
1
|
| 30 |
|
| 31 |
+
Why become
|
| 32 |
+
data-driven?
|
| 33 |
|
| 34 |
+
You may not have noticed, but everything around us has
|
|
|
|
|
|
|
| 35 |
|
| 36 |
+
turned into data. Not just our cars or mobile phones, a
|
|
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|
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|
|
|
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|
|
|
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|
|
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|
| 37 |
|
| 38 |
+
growing number of other appliances, machines and ‘things’
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 39 |
|
| 40 |
+
are generating a constant flux of data. Where we are and
|
|
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|
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|
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|
| 41 |
|
| 42 |
+
what we do is used for marketing purposes. Sensors in
|
|
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|
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|
|
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|
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|
| 43 |
|
| 44 |
+
machines tell companies how to improve their output.
|
|
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|
|
|
|
|
|
|
|
|
|
| 45 |
|
| 46 |
+
This flood of data is transforming our world. Companies that
|
| 47 |
+
|
| 48 |
+
want to stay ahead must become data-driven.
|
| 49 |
+
|
| 50 |
+
The rise of the data-driven organisation
|
| 51 |
+
|
| 52 |
+
Many organisations worry about staying competitive in the midst of Big
|
| 53 |
+
Data, Artificial Intelligence (AI), Machine Learning or the Internet of Things
|
| 54 |
+
(IoT). Especially as many of these concepts are already generating value
|
| 55 |
+
for many companies. The glue that binds all of these together is data.
|
| 56 |
+
|
| 57 |
+
What is being data-driven all about?
|
| 58 |
+
|
| 59 |
+
Data-driven organisations process and use ever more data
|
| 60 |
+
|
| 61 |
+
As consultancy firm McKinsey says:
|
| 62 |
+
|
| 63 |
+
to improve and speed up their decision-making. The goal of
|
| 64 |
+
|
| 65 |
+
having superior analytics is having superior insights. In data-
|
| 66 |
|
| 67 |
+
driven organisations, decisions that aren’t supported by data,
|
| 68 |
+
|
| 69 |
+
are considered suspicious. Smarter analytics technologies
|
| 70 |
+
|
| 71 |
+
now enable every company to become more data-driven.
|
| 72 |
+
|
| 73 |
+
“Businesses no longer have to go on gut instinct;
|
| 74 |
+
they can use data and analytics to make faster
|
| 75 |
+
decisions and more accurate forecasts supported
|
| 76 |
+
by a mountain of evidence.”
|
| 77 |
+
|
| 78 |
+
Becoming a data-driven organization
|
| 79 |
+
|
| 80 |
+
4
|
| 81 |
+
|
| 82 |
+
Data-driven organisations
|
| 83 |
+
use analytics to become smarter:
|
| 84 |
+
|
| 85 |
+
1
|
| 86 |
+
|
| 87 |
+
They perform
|
| 88 |
+
better
|
| 89 |
+
|
| 90 |
+
The data shows where
|
| 91 |
+
they can streamline
|
| 92 |
+
their processes.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 93 |
|
| 94 |
3
|
| 95 |
|
| 96 |
+
They are more
|
| 97 |
+
profitable
|
| 98 |
+
|
| 99 |
+
Constant improvements
|
| 100 |
+
and better predictions
|
| 101 |
+
help to outsmart the
|
| 102 |
+
competition and
|
| 103 |
+
improve innovation.
|
| 104 |
|
| 105 |
+
2
|
|
|
|
|
|
|
| 106 |
|
| 107 |
+
They are
|
| 108 |
+
operationally
|
| 109 |
+
more predictable
|
| 110 |
|
| 111 |
+
Data insights fuel
|
| 112 |
+
current and future
|
| 113 |
+
decision-making.
|
| 114 |
|
| 115 |
+
These advantages make an organisation more shock-resistant and less
|
| 116 |
+
likely to be surprised by the next economy - or technology disruption.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 117 |
|
| 118 |
+
Gut feeling no longer makes the difference
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 119 |
|
| 120 |
+
Gut feeling is not good enough anymore to differentiate yourself from
|
| 121 |
+
your competitors. To be truly competitive, you will need data. Lots of
|
| 122 |
+
relevant data. Luckily, any organisation can set out on the journey to
|
| 123 |
+
become data-driven. You no longer need to be a data scientist to work
|
| 124 |
+
with data. Citizen Data Scientists are not your professional statistician or
|
| 125 |
+
trained analyst, nor your maths wizard or computer scientist, but rather
|
| 126 |
+
regular business users who create and use advanced analytical models.
|
| 127 |
|
| 128 |
+
Citizen Data Scientists are part of the ongoing wave of democratization
|
| 129 |
+
of analytics in every department. These business people have the right
|
| 130 |
+
attitude – curious, adventurous, determined – to research and improve
|
| 131 |
+
things in your organisation. They want to get their hands on the data
|
| 132 |
+
themselves and find new ways to get answers. They’re willing to learn
|
| 133 |
+
new methods and use new tools. They often think, “I don’t want to ask a
|
| 134 |
+
statistician. I want to try it myself.”
|
| 135 |
|
| 136 |
+
Becoming a data-driven organization
|
| 137 |
|
| 138 |
+
5
|
| 139 |
|
| 140 |
+
2,500 PB
|
| 141 |
|
| 142 |
+
Every day, the world creates 2,500
|
| 143 |
+
petabytes of data. In the past two years,
|
| 144 |
+
mankind has generated more data than
|
| 145 |
+
in the preceding 5,000 years combined.
|
| 146 |
|
| 147 |
+
Source: IFL Science
|
|
|
|
| 148 |
|
| 149 |
+
ZOOM-IN ON
|
| 150 |
+
SWISSCOM
|
| 151 |
|
| 152 |
+
SWITZERLAND | TELECOM | CUSTOMER SERVICE
|
| 153 |
|
| 154 |
+
7 x FASTER
|
|
|
|
| 155 |
|
| 156 |
+
CUSTOMER SERVICE DATA IS NOW PROCESSED 7X FASTER
|
| 157 |
+
MAKING IT FAR MORE USEFUL IN ISSUE SOLVING.
|
| 158 |
|
| 159 |
+
Swisscom, Switzerland’s biggest telecom operator, found that the analysis
|
| 160 |
+
of their customer service data was too slow and required too much
|
| 161 |
+
manual work. As such, it did not really help to improve customer service.
|
| 162 |
+
Through smarter text analytics, however, relationships and possible
|
| 163 |
+
solutions were shown much faster, often almost simultaneously as the
|
| 164 |
+
ongoing call center documentation evolved. Reports are now sent daily
|
| 165 |
+
instead of weekly or even monthly.
|
| 166 |
|
| 167 |
+
“We are able to create fully automated daily reports, which
|
| 168 |
+
has a direct positive effect on service quality and customer
|
| 169 |
+
satisfaction.”
|
| 170 |
|
| 171 |
+
Albert Labermeier
|
| 172 |
+
Senior Marketing Analyst at Swisscom
|
| 173 |
|
| 174 |
+
Becoming a data-driven organization
|
| 175 |
|
| 176 |
+
6
|
| 177 |
|
| 178 |
+
2
|
|
|
|
|
|
|
| 179 |
|
| 180 |
+
The road to
|
| 181 |
+
becoming
|
| 182 |
+
data-driven
|
| 183 |
|
| 184 |
+
While the benefits of becoming more data-driven are
|
| 185 |
|
| 186 |
+
apparent, in our experience, many companies are still faced
|
| 187 |
|
| 188 |
+
with a few bumps in the road. Luckily, technical advances are
|
| 189 |
|
| 190 |
+
bringing data analytics within reach of a growing number of
|
| 191 |
|
| 192 |
+
organisations.
|
| 193 |
|
| 194 |
+
Changing mindsets
|
| 195 |
|
| 196 |
+
On the road to becoming data-driven, it’s crucial for people to change
|
| 197 |
+
their mindset and organisations to change their processes. Doing so, will
|
| 198 |
+
help overcome some of these hurdles:
|
|
|
|
| 199 |
|
| 200 |
+
1
|
| 201 |
|
| 202 |
+
2
|
| 203 |
|
| 204 |
+
3
|
| 205 |
|
| 206 |
+
4
|
| 207 |
|
| 208 |
+
UNSTRUCTURED DATA
|
| 209 |
|
| 210 |
+
UNCONNECTED SYSTEMS
|
| 211 |
|
| 212 |
+
LOW DATA QUALITY OR
|
| 213 |
+
UNAVAILABLE DATA
|
| 214 |
|
| 215 |
+
MISALIGNMENT WITH IT
|
| 216 |
|
| 217 |
+
Data that is not predefined or does
|
| 218 |
|
| 219 |
+
Organisations often use multiple
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
| 220 |
|
| 221 |
+
Sometimes, the data quality simply
|
| 222 |
|
| 223 |
+
Business units shouldn’t have to
|
|
|
|
| 224 |
|
| 225 |
+
not fit the mould of traditional
|
| 226 |
|
| 227 |
+
information storage systems side by
|
| 228 |
|
| 229 |
+
isn’t good enough, because of poor
|
| 230 |
|
| 231 |
+
depend on IT for data analytics, they
|
|
|
|
| 232 |
|
| 233 |
+
data models. This includes text
|
|
|
|
| 234 |
|
| 235 |
+
side with no or difficult connections
|
|
|
|
|
|
|
| 236 |
|
| 237 |
+
data input or poorly implemented
|
| 238 |
|
| 239 |
+
should be able to run it themselves.
|
|
|
|
| 240 |
|
| 241 |
+
documents, pictures, e-mails, sensor
|
| 242 |
|
| 243 |
+
between them. These systems may
|
|
|
|
| 244 |
|
| 245 |
+
data connections. It is hard to get
|
| 246 |
|
| 247 |
+
With IT being under constant
|
|
|
|
|
|
|
| 248 |
|
| 249 |
+
data, and much more. This data
|
|
|
|
|
|
|
| 250 |
|
| 251 |
+
even offer conflicting information
|
| 252 |
|
| 253 |
+
good business intelligence from
|
| 254 |
|
| 255 |
+
pressure to keep delivering more
|
| 256 |
|
| 257 |
+
is hard to analyse for traditional
|
| 258 |
|
| 259 |
+
because they use different sources,
|
|
|
|
| 260 |
|
| 261 |
+
poor – or plain wrong – data.
|
| 262 |
|
| 263 |
+
at lower costs, your data analytics
|
|
|
|
|
|
|
| 264 |
|
| 265 |
+
analytics programs, although it
|
|
|
|
| 266 |
|
| 267 |
+
processing methods or naming
|
|
|
|
| 268 |
|
| 269 |
+
contains valuable information.
|
|
|
|
| 270 |
|
| 271 |
+
conventions.
|
| 272 |
|
| 273 |
+
requests may end up at the bottom
|
|
|
|
| 274 |
|
| 275 |
+
of their list.
|
| 276 |
|
| 277 |
+
But all of these challenges can be overcome by defining
|
| 278 |
+
a roadmap towards better data analytics.
|
| 279 |
|
| 280 |
+
Becoming a data-driven organization
|
|
|
|
|
|
|
| 281 |
|
| 282 |
8
|
| 283 |
|
| 284 |
+
ZOOM-IN ON
|
| 285 |
+
ASTRAZENECA
|
| 286 |
+
|
| 287 |
+
SWEDEN | HEALTHCARE | MANUFACTURING
|
| 288 |
+
|
| 289 |
+
VARIATIONS IN THE PRODUCTION PROCESS HAVE BEEN MINIMIZED.
|
| 290 |
|
| 291 |
+
THE CONTENT OF THE ANALYSES HAS BEEN GREATLY EXPANDED.
|
| 292 |
|
| 293 |
+
PRODUCTION CYCLES HAVE BECOME LEANER.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 294 |
|
| 295 |
+
AstraZeneca, a global pharmaceutical company, wanted to make the
|
| 296 |
+
production process for its inhalers more cost-effective and qualitative by
|
| 297 |
+
better using the production data. Not an easy task, given the system’s 1,700
|
| 298 |
+
parameters and a total data growth of 1.5 million rows per week.
|
|
|
|
|
|
|
| 299 |
|
| 300 |
+
With the proper analytics system in place, automated data management
|
| 301 |
+
for each production batch has become possible, thus allowing for quick
|
| 302 |
+
analysis throughout the manufacturing process. Between 50 and 100
|
| 303 |
+
employees – as diverse as engineers, operators and managers – now create
|
| 304 |
+
or receive reports from the system while knowledge sharing is greatly
|
| 305 |
+
facilitated.
|
| 306 |
|
| 307 |
+
“Due to the success of the program, several other products
|
| 308 |
+
from the same family which are produced in AstraZeneca’s
|
| 309 |
+
Swedish operations have now been included under the
|
| 310 |
+
system. We plan to use the same system for completely
|
| 311 |
+
different product groups as well.”
|
| 312 |
|
| 313 |
+
Henrik Åkerblom
|
| 314 |
+
Process Engineer at AstraZeneca
|
| 315 |
|
| 316 |
+
80%
|
| 317 |
|
| 318 |
+
Analysts at Gartner
|
| 319 |
+
estimate that 80% of all
|
| 320 |
+
enterprise data today is
|
| 321 |
+
unstructured
|
| 322 |
|
| 323 |
+
Source: Gartner
|
| 324 |
|
| 325 |
+
45%
|
| 326 |
+
|
| 327 |
+
According to an IDG
|
| 328 |
+
survey, 45% of business
|
| 329 |
+
leaders cite ‛unstructured
|
| 330 |
+
data’ as their single
|
| 331 |
+
biggest hurdle to
|
| 332 |
+
overcome in analytics.
|
| 333 |
+
|
| 334 |
+
Source: IDG
|
| 335 |
+
|
| 336 |
+
Becoming a data-driven organization
|
| 337 |
|
| 338 |
9
|
| 339 |
|
| 340 |
+
3
|
| 341 |
+
|
| 342 |
+
The three
|
| 343 |
+
foundations of
|
| 344 |
+
better analytics
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 345 |
|
| 346 |
+
Technological improvements within analytics platforms
|
|
|
|
| 347 |
|
| 348 |
+
enable more companies to become data-driven, as it
|
|
|
|
| 349 |
|
| 350 |
+
enables organisations to manage their data better, run more
|
| 351 |
|
| 352 |
+
complex analyses and visualize the outcome in a more
|
| 353 |
|
| 354 |
+
understandable manner. Getting the technical foundations
|
|
|
|
| 355 |
|
| 356 |
+
right puts you well on your way.
|
| 357 |
+
|
| 358 |
+
Laying the foundation
|
| 359 |
+
|
| 360 |
+
There are three foundations to becoming data-driven.
|
| 361 |
+
|
| 362 |
+
1
|
| 363 |
|
| 364 |
+
2
|
| 365 |
|
| 366 |
+
3
|
|
|
|
|
|
|
| 367 |
|
| 368 |
+
DATA MANAGEMENT
|
| 369 |
|
| 370 |
+
This is the data you use as input. A good analytics platform can process any combination of structured, semi-structured and unstructured data. Automated
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 371 |
|
| 372 |
+
connections between your analytics platform and other systems ensure that the most recent data is always available and used. While not every data point will
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 373 |
|
| 374 |
+
be crystal clear from the start, technical advances in Machine Learning and the like already automate data management, for the most part. Similarly, data inputs
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 375 |
|
| 376 |
+
and data comparisons can be automated, neatly breaking down the obstacle of handling semi- and unstructured data. By applying the right governance
|
| 377 |
|
| 378 |
+
structure, privacy rules can be applied to personally identifiable information.
|
| 379 |
|
| 380 |
+
ANALYTICS
|
|
|
|
|
|
|
| 381 |
|
| 382 |
+
Pouring over endless rows of figures and numbers is the heavy lifting of data science. By leaving this task to specialized software, you leave less room for
|
|
|
|
|
|
|
|
|
|
|
|
|
| 383 |
|
| 384 |
+
human error and create more room to actually start using the results of your analysis. Complex calculations can now be run by a click of a button, making it
|
|
|
|
| 385 |
|
| 386 |
+
available to any regular business user.
|
| 387 |
|
| 388 |
+
DATA VISUALIZATION
|
| 389 |
|
| 390 |
+
The end result of your analytical work should be smarter insights. By visualizing this in different types of graphics and charts, the outcomes become easily
|
| 391 |
|
| 392 |
+
understandable for everyone at a glance, while reports and dashboards can quickly be set up, thus opening up the insights to a growing number of people
|
| 393 |
|
| 394 |
+
across the whole organisation.
|
| 395 |
|
| 396 |
+
Becoming a data-driven organization
|
| 397 |
|
| 398 |
+
11
|
| 399 |
|
| 400 |
+
74%
|
| 401 |
|
| 402 |
+
According to a Forrester
|
| 403 |
+
study, 74% of all companies
|
| 404 |
+
would like to be more data-
|
| 405 |
+
driven, but only 29% claim
|
| 406 |
+
that they are actually good
|
| 407 |
+
at putting this idea into
|
| 408 |
+
action.
|
| 409 |
|
| 410 |
+
Source: Forrester
|
| 411 |
|
| 412 |
+
The power of analytics that everyone can use
|
| 413 |
|
| 414 |
+
These three solid foundations enable you to build an analytics platform
|
| 415 |
+
that works for everyone. This has major benefits that help eliminate the
|
| 416 |
+
obstacles on your data-driven journey.
|
| 417 |
|
| 418 |
+
You get clear, actionable results, even from imperfect or
|
| 419 |
+
unstructured data. Cleaning up your data and perfecting your input
|
| 420 |
+
models can come later.
|
| 421 |
|
| 422 |
+
Your intelligence is easy to view and understand with visuals that
|
| 423 |
+
are more captivating than any line of text could ever be.
|
| 424 |
|
| 425 |
+
Because the platform is easy to use, self-service reduces reliance on
|
| 426 |
+
IT. In turn, IT can focus more on its core business.
|
| 427 |
|
| 428 |
+
1
|
| 429 |
|
| 430 |
+
2
|
|
|
|
| 431 |
|
| 432 |
+
3
|
| 433 |
|
| 434 |
+
ZOOM-IN ON
|
| 435 |
+
RABOBANK
|
| 436 |
|
| 437 |
+
THE NETHERLANDS | BANKING | OPERATIONS
|
| 438 |
|
| 439 |
+
TRANSPARENCY THROUGHOUT THE ORGANISATION HAS
|
| 440 |
+
INCREASED. DATA VISUALIZATION ENABLES THE BANK TO PROVIDE
|
| 441 |
+
PERTINENT INFORMATION AND DIRECT CHAIN MANAGERS MORE
|
| 442 |
+
EFFECTIVELY.
|
| 443 |
|
| 444 |
+
The Rabobank Group, a leading global financial services provider serving
|
| 445 |
+
more than 10 million customers and headquartered in the Netherlands,
|
| 446 |
+
wanted to optimize its operations by improving the financial and
|
| 447 |
+
collaborative alignment across its chains. The company discovered that
|
| 448 |
+
there was a huge amount of data available from all groups of the bank’s
|
| 449 |
+
organisational chain such as departments, business units and local
|
| 450 |
+
branches, but there wasn’t one single system that could integrate and
|
| 451 |
+
structure all the information efficiently and provide the ability to share
|
| 452 |
+
results.
|
| 453 |
|
| 454 |
+
With data visualization, large amounts of data are presented visually. The
|
| 455 |
+
diverse pictorial or graphical options lead to new questions that weren’t
|
| 456 |
+
asked before. The bank is now much more flexible in its ability to provide
|
| 457 |
+
information and it can direct chain managers more effectively. At the
|
| 458 |
+
same time, employees have become more engaged because they can
|
| 459 |
+
quickly see the results of what they do.
|
| 460 |
|
| 461 |
+
“With the knowledge and access to all chain information,
|
| 462 |
+
we are able to let go of old business models and replace
|
| 463 |
+
them with more dynamic ones.”
|
| 464 |
|
| 465 |
+
John Lambrechts
|
| 466 |
+
Manager Concern Control at Rabobank
|
| 467 |
|
| 468 |
+
Becoming a data-driven organization
|
|
|
|
|
|
|
|
|
|
| 469 |
|
| 470 |
+
12
|
| 471 |
|
| 472 |
+
4
|
| 473 |
|
| 474 |
+
The
|
| 475 |
+
data-driven
|
| 476 |
+
journey
|
| 477 |
|
| 478 |
+
So where do you start your data-driven journey? Anywhere is
|
| 479 |
|
| 480 |
+
good, as long as it isn’t everywhere. A ‘big bang’ approach is
|
| 481 |
|
| 482 |
+
risky: it can overcomplicate things or may simply lack focus.
|
| 483 |
|
| 484 |
+
We recommend a step-by-step approach as the surest way
|
| 485 |
|
| 486 |
+
forward to success.
|
| 487 |
|
| 488 |
+
Plotting the course
|
|
|
|
|
|
|
| 489 |
|
| 490 |
1
|
| 491 |
|
|
|
|
| 493 |
|
| 494 |
3
|
| 495 |
|
| 496 |
+
Choose your starting point
|
| 497 |
+
|
| 498 |
+
The most important datasets have priority
|
| 499 |
+
|
| 500 |
+
Expand the reach of the platform
|
| 501 |
+
|
| 502 |
+
This can be a team (e.g. the marketing
|
| 503 |
+
department) or a specific data source. Consider
|
| 504 |
+
collecting data from your CRM system to get a
|
| 505 |
+
better insight into customer behavior, or begin
|
| 506 |
+
with productivity data from the shop-floor.
|
| 507 |
+
|
| 508 |
+
Recorded customer service calls or data from your
|
| 509 |
+
finance department could equally be your first
|
| 510 |
+
project. It is best if your starting-point is something
|
| 511 |
+
you’re already familiar with, and if you have a clear
|
| 512 |
+
goal in mind.
|
| 513 |
+
|
| 514 |
+
You must make a distinction between must-have
|
| 515 |
+
datasets that will work towards your goal and nice-
|
| 516 |
+
to-have datasets that are only loosely related.
|
| 517 |
+
|
| 518 |
+
Data may be a mix of structured, semi-structured
|
| 519 |
+
and unstructured data. Pour it all in and look at
|
| 520 |
+
what your analytics platform comes up with and
|
| 521 |
+
whether the results are actionable. Consider if
|
| 522 |
+
additional data management (e.g. data cleaning)
|
| 523 |
+
is needed or whether you can already continue
|
| 524 |
+
using the current datasets.
|
| 525 |
+
|
| 526 |
+
Once you have value-added results, you can start
|
| 527 |
+
expanding the reach of the platform within and
|
| 528 |
+
across teams. This can happen in a series of waves
|
| 529 |
+
that create more and more buy-in as the results
|
| 530 |
+
begin to show more and more benefits.
|
| 531 |
+
|
| 532 |
+
Becoming a data-driven organization
|
| 533 |
+
|
| 534 |
+
14
|
| 535 |
+
|
| 536 |
+
Start
|
| 537 |
+
|
| 538 |
+
expand
|
| 539 |
+
within the team
|
| 540 |
+
|
| 541 |
+
Scale
|
| 542 |
+
|
| 543 |
+
Grow
|
| 544 |
+
|
| 545 |
+
expand
|
| 546 |
+
beyond the team
|
| 547 |
+
|
| 548 |
+
get the entire
|
| 549 |
+
organization on-board
|
| 550 |
+
|
| 551 |
4
|
| 552 |
|
| 553 |
+
The data-driven organisation is born
|
| 554 |
|
| 555 |
+
Once you have moved from a limited number of data sources to an all-
|
| 556 |
+
encompassing data management flow; you’ve extended the reach of
|
| 557 |
+
data analytics from the few to the many and every key decision is backed
|
| 558 |
+
by data, you’ve truly become a data-driven organisation. You‘ll find that,
|
| 559 |
+
as you become better at analytics, you’ll move from hindsight to insight
|
| 560 |
|
| 561 |
+
to foresight. You’ll no longer simply look back at ‘what happened’, but
|
| 562 |
+
you’ll steer your gaze to the future. Not only can you track ROI on all
|
| 563 |
+
data-enabled projects, you can also run predictive analytics and simulate
|
| 564 |
+
‘what-if’ scenarios. The backbone of your business strategy is now
|
| 565 |
+
formed by undisputable facts.
|
| 566 |
|
| 567 |
+
Becoming a data-driven organization
|
| 568 |
|
| 569 |
+
15
|
| 570 |
|
| 571 |
+
ZOOM-IN ON
|
| 572 |
+
Eni
|
| 573 |
|
| 574 |
+
BELGIUM | ENERGY | MARKETING & OPERATIONS
|
|
|
|
|
|
|
| 575 |
|
| 576 |
+
a
|
| 577 |
+
360°
|
| 578 |
+
view
|
| 579 |
|
| 580 |
+
on your
|
| 581 |
+
customers
|
| 582 |
|
| 583 |
+
‛What-if’ scenarios, allowing them to assess the impact of strategic
|
| 584 |
+
decisions, such as changes in price or margin, reduced customer
|
| 585 |
+
churn and more.
|
|
|
|
| 586 |
|
| 587 |
+
User-friendly dashboards that help to keep an eye on the long-term
|
| 588 |
+
profitability of the entire customer base.
|
|
|
|
|
|
|
| 589 |
|
| 590 |
+
“We calculate how much the customer will spend with us
|
| 591 |
+
(revenues) and how long they will stay (retention). We also
|
| 592 |
+
predict when we might experience payment issues (credit
|
| 593 |
+
losses) with them and how much it will cost us to serve their
|
| 594 |
+
needs (service costs).”
|
| 595 |
|
| 596 |
+
Zdravka Jevtimov
|
| 597 |
+
Customer Insights Manager at Eni
|
|
|
|
|
|
|
|
|
|
|
|
|
| 598 |
|
| 599 |
+
CUSTOMER CHURN AND RETENTION CAN NOW BE PREDICTED.
|
|
|
|
|
|
|
| 600 |
|
| 601 |
+
FUTURE PROFITABILITY OF PRODUCTS, CHANNELS AND
|
| 602 |
+
SEGMENTS CAN BE BETTER EVALUATED UP FRONT.
|
|
|
|
|
|
|
| 603 |
|
| 604 |
+
Eni is an integrated energy company with operations on five continents.
|
| 605 |
+
In the highly competitive energy market, it’s crucial to build long-term
|
| 606 |
+
relationships with clients. That’s why the company continuously monitors
|
| 607 |
+
and analyses the behaviour of its entire client base throughout the
|
| 608 |
+
complete customer life cycle.
|
|
|
|
|
|
|
|
|
|
| 609 |
|
| 610 |
+
The company developed a solid and trustworthy prediction model using
|
| 611 |
+
more than 700 parameters offering Eni’s management:
|
|
|
|
| 612 |
|
| 613 |
+
Valuable information about customers
|
|
|
|
|
|
|
|
|
|
| 614 |
|
| 615 |
+
Help in evaluating the future profitability of the company’s product
|
| 616 |
+
portfolio, sales channels and customer segments
|
| 617 |
|
| 618 |
+
60%
|
| 619 |
|
| 620 |
+
56%
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 621 |
|
| 622 |
+
Analyst firm Gartner estimates that
|
| 623 |
|
| 624 |
+
According to CMO.com, best-in-
|
| 625 |
|
| 626 |
+
over half of Big Data projects at
|
| 627 |
|
| 628 |
+
class marketeers are 56% more likely
|
| 629 |
|
| 630 |
+
companies fail. One big reason for
|
| 631 |
|
| 632 |
+
to use data and analytics platforms.
|
| 633 |
|
| 634 |
+
this is that companies often want
|
| 635 |
|
| 636 |
+
However, only 19% of marketers fully
|
| 637 |
|
| 638 |
+
to do everything at once instead of
|
| 639 |
|
| 640 |
+
track all their marketing efforts with
|
| 641 |
|
| 642 |
+
focusing on smaller projects with a
|
|
|
|
| 643 |
|
| 644 |
+
data.
|
| 645 |
|
| 646 |
+
clear end goal or a quick win.
|
| 647 |
|
| 648 |
+
Source: CMO.com
|
| 649 |
|
| 650 |
+
Source: Gartner
|
| 651 |
|
| 652 |
+
Becoming a data-driven organization
|
| 653 |
|
| 654 |
+
16
|
| 655 |
|
| 656 |
+
5
|
| 657 |
|
| 658 |
+
The next level
|
| 659 |
+
in data-driven
|
| 660 |
+
work
|
| 661 |
|
| 662 |
+
Being data-driven is not an end-state. It’s the beginning of an exploration of exciting possibilities. As the pace of technology
|
| 663 |
|
| 664 |
+
innovation keeps accelerating, yesterday’s science fiction becomes today’s reality. Here are some of the elements that will fuel
|
| 665 |
|
| 666 |
+
the data-driven organisation of the future.
|
| 667 |
|
| 668 |
+
On the edge of Tomorrow
|
| 669 |
|
| 670 |
+
Edge analytics
|
| 671 |
|
| 672 |
+
Transparency
|
| 673 |
|
| 674 |
+
Security
|
| 675 |
|
| 676 |
+
IoT
|
| 677 |
|
| 678 |
+
AI
|
| 679 |
|
| 680 |
+
Supply chain
|
|
|
|
| 681 |
|
| 682 |
+
Real-time on site analytics
|
| 683 |
|
| 684 |
+
Why not be transparent with
|
| 685 |
|
| 686 |
+
Analytics can be put to work
|
| 687 |
|
| 688 |
+
With the wealth of data
|
| 689 |
|
| 690 |
+
Artificial intelligence (AI)
|
| 691 |
|
| 692 |
+
Experts can use Big Data to
|
| 693 |
|
| 694 |
+
can track consumers’ in-store
|
| 695 |
|
| 696 |
+
consumers about the huge
|
| 697 |
|
| 698 |
+
for data protection as well.
|
| 699 |
|
| 700 |
+
generated by machines, your
|
| 701 |
|
| 702 |
+
makes it possible for
|
| 703 |
|
| 704 |
+
further optimize logistics.
|
| 705 |
|
| 706 |
+
behavior and pair it with the
|
| 707 |
|
| 708 |
+
amounts of data that are
|
| 709 |
|
| 710 |
+
With advanced pattern
|
| 711 |
|
| 712 |
+
production lines could map
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 713 |
|
| 714 |
+
machines to learn from
|
|
|
|
| 715 |
|
| 716 |
+
By taking into account
|
| 717 |
|
| 718 |
+
right kind of offer bundles to
|
|
|
|
|
|
|
|
|
|
| 719 |
|
| 720 |
+
collected? Some information
|
|
|
|
|
|
|
|
|
|
|
|
|
| 721 |
|
| 722 |
+
recognition and correlating
|
| 723 |
|
| 724 |
+
out ways to become even
|
|
|
|
|
|
|
|
|
|
|
|
|
| 725 |
|
| 726 |
+
experience, adjust to new
|
|
|
|
|
|
|
|
|
|
|
|
|
| 727 |
|
| 728 |
+
circumstantial factors that
|
|
|
|
|
|
|
|
|
|
|
|
|
| 729 |
|
| 730 |
+
attract attention and capture
|
| 731 |
+
|
| 732 |
+
will always remain sensitive,
|
| 733 |
+
|
| 734 |
+
the needs of the individual.
|
| 735 |
+
|
| 736 |
+
but offering transparency
|
| 737 |
+
|
| 738 |
+
This effectively creates the
|
| 739 |
+
|
| 740 |
+
to your customers can be
|
| 741 |
+
|
| 742 |
+
segment of one.
|
| 743 |
+
|
| 744 |
+
a big win in the branding
|
| 745 |
+
|
| 746 |
+
department. According to
|
| 747 |
|
| 748 |
+
recent surveys, over 80%
|
| 749 |
+
of consumers say ethics
|
| 750 |
+
matter when they buy. With
|
| 751 |
+
the General Data Protection
|
| 752 |
|
| 753 |
+
Regulation (GDPR), adhering
|
| 754 |
+
to privacy rules has become
|
| 755 |
+
an absolute must.
|
|
|
|
|
|
|
| 756 |
|
| 757 |
+
behaviours, risks can be
|
| 758 |
+
assessed better and cyber
|
| 759 |
+
attacks or real-life security
|
| 760 |
+
threats can be prevented
|
| 761 |
+
before they even occur.
|
| 762 |
|
| 763 |
+
more productive, discover
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 764 |
|
| 765 |
+
inputs and perform human-
|
|
|
|
|
|
|
|
|
|
|
|
|
| 766 |
|
| 767 |
+
influence delivery speed and
|
|
|
|
| 768 |
|
| 769 |
+
hidden costs and unlikely
|
| 770 |
|
| 771 |
+
like tasks. AI relies heavily on
|
| 772 |
|
| 773 |
+
reliability (e.g. traffic flows,
|
|
|
|
| 774 |
|
| 775 |
+
sources of revenue. The
|
| 776 |
|
| 777 |
+
deep learning and natural
|
| 778 |
|
| 779 |
+
accidents, weather patterns,
|
|
|
|
| 780 |
|
| 781 |
+
Internet of Things (IoT) will
|
| 782 |
+
revolutionize production
|
| 783 |
+
as well as consumption
|
|
|
|
| 784 |
|
| 785 |
+
language processing.
|
| 786 |
+
Computers are ‘trained’ to
|
| 787 |
|
| 788 |
+
rain storms), smarter logistics
|
| 789 |
+
|
| 790 |
+
could even be used to
|
| 791 |
+
|
| 792 |
+
accomplish specific tasks by
|
| 793 |
+
|
| 794 |
+
operate more sustainably.
|
| 795 |
+
|
| 796 |
+
patterns. And it’s just around
|
| 797 |
+
|
| 798 |
+
processing large amounts
|
| 799 |
+
|
| 800 |
+
the corner.
|
| 801 |
+
|
| 802 |
+
of data and recognizing
|
| 803 |
+
|
| 804 |
+
patterns in that data.
|
| 805 |
+
|
| 806 |
+
Becoming a data-driven organization
|
| 807 |
|
| 808 |
18
|
| 809 |
|
| 810 |
+
ZOOM-IN ON
|
| 811 |
+
INTERAMERICAN
|
| 812 |
+
|
| 813 |
+
GREECE | INSURANCE | COMPLIANCE
|
| 814 |
+
|
| 815 |
+
BE FULLY GDPR-COMPLIANT.
|
| 816 |
+
MAKE A BIG STEP TOWARDS BECOMING A DIGITAL-ONLY INSURER.
|
| 817 |
+
|
| 818 |
+
For INTERAMERICAN, a leading insurance provider in Greece, trust
|
| 819 |
+
is crucial to retaining loyal customers. The company adopted a data
|
| 820 |
+
analytics platform to be fully compliant with the EU General Data
|
| 821 |
+
Protection Regulation (GDPR) while also supporting the company’s
|
| 822 |
+
strategic focus of transforming itself into a digital-only insurer.
|
| 823 |
+
|
| 824 |
+
Its data governance initiative improves the availability, completeness and
|
| 825 |
+
accuracy of the information and data being managed. Topics covered
|
| 826 |
+
are data ownership, data location, data access, data provenance, risk
|
| 827 |
+
assessments and proper recovery procedures in case of breaches. All vital
|
| 828 |
+
elements in helping give customers peace of mind that their personal
|
| 829 |
+
data will be safe.
|
| 830 |
+
|
| 831 |
+
“Our organisation is working to transition to the new digital
|
| 832 |
+
age and create long-term, trust-based relationships with our
|
| 833 |
+
customers. SAS for Data Protection helps us work towards
|
| 834 |
+
compliance with the requirements of the new regulation
|
| 835 |
+
and foster customer trust.”
|
| 836 |
+
|
| 837 |
+
Xenophon Liapakis
|
| 838 |
+
CIO at INTERAMERICAN
|
| 839 |
+
|
| 840 |
+
41%
|
| 841 |
+
|
| 842 |
+
According to a CFI Group
|
| 843 |
+
survey, 41% of all consumers
|
| 844 |
+
use mobile apps while
|
| 845 |
+
shopping. For Millennials, this
|
| 846 |
+
figure even rises to 67%. 51%
|
| 847 |
+
of those polled said they would
|
| 848 |
+
be likely to use apps if they
|
| 849 |
+
made the shopping experience
|
| 850 |
+
easier and faster.
|
| 851 |
+
|
| 852 |
+
Source: CFI Group
|
| 853 |
+
|
| 854 |
+
Over half of organisations
|
| 855 |
+
surveyed by IDG say that
|
| 856 |
+
they are already deploying
|
| 857 |
+
analytics to detect cyber
|
| 858 |
+
attacks, denial-of-service
|
| 859 |
+
attacks and phishing.
|
| 860 |
+
However, 59% among them
|
| 861 |
+
still said they have been
|
| 862 |
+
compromised at least once
|
| 863 |
+
per month “because they
|
| 864 |
+
were not able to keep up
|
| 865 |
+
and fully analyse the data.”
|
| 866 |
+
|
| 867 |
+
Source: IDG
|
| 868 |
+
|
| 869 |
+
According to Accenture
|
| 870 |
+
research, using Big Data
|
| 871 |
+
analytics had a net positive
|
| 872 |
+
impact on customer service
|
| 873 |
+
and demand fulfilment
|
| 874 |
+
for nearly half of all supply
|
| 875 |
+
chain experts polled.
|
| 876 |
+
Other advantages listed
|
| 877 |
+
included greater supply
|
| 878 |
+
chain integration (36%),
|
| 879 |
+
productivity improvements
|
| 880 |
+
(33%) and improved cost to
|
| 881 |
+
serve (28%).
|
| 882 |
+
|
| 883 |
+
Source: Accenture
|
| 884 |
+
|
| 885 |
+
46%
|
| 886 |
+
|
| 887 |
+
53%
|
| 888 |
+
|
| 889 |
+
Becoming a data-driven organization
|
| 890 |
+
|
| 891 |
+
19
|
| 892 |
+
|
| 893 |
+
6
|
| 894 |
+
|
| 895 |
+
Getting in
|
| 896 |
+
on the action
|
| 897 |
+
|
| 898 |
+
Becoming a data-driven organisation is now within reach
|
| 899 |
+
of every company. Cloud solutions have made access to
|
| 900 |
+
data analytics platforms much easier: software-as-a-service
|
| 901 |
+
(SaaS) enables organisations to no longer build and
|
| 902 |
+
maintain everything on premise but rent this for as long as
|
| 903 |
+
needed. And with Results-as-a-Service (RaaS), it becomes
|
| 904 |
+
even possible to completely ‘outsource’ your analytics.
|
| 905 |
+
If you do not have tools and expertise to turn data into
|
| 906 |
+
insights, you can still get results.
|
| 907 |
+
Your organization provides the data and the business
|
| 908 |
+
problem to be solved, and RaaS delivers results you can
|
| 909 |
+
act on.
|
| 910 |
+
|
| 911 |
+
By starting your data-driven journey in one specific area
|
| 912 |
+
of your company, clearly defining your path towards data
|
| 913 |
+
analytics, adopting the right mindset and technologies,
|
| 914 |
+
and gradually extending the reach and impact throughout
|
| 915 |
+
your company, you too can become the type of data-driven
|
| 916 |
+
company that is ready for tomorrow’s challenges.
|
| 917 |
+
Start your data-driven journey now and, in no time, you’ll
|
| 918 |
+
find yourself wondering: ‘How on earth did we run our
|
| 919 |
+
business without analytics?’
|
| 920 |
+
|
| 921 |
+
Becoming a data-driven organization
|
| 922 |
+
|
| 923 |
+
21
|
| 924 |
+
|
| 925 |
+
Learn more about the what, why and how of
|
| 926 |
+
becoming a data-driven organisation
|
| 927 |
+
|
| 928 |
+
Read more
|
| 929 |
+
|
| 930 |
+
Follow us:
|
| 931 |
+
|
| 932 |
+
For more information, contact us
|
| 933 |
+
|
| 934 |
+
SOURCES
|
| 935 |
+
|
| 936 |
+
https://www.cio.com/article/3204131/analytics/intelligent-analytics-fuels-faster-smarter-decision-making.html
|
| 937 |
+
|
| 938 |
+
http://www.gartner.com/newsroom/id/3130017
|
| 939 |
+
|
| 940 |
+
https://www.retailcustomerexperience.com/news/report-says-most-millennials-are-using-mobile-retail-apps/?utm_source=NetWorld%20Alliance&utm_
|
| 941 |
+
|
| 942 |
+
medium=email&utm_campaign=EMNARCE07022014
|
| 943 |
+
|
| 944 |
+
http://www.sustainablebrands.com/news_and_views/stakeholder_trends_insights/sustainable_brands/study_81_consumers_say_they_will_make_
|
| 945 |
+
|
| 946 |
+
http://www.cmo.com/features/articles/2016/5/31/15-mind-blowing-stats-about-data-driven-marketing.html#gs.uH3Iceg
|
| 947 |
+
|
| 948 |
+
https://www.csoonline.com/article/3139923/security/how-big-data-is-improving-cyber-security.html
|
| 949 |
+
|
| 950 |
+
https://www.forbes.com/sites/louiscolumbus/2015/07/13/ten-ways-big-data-is-revolutionizing-supply-chain-management/#53f4e2769f59
|
| 951 |
+
|
| 952 |
+
https://www.shopify.com/enterprise/94678726-the-need-for-speed-why-customer-service-needs-to-be-faster-than-ever
|
| 953 |
+
|
| 954 |
+
https://reprints.forrester.com/#/assets/2/202/’RES127061’/reports
|
| 955 |
+
|
| 956 |
+
https://www.sas.com/nl_nl/training/citizen-data-scientist.html
|
| 957 |
+
|
| 958 |
+
https://www.sas.com/en_us/insights/articles/analytics/how-to-find-and-equip-citizen-data-scientists.html
|
| 959 |
+
|
| 960 |
+
https://www.forbes.com/sites/forbestechcouncil/2017/06/05/the-big-unstructured-data-problem/#28e176dd493a
|
| 961 |
+
|
| 962 |
+
SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration.
|
| 963 |
+
Other brand and product names are trademarks of their respective companies. Copyright © 2017, SAS Institute Inc. All rights reserved. 109150_G66177.1117
|
| 964 |
+
|
| 965 |
+
Becoming a data-driven organization
|
| 966 |
+
|
| 967 |
+
22
|
| 968 |
+
|
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Eight easy steps to develop your
|
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|
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2
|
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|
| 48 |
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|
| 49 |
|
| 50 |
-
|
| 51 |
-
that Really Matter—and
|
| 52 |
-
How to Track Them
|
| 53 |
|
| 54 |
-
|
| 55 |
|
| 56 |
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|
| 57 |
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|
| 59 |
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The
|
| 60 |
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| 61 |
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| 62 |
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|
| 63 |
|
| 64 |
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The
|
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-
|
| 66 |
-
|
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|
| 68 |
-
|
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|
| 69 |
|
| 70 |
-
|
| 71 |
-
|
| 72 |
-
Measurable
|
| 73 |
-
|
| 74 |
-
Attainable
|
| 75 |
-
|
| 76 |
-
Relevant
|
| 77 |
-
|
| 78 |
-
Time-bound
|
| 79 |
-
|
| 80 |
-
An example of a SMART goal for your business might be "Grow our Instagram
|
| 81 |
-
audience by 50 new followers per week."
|
| 82 |
-
|
| 83 |
-
With SMART goals, you’ll make sure your goals actually lead to real business
|
| 84 |
-
results, rather than just lofty ideals.
|
| 85 |
-
|
| 86 |
-
GUIDE / Social Media Marketing Strategy
|
| 87 |
|
| 88 |
3
|
| 89 |
|
| 90 |
-
|
| 91 |
-
|
| 92 |
-
|
| 93 |
-
track, it’s hard to prove their real value for your business. Instead, focus on
|
| 94 |
-
targets such as leads generated, web referrals, and conversion rate.
|
| 95 |
-
|
| 96 |
-
You may want to track different goals for different channels, or even different uses
|
| 97 |
-
of each channel. For example, you can use paid campaigns to increase brand
|
| 98 |
-
awareness, but measure acquisition and engagement for organic social posts.
|
| 99 |
-
|
| 100 |
-
Make sure to align your social media goals with your overall marketing
|
| 101 |
-
strategy. This will make it easier for you to show the value of your work and
|
| 102 |
-
get executive buy-in and investment.
|
| 103 |
-
|
| 104 |
-
Start developing your social media marketing plan by writing down at least
|
| 105 |
-
three social media goals.
|
| 106 |
-
|
| 107 |
-
Goals
|
| 108 |
-
|
| 109 |
-
1.
|
| 110 |
-
|
| 111 |
-
2.
|
| 112 |
-
|
| 113 |
-
3.
|
| 114 |
-
|
| 115 |
-
Step 2
|
| 116 |
-
|
| 117 |
-
Related resource
|
| 118 |
-
|
| 119 |
-
How to build audience
|
| 120 |
-
personas
|
| 121 |
-
|
| 122 |
-
Learn everything you can about your audience
|
| 123 |
-
|
| 124 |
-
if you’re not engaged in social media listening, you’re creating your business
|
| 125 |
-
strategy with blinders on—and you’re missing out on mountains of actionable
|
| 126 |
-
insights from real people who are actively talking about you or your industry online.
|
| 127 |
-
|
| 128 |
-
Here’s how to start listening and building your understanding of your
|
| 129 |
-
audience and their needs.
|
| 130 |
-
|
| 131 |
-
Create audience personas
|
| 132 |
-
|
| 133 |
-
tKnowing who your audience is and what they want to see on social is key to
|
| 134 |
-
creating content that they will like, comment on, and share. This knowledge
|
| 135 |
-
also critical for planning how to develop your social media fans into
|
| 136 |
-
customers for your business.
|
| 137 |
-
|
| 138 |
-
Try creating audience personas. For example, a retail brand might create
|
| 139 |
-
different personas based on demographics, buying motivations, common
|
| 140 |
-
buying objections, and the emotional needs of each type of customer.
|
| 141 |
-
|
| 142 |
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GUIDE / Social Media Marketing Strategy
|
| 143 |
|
| 144 |
-
|
| 145 |
|
| 146 |
-
|
| 147 |
-
might not respond to Facebook ads with sales. But they might respond to
|
| 148 |
-
Facebook ads with exclusive in-store events to be the first to see a new line of
|
| 149 |
-
clothing. With personas, you’ll have the customer insights you need to create
|
| 150 |
-
campaigns that speak to the real desires and motivations of your buyers.
|
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|
| 154 |
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|
| 155 |
-
valuable information about who your followers are, where they live, which
|
| 156 |
-
languages they speak, and how they interact with your brand on social. These
|
| 157 |
-
insights allow you to refine your strategy and better target your social ads.
|
| 158 |
|
| 159 |
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|
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|
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you can learn from what they’re already doing.
|
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your audience is underserved, rather than trying to win fans away from a
|
| 183 |
-
dominant player.
|
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Watch: How to set up
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social listening streams
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GUIDE / Social Media Marketing Strategy
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Create a Facebook
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business page
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Create an Instagram
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business account
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you. Remember, it’s better to
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use fewer channels well than
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to stretch yourself thin trying
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to maintain a presence on
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every social network.
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reference guide for image
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sizes for every network.
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Set up accounts and improve existing profiles
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Decide which networks you’ll focus on, and then set up and optimize your
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Determine which networks to use (and how to use them)
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strategy for each network. For example, you might decide to use Twitter for
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customer service, Facebook for customer acquisition, and Instagram for
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engaging existing customers.
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It’s a good exercise to create mission statements for each network. These
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one-sentence declarations will help you focus on a very specific goal for
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each account on each social network.
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•• LinkedIn is where you engage existing employees and attract new talent.
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video help content.
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•• Snapchat is where you distribute content with the goal of building brand
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awareness with younger consumers.
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If you can’t create a solid mission statement for a particular social network,
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you may want to reconsider whether that network is worth it.
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Set up (and optimize) your accounts
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Once you’ve decided which networks to focus on, it’s time to create your
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profiles—or improve existing profiles so they align with your strategic plan.
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In general, make sure you fill out all profile fields, use keywords people will
|
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use to search for your business, and use images that are correctly sized for
|
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each network.
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GUIDE / Social Media Marketing Strategy
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readers, and generates profit
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•• One-third of your social content shares ideas and stories from thought
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leaders in your industry or like-minded businesses
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•• One-third of your social content involves personal interactions with your
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audience
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Once you have your calendar set, use scheduling tools or bulk scheduling to
|
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prepare your posting in advance rather than updating constantly throughout
|
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the day. This allows you to focus on crafting the language and format of your
|
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posts, rather than writing them on the fly whenever you have time.
|
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GUIDE / Social Media Marketing Strategy
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You can also use this information to test different posts, campaigns, and
|
| 492 |
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strategies against one another. Constant testing allows you to understand
|
| 493 |
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what works and what doesn’t, so you can refine your strategy in real time.
|
| 494 |
|
| 495 |
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|
| 496 |
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Ask your social media followers, email list, and website visitors whether
|
| 497 |
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you’re meeting their needs and expectations on social media. You can even
|
| 498 |
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ask them what they’d like to see more of—and then make sure to deliver on
|
| 499 |
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what they tell you.
|
| 500 |
|
| 501 |
-
|
| 502 |
-
go through significant demographic shifts. Your business will go through
|
| 503 |
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periods of change as well. All this means that your social media strategy
|
| 504 |
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should be a living document that you look at regularly and adjust as needed.
|
| 505 |
-
Refer to it often to keep you on track, but don’t be afraid to make changes
|
| 506 |
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so that it better reflects new goals, tools, or plans.
|
| 507 |
|
| 508 |
-
|
| 509 |
-
social team know, so they can all work together to help your business make
|
| 510 |
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the most of your social media accounts.
|
| 511 |
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| 512 |
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| 514 |
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| 515 |
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| 516 |
-
|
| 517 |
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strategy template
|
| 518 |
-
Does this all feel a little overwhelming? The truth is that building your social
|
| 519 |
-
media strategy is a substantial job. It should be, since it’s such an important
|
| 520 |
-
document for your business. But it doesn’t have to be complicated.
|
| 521 |
|
| 522 |
-
|
| 523 |
-
creating your social media marketing plan. Visit our blog to download it (plus
|
| 524 |
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six other social media templates that can save you hours of work).
|
| 525 |
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| 541 |
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We’re the world’s most widely used platform for managing social media.
|
| 542 |
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| 553 |
|
|
|
|
| 1 |
+
FOR PUBLICATION
|
| 2 |
|
| 3 |
+
UNITED STATES COURT OF APPEALS
|
| 4 |
+
FOR THE NINTH CIRCUIT
|
|
|
|
|
|
|
| 5 |
|
| 6 |
+
X CORP.,
|
| 7 |
|
| 8 |
+
Plaintiff - Appellant,
|
| 9 |
|
| 10 |
+
v.
|
| 11 |
|
| 12 |
+
ROBERT BONTA, in his official
|
| 13 |
+
capacity as Attorney General of
|
| 14 |
+
California,
|
| 15 |
|
| 16 |
+
Defendant - Appellee.
|
| 17 |
|
| 18 |
+
No. 24-271
|
| 19 |
|
| 20 |
+
D.C. No.
|
| 21 |
+
2:23-cv-01939-
|
| 22 |
+
WBS-AC
|
| 23 |
|
| 24 |
+
OPINION
|
| 25 |
|
| 26 |
+
Appeal from the United States District Court
|
| 27 |
+
for the Eastern District of California
|
| 28 |
+
William B. Shubb, District Judge, Presiding
|
| 29 |
|
| 30 |
+
Argued and Submitted July 17, 2024
|
| 31 |
+
San Francisco, California
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 32 |
|
| 33 |
+
Filed September 4, 2024
|
| 34 |
|
| 35 |
+
Before: MILAN D. SMITH, JR., MARK J. BENNETT,
|
| 36 |
+
and ANTHONY D. JOHNSTONE, Circuit Judges.
|
| 37 |
|
| 38 |
+
Opinion by Judge Milan D. Smith, Jr.
|
| 39 |
|
| 40 |
+
2
|
| 41 |
|
| 42 |
+
X CORP. V. BONTA
|
| 43 |
|
| 44 |
+
SUMMARY*
|
|
|
|
|
|
|
| 45 |
|
| 46 |
+
First Amendment / Social Media Platforms
|
| 47 |
|
| 48 |
+
The panel reversed the district court’s order denying
|
| 49 |
+
social media platform owner X Corp.’s motion for a
|
| 50 |
+
preliminary injunction to enjoin enforcement of California
|
| 51 |
+
Assembly Bill AB 587 (AB 587), which requires large social
|
| 52 |
+
media companies to post their terms of service and to submit
|
| 53 |
+
reports to the Attorney General of California (the State)
|
| 54 |
+
about their terms of service and their content-moderation
|
| 55 |
+
policies and practices.
|
| 56 |
|
| 57 |
+
The Content Category Report provisions of AB 587
|
| 58 |
+
require social media companies to submit to the State a
|
| 59 |
+
semiannual report detailing whether and how they define six
|
| 60 |
+
categories of content: hate speech or racism, extremism or
|
| 61 |
+
radicalization,
|
| 62 |
+
or misinformation,
|
| 63 |
+
harassment, foreign political interference, and controlled
|
| 64 |
+
substance distribution.
|
| 65 |
|
| 66 |
+
disinformation
|
| 67 |
|
| 68 |
+
The panel held that X Corp. was likely to succeed on the
|
| 69 |
+
merits of its claim that the Content Category Report
|
| 70 |
+
provisions facially violate the First Amendment. A facial
|
| 71 |
+
challenge is permissible because the Content Category
|
| 72 |
+
Report provisions raise the same First Amendment issues for
|
| 73 |
+
every social media company. The Content Category Report
|
| 74 |
+
provisions compel non-commercial speech, and are subject
|
| 75 |
+
to strict scrutiny because the provisions are content-
|
| 76 |
+
based. The Content Category Report provisions likely fail
|
| 77 |
+
strict scrutiny because they are not narrowly tailored to serve
|
| 78 |
|
| 79 |
+
* This summary constitutes no part of the opinion of the court. It has
|
| 80 |
+
been prepared by court staff for the convenience of the reader.
|
| 81 |
|
| 82 |
+
X CORP. V. BONTA
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 83 |
|
| 84 |
3
|
| 85 |
|
| 86 |
+
the State’s purported goal of requiring social media
|
| 87 |
+
companies to be transparent about their policies and
|
| 88 |
+
practices.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 89 |
|
| 90 |
+
The panel held that the remaining factors weighed in
|
| 91 |
|
| 92 |
+
favor of a preliminary injunction.
|
|
|
|
|
|
|
|
|
|
|
|
|
| 93 |
|
| 94 |
+
Accordingly, the panel reversed the district court’s
|
| 95 |
+
denial of a preliminary injunction, and remanded with
|
| 96 |
+
instructions to enter a preliminary injunction consistent with
|
| 97 |
+
the opinion and to determine whether the Content Category
|
| 98 |
+
Report provisions are severable from the remainder of AB
|
| 99 |
+
587 and, if so, which, if any, of the remaining challenged
|
| 100 |
+
provisions should also be enjoined.
|
| 101 |
|
| 102 |
+
COUNSEL
|
|
|
|
|
|
|
|
|
|
| 103 |
|
| 104 |
+
Joel L. Kurtzberg (argued), Floyd Abrams, Jason D.
|
| 105 |
+
Rozbruch, and Lisa J. Cole, Cahill Gordon & Reindel LLP,
|
| 106 |
+
New York, New York; William R. Warne and Meghan M.
|
| 107 |
+
Baker, Downey Brand LLP, Sacramento, California; for
|
| 108 |
+
Plaintiff-Appellant.
|
| 109 |
|
| 110 |
+
Gabrielle D. Boutin (argued), Deputy Attorney General;
|
| 111 |
+
Anthony R. Hakl, Supervising Deputy Attorney General;
|
| 112 |
+
Thomas S. Patterson, Senior Deputy Attorney General; Rob
|
| 113 |
+
Bonta, Attorney General of California; Office of the
|
| 114 |
+
California Attorney General, Sacramento, California; for
|
| 115 |
+
Defendant-Appellee.
|
| 116 |
|
| 117 |
+
Robert Corn-Revere and Joshua A. House, Foundation for
|
| 118 |
+
Individual Rights and Expression, Washington, D.C., for
|
| 119 |
+
Amicus Curiae Foundation for Individual Rights and
|
| 120 |
+
Expression.
|
| 121 |
|
| 122 |
+
4
|
|
|
|
| 123 |
|
| 124 |
+
X CORP. V. BONTA
|
| 125 |
|
| 126 |
+
Trenton H. Norris, Mark W. Brennan, J. Ryan Thompson,
|
| 127 |
+
Sophie Baum, and Alexander Tablan, Hogan Lovells LLP,
|
| 128 |
+
San Francisco, California; Cory L. Andrews and John M.
|
| 129 |
+
Masslon II, Washington Legal Foundation, Washington,
|
| 130 |
+
D.C.; for Amicus Curiae Washington Legal Foundation.
|
| 131 |
|
| 132 |
+
Gene C. Schaerr, Schaerr Jaffe LLP, Washington, D.C., for
|
| 133 |
+
Amici Curiae Professor Eugene Volokh and Protect the First
|
| 134 |
+
Foundation.
|
|
|
|
|
|
|
| 135 |
|
| 136 |
+
Megan L. Brown, Jeremy J. Broggi, and Boyd Garriott,
|
| 137 |
+
Wiley Rein LLP, Washington, D.C.; Jonathan D. Urick and
|
| 138 |
+
Maria C. Monaghan, United States Chamber Litigation
|
| 139 |
+
Center; Washington, D.C.; for Amicus Curiae United States
|
| 140 |
+
of America Chamber of Commerce.
|
| 141 |
|
| 142 |
+
Bruce D. Brown, Katie Townsend, Gabe Rottman, Grayson
|
| 143 |
+
Clary and Emily Hockett, Reporters Committee for Freedom
|
| 144 |
+
of the Press, Washington, D.C.; for Amicus Curiae Reporters
|
| 145 |
+
Committee for Freedom of the Press.
|
| 146 |
|
| 147 |
+
David A. Greene and Aaron Mackey, Electronic Frontier
|
| 148 |
+
Foundation, San Francisco, California, for Amicus Curiae
|
| 149 |
+
Electronic Frontier Foundation.
|
|
|
|
| 150 |
|
| 151 |
+
Jacob M. Karr, Technology Law and Policy Clinic at New
|
| 152 |
+
York University, New York, New York; G.S. Hans, Cornell
|
| 153 |
+
Law School, Ithaca, New York; for Amici Curiae First
|
| 154 |
+
Amendment and Internet Law Scholars.
|
| 155 |
|
| 156 |
+
Michelle Quist and Lauren D. Wigginton, Buchalter APC,
|
| 157 |
+
Salt Lake City, Utah; Jon M. Greenbaum, Edward G. Caspar,
|
| 158 |
+
and Marc P. Epstein, Lawyers' Committee for Civil Rights
|
| 159 |
+
Under Law, Washington, D.C.; for Amicus Curiae Lawyers'
|
| 160 |
+
Committee for Civil Rights Under Law.
|
| 161 |
|
| 162 |
+
X CORP. V. BONTA
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 163 |
|
| 164 |
5
|
| 165 |
|
| 166 |
+
Viviana M. Hanley and Nathanial I. Levy, Deputy Attorneys
|
| 167 |
+
General; Michael L. Zuckerman, Deputy Solicitor General;
|
| 168 |
+
Jeremy Feigenbaum, Solicitor General; Metthew J. Platkin,
|
| 169 |
+
Attorney General of New Jersey; Office of the New Jersey
|
| 170 |
+
Attorney General, Trenton, New Jersey; Kristin K. Mayes,
|
| 171 |
+
Attorney General of Arizona, Office of the Arizona Attorney
|
| 172 |
+
General, Phoenix, Arizona; Philip J. Weiser, Attorney
|
| 173 |
+
General of Colorado, Office of the Colorado Attorney
|
| 174 |
+
General, Denver, Colorado; William Tong, Attorney
|
| 175 |
+
General of Connecticut, Office of the Connecticut Attorney
|
| 176 |
+
General, Hartford, Connecticut; Kathleen
|
| 177 |
+
Jennings,
|
| 178 |
+
Attorney General of Delaware, Office of the Delaware
|
| 179 |
+
Attorney General, Wilmington, Delaware; Brian L.
|
| 180 |
+
Schwalb, Attorney General of the District of Columbia,
|
| 181 |
+
Office of the District of Columbia Attorney General,
|
| 182 |
+
Washington, D.C.; Kwame Raoul, Attorney General of
|
| 183 |
+
Illinois, Office of the Illinois Attorney General, Chicago,
|
| 184 |
+
Illinois; Aaron M. Frey, Attorney General of Maine, Office
|
| 185 |
+
of the Maine Attorney General, Augusta, Maine; Anthony
|
| 186 |
+
G. Brown, Attorney General of Maryland, Office of the
|
| 187 |
+
Maryland Attorney General, Baltimore, Maryland; Andrea
|
| 188 |
+
J. Campbell, Attorney General of Massachusetts, Office of
|
| 189 |
+
the Massachusetts
|
| 190 |
+
Boston,
|
| 191 |
+
Attorney
|
| 192 |
+
Massachusetts; Dana Nessel, Attorney General of Michigan,
|
| 193 |
+
Office of
|
| 194 |
+
the Michigan Attorney General, Lansing,
|
| 195 |
+
Michigan; Keith Ellison, Attorney General of Minnesota,
|
| 196 |
+
Office of the Minnesota Attorney General, St. Paul,
|
| 197 |
+
Minnesota; Aaron D. Ford, Attorney General of Nevada,
|
| 198 |
+
Office of the Nevada Attorney General, Carson City,
|
| 199 |
+
Nevada; Letitia James, Attorney General of New York,
|
| 200 |
+
Office of the New York Attorney General, New York, New
|
| 201 |
+
York; Ellen F. Rosenblum, Attorney General of Oregon,
|
| 202 |
+
Office of the Oregon Attorney General, Salem, Oregon;
|
| 203 |
+
|
| 204 |
+
General,
|
| 205 |
+
|
| 206 |
+
6
|
| 207 |
+
|
| 208 |
+
X CORP. V. BONTA
|
| 209 |
+
|
| 210 |
+
Michelle A. Henry, Attorney General of Pennsylvania,
|
| 211 |
+
Office of Harrisburg, Pennsylvania; Charity R. Clark,
|
| 212 |
+
Attorney General of Vermont, Office of the Vermont
|
| 213 |
+
Attorney General, Montpelier, Vermont; Robert M.
|
| 214 |
+
Ferguson, Attorney General of Washington, Office of the
|
| 215 |
+
Washington Attorney General, Olympia, Washington; for
|
| 216 |
+
Amici Curiae States of New Jersey, Arizona, Colorado,
|
| 217 |
+
Connecticut, Delaware, The District of Columbia, Illinois,
|
| 218 |
+
Maine, Maryland, Massachusetts, Michigan, Minnesota,
|
| 219 |
+
Nevada, New York, Oregon, Pennsylvania, Vermont, and
|
| 220 |
+
Washington.
|
| 221 |
+
|
| 222 |
+
Jason S. Harrow and Charles Gerstein, Gerstein Harrow
|
| 223 |
+
LLP, Los Angeles, California, for Amicus Curiae Institute
|
| 224 |
+
for Strategic Dialogue.
|
| 225 |
+
|
| 226 |
+
Megan Iorio and Schuyler Standley, Electronic Privacy
|
| 227 |
+
Information Center, Washington, D.C., for Amicus Curiae
|
| 228 |
+
Electronic Privacy Information Center.
|
| 229 |
+
|
| 230 |
+
Kristen G. Simplicio and Cort T. Carlson, Tycko & Zavareei
|
| 231 |
+
LLP, Washington, D.C.; John Yang, Niyati Shah, and Noah
|
| 232 |
+
Baron, Asian Americans Advancing Justice, Washington,
|
| 233 |
+
D.C.; for Amicus Curiae Asian Americans Advancing
|
| 234 |
+
Justice.
|
| 235 |
+
|
| 236 |
+
X CORP. V. BONTA
|
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|
| 237 |
|
| 238 |
7
|
| 239 |
|
| 240 |
+
OPINION
|
| 241 |
+
|
| 242 |
+
M. SMITH, Circuit Judge:
|
| 243 |
+
|
| 244 |
+
The California State Legislature enacted Assembly Bill
|
| 245 |
+
587 (AB 587) in September 2022. Cal. Bus. & Prof. Code
|
| 246 |
+
§§ 22675–81.
|
| 247 |
+
The law requires large social media
|
| 248 |
+
companies to, inter alia, post their terms of service and to
|
| 249 |
+
submit, on a semiannual basis, reports to the Attorney
|
| 250 |
+
General of California (the State) about their terms of service
|
| 251 |
+
and content-moderation policies and practices. X Corp., the
|
| 252 |
+
owner of the large social media platform X (formerly known
|
| 253 |
+
as Twitter), moved for a preliminary injunction to enjoin
|
| 254 |
+
enforcement of AB 587 on free speech and federal
|
| 255 |
+
preemption grounds. The district court denied X Corp.’s
|
| 256 |
+
motion, finding that X Corp. failed to establish a likelihood
|
| 257 |
+
of success on the merits. X Corp. appeals. For the reasons
|
| 258 |
+
below, we reverse and remand to the district court for further
|
| 259 |
+
proceedings consistent with this opinion.
|
| 260 |
+
|
| 261 |
+
FACTUAL AND PROCEDURAL BACKGROUND
|
| 262 |
+
|
| 263 |
+
AB 587 has three primary elements: (1) a requirement
|
| 264 |
+
that social media companies 1 publicly post their terms of
|
| 265 |
+
service, including processes for flagging content and
|
| 266 |
+
potential actions that may be taken with respect to flagged
|
| 267 |
+
content (Terms of Service (TOS) Posting), see Cal. Bus. &
|
| 268 |
+
Prof. Code § 22676, (2) a requirement that social media
|
| 269 |
+
|
| 270 |
+
1 AB 587 does not apply to social media companies with gross annual
|
| 271 |
+
revenues of less than $100 million, Cal. Bus. & Prof. Code § 22680, nor
|
| 272 |
+
to “an internet-based service or application for which interactions
|
| 273 |
+
between users are limited to direct messages, commercial transactions,
|
| 274 |
+
consumer reviews of products, sellers, services, events, or places, or any
|
| 275 |
+
combination thereof,” id. § 22681.
|
| 276 |
+
|
| 277 |
+
8
|
| 278 |
+
|
| 279 |
+
X CORP. V. BONTA
|
| 280 |
+
|
| 281 |
+
racism;
|
| 282 |
+
|
| 283 |
+
(b) extremism or
|
| 284 |
+
|
| 285 |
+
companies submit to the State a semiannual report detailing
|
| 286 |
+
their TOS and content-moderation practices including, if at
|
| 287 |
+
all, how the terms of service define and address (a) hate
|
| 288 |
+
speech or
|
| 289 |
+
radicalization;
|
| 290 |
+
(c) disinformation or misinformation; (d) harassment; and
|
| 291 |
+
(e) foreign political interference, as well as statistics on
|
| 292 |
+
content that was flagged by the social media company as
|
| 293 |
+
belonging to any of the categories (TOS Report), see id.
|
| 294 |
+
§ 22677, 2 and (3) a penalty provision, whereby the social
|
| 295 |
+
media company may be sued in court for, inter alia,
|
| 296 |
+
materially omitting or misrepresenting required information
|
| 297 |
+
and may be liable to pay up to $15,000 per violation per day,
|
| 298 |
+
see id. § 22678.3
|
| 299 |
+
|
| 300 |
+
On September 8, 2023, X Corp. filed a complaint against
|
| 301 |
+
the State seeking declaratory relief and injunctive relief
|
| 302 |
+
barring the law’s enforcement. The complaint alleges three
|
| 303 |
+
causes of action challenging the TOS Posting, TOS Report,
|
| 304 |
+
and penalty provision of AB 587 as: (1) a violation of the
|
| 305 |
+
free speech clauses of the U.S. and California Constitutions;
|
| 306 |
+
(2) a violation of the Dormant Commerce Clause; and
|
| 307 |
+
(3) federally preempted pursuant to the Communications
|
| 308 |
+
Decency Act, 47 U.S.C. § 230(c). X Corp. filed a motion for
|
| 309 |
+
preliminary injunction based on its free speech and
|
| 310 |
+
|
| 311 |
+
2 AB 587 was subsequently amended to add to this list “[c]ontrolled
|
| 312 |
+
substance distribution.” 2023 Cal. Legis. Serv. 7680 (West).
|
| 313 |
+
|
| 314 |
+
3 In assessing the amount of any penalty, a court is to consider whether
|
| 315 |
+
the social media company has made a reasonable, good faith attempt to
|
| 316 |
+
comply with the provisions of the statute. Cal. Bus. & Prof. Code
|
| 317 |
+
§ 22678(a)(3).
|
| 318 |
+
|
| 319 |
+
X CORP. V. BONTA
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
| 320 |
|
| 321 |
9
|
| 322 |
|
| 323 |
+
preemption claims, seeking to enjoin the State from
|
| 324 |
+
enforcing the challenged provisions of AB 587.4
|
| 325 |
+
|
| 326 |
+
On December 28, 2023, the district court denied X
|
| 327 |
+
Corp.’s motion. The court began its analysis with X Corp.’s
|
| 328 |
+
First Amendment claim.5 The court held that X Corp. was
|
| 329 |
+
unlikely to prevail because the TOS Posting and TOS Report
|
| 330 |
+
requirements appeared constitutionally permissible in light
|
| 331 |
+
of Zauderer v. Office of Disciplinary Counsel of Supreme
|
| 332 |
+
Court of Ohio, 471 U.S. 626 (1985), the Supreme Court’s
|
| 333 |
+
test for compelled commercial speech. See X Corp. v. Bonta,
|
| 334 |
+
No. 23-cv-01939, 2023 WL 8948286, at *1–2 (E.D. Cal.
|
| 335 |
+
Dec. 28, 2023).
|
| 336 |
+
|
| 337 |
+
The court’s analysis of the TOS Report requirement
|
| 338 |
+
focused primarily on the provisions requiring that social
|
| 339 |
+
media companies report whether and how they define and
|
| 340 |
+
address certain enumerated content categories. Id. at *2.
|
| 341 |
+
The court acknowledged that such reports do “not so easily
|
| 342 |
+
fit the traditional definition of commercial speech” because
|
| 343 |
+
they “are not advertisements” and because “social media
|
| 344 |
+
companies have no particular economic motivation to
|
| 345 |
+
provide them.” Id. However, the court applied Zauderer to
|
| 346 |
+
those provisions nevertheless so as to “follow[] the lead of
|
| 347 |
+
the Fifth and Eleventh Circuits.” Id. (citing NetChoice, LLC
|
| 348 |
+
v. Paxton, 49 F.4th 439, 485 (5th Cir. 2022), rev’d on other
|
| 349 |
+
grounds sub nom. Moody v. NetChoice, LLC, 144 S. Ct. 2383
|
| 350 |
+
|
| 351 |
+
4 X Corp. did not seek a preliminary injunction based upon the Dormant
|
| 352 |
+
Commerce Clause.
|
| 353 |
+
|
| 354 |
+
5 The district court did not analyze X Corp.’s free speech claim under
|
| 355 |
+
Article I, Section 2, of the California Constitution, nor do the parties
|
| 356 |
+
meaningfully address this claim on appeal. Because we hold that X
|
| 357 |
+
Corp. is likely to succeed on its First Amendment claim, we do not reach
|
| 358 |
+
X Corp.’s free speech claim pursuant to the California Constitution.
|
| 359 |
+
|
| 360 |
+
10
|
| 361 |
+
|
| 362 |
+
X CORP. V. BONTA
|
| 363 |
+
|
| 364 |
+
to
|
| 365 |
+
|
| 366 |
+
(2024) (“NetChoice (Tex.)”), and NetChoice, LLC v. Att’y
|
| 367 |
+
Gen., Fla., 34 F.4th 1196, 1230 (11th Cir. 2022), rev’d on
|
| 368 |
+
other grounds sub nom. Moody, 144 S. Ct. 2383 (“NetChoice
|
| 369 |
+
(Fla.)”)). The court then concluded that the TOS Report
|
| 370 |
+
requirement satisfies Zauderer. Id. The court reasoned that
|
| 371 |
+
the provisions require speech that is “purely factual” and
|
| 372 |
+
“uncontroversial” because they “merely require[] social
|
| 373 |
+
media companies
|
| 374 |
+
their existing content
|
| 375 |
+
identify
|
| 376 |
+
moderation policies, if any, related to the specified
|
| 377 |
+
categories” and the “mere fact that the reports may be ‘tied
|
| 378 |
+
in some way to a controversial issue’ does not make the
|
| 379 |
+
reports themselves controversial.” Id. (quoting CTIA - The
|
| 380 |
+
Wireless Ass’n v. City of Berkeley, 928 F.3d 832, 845 (9th
|
| 381 |
+
Cir. 2019) (“CTIA II”)). The court rejected X Corp.’s
|
| 382 |
+
argument that the TOS Report requirement is “unduly
|
| 383 |
+
burdensome,” explaining that “AB 587 does not require that
|
| 384 |
+
a social media company adopt any of the specified
|
| 385 |
+
categories” of speech, and that in any event “Zauderer is
|
| 386 |
+
concerned not merely with logistical or economic burdens,
|
| 387 |
+
but burdens on speech.” Id. It further held that the TOS
|
| 388 |
+
Report requirement is “reasonably related to a substantial
|
| 389 |
+
government interest in requiring social media companies to
|
| 390 |
+
be transparent about their content moderation policies and
|
| 391 |
+
practices so that consumers can make informed decisions
|
| 392 |
+
about where they consume and disseminate news and
|
| 393 |
+
information.” Id.
|
| 394 |
+
|
| 395 |
+
The district court also determined that X Corp. had failed
|
| 396 |
+
to show a likelihood of success on its claim that AB 587 is
|
| 397 |
+
preempted by 47 U.S.C. § 230(c). Id. at *3. The court
|
| 398 |
+
observed that the purpose of section 230(c) “is to provide
|
| 399 |
+
‘protection for “Good Samaritan” blocking and screening of
|
| 400 |
+
offensive material’” so that a website may “self-regulate
|
| 401 |
+
offensive third party content without fear of liability.” Id.
|
| 402 |
+
|
| 403 |
+
X CORP. V. BONTA
|
| 404 |
+
|
| 405 |
+
11
|
| 406 |
|
| 407 |
+
(quoting Doe v. Internet Brands, Inc., 824 F.3d 846, 851–52
|
| 408 |
+
(9th Cir. 2016)). The court concluded that AB 587 is not
|
| 409 |
+
preempted because, under its plain language, it “does not
|
| 410 |
+
provide for any potential liability stemming from a
|
| 411 |
+
company’s content moderation activities per se,” only for
|
| 412 |
+
failing to make AB 587’s required disclosures. Id.
|
| 413 |
|
| 414 |
+
On January 12, 2024, X Corp. timely filed notice of its
|
| 415 |
+
appeal. The provision of AB 587 most relevant in this appeal
|
| 416 |
+
is section 22677(a), which reads in its entirety:
|
| 417 |
|
| 418 |
+
(a) On a semiannual basis in accordance with
|
| 419 |
+
subdivision (b), a social media company shall
|
| 420 |
+
submit to the Attorney General a terms of
|
| 421 |
+
service report. The terms of service report
|
| 422 |
+
shall include, for each social media platform
|
| 423 |
+
owned or operated by the company, all of the
|
| 424 |
+
following:
|
| 425 |
|
| 426 |
+
(1) The current version of the terms of service
|
| 427 |
+
of the social media platform.
|
| 428 |
|
| 429 |
+
(2) If a social media company has filed its
|
| 430 |
+
first
|
| 431 |
+
report, a complete and detailed
|
| 432 |
+
description of any changes to the terms of
|
| 433 |
+
service since the previous report.
|
| 434 |
|
| 435 |
+
(3) A statement of whether the current
|
| 436 |
+
version of the terms of service defines each
|
| 437 |
+
of the following categories of content, and, if
|
| 438 |
+
so,
|
| 439 |
+
those categories,
|
| 440 |
+
the definitions of
|
| 441 |
+
including any subcategories:
|
| 442 |
|
| 443 |
+
(A) Hate speech or racism.
|
|
|
|
|
|
|
|
|
|
| 444 |
|
| 445 |
+
(B) Extremism or radicalization.
|
|
|
|
|
|
|
|
|
|
|
|
|
| 446 |
|
| 447 |
+
(C) Disinformation or misinformation.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 448 |
|
| 449 |
+
12
|
|
|
|
|
|
|
| 450 |
|
| 451 |
+
X CORP. V. BONTA
|
| 452 |
|
| 453 |
+
(D) Harassment.
|
| 454 |
|
| 455 |
+
(E) Foreign political interference.
|
|
|
|
|
|
|
|
|
|
|
|
|
| 456 |
|
| 457 |
+
(F) Controlled substance distribution.6
|
|
|
|
|
|
|
| 458 |
|
| 459 |
+
(4) A detailed description of content
|
| 460 |
+
moderation practices used by the social
|
| 461 |
+
media company for that platform, including,
|
| 462 |
+
but not limited to, all of the following:
|
| 463 |
|
| 464 |
+
(A) Any existing policies intended to
|
| 465 |
+
address
|
| 466 |
+
the categories of content
|
| 467 |
+
described in paragraph (3).
|
| 468 |
|
| 469 |
+
(B) How automated content moderation
|
| 470 |
+
systems enforce terms of service of the
|
| 471 |
+
social media platform and when these
|
| 472 |
+
systems involve human review.
|
| 473 |
|
| 474 |
+
(C) How the social media company
|
| 475 |
+
responds to user reports of violations of
|
| 476 |
+
the terms of service.
|
| 477 |
|
| 478 |
+
(D) How the social media company
|
| 479 |
+
would remove
|
| 480 |
+
individual pieces of
|
| 481 |
+
content, users, or groups that violate the
|
| 482 |
+
terms of service, or take broader action
|
| 483 |
+
against individual users or against groups
|
| 484 |
+
of users that violate the terms of service.
|
| 485 |
+
|
| 486 |
+
(E) The languages in which the social
|
| 487 |
+
media platform does not make terms of
|
| 488 |
+
service available, but does offer product
|
| 489 |
|
| 490 |
+
6 As noted above, section 22677(a)(3)(F) was added subsequent to X
|
| 491 |
+
Corp. filing its lawsuit in the district court.
|
|
|
|
| 492 |
|
| 493 |
+
X CORP. V. BONTA
|
| 494 |
|
| 495 |
+
13
|
| 496 |
|
| 497 |
+
features, including, but not limited to,
|
| 498 |
+
menus and prompts.
|
| 499 |
|
| 500 |
+
(5) (A) Information on content that was
|
| 501 |
+
flagged by the social media company as
|
| 502 |
+
content belonging to any of the categories
|
| 503 |
+
described in paragraph (3), including all of
|
| 504 |
+
the following:
|
| 505 |
|
| 506 |
+
(i) The total number of flagged items of
|
| 507 |
+
content.
|
| 508 |
+
|
| 509 |
+
(ii) The total number of actioned items of
|
| 510 |
+
content.
|
| 511 |
+
|
| 512 |
+
(iii) The total number of actioned items of
|
| 513 |
+
content that resulted in action taken by
|
| 514 |
+
the social media company against the
|
| 515 |
+
user or group of users responsible for the
|
| 516 |
+
content.
|
| 517 |
+
|
| 518 |
+
(iv) The total number of actioned items of
|
| 519 |
+
content that were removed, demonetized,
|
| 520 |
+
or deprioritized by the social media
|
| 521 |
+
company.
|
| 522 |
+
|
| 523 |
+
(v) The number of times actioned items
|
| 524 |
+
of content were viewed by users.
|
| 525 |
+
|
| 526 |
+
(vi) The number of times actioned items
|
| 527 |
+
of content were shared, and the number of
|
| 528 |
+
users that viewed the content before it
|
| 529 |
+
was actioned.
|
| 530 |
+
|
| 531 |
+
(vii) The number of times users appealed
|
| 532 |
+
social media company actions taken on
|
| 533 |
+
that platform and the number of reversals
|
| 534 |
+
of social media company actions on
|
| 535 |
+
|
| 536 |
+
14
|
| 537 |
+
|
| 538 |
+
X CORP. V. BONTA
|
| 539 |
+
|
| 540 |
+
appeal disaggregated by each type of
|
| 541 |
+
action.
|
| 542 |
+
|
| 543 |
+
(B) All information required by subparagraph
|
| 544 |
+
(A) shall be disaggregated into the following
|
| 545 |
+
categories:
|
| 546 |
+
|
| 547 |
+
(i) The category of content, including any
|
| 548 |
+
relevant
|
| 549 |
+
in
|
| 550 |
+
paragraph (3).
|
| 551 |
+
|
| 552 |
+
categories
|
| 553 |
+
|
| 554 |
+
described
|
| 555 |
+
|
| 556 |
+
(ii) The type of content, including, but not
|
| 557 |
+
limited to, posts, comments, messages,
|
| 558 |
+
profiles of users, or groups of users.
|
| 559 |
+
|
| 560 |
+
(iii) The type of media of the content,
|
| 561 |
+
including, but not limited to, text, images,
|
| 562 |
+
and videos.
|
| 563 |
+
|
| 564 |
+
the content was flagged,
|
| 565 |
+
(iv) How
|
| 566 |
+
including, but not limited to, flagged by
|
| 567 |
+
company employees or contractors,
|
| 568 |
+
flagged by artificial intelligence software,
|
| 569 |
+
flagged by community moderators,
|
| 570 |
+
flagged by civil society partners, and
|
| 571 |
+
flagged by users.
|
| 572 |
+
|
| 573 |
+
(v) How
|
| 574 |
+
the content was actioned,
|
| 575 |
+
including, but not limited to, actioned by
|
| 576 |
+
company employees or contractors,
|
| 577 |
+
intelligence
|
| 578 |
+
actioned
|
| 579 |
+
software,
|
| 580 |
+
community
|
| 581 |
+
moderators, actioned by civil society
|
| 582 |
+
partners, and actioned by users.
|
| 583 |
+
|
| 584 |
+
by
|
| 585 |
+
actioned
|
| 586 |
+
|
| 587 |
+
artificial
|
| 588 |
+
by
|
| 589 |
+
|
| 590 |
+
X CORP. V. BONTA
|
| 591 |
+
|
| 592 |
+
15
|
| 593 |
+
|
| 594 |
+
JURISDICTION AND STANDARD OF REVIEW
|
| 595 |
+
|
| 596 |
+
We have jurisdiction pursuant to 28 U.S.C. § 1292(a)(1)
|
| 597 |
+
to review the denial of a preliminary injunction. Creech v.
|
| 598 |
+
Idaho Comm’n of Pardons & Parole, 94 F.4th 851, 854 (9th
|
| 599 |
+
Cir. 2024). We review the denial of a preliminary injunction
|
| 600 |
+
for abuse of discretion, but we review de novo the
|
| 601 |
+
underlying issues of law. Cal. Chamber of Com. v. Council
|
| 602 |
+
for Educ. & Rsch. on Toxics, 29 F.4th 468, 475 (9th Cir.
|
| 603 |
+
2022).
|
| 604 |
+
|
| 605 |
+
“The appropriate legal standard to analyze a preliminary
|
| 606 |
+
injunction motion requires a district court to determine
|
| 607 |
+
whether a movant has established that (1) [it] is likely to
|
| 608 |
+
succeed on the merits of [its] claim, (2) [it] is likely to suffer
|
| 609 |
+
irreparable harm absent the preliminary injunction, (3) the
|
| 610 |
+
balance of equities tips in [its] favor, and (4) a preliminary
|
| 611 |
+
injunction is in the public interest.” Baird v. Bonta, 81 F.4th
|
| 612 |
+
1036, 1040 (9th Cir. 2023); see Winter v. Nat. Res. Def.
|
| 613 |
+
Council, Inc., 555 U.S. 7, 20 (2008). Because “the party
|
| 614 |
+
opposing injunctive relief is a government entity” here, the
|
| 615 |
+
third and fourth factors “merge.” Fellowship of Christian
|
| 616 |
+
Athletes v. San Jose Unified Sch. Dist. Bd. of Educ., 82 F.4th
|
| 617 |
+
664, 695 (9th Cir. 2023) (en banc) (quoting Nken v. Holder,
|
| 618 |
+
556 U.S. 418, 435 (2009)).
|
| 619 |
+
|
| 620 |
+
ANALYSIS
|
| 621 |
+
|
| 622 |
+
On appeal, X Corp. challenges the district court’s ruling
|
| 623 |
+
on the TOS Report requirement and penalty provision as
|
| 624 |
+
applied to the TOS Report requirement. X Corp. does not
|
| 625 |
+
appeal the district court’s denial of a preliminary injunction
|
| 626 |
+
as to the TOS Posting requirement, Cal. Bus. & Prof. Code
|
| 627 |
+
§ 22676.
|
| 628 |
+
|
| 629 |
+
16
|
| 630 |
+
|
| 631 |
+
X CORP. V. BONTA
|
| 632 |
+
|
| 633 |
+
X Corp. argues that the district court erred by finding that
|
| 634 |
+
X Corp. did not establish a likelihood of success on the
|
| 635 |
+
merits because
|
| 636 |
+
is
|
| 637 |
+
(1) the TOS Report
|
| 638 |
+
compelled, non-commercial speech subject to strict scrutiny,
|
| 639 |
+
not the lower tier of scrutiny in Zauderer, (2) regardless, the
|
| 640 |
+
TOS Report requirement fails under any level of scrutiny,
|
| 641 |
+
and (3) section 230’s broad immunity precludes liability
|
| 642 |
+
under AB 587.
|
| 643 |
+
|
| 644 |
+
requirement
|
| 645 |
+
|
| 646 |
+
X Corp. seeks to reverse the district court’s ruling as to
|
| 647 |
+
the entirety of the TOS Report requirement. But the thrust
|
| 648 |
+
of the appeal concerns section 22677(a)(3), which requires
|
| 649 |
+
that social media companies report whether and how they
|
| 650 |
+
define six categories of content, and sections 22677(a)(4)(A)
|
| 651 |
+
and (a)(5), which directly incorporate section 22677(a)(3).
|
| 652 |
+
For ease of reference, we refer to these sections as the
|
| 653 |
+
Content Category Report provisions.
|
| 654 |
+
|
| 655 |
+
For the reasons below, we hold that the Content Category
|
| 656 |
+
Report provisions likely compel non-commercial speech and
|
| 657 |
+
are subject to strict scrutiny, under which they do not
|
| 658 |
+
survive. We reverse the district court on that basis. Because
|
| 659 |
+
we reverse on free speech grounds, we need not reach X
|
| 660 |
+
Corp.’s section 230 theory. We remand to the district court
|
| 661 |
+
to determine in the first instance whether the Content
|
| 662 |
+
Category Report provisions are severable from
|
| 663 |
+
the
|
| 664 |
+
remainder of AB 587, and if so, which, if any, of the
|
| 665 |
+
remaining challenged provisions should also be subject to
|
| 666 |
+
the preliminary injunction.7
|
| 667 |
+
|
| 668 |
+
7 We do not decide whether sections 22677(a)(1), (2), and (4)(B)–(E)—
|
| 669 |
+
which require that social media companies disclose the text of their TOS
|
| 670 |
+
and describe their enforcement mechanisms, without mention of specific
|
| 671 |
+
|
| 672 |
+
X CORP. V. BONTA
|
| 673 |
+
|
| 674 |
+
17
|
| 675 |
+
|
| 676 |
+
I. X Corp. is likely to succeed in showing that the
|
| 677 |
+
Content Category Report provisions facially violate
|
| 678 |
+
the First Amendment.
|
| 679 |
+
|
| 680 |
+
“For a host of good reasons, courts usually handle
|
| 681 |
+
constitutional claims case by case, not en masse.” Moody,
|
| 682 |
+
144 S. Ct. at 2397. The Supreme Court “has therefore made
|
| 683 |
+
facial challenges hard to win.” Id. In a typical facial
|
| 684 |
+
challenge, a plaintiff cannot
|
| 685 |
+
succeed “unless he
|
| 686 |
+
‘establish[es] that no set of circumstances exists under which
|
| 687 |
+
the [law] would be valid,’ or he shows that the law lacks a
|
| 688 |
+
‘plainly legitimate sweep.’” Id. (alterations in original) (first
|
| 689 |
+
quoting United States v. Salerno, 481 U.S. 739, 745 (1987);
|
| 690 |
+
then quoting Wash. State Grange v. Wash. State Republican
|
| 691 |
+
Party, 552 U.S. 442, 449 (2008)).
|
| 692 |
+
|
| 693 |
+
less demanding
|
| 694 |
+
|
| 695 |
+
However, in First Amendment cases, the Supreme Court
|
| 696 |
+
“has lowered that very high bar.” Id. “To provide breathing
|
| 697 |
+
the Supreme Court has
|
| 698 |
+
room for free expression,”
|
| 699 |
+
“substituted a
|
| 700 |
+
though still rigorous
|
| 701 |
+
standard.” Id. (cleaned up) (quoting United States v.
|
| 702 |
+
Hansen, 599 U.S. 762, 769 (2023)); see also Tucson v. City
|
| 703 |
+
of Seattle, 91 F.4th 1318, 1327 (9th Cir. 2024). “[I]f the
|
| 704 |
+
law’s unconstitutional applications substantially outweigh
|
| 705 |
+
its constitutional ones,” then a court may sustain a facial
|
| 706 |
+
challenge to the law and strike it down. Moody, 144 S. Ct.
|
| 707 |
+
at 2397. As Moody clarified, a First Amendment facial
|
| 708 |
+
challenge has two parts: first, the courts must “assess the
|
| 709 |
+
state laws’ scope”; and second, the courts must “decide
|
| 710 |
+
|
| 711 |
+
content categories—are facially constitutional. Neither party—either
|
| 712 |
+
below or on appeal—briefed what should happen to the remainder of
|
| 713 |
+
section 22677 if the Content Category Report provisions were found to
|
| 714 |
+
be likely unconstitutional.
|
| 715 |
+
|
| 716 |
+
18
|
| 717 |
+
|
| 718 |
+
X CORP. V. BONTA
|
| 719 |
+
|
| 720 |
+
which of the laws’ applications violate the First Amendment,
|
| 721 |
+
and . . . measure them against the rest.” Id. at 2398.
|
| 722 |
+
|
| 723 |
+
“[N]o one has paid much attention to” the requirements
|
| 724 |
+
for a facial challenge so far in this case. Id. at 2397.
|
| 725 |
+
Nevertheless, we conclude that a facial challenge is
|
| 726 |
+
permissible here. That is because all aspects of the Content
|
| 727 |
+
Category Report, in every application to a covered social
|
| 728 |
+
media company, raise the same First Amendment issues. As
|
| 729 |
+
explained in further detail below, every Content Category
|
| 730 |
+
Report must detail the company’s policies and actions
|
| 731 |
+
concerning certain state-specified categories of content
|
| 732 |
+
(even if only to detail the company’s decision not to define
|
| 733 |
+
the enumerated categories of section 22677(a)(3)). In effect,
|
| 734 |
+
the Content Category Report provisions compel every
|
| 735 |
+
covered social media company to reveal its policy opinion
|
| 736 |
+
about contentious issues, such as what constitutes hate
|
| 737 |
+
speech or misinformation and whether to moderate such
|
| 738 |
+
expression.8
|
| 739 |
+
|
| 740 |
+
8 X Corp. cites legislative history and statements from the California
|
| 741 |
+
State Attorney General in describing the indirect chilling effects AB 587
|
| 742 |
+
may have by generating public controversy about the actions of social
|
| 743 |
+
media companies and thereby pressuring them to change their content
|
| 744 |
+
moderation policies. No matter how a social media company chooses to
|
| 745 |
+
moderate such content, the company will face backlash from its users
|
| 746 |
+
and the public. That is true even if the company decides not to define
|
| 747 |
+
the enumerated categories, because they will draw criticism for under-
|
| 748 |
+
moderating their community. While we account for these effects in our
|
| 749 |
+
analysis, whether State officials intended these effects plays no role in
|
| 750 |
+
our analysis of the merits of this facial challenge. See B & L Prods., Inc.
|
| 751 |
+
v. Newsom, 104 F.4th 108, 116 (9th Cir. 2024) (citing United States v.
|
| 752 |
+
O’Brien, 391 U.S. 367, 383 n.30 (1968)) (rejecting “the idea that
|
| 753 |
+
‘legislative motive’” of indirectly chilling speech “‘is a proper basis for
|
| 754 |
+
declaring a statute unconstitutional’”).
|
| 755 |
+
|
| 756 |
+
X CORP. V. BONTA
|
| 757 |
+
|
| 758 |
+
19
|
| 759 |
+
|
| 760 |
+
Thus, the Content Category Report provisions raise the
|
| 761 |
+
same First Amendment issues for every covered social
|
| 762 |
+
media company. That is true from the face of the law; we
|
| 763 |
+
need not “speculate about ‘hypothetical’ or ‘imaginary’
|
| 764 |
+
cases.” See Wash. State Grange, 552 U.S. at 450. We
|
| 765 |
+
therefore proceed to consider whether the Content Category
|
| 766 |
+
Report provisions are likely to survive X Corp.’s First
|
| 767 |
+
Amendment facial challenge.
|
| 768 |
+
|
| 769 |
+
A. The Content Category Report provisions compel
|
| 770 |
+
non-commercial speech and are subject to strict
|
| 771 |
+
scrutiny.
|
| 772 |
+
|
| 773 |
+
regulation
|
| 774 |
+
|
| 775 |
+
One of the First Amendment’s core purposes is “to
|
| 776 |
+
preserve an uninhibited marketplace of ideas in which truth
|
| 777 |
+
will ultimately prevail.” McCullen v. Coakley, 573 U.S. 464,
|
| 778 |
+
476 (2014) (quoting FCC v. League of Women Voters of
|
| 779 |
+
Cal., 468 U.S. 364, 377 (1984)). In evaluating whether a
|
| 780 |
+
regulation violates the First Amendment, courts “distinguish
|
| 781 |
+
between content-based and content-neutral regulations of
|
| 782 |
+
speech.” Vidal v. Elster, 602 U.S. 286, 292 (2024) (internal
|
| 783 |
+
quotation marks omitted) (quoting Nat’l Inst. of Fam. & Life
|
| 784 |
+
Advocs. v. Becerra, 585 U.S. 755, 766 (2018)). A content-
|
| 785 |
+
based
|
| 786 |
+
its
|
| 787 |
+
communicative content,” restricting discussion of a subject
|
| 788 |
+
matter or topic. Reed v. Town of Gilbert, 576 U.S. 155, 163
|
| 789 |
+
(2015). “As a general matter,” a content-based regulation is
|
| 790 |
+
“presumptively unconstitutional and may be justified only if
|
| 791 |
+
the government proves that [it is] narrowly tailored to serve
|
| 792 |
+
compelling state interests.” Nat’l Inst. of Fam. & Life
|
| 793 |
+
Advocs., 585 U.S. at 766 (quoting Reed, 576 U.S. at 163).
|
| 794 |
+
When a state “compel[s] individuals to speak a particular
|
| 795 |
+
message,” the state “alter[s] the content of their speech,” and
|
| 796 |
+
engages in content-based regulation. Id. (cleaned up)
|
| 797 |
+
(quoting Riley v. Nat’l Fed’n of the Blind of N.C., Inc., 487
|
| 798 |
+
|
| 799 |
+
speech based on
|
| 800 |
+
|
| 801 |
+
“target[s]
|
| 802 |
+
|
| 803 |
+
20
|
| 804 |
+
|
| 805 |
+
X CORP. V. BONTA
|
| 806 |
+
|
| 807 |
+
U.S. 781, 795 (1988)). The First Amendment’s guarantee of
|
| 808 |
+
freedom of speech makes no distinction of “constitutional
|
| 809 |
+
significance” “between compelled speech and compelled
|
| 810 |
+
silence.” Riley, 487 U.S. at 796–97.
|
| 811 |
+
|
| 812 |
+
In general, laws regulating commercial speech are
|
| 813 |
+
subject to a lesser standard of scrutiny. See Bolger v. Youngs
|
| 814 |
+
Drug Prods. Corp., 463 U.S. 60, 64–65 (1983) (discussing
|
| 815 |
+
recognition and evolution of commercial speech doctrine).
|
| 816 |
+
This holds true for both corporations and individuals alike.
|
| 817 |
+
See Pac. Gas & Elec. Co. v. Pub. Utils. Comm’n of Cal., 475
|
| 818 |
+
U.S. 1, 16 (1986). Commercial speech is “usually defined
|
| 819 |
+
as speech that does no more than propose a commercial
|
| 820 |
+
transaction.” United States v. United Foods, Inc., 533 U.S.
|
| 821 |
+
405, 409 (2001). “Courts view this definition as just a
|
| 822 |
+
starting point, however, and instead try to give effect to a
|
| 823 |
+
‘common-sense distinction’ between commercial speech
|
| 824 |
+
and other varieties of speech.” Ariix, LLC v. NutriSearch
|
| 825 |
+
Corp., 985 F.3d 1107, 1115 (9th Cir. 2021) (cleaned up)
|
| 826 |
+
(quoting Jordan v. Jewel Food Stores, Inc., 743 F.3d 509,
|
| 827 |
+
516–17 (7th Cir. 2014)). Indeed, the “commercial speech
|
| 828 |
+
analysis is fact-driven, due to the inherent difficulty of
|
| 829 |
+
drawing bright lines that will clearly cabin commercial
|
| 830 |
+
speech in a distinct category.” First Resort, Inc. v. Herrera,
|
| 831 |
+
860 F.3d 1263, 1272 (9th Cir. 2017) (internal quotation
|
| 832 |
+
marks omitted) (quoting Greater Balt. Ctr. for Pregnancy
|
| 833 |
+
Concerns, Inc. v. Mayor & City Council of Balt., 721 F.3d
|
| 834 |
+
264, 284 (4th Cir. 2013)).
|
| 835 |
+
|
| 836 |
+
Because of the difficulty of drawing clear lines between
|
| 837 |
+
commercial and non-commercial speech, the Supreme Court
|
| 838 |
+
in Bolger outlined three factors to consider. 463 U.S. at 64–
|
| 839 |
+
67. “Where the facts present a close question, ‘strong
|
| 840 |
+
support’ that the speech should be characterized as
|
| 841 |
+
commercial speech is found where [1] the speech is an
|
| 842 |
+
|
| 843 |
+
X CORP. V. BONTA
|
| 844 |
+
|
| 845 |
+
21
|
| 846 |
+
|
| 847 |
+
advertisement, [2] the speech refers to a particular product,
|
| 848 |
+
and [3] the speaker has an economic motivation.” Hunt v.
|
| 849 |
+
City of L.A., 638 F.3d 703, 715 (9th Cir. 2011) (citing
|
| 850 |
+
Bolger, 463 U.S. at 66–67). These so-called Bolger factors
|
| 851 |
+
are important guideposts, but they are not necessarily
|
| 852 |
+
dispositive. See Bolger, 463 U.S. at 67 n.14 (“Nor do we
|
| 853 |
+
mean to suggest that each of the characteristics present in
|
| 854 |
+
this case must necessarily be present in order for speech to
|
| 855 |
+
be commercial.”); Dex Media W., Inc. v. City of Seattle, 696
|
| 856 |
+
F.3d 952, 958 (9th Cir. 2012).
|
| 857 |
+
|
| 858 |
+
Commercial speech is generally subject to intermediate
|
| 859 |
+
scrutiny. Nat’l Ass’n of Wheat Growers v. Bonta, 85 F.4th
|
| 860 |
+
1263, 1266 (9th Cir. 2023). However, an exception applies
|
| 861 |
+
to compelled commercial speech that is “purely factual and
|
| 862 |
+
uncontroversial.” Id.; see Pac. Coast Horseshoeing Sch.,
|
| 863 |
+
Inc. v. Kirchmeyer, 961 F.3d 1062, 1074 (9th Cir. 2020)
|
| 864 |
+
(citing Zauderer as a variation in the treatment of speech
|
| 865 |
+
“within the class of commercial speech”). “In that scenario,
|
| 866 |
+
the government need only demonstrate the compelled speech
|
| 867 |
+
survives a lesser form of scrutiny akin to a rational basis
|
| 868 |
+
test.” Nat’l Wheat, 85 F.4th at 1266.
|
| 869 |
+
|
| 870 |
+
State legislatures do not have “freewheeling authority to
|
| 871 |
+
declare new categories of speech outside the scope of the
|
| 872 |
+
First Amendment.” United States v. Stevens, 559 U.S. 460,
|
| 873 |
+
472, (2010). Thus, “without persuasive evidence that a
|
| 874 |
+
novel restriction on content is part of a long (if heretofore
|
| 875 |
+
unrecognized) tradition of proscription, a legislature may not
|
| 876 |
+
revise the ‘judgment [of] the American people,’ embodied in
|
| 877 |
+
the First Amendment, ‘that the benefits of its restrictions on
|
| 878 |
+
the Government outweigh the costs.’” Brown v. Entm’t
|
| 879 |
+
Merchs. Ass’n, 564 U.S. 786, 792 (2011) (alteration in
|
| 880 |
+
original) (quoting Stevens, 559 U.S. at 470).
|
| 881 |
+
|
| 882 |
+
22
|
| 883 |
+
|
| 884 |
+
X CORP. V. BONTA
|
| 885 |
+
|
| 886 |
+
Here, the Content Category Reports are not commercial
|
| 887 |
+
speech. They require a company to recast its content-
|
| 888 |
+
moderation practices in language prescribed by the State,
|
| 889 |
+
implicitly opining on whether and how certain controversial
|
| 890 |
+
categories of content should be moderated. As a result, few
|
| 891 |
+
indicia of commercial speech are present in the Content
|
| 892 |
+
Category Reports.
|
| 893 |
+
|
| 894 |
+
First, the Content Category Reports do not satisfy the
|
| 895 |
+
“usual[] defin[ition]” of commercial speech—i.e., “speech
|
| 896 |
+
that does no more than propose a commercial transaction.”
|
| 897 |
+
See United Foods, Inc., 533 U.S. at 409; see also IMDb.com
|
| 898 |
+
Inc. v. Becerra, 962 F.3d 1111, 1122 (2020) (“Because
|
| 899 |
+
IMDb’s public profiles do not ‘propose a commercial
|
| 900 |
+
transaction,’ we need not reach the Bolger factors.”). The
|
| 901 |
+
State appears to concede as much in its answering brief.
|
| 902 |
+
|
| 903 |
+
To the extent our circuit has recognized exceptions to
|
| 904 |
+
that general rule, those exceptions are limited and are
|
| 905 |
+
inapplicable to the Content Category Reports here. For
|
| 906 |
+
example, as identified by the First Amendment and Internet
|
| 907 |
+
Law Scholars amici, we have characterized the following
|
| 908 |
+
speech as commercial even if not a clear fit with the Supreme
|
| 909 |
+
Court’s above articulation: (i) targeted, individualized
|
| 910 |
+
solicitations, see Nationwide Biweekly Admin., Inc. v. Owen,
|
| 911 |
+
873 F.3d. 716, 731–32 (9th Cir. 2017); contract negotiations,
|
| 912 |
+
see S.F. Apartment Ass’n v. San Francisco, 881 F.3d 1169,
|
| 913 |
+
1177–78 (9th Cir. 2018); and retail product warnings, see
|
| 914 |
+
CTIA II, 928 F.3d at 845. Though it does not directly or
|
| 915 |
+
exclusively propose a commercial transaction, all of this
|
| 916 |
+
speech communicates the terms of an actual or potential
|
| 917 |
+
transaction. But the Content Category Reports go further:
|
| 918 |
+
they express a view about those terms by conveying whether
|
| 919 |
+
a company believes certain categories should be defined and
|
| 920 |
+
proscribed.
|
| 921 |
+
|
| 922 |
+
X CORP. V. BONTA
|
| 923 |
+
|
| 924 |
+
23
|
| 925 |
+
|
| 926 |
+
Second, the Content Category Reports fail to satisfy at
|
| 927 |
+
least two of the three Bolger factors. The compelled
|
| 928 |
+
disclosures are not advertisements. See Hunt, 638 F.3d at
|
| 929 |
+
715. Nor do the Content Category Reports merely disclose
|
| 930 |
+
existing commercial speech, so a social media company has
|
| 931 |
+
no economic motivation in their content. See id. The district
|
| 932 |
+
court found the same. The State does not dispute the district
|
| 933 |
+
court’s finding on appeal. Although the Bolger factors are
|
| 934 |
+
not dispositive, they are “important guideposts” to the
|
| 935 |
+
analysis and, here, further support the conclusion that the
|
| 936 |
+
compelled speech is non-commercial. See Ariix, LLC, 985
|
| 937 |
+
F.3d at 1116.
|
| 938 |
+
|
| 939 |
+
topics,
|
| 940 |
+
|
| 941 |
+
Third, while a social media platform’s existing TOS and
|
| 942 |
+
content moderation policies may be commercial speech, its
|
| 943 |
+
opinions about and reasons for those policies are different in
|
| 944 |
+
character and kind. The Content Category Report provisions
|
| 945 |
+
would require 9 a social media company to convey the
|
| 946 |
+
company’s policy views on intensely debated and politically
|
| 947 |
+
fraught
|
| 948 |
+
racism,
|
| 949 |
+
misinformation, and radicalization, and also convey how the
|
| 950 |
+
company has applied its policies. The State suggests that
|
| 951 |
+
this requirement is subject to lower scrutiny because “it is
|
| 952 |
+
only a transparency measure” about the product. But even if
|
| 953 |
+
the Content Category Report provisions concern only
|
| 954 |
+
transparency, the relevant question here is: transparency into
|
| 955 |
+
what? Even a pure “transparency” measure, if it compels
|
| 956 |
+
non-commercial speech, is subject to strict scrutiny. See
|
| 957 |
+
|
| 958 |
+
including
|
| 959 |
+
|
| 960 |
+
speech,
|
| 961 |
+
|
| 962 |
+
hate
|
| 963 |
+
|
| 964 |
+
9 The State relies heavily on the fact that AB 587 does not affirmatively
|
| 965 |
+
require any social media company to opine on these topics, instead
|
| 966 |
+
requiring the company to convey its position only to the extent such a
|
| 967 |
+
policy already exists. That fact, however, is immaterial or at least non-
|
| 968 |
+
dispositive as to the nature of the speech being conveyed, which is
|
| 969 |
+
fundamentally non-commercial.
|
| 970 |
+
|
| 971 |
+
24
|
| 972 |
+
|
| 973 |
+
X CORP. V. BONTA
|
| 974 |
+
|
| 975 |
+
Riley, 487 U.S. at 796–97. That is true of the Content
|
| 976 |
+
Category Report provisions. Insight into whether a social
|
| 977 |
+
media company considers, for example, (1) a post citing
|
| 978 |
+
rhetoric from on-campus protests to constitute hate speech;
|
| 979 |
+
(2) reports about a seized laptop to constitute foreign
|
| 980 |
+
political interference; or (3) posts about election fraud to
|
| 981 |
+
constitute misinformation
|
| 982 |
+
is sensitive, constitutionally
|
| 983 |
+
protected speech that the State could not otherwise compel a
|
| 984 |
+
social media company to disclose without satisfying strict
|
| 985 |
+
scrutiny. The mere fact that those beliefs are memorialized
|
| 986 |
+
in the company’s content moderation policy does not, by
|
| 987 |
+
itself, convert expression about
|
| 988 |
+
into
|
| 989 |
+
commercial speech. As X Corp. argues in its reply brief,
|
| 990 |
+
such a rule would be untenable. It would mean that basically
|
| 991 |
+
any compelled disclosure by any business about its activities
|
| 992 |
+
would be commercial and subject to a lower tier of scrutiny,
|
| 993 |
+
no matter how political in nature. Protection under the First
|
| 994 |
+
Amendment cannot be vitiated so easily.10
|
| 995 |
+
|
| 996 |
+
those beliefs
|
| 997 |
+
|
| 998 |
+
The district court performed, essentially, no analysis on
|
| 999 |
+
this question. In fact, the district court acknowledged that
|
| 1000 |
+
the Content Category Reports “do not so easily fit the
|
| 1001 |
+
traditional definition of commercial speech” as they “are not
|
| 1002 |
+
advertisements, and social media companies have no
|
| 1003 |
+
|
| 1004 |
+
10 For substantially the same reason, nor can the test for whether speech
|
| 1005 |
+
is commercial or non-commercial turn on whether the speech is “directed
|
| 1006 |
+
to potential consumers and may presumably play a role in the decision
|
| 1007 |
+
of whether to use the platform,” as the district court seemed to suggest.
|
| 1008 |
+
Consider, for example, a state law that compels a social media company
|
| 1009 |
+
to disclose the political affiliations of its managers. That information
|
| 1010 |
+
could conceivably “play a role in the [potential consumer’s] decision of
|
| 1011 |
+
whether to use the platform”—i.e., if the consumer is concerned about
|
| 1012 |
+
the platform’s content being politically skewed. It could not be that such
|
| 1013 |
+
a law compels only commercial speech subject to a lower tier of scrutiny.
|
| 1014 |
+
|
| 1015 |
+
X CORP. V. BONTA
|
| 1016 |
+
|
| 1017 |
+
25
|
| 1018 |
+
|
| 1019 |
+
to provide
|
| 1020 |
+
|
| 1021 |
+
particular economic motivation
|
| 1022 |
+
them.”
|
| 1023 |
+
Nevertheless, the court applied Zauderer, suggesting the
|
| 1024 |
+
compelled speech is commercial. See Nat’l Wheat, 85 F.4th
|
| 1025 |
+
at 1275 (identifying Central Hudson Gas & Electric Corp.
|
| 1026 |
+
v. Public Service Commission of New York, 447 U.S. 557
|
| 1027 |
+
(1980), and Zauderer as “two levels of scrutiny governing
|
| 1028 |
+
compelled commercial speech” (emphasis added)); CTIA II,
|
| 1029 |
+
928 F.3d at 843 (endorsing proposition that Zauderer is
|
| 1030 |
+
merely the “exception to the general rule of Central
|
| 1031 |
+
Hudson”). The district court offered no reason for that
|
| 1032 |
+
decision except for wanting to “follow[] the lead of the Fifth
|
| 1033 |
+
and Eleventh Circuits.”
|
| 1034 |
+
|
| 1035 |
+
But neither the Fifth nor Eleventh Circuit dealt with
|
| 1036 |
+
speech similar to the Content Category Reports. Unlike
|
| 1037 |
+
Texas HB 20 or Florida SB 7072, the Content Category
|
| 1038 |
+
Report provisions compel social media companies to report
|
| 1039 |
+
whether and how they believe particular, controversial
|
| 1040 |
+
categories of content should be defined and regulated on
|
| 1041 |
+
their platforms. Neither the Texas nor Florida provisions at
|
| 1042 |
+
issue in the NetChoice cases require a company to disclose
|
| 1043 |
+
the existence or substance of its policies addressing such
|
| 1044 |
+
categories. See NetChoice (Tex.), 49 F.4th at 446 (requiring
|
| 1045 |
+
platforms to disclose “how they moderate and promote
|
| 1046 |
+
content” and provide “high-level statistics” about their
|
| 1047 |
+
moderation efforts without mention of controversial topics);
|
| 1048 |
+
NetChoice (Fla.), 34 F.4th at 1206–07 (requiring platforms
|
| 1049 |
+
to disclose information about their content-moderation
|
| 1050 |
+
“standards” and “rule changes” without regard to particular
|
| 1051 |
+
content categories). Though perhaps relevant to an analysis
|
| 1052 |
+
of sections 22677(a)(1), (2), and (4)(B)–(E), these cases are
|
| 1053 |
+
unhelpful on the issue of the Content Category Reports and
|
| 1054 |
+
offer no compelling reason to apply Zauderer.
|
| 1055 |
+
|
| 1056 |
+
26
|
| 1057 |
+
|
| 1058 |
+
X CORP. V. BONTA
|
| 1059 |
+
|
| 1060 |
+
For these reasons, we conclude that the Content
|
| 1061 |
+
Category Report provisions compel non-commercial speech.
|
| 1062 |
+
Because the provisions are content-based, which the State
|
| 1063 |
+
does not contest, they are subject to strict scrutiny. See Nat’l
|
| 1064 |
+
Inst. of Fam. & Life Advocs., 585 U.S. at 766.11
|
| 1065 |
+
|
| 1066 |
+
B. The Content Category Report provisions likely
|
| 1067 |
+
|
| 1068 |
+
fail strict scrutiny.
|
| 1069 |
+
|
| 1070 |
+
Strict scrutiny “is a demanding standard.” Brown v. Ent.
|
| 1071 |
+
Merchants Ass’n, 564 U.S. 786, 799 (2011). “It is rare that
|
| 1072 |
+
a regulation restricting speech because of its content will
|
| 1073 |
+
ever be permissible.” United States v. Playboy Ent. Grp.,
|
| 1074 |
+
Inc., 529 U.S. 803, 818 (2000). A state must show that the
|
| 1075 |
+
statute “furthers a compelling governmental interest and is
|
| 1076 |
+
narrowly tailored to that end.” Reed, 576 U.S. at 171. “If a
|
| 1077 |
+
less restrictive alternative would serve the [g]overnment’s
|
| 1078 |
+
purpose, the legislature must use that alternative.” Playboy
|
| 1079 |
+
Ent. Grp., Inc., 529 U.S. at 813.
|
| 1080 |
+
|
| 1081 |
+
At minimum, the Content Category Report provisions
|
| 1082 |
+
likely fail under strict scrutiny because they are not narrowly
|
| 1083 |
+
tailored. They are more extensive than necessary to serve
|
| 1084 |
+
the State’s purported goal of “requiring social media
|
| 1085 |
+
companies to be transparent about their content-moderation
|
| 1086 |
+
policies and practices so that consumers can make informed
|
| 1087 |
+
decisions about where they consume and disseminate news
|
| 1088 |
+
and information.” Consumers would still be meaningfully
|
| 1089 |
+
informed if, for example, a company disclosed whether it
|
| 1090 |
+
|
| 1091 |
+
11 X Corp. argues that strict scrutiny applies for the following additional
|
| 1092 |
+
reasons: because AB 587 is viewpoint discriminatory, interferes with a
|
| 1093 |
+
social media company’s constitutionally protected editorial judgment,
|
| 1094 |
+
and regulates “speech about speech.” Several of the amici raise similar
|
| 1095 |
+
arguments. Because we agree that strict scrutiny applies, we need not
|
| 1096 |
+
reach these arguments.
|
| 1097 |
+
|
| 1098 |
+
X CORP. V. BONTA
|
| 1099 |
+
|
| 1100 |
+
27
|
| 1101 |
+
|
| 1102 |
+
was moderating certain categories of speech without having
|
| 1103 |
+
to define those categories in a public report. Or, perhaps, a
|
| 1104 |
+
company could be compelled to disclose a sample of posts
|
| 1105 |
+
that have been removed without requiring the company to
|
| 1106 |
+
explain why or on what grounds.12
|
| 1107 |
+
|
| 1108 |
+
In any event, the State does not attempt to argue that the
|
| 1109 |
+
law survives strict scrutiny. For the reasons above, X Corp.
|
| 1110 |
+
has shown a likelihood of success on the merits of its First
|
| 1111 |
+
Amendment claim as to sections 22677(a)(3), (a)(4)(A), and
|
| 1112 |
+
(a)(5).
|
| 1113 |
+
|
| 1114 |
+
C. The remaining Winter factors weigh in favor of a
|
| 1115 |
+
|
| 1116 |
+
preliminary injunction.
|
| 1117 |
+
|
| 1118 |
+
With respect to the second factor, a loss of First
|
| 1119 |
+
Amendment freedoms constitutes an irreparable injury. See
|
| 1120 |
+
Fellowship of Christian Athletes, 82 F.4th at 694 (“It is
|
| 1121 |
+
axiomatic that ‘[t]he loss of First Amendment freedoms, for
|
| 1122 |
+
even minimal periods of time, unquestionably constitutes
|
| 1123 |
+
irreparable injury.’” (citation omitted)). Because X Corp.
|
| 1124 |
+
has a colorable First Amendment claim, it has demonstrated
|
| 1125 |
+
that it likely will suffer irreparable harm. See Am. Bev. Ass’n
|
| 1126 |
+
v. San Francisco, 916 F.3d 749, 758 (9th Cir. 2019) (en
|
| 1127 |
+
banc).
|
| 1128 |
+
|
| 1129 |
+
The third and fourth factors—balance of equities and
|
| 1130 |
+
public interest—also favor X Corp. “[I]t is always in the
|
| 1131 |
+
public interest to prevent the violation of a party’s
|
| 1132 |
+
constitutional rights.” Fellowship of Christian Athletes, 82
|
| 1133 |
+
F.4th at 695 (citation omitted). When a party “‘raise[s]
|
| 1134 |
+
serious First Amendment questions,’ that alone ‘compels a
|
| 1135 |
+
|
| 1136 |
+
12 We do not opine on whether such laws would survive constitutional
|
| 1137 |
+
scrutiny. They are offered only to illustrate that the Content Category
|
| 1138 |
+
Report provisions are not narrowly tailored to the State’s interest.
|
| 1139 |
+
|
| 1140 |
+
28
|
| 1141 |
+
|
| 1142 |
+
X CORP. V. BONTA
|
| 1143 |
+
|
| 1144 |
+
finding that the balance of hardships tips sharply in [its]
|
| 1145 |
+
favor.’” Id. (second alteration in original) (quoting Am. Bev.
|
| 1146 |
+
Ass’n, 916 F.3d at 758). The government reasonably has an
|
| 1147 |
+
interest in transparency by social media platforms. But even
|
| 1148 |
+
“undeniably admirable goals” “must yield” when they
|
| 1149 |
+
“collide with the . . . Constitution.” Id.
|
| 1150 |
+
|
| 1151 |
+
Because X Corp. has shown a likelihood of success on
|
| 1152 |
+
the merits of its First Amendment claim, and the remaining
|
| 1153 |
+
Winter factors weigh in favor of an injunction, we reverse
|
| 1154 |
+
the district court’s decision denying a preliminary injunction
|
| 1155 |
+
as to AB 587’s Content Category Report provisions.
|
| 1156 |
+
|
| 1157 |
+
II. We remand to the district court to determine whether
|
| 1158 |
+
the Content Category Report provisions are likely
|
| 1159 |
+
severable from the remainder of AB 587.
|
| 1160 |
+
|
| 1161 |
+
“Severability is . . . a matter of state law.” Sam Francis
|
| 1162 |
+
Found. v. Christies, Inc., 784 F.3d 1320, 1325 (9th Cir.
|
| 1163 |
+
2015) (en banc) (alteration in original) (quoting Leavitt v.
|
| 1164 |
+
Jane L., 518 U.S. 137, 139 (1996) (per curiam)). “In
|
| 1165 |
+
California, the presence of a severability clause in a statutory
|
| 1166 |
+
scheme that contains an invalid provision ‘normally calls for
|
| 1167 |
+
sustaining the valid part of the enactment.’” Garcia v. City
|
| 1168 |
+
of Los Angeles, 11 F.4th 1113, 1120 (9th Cir. 2021) (quoting
|
| 1169 |
+
Cal. Redevelopment Ass’n v. Matosantos, 267 P.3d 580, 607
|
| 1170 |
+
(Cal. 2011)).
|
| 1171 |
+
|
| 1172 |
+
The parties did not brief severability on appeal, and the
|
| 1173 |
+
severability arguments below appear to have been cursory.
|
| 1174 |
+
During oral argument, counsel for the State suggested that,
|
| 1175 |
+
were we to find that any part of the statute should be
|
| 1176 |
+
enjoined, the issue of severability should be remanded. We
|
| 1177 |
+
agree and leave it to the district court to determine in the first
|
| 1178 |
+
instance whether the likely unconstitutional provisions of
|
| 1179 |
+
AB 587, sections 22677(a)(3), (a)(4)(A), and (a)(5), are
|
| 1180 |
+
|
| 1181 |
+
X CORP. V. BONTA
|
| 1182 |
+
|
| 1183 |
+
29
|
| 1184 |
+
|
| 1185 |
+
severable from its remainder. See generally Detrich v. Ryan,
|
| 1186 |
+
740 F.3d 1237, 1248–49 (9th Cir. 2013) (en banc) (observing
|
| 1187 |
+
that it is “standard practice . . . to remand to the district court
|
| 1188 |
+
for a decision in the first instance without requiring any
|
| 1189 |
+
special justification for so doing”), overruled on other
|
| 1190 |
+
grounds by Shinn v. Ramirez, 596 U.S. 366 (2022).
|
| 1191 |
+
|
| 1192 |
+
CONCLUSION
|
| 1193 |
+
|
| 1194 |
+
For the foregoing reasons, we REVERSE the district
|
| 1195 |
+
court’s denial of a preliminary injunction as to California
|
| 1196 |
+
Business and Professions Code sections 22677(a)(3),
|
| 1197 |
+
(a)(4)(A), and (a)(5). We remand with instructions to enter
|
| 1198 |
+
a preliminary injunction consistent with this opinion and to
|
| 1199 |
+
determine whether these provisions are severable from the
|
| 1200 |
+
remainder of AB 587 and, if so, which, if any, of the
|
| 1201 |
+
remaining challenged provisions should also be enjoined.
|
| 1202 |
|
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|
@@ -15,8 +15,8 @@
|
|
| 15 |
],
|
| 16 |
"original_filenames": [
|
| 17 |
"Campaign_038_Introducing_AC_Whitepaper_v5e.pdf",
|
| 18 |
-
"
|
| 19 |
-
"
|
| 20 |
],
|
| 21 |
"modality": "markdown"
|
| 22 |
}
|
|
|
|
| 15 |
],
|
| 16 |
"original_filenames": [
|
| 17 |
"Campaign_038_Introducing_AC_Whitepaper_v5e.pdf",
|
| 18 |
+
"resize_r1_37.pdf",
|
| 19 |
+
"web_74331e85a10815bd.pdf"
|
| 20 |
],
|
| 21 |
"modality": "markdown"
|
| 22 |
}
|
q131/random_k2/random_1.md
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with Great In-Store Retail Experiences
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September 2014
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Table Of Contents
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Executive Summary ............... 2
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Key Findings ........................... 3
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Research Findings
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Investing in People &
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Technology
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to Enhance In-Store
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Experiences ............................... 4
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The Challenge of
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Cross-Channel Consistency ....... 6
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Turning In-Store Data
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into Actionable Messaging ........ 9
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The Future of
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Store Technologies .................. 10
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Key Recommendations ........ 13
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Appendices ........................... 14
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About Future Stores ............ 16
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About CFI Group .................. 16
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About WBR & WBR Digital .. 17
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Register for Next Year’s
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Future Stores Conference .... 17
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Executive Summary
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How to Engage and Convert Consumers with Great
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In-Store Retail Experiences
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Technology has had an expansive and multidimensional impact on retail in recent
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years. In particular, the ascendance of multichannel e-commerce platforms has
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challenged brands to reimagine how they interact with consumers. As a result, today’s
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connected consumers have access to a whole host of digital shopping tools, including
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interactive websites with high-definition images and mobile-optimized web and email.
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E-commerce offers variety, convenience, and information, empowering consumers to
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engage with retailers when, where, and how they please.
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Despite e-commerce’s growing popularity, stores are still the lynchpins of retail strategy.
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The Department of Commerce estimates that e-commerce accounted for approximately
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6.5% of all retail sales in the U.S. during the second quarter of 2014. Although this
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reaffirms that physical stores remain retailers’ most prominent sources of revenue, it
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also suggests that there are great opportunities for synergy between a brand’s physical
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locations and its e-commerce platform.
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Indeed, many of the technological innovations that have threatened to erode in-store
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sales have turned out to be great assets to retailers. Mobile devices enable businesses
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to send extremely relevant and timely messages to consumers by using location-based
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services and Bluetooth Low Energy (BLE) beacons. Loyalty programs deployed across
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channels encourage repeat business both in-store and online. QR codes and interactive
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displays offer customers new ways to engage with and learn about products and
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services. Omnichannel initiatives (e.g., an option for the consumer to buy online and
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pick up in-store) promote interchannel traffic. Because of these innovations, today’s
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consumers begin shopping before they walk into the store and continue shopping after
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they leave, making their in-store experiences the unifying element.
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The mission of retail stores has evolved and expanded greatly in recent years, and
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it has been influenced in large part by technological innovation and new consumer
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insights. The most successful retail stores not only leverage new technologies to drive
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in-store conversions, but they also enhance the shopping experience, collect actionable
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customer data, and serve as a physical extension of the brand. This is the store of the
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future: a connected showroom that fuses together multichannel experiences to convert
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and engage customers while also learning from them.
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What follows is an analysis of the best practices and paradigm-shifting experiences
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retailers are creating in their stores. The analysis is based on survey data collected from
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retail executives and professionals in a variety of industries. This data was collected on-site
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at the 2014 Future Stores Conference and through an online survey. The findings are
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based on the insights and practices of some of the world’s leading retailers and brands.
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2
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How to Engage and Convert Consumers with Great In-Store Retail ExperiencesKey Findings
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Retailers are increasing their investments in
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technology in order to make their in-store
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experiences more relevant and engaging.
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Although associates are still the most important in-store sales
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assets, retailers are investing equally in new store technologies
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and personnel training. Will this shift in emphasis produce a more
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technology-driven in-store sales process?
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shopping experiences across channels.
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In today’s omnichannel commercial world, consistency of experience
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is key to improving conversions and enhancing consumer loyalty.
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Unfortunately, most retailers’ shopping experiences are only somewhat
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consistent across channels, resulting in significant missed opportunities.
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collection in order to create more targeted
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and personalized marketing activities.
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them with an incomplete view of the customer and ineffective
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marketing messages.
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the future will create seamless shopping
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experiences and integrate with other
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technologies and services.
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of solutions and only implement those that enhance conversions while
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providing customers with effortless, engaging experiences.
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more of what they’re
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not getting. They want
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outcomes to be easier to
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achieve, and they would
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like them with greater
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convenience and at a
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higher value.”
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Experiences
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generation. Stores have become the standard-bearers for a brand’s customer experience,
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driving consumer loyalty and engagement through innovative interactions and inventive
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campaigns. Stores are also a burgeoning source of data that can be turned into rich insights
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into shoppers’ tendencies and preferences. Add in customers’ lofty expectations for shopping
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experiences and the value of the modern store becomes undeniable. With few exceptions,
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stores continue to be the backbone of retail businesses, even in today’s world of e-commerce
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and digital interconnectedness.
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they are constantly updating designs, technology, and personnel to get the most out of
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each location. Creating a store of the future means seamlessly integrating cutting-edge
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technology with tried and true designs and tactics, providing a strong balance of analog
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and digital elements that help deliver to customers higher value outcomes that are easier
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to achieve. When it comes to technology, electronic point of sale (EPOS) tools have
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become extremely common, with over three quarters of survey respondents indicating
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that they are already utilizing the capability. A robust 72% are leveraging mobile devices
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and tablets in stores, and 60% are making use of digital displays or kiosks.
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of store associates, 91% of those surveyed said that the greatest sales assets in their
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stores are still sales associates. New technologies are providing good value to the in-store
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experience, but they have yet to supplant personnel as key sales elements.
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displays, etc.)
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beacons, etc.)
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In-Store Conversions
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Common Technologies Being Leveraged to
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Enhance In-Store Experiences
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experiences, they just
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aren’t always being
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implemented. There is
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a resistance to change,
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because making changes
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costs a lot of time and
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money.”
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Today, consumers are increasingly engaging with brands across a variety of diverse media.
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The customer journey has become expansive, dynamic, and multilayered; it permeates
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desktop websites, mobile-optimized sites and apps, social networks, and retail stores
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themselves. For retailers, this has meant a multiplication of consumer touch points and
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an unprecedented demand for innovative digital shopping tools. However, the challenge
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for retailers is not just to develop spectacular omnichannel shopping capabilities but also
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to deliver outstanding experiences across all channels. When it comes to omnichannel
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customer experiences, consistency is key.
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The majority (60%) of those surveyed noted that their experiences are only somewhat
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consistent. In their quest to provide a great customer experience, these retailers are facing
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many complex challenges, including creating consistency across channels, personalizing
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the experience, capturing and applying relevant customer data, and the implementation
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of customer experience initiatives across store locations.
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Unfortunately, the way retailers view their shopping experience can differ greatly from
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consumers’ perspectives. For instance, in a Bain & Co. customer experience survey,
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80% of companies stated that they were delivering a “superior experience” to their
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customers. However, consumers in the survey said that only 8% of companies were
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actually delivering high-quality experiences. This discrepancy underlines how critical it is
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for retailers to listen to their customers, especially when it comes to experiences.
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advances. In part, a successful omnichannel strategy demands that retailers understand
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the key actions that consumers take during their shopping experiences, and retailers
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must then make those actions available across multiple channels. Enabling consumers to
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engage with multiple platforms en route to a purchase not only improves the shopping
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experience but also increases conversion rates and reduces cart abandonment.
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buying them online, poses a clear threat to traditional retailers, which are susceptible to
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customers using mobile devices to compare prices while in the store. Despite the threat,
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nearly three quarters of respondents reported that they have not seen any sort of impact
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from showrooming. In fact, 19% noted that showrooming has had a positive impact on
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their businesses. This is likely because omnichannel shoppers have been shown to spend
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significantly more than single-channel shoppers. Similarly, “buy online, pick up in store”
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options, which offer the convenience of an online transaction alongside the satisfaction
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of instantly picking up an item, are expanding although only 26% of respondents
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currently have fully-deployed programs.
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between in-store and online?
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stores
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Standing Out Above the Rest
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change
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drive sales
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Products Online and Pick Them Up In-Store
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collected in their stores. Using BLE beacons, location-based mobile services, loyalty programs,
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promotions, and sales trends, merchants can uncover valuable data on the in-store customer
|
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experience. This data can then help them track traffic patterns, evaluate how customers are
|
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interacting with displays, and determine which promotions and marketing messages are
|
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having the greatest impact. In other words, these insights lead to optimized stores, improved
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marketing campaigns, and more effective omnichannel commerce interfaces.
|
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effectively collecting customer data in their stores. Similarly, a third of respondents said that
|
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their in-store data collection has been ineffective. As a result, just under a fifth of the retailers
|
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surveyed said that their marketing activities are very targeted and personalized. This lack of
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personalization indicates that most retailers are missing major opportunities to reap the many
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benefits of in-store data insights.
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build processes to capture that information. Those retailers that have processes in place now
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have access to a new age of sophisticated key performance indicators, such as conversion
|
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rate, shopper yield, Average Transaction Value (ATV), entrance traffic, and sales per square
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foot, as well as a whole host of omnichannel metrics and capabilities.
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data in-store
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Businesses Are Doing a Very Effective Job of
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Collecting Customer Data in Stores
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shopping in-store. This
|
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embrace of mobile
|
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shopping is where the
|
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real opportunity lies for
|
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retailers to make their
|
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store a better place to
|
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shop. It is gradually
|
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becoming clear: the
|
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stores that make proper
|
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use of mobile wallets
|
| 449 |
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are the ones who will
|
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come out on top in the
|
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modern retail era.”
|
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Retail
|
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and
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Targeting Their Marketing Messages, but There
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Is Still Room for Improvement
|
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| 479 |
-
intersections between physical and digital retail channels have become so extensive that
|
| 480 |
-
many companies are no longer differentiating between sales made in stores and those
|
| 481 |
-
made digitally. As Saks Inc. CEO Stephen Sadove has said, “There is so much integration
|
| 482 |
-
between store and online sales that we can’t report the numbers separately. [That just
|
| 483 |
-
doesn’t] make sense, because we are moving inventory from one to another all the time.”
|
| 484 |
|
| 485 |
-
|
| 486 |
-
New devices, online offerings, and digital touch points are the engines of retail growth
|
| 487 |
-
because they streamline shopping experiences across channels and engage consumers on
|
| 488 |
-
their own terms. Novel technologies also enable businesses to gather a massive amount
|
| 489 |
-
of customer data, which can then be used to personalize marketing messages and shift
|
| 490 |
-
inventory to the right places. However, given the abundance of tools and technologies
|
| 491 |
-
available, choosing the right solutions can prove challenging. The best brands are those
|
| 492 |
-
that cut through unessential capabilities and focus only on those that add significant
|
| 493 |
-
value to the customer experience.
|
| 494 |
|
| 495 |
-
|
| 496 |
-
|
| 497 |
-
be at the center of the stores of the future? Despite the relatively wide utilization of QR
|
| 498 |
-
codes in retail stores, 61% of those surveyed said that they believe that QR codes will
|
| 499 |
-
disappear on the next 2-5 years. In contrast, 71% of respondents indicated anticipation
|
| 500 |
-
that mobile wallet capabilities will become standard over the same time period. In many
|
| 501 |
-
cases, the utilization of a given capability will not just depend on how sophisticated a
|
| 502 |
-
technology is but also on how that technology can be leveraged during a customer’s
|
| 503 |
|
| 504 |
-
|
|
|
|
| 505 |
|
| 506 |
-
|
|
|
|
| 507 |
|
| 508 |
-
|
| 509 |
-
|
| 510 |
-
loyalty programs by capturing more data and improving incentives.
|
| 511 |
|
| 512 |
-
|
| 513 |
-
|
| 514 |
-
of the most successful retail technologies are the least intrusive and most intuitive for
|
| 515 |
-
consumers to interact with. This is the principle of Invisible Design: the less intrusive and
|
| 516 |
-
more streamlined a technology is, the more likely it is to become widely adopted.
|
| 517 |
|
| 518 |
-
|
| 519 |
-
next 2-5 years?
|
| 520 |
|
| 521 |
-
|
|
|
|
| 522 |
|
| 523 |
-
|
|
|
|
| 524 |
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| 525 |
-
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| 526 |
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| 527 |
-
|
| 528 |
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| 529 |
-
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|
| 530 |
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| 531 |
-
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| 532 |
|
| 533 |
-
|
| 534 |
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| 535 |
-
|
| 536 |
|
| 537 |
-
|
| 538 |
-
|
| 539 |
-
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| 540 |
-
|
| 541 |
|
| 542 |
-
|
| 543 |
|
| 544 |
-
|
| 545 |
|
| 546 |
-
|
|
|
|
|
|
|
| 547 |
|
| 548 |
-
|
| 549 |
|
| 550 |
-
|
|
|
|
|
|
|
| 551 |
|
| 552 |
-
|
| 553 |
|
| 554 |
-
|
| 555 |
|
| 556 |
-
|
| 557 |
-
standard practice in the next 2-5 years?
|
| 558 |
|
| 559 |
-
|
| 560 |
|
| 561 |
-
|
| 562 |
|
| 563 |
-
|
| 564 |
|
| 565 |
-
|
| 566 |
|
| 567 |
-
|
| 568 |
|
| 569 |
-
|
| 570 |
-
virtual displays
|
| 571 |
|
| 572 |
-
|
| 573 |
|
| 574 |
-
|
| 575 |
|
| 576 |
-
|
| 577 |
-
70
|
| 578 |
-
50
|
| 579 |
-
Becoming Standard over the next 2-5 Years
|
| 580 |
|
| 581 |
-
|
|
|
|
| 582 |
|
| 583 |
-
|
|
|
|
| 584 |
|
| 585 |
-
|
|
|
|
| 586 |
|
| 587 |
-
|
|
|
|
| 588 |
|
| 589 |
-
|
| 590 |
|
| 591 |
-
|
| 592 |
|
| 593 |
-
|
|
|
|
| 594 |
|
| 595 |
-
|
|
|
|
| 596 |
|
| 597 |
-
|
| 598 |
-
|
| 599 |
-
most exceptional in-store experiences?
|
| 600 |
|
| 601 |
-
|
|
|
|
| 602 |
|
| 603 |
-
|
| 604 |
|
| 605 |
-
|
| 606 |
|
| 607 |
-
|
| 608 |
|
| 609 |
-
|
| 610 |
|
| 611 |
-
|
| 612 |
|
| 613 |
-
|
| 614 |
|
| 615 |
-
|
| 616 |
|
| 617 |
-
|
| 618 |
|
| 619 |
-
|
| 620 |
|
| 621 |
-
|
| 622 |
-
Retailers Providing Exceptional In-Store
|
| 623 |
-
Experiences
|
| 624 |
|
| 625 |
-
|
| 626 |
|
| 627 |
-
|
|
|
|
| 628 |
|
| 629 |
-
|
| 630 |
-
technologies, there may come a time when
|
| 631 |
-
technology is seen as a more critical in-store
|
| 632 |
-
sales asset than associates.
|
| 633 |
|
| 634 |
-
|
| 635 |
-
and enjoyable shopping experience, customers will willingly turn to those technologies.
|
| 636 |
-
As those tools become more sophisticated, they may eventually supersede sales
|
| 637 |
-
associates as the greatest in-store revenue drivers.
|
| 638 |
|
| 639 |
-
|
| 640 |
-
are interacting with their products and
|
| 641 |
-
brands, businesses must prioritize a new set
|
| 642 |
-
of consumer engagement metrics alongside
|
| 643 |
-
traditional measures like conversions.
|
| 644 |
|
| 645 |
-
|
| 646 |
-
metrics, including involvement (i.e., whether or not consumers are relying on the brand
|
| 647 |
-
for information, goods, and services on an ongoing basis) and time of awareness to
|
| 648 |
-
time of satisfaction (i.e., how long it takes for a customer to acquire a good or service
|
| 649 |
-
from the time they become aware of it). Improving involvement and shortening the
|
| 650 |
-
time of awareness to time of satisfaction are becoming central objectives for businesses.
|
| 651 |
|
| 652 |
-
|
| 653 |
-
how well businesses are learning from and
|
| 654 |
-
listening to customers.
|
| 655 |
|
| 656 |
-
|
| 657 |
-
listen to customer feedback and effectively collect customer data. Stores are a great
|
| 658 |
-
source of these inputs, which enable organizations to optimize their offerings and
|
| 659 |
-
create personalized marketing messages.
|
| 660 |
|
| 661 |
-
|
| 662 |
-
the right services to the right places at the right
|
| 663 |
-
times while maintaining a consistent feel.
|
| 664 |
-
Not only must retail organizations become more agile in order to create the capabilities
|
| 665 |
-
customers demand, they must also extend those capabilities across a variety of channels
|
| 666 |
-
without detracting from the overall experience. Many retailers are struggling with this
|
| 667 |
-
cross-channel consistency, highlighting the need for them to critically evaluate how they
|
| 668 |
-
interact with customers on different media.
|
| 669 |
|
| 670 |
-
|
| 671 |
-
leveraging the right technologies and phasing
|
| 672 |
-
out anachronistic elements.
|
| 673 |
|
| 674 |
-
|
| 675 |
-
revenue, companies must replace outmoded elements with the right technologies,
|
| 676 |
-
particularly digital tools that enhance product interactions and capture key data points.
|
| 677 |
-
This requires constant re-evaluation and, occasionally, reinvention of store components
|
| 678 |
|
| 679 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 680 |
|
| 681 |
-
|
| 682 |
|
| 683 |
-
|
| 684 |
-
|
| 685 |
-
of 104 store, operations, IT, cross-channel, and retail customer experience executives
|
| 686 |
-
representing 14 industries (see Appendix B for demographic information). Survey
|
| 687 |
-
participants included decision-makers and executives with responsibility for their
|
| 688 |
-
businesses’ in-store and digital experiences and performance. In-person surveys and
|
| 689 |
-
interviews were conducted on-site at the 2014 Future Stores Conference. Data was
|
| 690 |
-
collected in June of 2014.
|
| 691 |
|
| 692 |
-
|
| 693 |
|
| 694 |
-
|
|
|
|
|
|
|
|
|
|
| 695 |
|
| 696 |
-
|
| 697 |
|
| 698 |
-
|
|
|
|
|
|
|
|
|
|
| 699 |
|
| 700 |
-
|
|
|
|
| 701 |
|
| 702 |
-
|
| 703 |
|
| 704 |
-
|
| 705 |
|
| 706 |
-
|
| 707 |
|
| 708 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 709 |
|
| 710 |
-
|
| 711 |
|
| 712 |
-
|
| 713 |
-
|
| 714 |
|
| 715 |
-
|
| 716 |
|
| 717 |
-
|
| 718 |
|
| 719 |
-
|
| 720 |
|
| 721 |
-
|
|
|
|
| 722 |
|
| 723 |
-
|
| 724 |
-
|
| 725 |
-
2% Supermarkets
|
| 726 |
-
|
| 727 |
-
1% Toys & Hobbies
|
| 728 |
-
|
| 729 |
-
14
|
| 730 |
-
|
| 731 |
-
How to Engage and Convert Consumers with Great In-Store Retail Experiences
|
| 732 |
-
|
| 733 |
-
Roles and Titles
|
| 734 |
-
|
| 735 |
-
Revenue Breakdown
|
| 736 |
-
|
| 737 |
-
15% Marketing
|
| 738 |
-
|
| 739 |
-
15% Executive
|
| 740 |
-
|
| 741 |
-
Management
|
| 742 |
-
|
| 743 |
-
15% Information
|
| 744 |
-
|
| 745 |
-
Technology
|
| 746 |
-
|
| 747 |
-
12% Omni- channel
|
| 748 |
-
|
| 749 |
-
12% Customer
|
| 750 |
-
Experience
|
| 751 |
-
|
| 752 |
-
8% eCommerce
|
| 753 |
-
|
| 754 |
-
6% Operations
|
| 755 |
-
|
| 756 |
-
6% Customer Insights
|
| 757 |
-
|
| 758 |
-
and Analytics
|
| 759 |
-
|
| 760 |
-
6% Consulting & Agency
|
| 761 |
-
|
| 762 |
-
3%
|
| 763 |
-
|
| 764 |
-
Innovation
|
| 765 |
-
|
| 766 |
-
2% Story Design &
|
| 767 |
-
|
| 768 |
-
Management
|
| 769 |
-
|
| 770 |
-
22% Less than $50 million
|
| 771 |
-
|
| 772 |
-
17% $50- ‐150 million
|
| 773 |
-
|
| 774 |
-
61% Greater than $150
|
| 775 |
-
|
| 776 |
-
million
|
| 777 |
-
|
| 778 |
-
15
|
| 779 |
-
|
| 780 |
-
How to Engage and Convert Consumers with Great In-Store Retail Experiences
|
| 781 |
-
|
| 782 |
-
“The event was fantastic.
|
| 783 |
-
It was very well executed,
|
| 784 |
-
and I have taken a lot
|
| 785 |
-
of information from the
|
| 786 |
-
event that we will be
|
| 787 |
-
working to implement in
|
| 788 |
-
our stores.”
|
| 789 |
-
|
| 790 |
-
- Chanel Chartrand, Visual
|
| 791 |
-
Merchandiser, Coastal.com
|
| 792 |
-
|
| 793 |
-
About Future Stores
|
| 794 |
-
|
| 795 |
-
Future Stores is WBR’s intensive event focused on cutting-edge omnichannel retail
|
| 796 |
-
strategies. From omnichannel marketing and customer analytics to retail technology
|
| 797 |
-
and store operations, Future Stores will show you how to design and implement
|
| 798 |
-
winning in-store strategies to beat the competition and boost customer loyalty.
|
| 799 |
-
|
| 800 |
-
The conference is centered on the pain points of store, operations, IT, cross-channel
|
| 801 |
-
and customer experience executives to bridge the gap between the store experience
|
| 802 |
-
and the digital experience. Future Stores provides tactical strategies for brick and
|
| 803 |
-
mortar retailers to improve and increase conversion rates in-store as well as make the
|
| 804 |
-
store and cross-channel shopping experiences as seamless and easy as they are online.
|
| 805 |
-
|
| 806 |
-
About CFI Group
|
| 807 |
-
|
| 808 |
-
CFI Group is a global leader in providing customer feedback insights through analytics.
|
| 809 |
-
CFI Group provides a technology platform that leverages the science of the American
|
| 810 |
-
Customer Satisfaction Index (ACSI). This platform continuously measures the customer
|
| 811 |
-
experience across multiple channels, benchmarks performance, and prioritizes
|
| 812 |
-
improvements for maximum impact.
|
| 813 |
-
|
| 814 |
-
Founded in 1988 and headquartered in Ann Arbor, Michigan, CFI Group serves
|
| 815 |
-
global clients from a network of offices worldwide. Our clients span a variety of
|
| 816 |
-
industries, including financial services, hospitality, manufacturing, telecom, retail, and
|
| 817 |
-
government. Regardless of your industry, we can put the power of our technology and
|
| 818 |
-
the science of the ACSI methodology to work for you.
|
| 819 |
-
|
| 820 |
-
CFI Group USA, L.L.C.
|
| 821 |
-
625 Avis Drive
|
| 822 |
-
Ann Arbor, MI 48108
|
| 823 |
-
(734) 930-9090
|
| 824 |
-
Askcfi@cfigroup.com
|
| 825 |
-
|
| 826 |
-
16
|
| 827 |
-
|
| 828 |
-
How to Engage and Convert Consumers with Great In-Store Retail ExperiencesAbout WBR &
|
| 829 |
-
WBR Digital
|
| 830 |
-
|
| 831 |
-
WBR is the world’s biggest large-scale conference company and part of the PLS group,
|
| 832 |
-
one of the world’s leading providers of strategic business intelligence with 16 offices
|
| 833 |
-
worldwide. Our conference divisions consistently out-perform their industry sector
|
| 834 |
-
competitors on the quality of the events we produce and the relationships we nurture
|
| 835 |
-
with both attendees and sponsors.
|
| 836 |
-
|
| 837 |
-
Every year, over 10,000 senior executives from Fortune 1,000 companies attend over
|
| 838 |
-
100 of our annual conferences – a true “Who’s Who” of today’s corporate world.
|
| 839 |
-
From Automotive events in Bucharest to Logistics conferences in Arizona to Luxury
|
| 840 |
-
conferences in New York and Finance summits in Hong Kong, WBR is dedicated to
|
| 841 |
-
exceeding the needs of its customers around the world.
|
| 842 |
-
|
| 843 |
-
In addition to our industry leading conferences, our professional services marketing
|
| 844 |
-
division, WBR Digital, connects solutions providers to their target audiences with
|
| 845 |
-
digital branding and engagement services and lead generation campaigns. WBR’s
|
| 846 |
-
marketers act as an extension of your team, relieving strain on your internal resources
|
| 847 |
-
while engaging with customers and prospects on your brand and solutions. Solutions
|
| 848 |
-
providers can target identified accounts or relevant industry/function segments of WBR’s
|
| 849 |
-
global database of senior-level decision makers.
|
| 850 |
-
|
| 851 |
-
Contact:
|
| 852 |
-
Andrew Cole
|
| 853 |
-
Digital Content Manager
|
| 854 |
-
646-200-7541
|
| 855 |
-
Andrew.Cole@wbresearch.com
|
| 856 |
-
|
| 857 |
-
Be a Part of Next Year’s
|
| 858 |
-
Future Stores Conference
|
| 859 |
-
|
| 860 |
-
Be a part of next year’s event and discuss the new trends shaping the retail industry.
|
| 861 |
-
|
| 862 |
-
Click To Register Now
|
| 863 |
-
|
| 864 |
-
Call our customer service team to get the best available discounts for your firm at
|
| 865 |
-
1.888.482.6012, or email us at futurestores@wbresearch.com
|
| 866 |
-
|
| 867 |
-
17
|
| 868 |
-
|
| 869 |
-
How to Engage and Convert Consumers with Great In-Store Retail ExperiencesWhat did you think? Rate this content and help us improve!
|
| 870 |
-
|
| 871 |
-
“An organization’s ability to learn, and translate that learning into
|
| 872 |
-
action rapidly, is the ultimate competitive advantage.” - Jack Welch
|
| 873 |
-
|
| 874 |
-
It is our goal to produce relevant, valuable content to help inform
|
| 875 |
-
your strategic business decisions, so we would love to know what
|
| 876 |
-
you thought of this report. Your feedback goes directly to our
|
| 877 |
-
content team and helps us to improve.
|
| 878 |
-
|
| 879 |
-
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|
| 880 |
-
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| 881 |
-
|
| 882 |
-
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|
| 883 |
-
|
| 884 |
-
18
|
| 885 |
-
|
| 886 |
-
How to Engage and Convert Consumers with Great In-Store Retail Experiences
|
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Here’s how you know
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Here’s how you know
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**Official websites use .gov**
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| 12 |
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| 13 |
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A
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**lock**
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(
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) or
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**https://**
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means you’ve safely connected to the .gov website. Share sensitive
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information only on official, secure websites.
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[](/ "HealthIt.gov")
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Menu
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[Skip Navigation](#ubermenu-main-36-skipnav)
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* Topics
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+ - Featured
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* ## Featured
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* [Certification of Health IT](/certification-health-it/)
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| 44 |
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Ensures health IT meets standards for functionality, security, and interoperability.
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| 46 |
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* [Information Blocking](https://healthit.gov/information-blocking/)
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Regulations ensuring health data is shared appropriately without improper barriers.
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* [Interoperability](/interoperability/)
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Enables secure and seamless exchange of electronic health information among authorized users.
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* [Health Information Technology Advisory Committee (HITAC)](/hitac/)
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Advises on policies, standards, and implementation specifications for health data and technology.
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* [United States Core Data for Interoperability (USCDI)](https://isp.healthit.gov/united-states-core-data-interoperability-uscdi)
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Offers a standardized set of health data classes and constituent data elements for nationwide, interoperable health information exchange.
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| 58 |
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* [Trusted Exchange Framework & Common Agreement (TEFCA)](https://healthit.gov/policy/tefca/)
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| 59 |
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Operates as a nationwide framework for the interoperability of electronic health information.
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- Artificial Intelligence
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* ## Artificial Intelligence
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* [Artificial Intelligence (AI) at HHS](https://healthit.gov/artificial-intelligence/)
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HHS’ list of AI use cases is publicly available to search and reference. In addition to AI use case summaries, the inventory also includes information on data, IT infrastructure, internal governance, and much more.
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- Care Continuum
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* ## Care Continuum
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Explore the roles of health information and technology in broad healthcare settings, supporting seamless, coordinated patient care from prevention through recovery.
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* ### Care Settings
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* [Behavioral Health](https://healthit.gov/behavioral-health/)
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Health information, policies, and technology supporting integrated care for mental health and substance use disorders.
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* [Emergency Medical Services](https://healthit.gov/emergency-medical-services/)
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Rapid response and communication during health emergencies through health information and technology.
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* [Long-Term & Post-Acute Care](https://healthit.gov/long-term-and-post-acute-care/)
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Health information and technology facilitating coordinated care beyond acute settings.
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| 82 |
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* [Maternal & Pediatric Care](https://healthit.gov/maternal-and-pediatric-care/)
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| 84 |
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Technology addressing unique health needs of mothers and children.
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| 85 |
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* [Pharmacy & PDMP](/pharmacy-pdmp/)
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Electronic tools tracking controlled substance prescriptions to improve patient safety.
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* [Public Health](https://healthit.gov/public-health/)
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Using health information and technology to prevent disease, diagnose health conditions, and promote population health.
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| 91 |
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* ### Clinical Topics
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| 92 |
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* [Clinical Quality & Safety](/clinical-quality-and-safety/)
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| 94 |
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Optimal care through measuring results, prioritizing improvements, and implementing and monitoring results.
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| 95 |
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* [Usability & Provider Burden](/usability-and-provider-burden/)
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| 97 |
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Promotes health information and technology usability to reduce clinician burden and enhance patient care.
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- Interoperability
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* ## Interoperability
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Promotes standardized exchange and use of electronic health data to improve patient care, coordination, and public health outcomes.
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* [Health IT Interoperability](/interoperability/)
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| 104 |
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| 105 |
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Enables secure and seamless exchange of electronic health information among authorized users.
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| 106 |
+
* [Trusted Exchange Framework & Common Agreement (TEFCA)](/interoperability/trusted-exchange-framework-and-common-agreement-tefca/)
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| 107 |
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| 108 |
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Facilitates secure, nationwide electronic health information sharing to connect providers, patients, public health agencies, and payers.
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* [Certification of Health IT](/certification-health-it/)
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Provides certification criteria for developers of health IT modules that ensures health IT products meet the standards for functionality, security, and interoperability.
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* [Standards & Technology](/standards-and-technology/)
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Advance healthcare quality and safety through standardized health IT and secure health data exchange.
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* [Information Blocking](https://healthit.gov/information-blocking/)
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Prevents practices that interfere with the access, exchange, or use of electronic health information, as defined by the Cures Act.
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* [Interoperability Standards Platform](https://www.healthit.gov/isp/)
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Serves as a homepage for tools and resources for understanding and using health IT standards and technologies.
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* [Investments](/investments/)
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Support interoperability improvements nationwide.
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* [Health IT & Health Information Exchange Basics](https://healthit.gov/health-it-basics/)
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Enable secure electronic sharing and access of patient health information, supporting healthcare providers and patients across care settings.
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* [Patient Access to Health Records](https://healthit.gov/patient-access-to-health-records/)
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| 129 |
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Ensure patients have secure and convenient access to their health records, supported by healthcare providers and health IT developers under HIPAA.
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- Policy
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* + ## [Policy](/policy/)
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+

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Outlines federal regulations and strategic initiatives guiding effective use and secure exchange of electronic health information.
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| 136 |
+
+ - [Legislation](https://healthit.gov/legislation/)
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| 137 |
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| 138 |
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Delivers improvements in the delivery and experience of health care while enhancing health outcomes by leveraging health information technology.
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- [Regulations](/regulations/)
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Supports the adoption and promotion of standards-based health information.
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- [TEFCA](/interoperability/trusted-exchange-framework-and-common-agreement-tefca/)
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Operates as a nationwide framework for the interoperability of electronic health information.
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- [HHS Health IT Alignment Program](/hhs-health-it-alignment-program/)
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| 146 |
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| 147 |
+
Coordinates health data and technology initiatives across HHS to enhance interoperability and effectiveness.
|
| 148 |
+
- [Health Information Technology Advisory Committee (HITAC)](/hitac/)
|
| 149 |
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| 150 |
+
Advises on policies, standards, and implementation specifications for health data and technology.
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- [Privacy & Security](/privacy-security/)
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+
Protects electronic health information security through policy.
|
| 154 |
+
* + ### Rulemaking
|
| 155 |
+
+ [HTI Rules](https://healthit.gov/regulations/hti-rules/)
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| 156 |
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| 157 |
+
Health data interoperability regulations ensuring secure, effective technology use.
|
| 158 |
+
+ [Information Blocking](https://healthit.gov/information-blocking/)
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| 159 |
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| 160 |
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Policies to prevent practices interfering with the access, exchange, and use of electronic health information.
|
| 161 |
+
+ [Certification Program Rules](/certification-program-regulations/)
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| 162 |
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| 163 |
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Ensures health IT meets standards for functionality, security, and interoperability.
|
| 164 |
+
- Research & Analysis
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* ## [Research & Analysis](/data/)
|
| 167 |
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| 168 |
+

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| 169 |
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| 170 |
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Interactive datasets related to health IT data analysis, providing insights into adoption and use.
|
| 171 |
+
* [Dashboards](/data/search/?postType=dashboard)
|
| 172 |
|
| 173 |
+
Gives data-driven insight on how dashboards are driving health IT adoption and how they have helped users to meet federal healthcare incentives or programs.
|
| 174 |
+
* [Data Briefs](/data/search/?postType=data-brief)
|
| 175 |
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| 176 |
+
Provides health IT adoption and use statistics derived from surveys and administrative data and in-depth analysis of health IT policies and programs.
|
| 177 |
+
* [Datasets](/data/search/?postType=dataset)
|
| 178 |
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| 179 |
+
Grants access to raw datasets from ONC related to health IT adoption, health IT capabilities and other topics.
|
| 180 |
+
* [Quick Stats](/data/search/?postType=quick-stat)
|
| 181 |
|
| 182 |
+
Streamlines data into visualizations of key data and summarizes the latest statistics, facts and figures about health IT.
|
| 183 |
+
* [About Health IT Research & Analysis](https://healthit.gov/data/about/)
|
| 184 |
|
| 185 |
+
Provides information about how health IT data are collected, analyzed, and published.
|
| 186 |
+
* Resources & Tools
|
| 187 |
+
+ - Featured
|
| 188 |
|
| 189 |
+
* ## Featured Resources & Tools
|
| 190 |
|
| 191 |
+
Highlights key tools and guidance supporting effective health IT implementation, interoperability, patient engagement, and compliance with federal standards.
|
| 192 |
+
* [Interoperability Standards](https://www.healthit.gov/isp/)
|
| 193 |
|
| 194 |
+
ONC’s initiatives in health data standards enable secure electronic health data exchange.
|
| 195 |
+
* [TEFCA Resources](https://healthit.gov/resources/?topics=tefca)
|
| 196 |
|
| 197 |
+
Data sheets, videos, and documents to guide users of the TEFCA framework and exchange.
|
| 198 |
+
* [Implementation Resources](https://healthit.gov/resources/?search-text=Implementation+Resources)
|
| 199 |
|
| 200 |
+
Technical resources and tools supporting healthcare providers, clinicians, and developers of health IT products.
|
| 201 |
+
* [Health IT Playbook](https://www.healthit.gov/playbook/)
|
| 202 |
|
| 203 |
+
Strategies, recommendations, and best practices for implementing and using health data and technology.
|
| 204 |
+
* [Security Risk Assessment Tool](https://healthit.gov/privacy-security/security-risk-assessment-tool/)
|
|
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| 205 |
|
| 206 |
+
Desktop application supporting providers conducting HIPAA security risk assessments.
|
| 207 |
+
* [Patient Engagement Playbook](https://www.healthit.gov/playbook/pe/)
|
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|
| 208 |
|
| 209 |
+
Practical reference tool for clinicians, staff, and other innovators around the world to improve patient engagement.
|
| 210 |
+
* [Certified Health IT Product List (CHPL)](https://chpl.healthit.gov/)
|
| 211 |
|
| 212 |
+
A comprehensive and authoritative listing of successfully tested and certified health IT modules.
|
| 213 |
+
* [Conformance Test Tools & Edge Testing Tool](https://healthit.gov/onc-conformance-test-tools/)
|
| 214 |
|
| 215 |
+
Resources for developers implementing standards to enable health information interoperability.
|
| 216 |
+
* [Health IT Feedback Form](https://inquiry.healthit.gov/support/plugins/servlet/desk/portal/2)
|
| 217 |
|
| 218 |
+
Users can submit feedback regarding health data and technology usability, interoperability, and compliance issues.
|
| 219 |
+
- Resources
|
| 220 |
|
| 221 |
+
* ## [Resources](/resources/)
|
|
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|
| 222 |
|
| 223 |
+

|
| 224 |
|
| 225 |
+
Collection of practical materials, videos, educational tools, and user guides designed to support successful implementation and adoption of health IT systems.
|
| 226 |
+
* [Get It, Check It, Use It Guide](https://healthit.gov/get-it-check-it-use-it/)
|
|
|
|
| 227 |
|
| 228 |
+
A guide for patients and caregivers who want to access, review, and use their health records.
|
| 229 |
+
* [Video Resources](https://healthit.gov/resources/?resource_types=video)
|
| 230 |
|
| 231 |
+
A repository of informational videos created by ONC.
|
| 232 |
+
* [Health IT Curriculum Resources for Educators](https://healthit.gov/health-it-basics/health-it-curriculum-resources-educators/)
|
| 233 |
|
| 234 |
+
Instructional materials to help healthcare workers stay current in the changing healthcare environment and deliver care more effectively.
|
| 235 |
+
* [Fact Sheets](https://healthit.gov/resources/?resource_types=fact-sheet)
|
| 236 |
|
| 237 |
+
A repository of fact sheets created by ONC.
|
| 238 |
+
- Tools & Technology
|
| 239 |
+
* + ### Implementation
|
| 240 |
+
+ [Certified Health IT Product List](https://chpl.healthit.gov/)
|
| 241 |
|
| 242 |
+
A comprehensive and authoritative listing of successfully tested and certified health IT modules.
|
| 243 |
+
+ [Electronic Clinical Quality Improvement Resource Center](https://ecqi.healthit.gov/)
|
| 244 |
|
| 245 |
+
Provides common standards and shared technologies to monitor and analyze the quality of health care and patient outcomes.
|
| 246 |
+
+ [Security Risk Assessment Tool](https://healthit.gov/privacy-security/security-risk-assessment-tool/)
|
| 247 |
|
| 248 |
+
Desktop application supporting providers conducting HIPAA security risk assessments.
|
| 249 |
+
* + ### Tools
|
| 250 |
+
+ [Edge Testing Tool](https://site.healthit.gov/)
|
| 251 |
|
| 252 |
+
A centralized collection of testing tools and resources supporting health IT developers and users fully evaluating specific technical standards.
|
| 253 |
+
+ [Conformance Test Tools](https://healthit.gov/onc-conformance-test-tools/)
|
|
|
|
| 254 |
|
| 255 |
+
ONC-approved conformance resources supporting developers implementing standards to enable health information interoperability.
|
| 256 |
+
+ [Get It, Check It, Use It Guide](https://healthit.gov/get-it-check-it-use-it/)
|
| 257 |
|
| 258 |
+
A guide for patients and caregivers who want to access, review, and use their health records.
|
| 259 |
+
* + ### Quick Links
|
| 260 |
+
+ [Certification & Testing](https://healthit.gov/onc-health-it-certification-program-test-method/)
|
| 261 |
+
+ [USCDI](https://isp.healthit.gov/united-states-core-data-interoperability-uscdi)
|
| 262 |
+
+ [USCDI+](https://healthit.gov/standards-and-technology/uscdi-plus/)
|
| 263 |
+
+ [Interoperability Standards Platform (ISP)](https://isp.healthit.gov/)
|
| 264 |
+
+ [FHIR](https://healthit.gov/fhir)
|
| 265 |
+
+ [ONC Standards Bulletins](https://healthit.gov/standards-and-technology/onc-standards-bulletin/)
|
| 266 |
+
+ [Patient ID & Matching Adopted Standards for HHS](https://healthit.gov/standards-and-technology/patient-identity-and-patient-record-matching/)
|
| 267 |
+
* News & Events
|
| 268 |
|
| 269 |
+
+ - [Media Center](/media-center)
|
| 270 |
+
- [News](/news)
|
| 271 |
+
- [Events](/events)
|
| 272 |
+
+ - ## Latest News & Events
|
| 273 |
+
- ### Upcoming Event
|
| 274 |
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| 275 |
+
[
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+
**June 25, 2026**
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| 278 |
|
| 279 |
+
#### Adoption of AI in Clinical Care: Updates from the HHS RFI](https://healthit.gov/event/adoption-of-ai-in-clinical-care-updates-from-the-hhs-rfi/)
|
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| 280 |
|
| 281 |
+
### Latest Blog
|
|
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|
| 282 |
|
| 283 |
+
[
|
| 284 |
|
| 285 |
+
**February 4, 2026**
|
| 286 |
|
| 287 |
+
#### Advancing the Future of Behavioral Health Data Exchange](https://healthit.gov/blog/behavioral-health/advancing-the-future-of-behavioral-health-data-exchange/)
|
| 288 |
|
| 289 |
+
### Recent News
|
| 290 |
|
| 291 |
+
[
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|
| 292 |
|
| 293 |
+
**April 20, 2026**
|
| 294 |
|
| 295 |
+
#### New Data Brief: Electronic Health Record Adoption and Exchange Capabilities Among Substance Use and Mental Health Treatment Facilities, 2024](https://healthit.gov/data/data-briefs/electronic-health-record-adoption-and-exchange-capabilities-among-substance-use-and-mental-health-treatment-facilities-2024/)
|
| 296 |
+
* About
|
| 297 |
+
+ - Overview
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| 298 |
|
| 299 |
+
* [About ONC](https://healthit.gov/about/)
|
|
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|
| 300 |
|
| 301 |
+
Mission, role, and responsibilities of ONC.
|
| 302 |
+
* [Leadership](/about/leadership)
|
| 303 |
|
| 304 |
+
Profiles of ONC’s senior leadership team.
|
| 305 |
+
* [History](https://healthit.gov/about/history/)
|
| 306 |
|
| 307 |
+
Timeline of ONC’s evolution and key milestones.
|
| 308 |
+
* [Budget & Performance](https://healthit.gov/about/onc-budget-and-performance/)
|
| 309 |
|
| 310 |
+
Financial reports and performance accountability.
|
| 311 |
+
* [Investments](https://healthit.gov/interoperability/investments/)
|
| 312 |
|
| 313 |
+
Strategic investments in programs, policies, and technology.
|
| 314 |
+
* [Reports to Congress](/reports-congress/)
|
| 315 |
|
| 316 |
+
Annual health data and technology progress updates to Congress.
|
| 317 |
+
- Careers
|
| 318 |
|
| 319 |
+
* [Careers at ONC](https://healthit.gov/about/careers/)
|
|
|
|
|
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|
| 320 |
|
| 321 |
+
View opportunities with ONC.
|
| 322 |
+
* [Working at ONC](https://healthit.gov/about/careers/working-at-onc/)
|
| 323 |
|
| 324 |
+
Overview of workplace culture and employee experience.
|
| 325 |
+
- Contact
|
|
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| 326 |
|
| 327 |
+
* [Contact Us](https://healthit.gov/contact-us/)
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|
| 328 |
|
| 329 |
+
Reach ONC with general inquiries.
|
| 330 |
+
* [Health IT Feedback Form](https://www.healthit.gov/feedback)
|
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| 331 |
|
| 332 |
+
Users can submit feedback regarding health data and technology usability, interoperability, and compliance issues.
|
| 333 |
+
* [Report Issue with Certified Health IT](/certification-health-it/certified-health-it-complaint-process/)
|
| 334 |
|
| 335 |
+
Complaint process to resolve any issues of potential noncompliance with certification requirements.
|
| 336 |
+
* [Information Blocking Claim](https://healthit.gov/report-info-blocking)
|
| 337 |
|
| 338 |
+
Form to report alleged information blocking practices.
|
| 339 |
+
* [Speaker Request](https://healthit.gov/speaker-request-form/)
|
|
|
|
| 340 |
|
| 341 |
+
Form to request ONC experts for speaking engagements.
|
| 342 |
+
- Funding Opportunities
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|
| 343 |
|
| 344 |
+
* [Funding Announcements](https://healthit.gov/about/funding-announcements/)
|
|
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|
| 345 |
|
| 346 |
+
ONC’s contractors and grantees play a valuable role in helping promote better health care for Americans by fostering interoperable health data and technology.
|
| 347 |
+
* [Grants Management & Process](https://healthit.gov/about/onc-grants-cooperative-agreements/)
|
| 348 |
|
| 349 |
+
Learn about opportunities for funding through grants and cooperative agreements.
|
| 350 |
+
* [Blog](/blog/)
|
| 351 |
|
| 352 |
+
Search
|
| 353 |
|
| 354 |
+

|
| 355 |
|
| 356 |
+
Popular searches:
|
| 357 |
+
[certification](https://healthit.gov/?swp_form%5Bform_id%5D=1&swps=certification)
|
| 358 |
+
[information blocking](https://healthit.gov/?swp_form%5Bform_id%5D=1&swps=information%20blocking)
|
| 359 |
+
[interoperability](https://healthit.gov/?swp_form%5Bform_id%5D=1&swps=interoperability)
|
| 360 |
|
| 361 |
+
1. Home
|
| 362 |
|
| 363 |
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|
| 364 |
|
| 365 |
+
The page you’re looking for is not available on our current site. To look for it, you can:
|
| 366 |
|
| 367 |
+
* Double-check the web address for any mistakes.
|
| 368 |
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* Use our search.
|
| 369 |
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* Visit our archives.
|
| 370 |
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* [Return to our front page](/).
|
| 371 |
|
| 372 |
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|
| 373 |
|
| 374 |
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#### Get in Touch
|
| 375 |
|
| 376 |
+
* [Health IT Feedback & Inquiry Form](/feedback)
|
| 377 |
+
* [ONC Speaker Form](/speaker-request-form/)
|
| 378 |
+
* [Contact Us](/about/contact)
|
| 379 |
|
| 380 |
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#### Get Involved
|
| 381 |
|
| 382 |
+
* [Careers](/about/careers/)
|
| 383 |
+
* [Events](/events/)
|
| 384 |
+
* [Funding Opportunities](/about/funding-announcements/)
|
| 385 |
|
| 386 |
+
[Submit Feedback](#helpful-modal)
|
| 387 |
|
| 388 |
+
## Submit Feedback
|
| 389 |
|
| 390 |
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Step 1 of 3
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| 409 |
|
| 410 |
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| 411 |
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| 412 |
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| 413 |
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Desktop
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| 433 |
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Mobile
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| 434 |
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| 435 |
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| 436 |
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Not device specific
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| 437 |
|
| 438 |
+
Select the type of issue you encountered. Select all that apply.
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| 439 |
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| 440 |
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| 441 |
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| 444 |
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| 447 |
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What page did you find this issue? e.g. Interoperability, ONC Blog
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| 449 |
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| 451 |
|
| 452 |
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e.g. https://healthit.gov/interoperability
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| 453 |
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| 454 |
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Describe the issue you've encountered.(Required)
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| 455 |
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| 456 |
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Please provide a detailed description of the issue you experienced.
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| 457 |
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| 458 |
+
Upload Screenshots or Files (optional)
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| 459 |
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| 460 |
+
Drop files here or
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| 461 |
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Select files
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| 462 |
|
| 463 |
+
Max. file size: 3 MB, Max. files: 3.
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| 464 |
|
| 465 |
+
If you have any screenshots or files related to the issue, please upload them here.
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|
| 466 |
|
| 467 |
+
* Cancel
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|
| 468 |
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| 469 |
+

|
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|
| 470 |
|
| 471 |
+
### Subscribe for Email Updates
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|
| 472 |
|
| 473 |
+
URL
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|
| 474 |
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| 475 |
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This field is for validation purposes and should be left unchanged.
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|
| 476 |
|
| 477 |
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Email(Required)
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| 478 |
|
| 479 |
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#### EXPLORE
|
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|
|
| 480 |
|
| 481 |
+
* [Certification of Health IT](https://healthit.gov/certification-health-it/)
|
| 482 |
+
* [Information Blocking](https://healthit.gov/information-blocking/)
|
| 483 |
+
* [Interoperability](https://healthit.gov/interoperability/)
|
| 484 |
+
* [Health Information Technology Advisory Committee (HITAC)](https://healthit.gov/hitac/)
|
| 485 |
+
* [Patient Access to Health Records](https://healthit.gov/patient-access-to-health-records/)
|
| 486 |
+
* [TEFCA](https://healthit.gov/policy/tefca/)
|
| 487 |
+
* [Policy](https://healthit.gov/policy/)
|
| 488 |
+
* [Resources](https://healthit.gov/resources/)
|
| 489 |
|
| 490 |
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#### DATA
|
| 491 |
|
| 492 |
+
* [HealthData.gov](https://healthdata.gov/)
|
| 493 |
+
* [Health IT Research & Analysis](/data/)
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|
| 494 |
|
| 495 |
+
#### NEWS & EVENTS
|
| 496 |
|
| 497 |
+
* [Media Center](https://healthit.gov/media-center)
|
| 498 |
+
* [ONC Blog](/blog/)
|
| 499 |
+
* [News](/news)
|
| 500 |
+
* [Events](/events)
|
| 501 |
|
| 502 |
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#### ABOUT
|
| 503 |
|
| 504 |
+
* [About ONC](/about/)
|
| 505 |
+
* [Careers](/about/careers/)
|
| 506 |
+
* [Contact](/contact-us/)
|
| 507 |
+
* [Funding Opportunities](/about/funding-announcements/)
|
| 508 |
|
| 509 |
+
[](https://healthit.gov/ "ONC")
|
| 510 |
+
[](https://hhs.gov/ "HHS Link")
|
| 511 |
|
| 512 |
+
[Linkedin](https://www.linkedin.com/company/office-of-the-national-coordinator-for-health-it)
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| 513 |
|
| 514 |
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[X](https://x.com/ONC_HealthIT)
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| 515 |
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| 516 |
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[YouTube](http://www.youtube.com/user/HHSONC/)
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| 517 |
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| 518 |
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* [Privacy Policy](https://www.hhs.gov/web/policies-and-standards/hhs-web-policies/privacy/index.html)
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| 519 |
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* [Website Disclaimers](/website-disclaimers/)
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| 520 |
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* [Viewers & Players](http://www.hhs.gov/plugins.html)
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| 521 |
+
* [GobiernoUSA.gov](https://gobierno.usa.gov/)
|
| 522 |
+
* [HHS Vulnerability Disclosure Policy](https://www.hhs.gov/vulnerability-disclosure-policy/index.html)
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| 523 |
+
* [Archived Content](https://healthit.gov/archive/)
|
| 524 |
|
| 525 |
+
### External Link Notice
|
| 526 |
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| 527 |
+
Continue
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| 528 |
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Cancel
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| 530 |
+
×
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| 532 |
+
## Welcome to HealthIT.gov!
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| 533 |
|
| 534 |
+
Thank you for visiting the HealthIT.gov website! We welcome your feedback using the "Submit Feedback" button at the bottom of the page to help us improve your experience!
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| 535 |
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* Close
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if you’re not engaged in social media listening, you’re creating your business
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tKnowing who your audience is and what they want to see on social is key to
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creating content that they will like, comment on, and share. This knowledge
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also critical for planning how to develop your social media fans into
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different personas based on demographics, buying motivations, common
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buying objections, and the emotional needs of each type of customer.
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dominant player.
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|
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As you track your competitors’ accounts and relevant industry keywords, you
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|
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one that bombs.
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How to conduct a
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competitor audit
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Getting started with
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social listening
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Watch: How to set up
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social listening streams
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GUIDE / Social Media Marketing Strategy
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Once you gather all this information in one place, you’ll have a good starting
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point for planning how to improve your results.
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Your audit should give you a clear picture of what purpose each of your
|
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social accounts serves. If the purpose of an account isn’t clear, think about
|
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whether it’s worth keeping. It may be a valuable account that just needs
|
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a strategic redirection, or it may be an outdated account that’s no longer
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worth your while.
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To help you decide, ask yourself the following questions:
|
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1. Is my audience here?
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2. If so, how are they using this platform?
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3. Can I use this account to help achieve meaningful business goals?
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Asking these tough questions now will help keep your social media strategy
|
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on track as you grow your social presence.
|
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Look for impostor accounts
|
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During your audit process, you may discover fraudulent accounts using your
|
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business name or the names of your products—that is, accounts that you
|
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and your business don’t own.
|
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These imposter accounts can be harmful to your brand (never mind
|
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capturing followers that should be yours), so be sure to report them. You
|
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may want to get your social accounts verified to ensure your fans and
|
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followers know they are dealing with the real you.
|
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GUIDE / Social Media Marketing Strategy
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accounts.
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Determine which networks to use (and how to use them)
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As you decide which social channels to use, you’ll also need to define your
|
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strategy for each network. For example, you might decide to use Twitter for
|
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customer service, Facebook for customer acquisition, and Instagram for
|
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engaging existing customers.
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It’s a good exercise to create mission statements for each network. These
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one-sentence declarations will help you focus on a very specific goal for
|
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each account on each social network.
|
| 334 |
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For example, you could decide that:
|
| 336 |
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•• Facebook is best for acquiring new customers via paid advertising.
|
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••
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Instagram is where you build brand affinity with existing customers.
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•• Twitter is where you engage press and industry influencers.
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•• LinkedIn is where you engage existing employees and attract new talent.
|
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•• YouTube is where you support existing customers with education and
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video help content.
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•• Snapchat is where you distribute content with the goal of building brand
|
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awareness with younger consumers.
|
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|
| 355 |
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If you can’t create a solid mission statement for a particular social network,
|
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you may want to reconsider whether that network is worth it.
|
| 357 |
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Set up (and optimize) your accounts
|
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| 360 |
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Once you’ve decided which networks to focus on, it’s time to create your
|
| 361 |
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profiles—or improve existing profiles so they align with your strategic plan.
|
| 362 |
-
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In general, make sure you fill out all profile fields, use keywords people will
|
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use to search for your business, and use images that are correctly sized for
|
| 365 |
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each network.
|
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| 367 |
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GUIDE / Social Media Marketing Strategy
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7
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Award-winning accounts and campaigns
|
| 387 |
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|
| 388 |
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For examples of brands that are at the top of their social media game, check
|
| 389 |
-
out the winners of The Facebook Awards or The Shorty Awards.
|
| 390 |
-
|
| 391 |
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Step 7
|
| 392 |
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|
| 393 |
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Create a social media content calendar
|
| 394 |
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|
| 395 |
-
Sharing great content is essential, of course, but it’s equally important to have
|
| 396 |
-
a plan in place for when you’ll share content to get the maximum impact.
|
| 397 |
-
|
| 398 |
-
Your social media content calendar also needs to account for the time you’ll
|
| 399 |
-
spend interacting with your audience (although you need to allow for some
|
| 400 |
-
spontaneous engagement as well).
|
| 401 |
-
|
| 402 |
-
Create a posting schedule
|
| 403 |
-
|
| 404 |
-
Your social media content calendar lists the dates and times at which you will
|
| 405 |
-
publish types of content on each channel. It’s the perfect place to plan all of your
|
| 406 |
-
social media activities—from images and link sharing to blog posts and videos.
|
| 407 |
-
|
| 408 |
-
Your calendar ensures your posts are spaced out appropriately and
|
| 409 |
-
published at the optimal times. It should include both your day-to-day posts
|
| 410 |
-
and your content for social media campaigns.
|
| 411 |
-
|
| 412 |
-
Related resources
|
| 413 |
-
|
| 414 |
-
How to create a social
|
| 415 |
-
media content calendar
|
| 416 |
-
|
| 417 |
-
Watch: How to save time
|
| 418 |
-
with bulk scheduling
|
| 419 |
-
|
| 420 |
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GUIDE / Social Media Marketing Strategy
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|
| 485 |
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use UTM parameters to track visitors as they move through your website, so
|
| 486 |
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you can see exactly which social posts drive the most traffic to your website.
|
| 487 |
-
|
| 488 |
-
Re-evaluate, test, and do it all again
|
| 489 |
-
|
| 490 |
-
When data starts coming in, use it to reevaluate your strategy regularly.
|
| 491 |
-
You can also use this information to test different posts, campaigns, and
|
| 492 |
-
strategies against one another. Constant testing allows you to understand
|
| 493 |
-
what works and what doesn’t, so you can refine your strategy in real time.
|
| 494 |
-
|
| 495 |
-
Surveys can also be a great way to find out how well your strategy is working.
|
| 496 |
-
Ask your social media followers, email list, and website visitors whether
|
| 497 |
-
you’re meeting their needs and expectations on social media. You can even
|
| 498 |
-
ask them what they’d like to see more of—and then make sure to deliver on
|
| 499 |
-
what they tell you.
|
| 500 |
-
|
| 501 |
-
Things change fast on social media. New networks emerge, while others
|
| 502 |
-
go through significant demographic shifts. Your business will go through
|
| 503 |
-
periods of change as well. All this means that your social media strategy
|
| 504 |
-
should be a living document that you look at regularly and adjust as needed.
|
| 505 |
-
Refer to it often to keep you on track, but don’t be afraid to make changes
|
| 506 |
-
so that it better reflects new goals, tools, or plans.
|
| 507 |
-
|
| 508 |
-
When you update your social strategy, make sure to let everyone on your
|
| 509 |
-
social team know, so they can all work together to help your business make
|
| 510 |
-
the most of your social media accounts.
|
| 511 |
-
|
| 512 |
-
GUIDE / Social Media Marketing Strategy
|
| 513 |
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| 514 |
10
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11
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|
| 1 |
+
FOR IMMEDIATE RELEASE Herzogenaurach, March 9, 2022
|
| 2 |
+
adidas delivers strong results in 2021 and
|
| 3 |
+
expects double-digit sales growth in 2022
|
| 4 |
+
Major developments FY 2021
|
| 5 |
+
• Currency-neutral revenues up 16% driven by growth in all markets
|
| 6 |
+
• Excellent top-line momentum in EMEA, North America and Latin America with strong
|
| 7 |
+
double-digit increases in each region
|
| 8 |
+
• Double-digit growth in DTC reflecting improvements in both online and offline
|
| 9 |
+
• Gross margin increases to 50.7% driven by higher full-price sales and better inventory
|
| 10 |
+
management
|
| 11 |
+
• Operating margin increases 5.3 percentage points to 9.4%
|
| 12 |
+
• Net income from continuing operations grows more than € 1 billion to € 1.492 billion
|
| 13 |
+
• Executive and Supervisory Boards propose dividend increase of 10% to € 3.30 per share
|
| 14 |
+
Outlook for FY 2022
|
| 15 |
+
• Currency-neutral sales to increase at a rate between 11% and 13%, already reflecting
|
| 16 |
+
up to € 250 million of risk in Russia/CIS business related to the war in Ukraine
|
| 17 |
+
• Gross margin to increase to a level of between 51.5% and 52.0%
|
| 18 |
+
• Operating margin to increase to a level of between 10.5% and 11.0%
|
| 19 |
+
• Net income from continuing operations to grow to between € 1.8 billion and € 1.9 billion
|
| 20 |
+
Kasper Rorsted, CEO of adidas: “Unfortunately, we release our 2021 results in unsettling
|
| 21 |
+
times. Our thoughts and prayers are with the Ukrainian people, our teams on the ground and
|
| 22 |
+
everyone affected by the war. We strongly condemn any form of violence and stand in solidarity
|
| 23 |
+
with all those calling for peace. We also provide immediate humanitarian aid to those in need
|
| 24 |
+
of support. We will continue to follow the situation closely and take future business decisions
|
| 25 |
+
and actions as needed, always prioritizing our employee’s safety and support.”
|
| 26 |
+
“In 2021, we delivered a strong set of results despite several external factors weighing on both
|
| 27 |
+
demand and supply throughout the year”, Kasper Rorsted continued. “Wherever markets
|
| 28 |
+
operated without major disruptions we have been experiencing strong top-line momentum.
|
| 29 |
+
This is reflected in double-digit revenue growth in EMEA, North America and Latin America.
|
| 30 |
+
While we continued to invest heavily into our brand, our direct-to-consumer business, and our
|
| 31 |
+
digital transformation, we improved our bottom-line by more than € 1 billion. Taking it all
|
| 32 |
+
together, 2021 was a successful first year within our new strategic cycle. In 2022, we will build
|
| 33 |
+
1
|
| 34 |
+
|
| 35 |
+
on this momentum and continue to grow both our top- and bottom-line at double-digit rates
|
| 36 |
+
amid heightened uncertainty.”
|
| 37 |
+
Financial Performance in 2021
|
| 38 |
+
Currency-neutral sales grow 16% despite challenging market environment
|
| 39 |
+
In 2021, adidas was able to increase its currency-neutral revenues by 16% despite several
|
| 40 |
+
external factors weighing on both demand and supply throughout the year. In total, the
|
| 41 |
+
challenging market environment in Greater China, extensive covid-19-related lockdowns in
|
| 42 |
+
Asia-Pacific as well as industry-wide supply chain disruptions reduced revenue growth by
|
| 43 |
+
more than € 1.5 billion during the year. From a channel perspective, the company’s top-line
|
| 44 |
+
increase was characterized by a strong recovery from the material revenue decline in its
|
| 45 |
+
physical distribution channels during 2020, when the global coronavirus pandemic had caused
|
| 46 |
+
a large number of temporary store closures. As a result, wholesale revenues as well as sales
|
| 47 |
+
in adidas’ own-retail stores grew at strong double-digit rates in 2021. E-commerce revenues
|
| 48 |
+
increased 4% during the year, on top of the exceptionally high growth in 2020 when e-
|
| 49 |
+
commerce revenues had grown by more than 50%. In euro terms, the company’s revenues
|
| 50 |
+
increased 15% in 2021 to € 21.234 billion (2020: € 18.435 billion).
|
| 51 |
+
Revenue improves in all market segments
|
| 52 |
+
While sales increased in all market segments in 2021, the top-line development in the regions
|
| 53 |
+
differed significantly depending on the impact the various demand and supply challenges had
|
| 54 |
+
on the specific region. While all markets were negatively impacted by industry-wide supply
|
| 55 |
+
chain challenges, the company recorded particularly strong developments in markets that
|
| 56 |
+
operated without major covid-19-related disruptions. Accordingly, currency-neutral sales in
|
| 57 |
+
EMEA, North America, and Latin America increased by 24%, 17%, and 47%, respectively. At
|
| 58 |
+
the same time, the challenging market environment in Greater China (+3%) and the extensive
|
| 59 |
+
covid-19-related restrictions in Asia-Pacific (+8%) weighed on adidas’ results in these
|
| 60 |
+
markets.
|
| 61 |
+
Gross margin at 50.7% driven by higher full-prices sales and better inventory management
|
| 62 |
+
The company’s gross margin increased 0.7 percentage points to 50.7% in 2021 (2020: 50.0%).
|
| 63 |
+
While negative currency developments, higher supply chain costs and a less favorable channel
|
| 64 |
+
and market mix weighed on the development in 2021, higher full-price sales and lower
|
| 65 |
+
inventory allowances as well as the non-recurrence of last year’s purchase order cancellation
|
| 66 |
+
costs were able to overcompensate the negative effects.
|
| 67 |
2
|
| 68 |
|
| 69 |
+
Operating margin improves by 5.3 percentage points
|
| 70 |
+
Other operating expenses increased 4% to € 8.892 billion in 2021 (2020: € 8.580 billion). As a
|
| 71 |
+
percentage of sales, other operating expenses were down 4.7 percentage points to 41.9%
|
| 72 |
+
(2020: 46.5%). Marketing and point-of-sale expenses increased 7% to € 2.547 billion
|
| 73 |
+
(2020: € 2.373 billion) due to increased investments into the brand supporting the introduction
|
| 74 |
+
of new products and to drive consumer experience across both digital and physical platforms.
|
| 75 |
+
As a percentage of sales, marketing and point-of-sale expenses decreased 0.9 percentage
|
| 76 |
+
points to 12.0% (2020: 12.9%). Operating overhead expenses increased 2% to € 6.345 billion
|
| 77 |
+
(2020: € 6.207 billion) including more than € 220 million stranded costs related to the
|
| 78 |
+
divestiture of the Reebok business. As a percentage of sales, operating overhead expenses
|
| 79 |
+
decreased 3.8 percentage points to 29.9% (2020: 33.7%). As a result of the strong top-line
|
| 80 |
+
increase in combination with the improved gross margin and lower operating expenses as a
|
| 81 |
+
percentage of sales, the company’s operating profit increased 166% to € 1.986 billion in 2021
|
| 82 |
+
(2020: € 746 million). Consequently, the operating margin increased 5.3 percentage points to
|
| 83 |
+
9.4% compared to the prior year level of 4.0%.
|
| 84 |
+
Net financial result decreases
|
| 85 |
+
Financial income decreased 32% to € 19 million in 2021 (2020: € 29 million), while financial
|
| 86 |
+
expenses were down 22% to € 153 million (2020: € 196 million). As a result, the company
|
| 87 |
+
recorded a negative net financial result of € 133 million (2020: negative € 167 million). The
|
| 88 |
+
company’s tax rate decreased 0.8 percentage points to 19.4% in 2021 (2020: 20.2%).
|
| 89 |
+
Net income from continuing operations increases by more than € 1 billion
|
| 90 |
+
Net income from continuing operations increased 223% to € 1.492 billion in 2021 (2020:
|
| 91 |
+
€ 461 million). Both basic and diluted EPS from continuing operations also increased 223% to
|
| 92 |
+
€ 7.47 (2020: € 2.31).
|
| 93 |
+
Average operating working capital as percentage of sales decreases 5.3 percentage points
|
| 94 |
+
At the end of December 2021, inventories were down 9% to € 4.009 billion (2020: € 4.397
|
| 95 |
+
billion), or 12% lower on a currency-neutral basis. This development mainly reflects the
|
| 96 |
+
divestiture of the Reebok business. The strong sell-through of the company’s products,
|
| 97 |
+
successful inventory management as well as the impact from industry-wide supply chain
|
| 98 |
+
challenges also contributed to the decline. Accounts receivable increased 11% to € 2.175
|
| 99 |
+
billion at the end of December 2021 (2020: € 1.952 billion) reflecting the company’s strong
|
| 100 |
+
top-line growth. On a currency-neutral basis, accounts receivables were up 6%. Accounts
|
| 101 |
+
payable were down 4% to € 2.294 billion at the end of December 2021 versus € 2.390 billion
|
| 102 |
+
in 2020. This development reflects the normalization of payment terms as well as the
|
| 103 |
+
divestiture of the Reebok business. On a currency-neutral basis, accounts payable decreased
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 104 |
3
|
| 105 |
|
| 106 |
+
6%. Average operating working capital as a percentage of sales decreased 5.3 percentage
|
| 107 |
+
points to 20.0% for the full year (2020: 25.3%).
|
| 108 |
+
Accelerated investments into DTC and digital
|
| 109 |
+
The company’s capital expenditure increased 51% in 2021 to € 667 million (2020: € 442
|
| 110 |
+
million). Investments in new or remodeled own-retail stores, the company’s e-commerce
|
| 111 |
+
business as well as the broader IT infrastructure represented once again the majority of the
|
| 112 |
+
expenditure.
|
| 113 |
+
Executive and Supervisory Boards propose dividend payment of € 3.30 per share
|
| 114 |
+
As a result of the strong operational and financial performance in 2021, the company’s
|
| 115 |
+
financial position as well as Management’s confidence in its long-term growth aspirations,
|
| 116 |
+
the adidas Executive and Supervisory Boards will recommend paying a dividend of € 3.30 per
|
| 117 |
+
dividend-entitled share to shareholders at the Annual General Meeting on May 12, 2022. This
|
| 118 |
+
represents an increase of 10% compared to the prior year dividend (2021: € 3.00).
|
| 119 |
+
Financial Performance in Q4 2021
|
| 120 |
+
Sales in the fourth quarter impacted by supply and demand challenges
|
| 121 |
+
Currency-neutral revenues in the fourth quarter declined 3%. Significant supply shortages as
|
| 122 |
+
a result of the lockdowns in Vietnam last year, the challenging market environment in Greater
|
| 123 |
+
China as well as covid-19-related lockdowns in Asia-Pacific reduced revenue growth by more
|
| 124 |
+
than € 400 million in Q4. In light of the supply shortages the company continued to prioritize
|
| 125 |
+
its own DTC channel. As a result, DTC revenues were stable versus the prior year, reflecting
|
| 126 |
+
a 14% increase compared to the 2019 level. While adidas e-commerce revenues experienced
|
| 127 |
+
a strong increase in full-price sales, revenues in the company’s own digital channel declined
|
| 128 |
+
by 2% during the quarter reflecting the exceptionally high growth in the prior year period.
|
| 129 |
+
Compared to the 2019 level, e-commerce revenues grew 39% in the fourth quarter. In euro
|
| 130 |
+
terms, adidas revenues were flat versus the prior year at € 5.137 billion (2020: € 5.142 billion).
|
| 131 |
+
Revenues in EMEA up strong double-digits in Q4
|
| 132 |
+
From a regional perspective, revenues in North America were most impacted by the supply
|
| 133 |
+
shortages in the fourth quarter with almost half of the total negative impact recorded in this
|
| 134 |
+
particular market. As a result, currency-neutral revenues in North America declined 4%
|
| 135 |
+
during the quarter. Nevertheless, revenues in the company’s direct-to-consumer business
|
| 136 |
+
continued to increase in the market, reflecting the company’s DTC-led strategy. While EMEA
|
| 137 |
+
was also significantly impacted by the supply shortages, revenues still grew 15%, driven by
|
| 138 |
+
double-digit growth in both DTC and wholesale. Fourth quarter revenues in Latin America
|
| 139 |
+
improved 9%, reflecting strong double-digit growth versus the 2019 level. Revenues in Greater
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 140 |
4
|
| 141 |
|
| 142 |
+
China (-24%) and APAC (-6%) declined due to the supply shortages, covid-19-related
|
| 143 |
+
restrictions and – in the case of China – the challenging market environment.
|
| 144 |
+
Gross margin slightly down 0.1 percentage points
|
| 145 |
+
In the fourth quarter of 2021, the gross margin declined slightly by 0.1 percentage points to
|
| 146 |
+
49.0% (2020: 49.1%). Significantly higher supply chain costs – the company recorded
|
| 147 |
+
additional freight costs of more than € 100 million this quarter alone – as well as continued
|
| 148 |
+
headwinds from unfavorable currency developments represented a material drag on gross
|
| 149 |
+
margin in Q4. This impact was almost completely offset by significantly higher full price sales.
|
| 150 |
+
Operating margin below prior year level
|
| 151 |
+
Other operating expenses were up 7% to € 2.501 billion during the fourth quarter (2020:
|
| 152 |
+
€ 2.331 billion). As a percentage of sales, other operating expenses increased 3.3 percentage
|
| 153 |
+
points to 48.7% (2020: 45.3%). Marketing and point-of-sale expenses increased 8% to
|
| 154 |
+
€ 715 million (2020: € 662 million) and as a percentage of sales were up to 13.9% (2020:
|
| 155 |
+
12.9%), reflecting higher investments to support the introduction of new products such as the
|
| 156 |
+
UltraBoost22, NMD S1 and the latest IVY PARK x adidas collection, as well as to elevate the
|
| 157 |
+
consumer experience across all touchpoints. Operating overhead expenses increased 7% to
|
| 158 |
+
€ 1.786 billion (2020: € 1.670 billion) and included stranded costs related to the divestiture of
|
| 159 |
+
the Reebok business in an amount of around € 60 million. As a percentage of sales, operating
|
| 160 |
+
overhead expenses increased to 34.8% (2020: 32.5%). Operating profit amounted to
|
| 161 |
+
€ 66 million (2020: € 225 million), resulting in an operating margin of 1.3% (2020: 4.4%). Net
|
| 162 |
+
income from continuing operations reached € 123 million in the quarter (2020: € 143 million),
|
| 163 |
+
supported by a positive tax benefit related to the divestiture of the Reebok business. Both basic
|
| 164 |
+
and diluted EPS from continuing operations were € 0.58 in Q4 (2020: € 0.70).
|
| 165 |
+
Outlook for 2022
|
| 166 |
+
Currency-neutral sales to increase between 11% and 13%
|
| 167 |
+
After the recovery from the coronavirus pandemic in 2021, adidas expects double-digit top-
|
| 168 |
+
line growth to continue in 2022 amid heightened uncertainty. Driven by the execution of the
|
| 169 |
+
company’s strategy ‘Own the Game’ as well as its strong product pipeline currency-neutral
|
| 170 |
+
revenues are projected to increase at a rate between 11% and 13%. This growth assumption
|
| 171 |
+
already includes a risk of up to € 250 million in the company’s Russia/CIS business – about
|
| 172 |
+
50% of adidas’ total revenues in the region – due to the war in Ukraine and reflects the
|
| 173 |
+
suspension of adidas’ retail and e-commerce operations in Russia. This amount represents
|
| 174 |
+
around 1 percentage point of growth for the total company and explains the difference to the
|
| 175 |
+
initial outlook as provided in the Management Report at the time of the preparation of the
|
| 176 |
+
company’s annual report.
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
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|
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|
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|
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|
|
| 177 |
5
|
| 178 |
|
| 179 |
+
Currency-neutral revenues to increase in all markets
|
| 180 |
+
From a regional perspective, currency-neutral revenues are expected to increase in all
|
| 181 |
+
markets. While currency-neutral sales in North America and Latin America are projected to
|
| 182 |
+
grow at a mid- to high-teens rate, currency-neutral revenues are expected to grow at a rate
|
| 183 |
+
in the mid-teens in EMEA and Asia-Pacific. Greater China is expected to record a sales
|
| 184 |
+
increase in the mid-single digits as the company continues to make progress with its action
|
| 185 |
+
plan aimed at stabilizing the business and re-igniting growth.
|
| 186 |
+
Gross margin expected to expand to a level of between 51.5% and 52.0%
|
| 187 |
+
adidas’ gross margin is expected to continue to increase and reach a level of between 51.5%
|
| 188 |
+
and 52.0%. A positive channel mix effect, significant price increases as well as the positive
|
| 189 |
+
impact from favorable currency developments will drive the gross margin improvement and
|
| 190 |
+
are expected to outweigh significantly higher supply chain costs.
|
| 191 |
+
Operating margin to increase to a level of between 10.5% and 11.0%
|
| 192 |
+
The company’s operating margin is expected to increase significantly to a level of between
|
| 193 |
+
10.5% and 11.0%. In addition to the higher gross margin, lower operating expenses in
|
| 194 |
+
percentage of sales will benefit the company’s operating margin in 2022. This development
|
| 195 |
+
will be supported by the non-recurrence of around 70% of the Reebok-related stranded costs,
|
| 196 |
+
which accounted to more than € 220 million in 2021. Driven by the strong top-line growth in
|
| 197 |
+
combination with the margin improvements net income from continuing operations is
|
| 198 |
+
projected to increase to a level of between € 1.8 billion and € 1.9 billion in 2022.
|
| 199 |
+
***
|
| 200 |
+
Contacts:
|
| 201 |
+
Media Relations Investor Relations
|
| 202 |
+
corporate.press@adidas.com investor.relations@adidas.com
|
| 203 |
+
Tel.: +49 (0) 9132 84-2352 Tel.: +49 (0) 9132 84-2920
|
| 204 |
+
For more information, please visit adidas-group.com or report.adidas-group.com.
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
| 205 |
6
|
| 206 |
|
| 207 |
+
| | | | | |
|
| 208 |
+
| --- | ---------------- | ---------------- | --- | --- |
|
| 209 |
+
| | Quarter ending | Quarter ending | | |
|
| 210 |
+
€ in millions December 31, 2021 December 31, 2020 Change
|
| 211 |
+
| Net sales | | 5,137 | 5,142 | (0.1%) |
|
| 212 |
+
| ------------------------------------- | --- | ----------- | -------- | -------- |
|
| 213 |
+
| Cost of sales | | 2,618 | 2,615 | 0.1% |
|
| 214 |
+
| Gross profit | | 2,519 | 2,526 | (0.3%) |
|
| 215 |
+
| (% of net sales) | | 49.0% | 49.1% | (0.1pp) |
|
| 216 |
+
| Royalty and commission income | | 33 | 18 | 86.4% |
|
| 217 |
+
| Other operating income | | 15 | 13 | 16.3% |
|
| 218 |
+
| Other operating expenses | | 2,501 | 2,331 | 7.3% |
|
| 219 |
+
| (% of net sales) | | 48.7% | 45.3% | 3.3pp |
|
| 220 |
+
| Marketing and point-of-sale expenses | | 715 | 662 | 8.2% |
|
| 221 |
+
| (% of net sales) | | 13.9% | 12.9% | 1.1pp |
|
| 222 |
+
| Operating overhead expenses2 | | 1,786 | 1,670 | 6.9% |
|
| 223 |
+
| (% of net sales) | | 34.8% | 32.5% | 2.3pp |
|
| 224 |
+
| Operating profit | | 66 | 225 | (70.9%) |
|
| 225 |
+
| (% of net sales) | | 1.3% | 4.4% | (3.1pp) |
|
| 226 |
+
| Financial income | | 17 | 11 | 59.1% |
|
| 227 |
+
| Financial expenses | | 39 | 76 | (49.4%) |
|
| 228 |
+
| Income before taxes | | 44 | 160 | (72.2%) |
|
| 229 |
+
| (% of net sales) | | 0.9% | 3.1% | (2.2pp) |
|
| 230 |
+
| Income taxes | | (79) | 17 | n.a. |
|
| 231 |
+
| (% of income before taxes) | | (177.6%) | 10.5% | n.a. |
|
| 232 |
+
Net income from continuing operations 123 143 (13.8%)
|
| 233 |
+
| (% of net sales) | | 2.4% | 2.8% | (0.4pp) |
|
| 234 |
+
| ----------------- | --- | ------- | ------- | -------- |
|
| 235 |
+
Gain from discontinued operations, net of tax 89 14 534.2%
|
| 236 |
+
| Net income | | 213 | 157 | 35.3% |
|
| 237 |
+
| ----------------- | --- | ------- | ------- | ------ |
|
| 238 |
+
| (% of net sales) | | 4.1% | 3.1% | 1.1pp |
|
| 239 |
+
Net income attributable to shareholders 202 151 33.6%
|
| 240 |
+
| (% of net sales) | | 3.9% | 2.9% | 1.0pp |
|
| 241 |
+
| ----------------- | --- | ------- | ------- | ------ |
|
| 242 |
+
Net income attributable to non-controlling interests 11 6 74.9%
|
| 243 |
+
| | | | | |
|
| 244 |
+
| --- | --- | --- | --- | --- |
|
| 245 |
+
Basic earnings per share from continuing operations (in €) 0.58 0.70 (16.8%)
|
| 246 |
+
Diluted earnings per share from continuing operations (in €) 0.58 0.70 (16.8%)
|
| 247 |
+
| | | | | |
|
| 248 |
+
| --- | --- | --- | --- | --- |
|
| 249 |
+
Basic earnings per share from continuing and discontinued operations (in €) 1.05 0.77 35.6 %
|
| 250 |
+
Diluted earnings per share from continuing and discontinued operations (in €) 1.05 0.77 35.6 %
|
| 251 |
+
| | | | | |
|
| 252 |
+
| --- | --- | --- | --- | --- |
|
| 253 |
+
1 2021 and 2020 figures reflect continuing operations as a result of the reclassification of the Reebok business to discontinued operations.
|
| 254 |
+
2 Aggregated distribution and selling expenses, general and administration expenses, sundry expenses and impairment losses (net) on accounts receivable and contract assets.
|
| 255 |
+
Rounding differences may arise.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
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|
|
|
|
|
|
| 256 |
|
| 257 |
7
|
| 258 |
|
| 259 |
+
| | | | | | | | |
|
| 260 |
+
| --- | --------------- | --- | --------------- | --- | --- | --- | ------- |
|
| 261 |
+
| | Quarter ending | | Quarter ending | | | | Change |
|
| 262 |
+
€ in millions December 31, 2021 December 31, 2020 Change (currency-neutral)
|
| 263 |
+
| EMEA | | 1,832 | | 1,559 | 17.5% | | 15.2% |
|
| 264 |
+
| ----------------- | --- | -------- | --- | -------- | -------- | --- | -------- |
|
| 265 |
+
| North America | | 1,303 | | 1,317 | (1.1%) | | (3.7%) |
|
| 266 |
+
| Greater China | | 1,037 | | 1,287 | (19.4%) | | (24.3%) |
|
| 267 |
+
| Asia-Pacific | | 541 | | 587 | (7.8%) | | (6.0%) |
|
| 268 |
+
| Latin America | | 397 | | 365 | 8.8% | | 8.7% |
|
| 269 |
+
| Other Businesses | | 28 | | 27 | 3.6% | | 4.1% |
|
| 270 |
+
| | | | | | | | |
|
| 271 |
+
1 2021 and 2020 figures reflect continuing operations as a result of the reclassification of the Reebok business to discontinued operations.
|
| 272 |
+
Rounding differences may arise.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
| 273 |
|
| 274 |
8
|
| 275 |
|
| 276 |
+
| | | | | |
|
| 277 |
+
| --- | --- | ------------ | ------------ | --- |
|
| 278 |
+
| | | Year ending | Year ending | |
|
| 279 |
+
€ in millions December 31, 2021 December 31, 2020 Change
|
| 280 |
+
| Net sales | | 21,234 | 18,435 | 15.2% |
|
| 281 |
+
| ------------------------------ | --- | --------- | --------- | -------- |
|
| 282 |
+
| Cost of sales | | 10,469 | 9,213 | 13.6% |
|
| 283 |
+
| Gross profit | | 10,765 | 9,222 | 16.7% |
|
| 284 |
+
| (% of net sales) | | 50.7% | 50.0% | 0.7pp |
|
| 285 |
+
| Royalty and commission income | | 86 | 61 | 40.9% |
|
| 286 |
+
| Other operating income | | 28 | 42 | (34.8%) |
|
| 287 |
+
| Other operating expenses | | 8,892 | 8,580 | 3.6% |
|
| 288 |
+
| (% of net sales) | | 41.9% | 46.5% | (4.7pp) |
|
| 289 |
+
Marketing and point-of-sale expenses 2,547 2,373 7.3%
|
| 290 |
+
| (% of net sales) | | 12.0% | 12.9% | (0.9pp) |
|
| 291 |
+
| ----------------------------- | --- | -------- | -------- | -------- |
|
| 292 |
+
| Operating overhead expenses2 | | 6,345 | 6,207 | 2.2% |
|
| 293 |
+
| (% of net sales) | | 29.9% | 33.7% | (3.8pp) |
|
| 294 |
+
| Operating profit | | 1,986 | 746 | 166.3% |
|
| 295 |
+
| (% of net sales) | | 9.4% | 4.0% | 5.3pp |
|
| 296 |
+
| Financial income | | 19 | 29 | (32.1%) |
|
| 297 |
+
| Financial expenses | | 153 | 196 | (22.0%) |
|
| 298 |
+
| Income before taxes | | 1,852 | 578 | 220.2% |
|
| 299 |
+
| (% of net sales) | | 8.7% | 3.1% | 5.6pp |
|
| 300 |
+
| Income taxes | | 360 | 117 | 207.9% |
|
| 301 |
+
| (% of income before taxes) | | 19.4% | 20.2% | (0.8pp) |
|
| 302 |
+
Net income from continuing operations 1,492 461 223.4%
|
| 303 |
+
| (% of net sales) | | 7.0% | 2.5% | 4.5pp |
|
| 304 |
+
| ----------------- | --- | ------- | ------- | ------ |
|
| 305 |
+
Gain/(loss) from discontinued operations, net of tax 666 –19 n.a
|
| 306 |
+
| Net income | | 2,158 | 443 | 387.4% |
|
| 307 |
+
| ----------------- | --- | -------- | ------- | ------- |
|
| 308 |
+
| (% of net sales) | | 10.2% | 2.4% | 7.8pp |
|
| 309 |
+
Net income attributable to shareholders 2,116 432 389.6%
|
| 310 |
+
| (% of net sales) | | 10.0% | 2.3% | 7.6pp |
|
| 311 |
+
| ----------------- | --- | -------- | ------- | ------ |
|
| 312 |
+
Net income attributable to non-controlling interests 42 11 296.5%
|
| 313 |
+
| | | | | |
|
| 314 |
+
| --- | --- | --- | --- | --- |
|
| 315 |
+
Basic earnings per share from continuing operations (in €) 7.47 2.31 223.3%
|
| 316 |
+
Diluted earnings per share from continuing operations (in €) 7.47 2.31 223.3%
|
| 317 |
+
| | | | | |
|
| 318 |
+
| --- | --- | --- | --- | --- |
|
| 319 |
+
Basic earnings per share from continuing and discontinued operations (in €) 10.90 2.21 392.1%
|
| 320 |
+
Diluted earnings per share from continuing and discontinued operations (in €) 10.90 2.21 392.1%
|
| 321 |
+
| | | | | |
|
| 322 |
+
| --- | --- | --- | --- | --- |
|
| 323 |
+
1 2021 and 2020 figures reflect continuing operations as a result of the reclassification of the Reebok business to discontinued operations.
|
| 324 |
+
2 Aggregated distribution and selling expenses, general and administration expenses, sundry expenses and impairment losses (net) on accounts receivable and contract assets.
|
| 325 |
+
Rounding differences may arise.
|
| 326 |
|
| 327 |
9
|
| 328 |
|
| 329 |
+
| | | | | | | |
|
| 330 |
+
| --- | --- | ------------ | ------------ | --- | --- | ------- |
|
| 331 |
+
| | | Year ending | Year ending | | | Change |
|
| 332 |
+
€ in millions December 31, 2021 December 31, 2020 Change (currency-neutral)
|
| 333 |
+
| EMEA | | 7,760 | 6,308 | | 23.0% | 24.0 % |
|
| 334 |
+
| ----------------- | --- | -------- | ------ | ------ | --------- | ------- |
|
| 335 |
+
| North America | | 5,105 | 4,519 | | 13.0% | 16.6 % |
|
| 336 |
+
| Greater China | | 4,597 | 4,342 | | 5.9% | 3.0 % |
|
| 337 |
+
| Asia-Pacific | | 2,180 | 2,083 | | 4.7% | 7.7 % |
|
| 338 |
+
| Latin America | | 1,446 | 1,035 | | 39.8% | 47.2 % |
|
| 339 |
+
| Other Businesses | | 145 | | 149 | (2.6%) | (2.0%) |
|
| 340 |
+
| | | | | | | |
|
| 341 |
+
1 2021 and 2020 figures reflect continuing operations as a result of the reclassification of the Reebok business to discontinued operations.
|
| 342 |
+
Rounding differences may arise.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 343 |
|
| 344 |
10
|
| 345 |
|
| 346 |
+
| | | | | |
|
| 347 |
+
| --- | --- | --- | --- | --- |
|
| 348 |
+
€ in millions December 31, 2021 December 31, 2020 Change in %
|
| 349 |
+
| Cash and cash equivalents | | 3,828 | 3,994 | (4.1) |
|
| 350 |
+
| ------------------------------- | --- | -------- | -------- | ------- |
|
| 351 |
+
| Accounts receivable | | 2,175 | 1,952 | 11.4 |
|
| 352 |
+
| Other current financial assets | | 745 | 702 | 6.1 |
|
| 353 |
+
| Inventories | | 4,009 | 4,397 | (8.8) |
|
| 354 |
+
| Income tax receivables | | 91 | 109 | (16.9) |
|
| 355 |
+
| Other current assets | | 1,062 | 999 | 6.3 |
|
| 356 |
+
Assets classified as held for sale 2,033 0 802,610.8
|
| 357 |
+
| Total current assets | | 13,944 | 12,154 | 14.7 |
|
| 358 |
+
| ---------------------------------------- | --- | --------- | --------- | ------- |
|
| 359 |
+
| Property, plant and equipment | | 2,256 | 2,157 | 4.6 |
|
| 360 |
+
| Right-of-use assets | | 2,569 | 2,430 | 5.7 |
|
| 361 |
+
| Goodwill | | 1,228 | 1,208 | 1.7 |
|
| 362 |
+
| Trademarks | | 16 | 750 | (97.8) |
|
| 363 |
+
| Other intangible assets | | 336 | 252 | 33.6 |
|
| 364 |
+
| Long-term financial assets | | 290 | 353 | (17.8) |
|
| 365 |
+
| Other non-current financial assets | | 160 | 414 | (61.2) |
|
| 366 |
+
| Deferred tax assets | | 1,263 | 1,233 | 2.5 |
|
| 367 |
+
| Other non-current assets | | 74 | 103 | (28.4) |
|
| 368 |
+
| Total non-current assets | | 8,193 | 8,899 | (7.9) |
|
| 369 |
+
| Total assets | | 22,137 | 21,053 | 5.1 |
|
| 370 |
+
| Short-term borrowings | | 29 | 686 | (95.8) |
|
| 371 |
+
| Accounts payable | | 2,294 | 2,390 | (4.0) |
|
| 372 |
+
| Current lease liabilities | | 573 | 563 | 1.8 |
|
| 373 |
+
| Other current financial liabilities | | 363 | 446 | (18.6) |
|
| 374 |
+
| Income taxes | | 536 | 562 | (4.7) |
|
| 375 |
+
| Other current provisions | | 1,458 | 1,609 | (9.4) |
|
| 376 |
+
| Current accrued liabilities | | 2,684 | 2,172 | 23.6 |
|
| 377 |
+
| Other current liabilities | | 434 | 398 | 9.0 |
|
| 378 |
+
| Liabilities classified as held for sale | | 594 | – | n.a. |
|
| 379 |
+
| Total current liabilities | | 8,965 | 8,827 | 1.6 |
|
| 380 |
+
| Long-term borrowings | | 2,466 | 2,482 | (0.7) |
|
| 381 |
+
| Non-current lease liabilities | | 2,263 | 2,159 | 4.8 |
|
| 382 |
+
Other non-current financial liabilities 51 115 (55.4)
|
| 383 |
+
| Pensions and similar obligations | | 267 | 284 | (6.1) |
|
| 384 |
+
| --------------------------------- | --- | -------- | -------- | ------- |
|
| 385 |
+
| Deferred tax liabilities | | 122 | 241 | (49.5) |
|
| 386 |
+
| Other non-current provisions | | 149 | 229 | (34.8) |
|
| 387 |
+
| Non-current accrued liabilities | | 8 | 8 | (3.2) |
|
| 388 |
+
| Other non-current liabilities | | 9 | 17 | (45.8) |
|
| 389 |
+
| Total non-current liabilities | | 5,334 | 5,535 | (3.6) |
|
| 390 |
+
| Share capital | | 192 | 195 | (1.8) |
|
| 391 |
+
Reserves (thereof at Dec. 31st, 2021 € 128 million relating to the Reebok disposal
|
| 392 |
+
| | | 69 | (474) | n.a. |
|
| 393 |
+
| --- | --- | ----- | -------- | ----- |
|
| 394 |
+
group)
|
| 395 |
+
| Retained earnings | | 7,259 | 6,733 | 7.8 |
|
| 396 |
+
| ----------------------------- | --- | --------- | --------- | ----- |
|
| 397 |
+
| Shareholders' equity | | 7,519 | 6,454 | 16.5 |
|
| 398 |
+
| Non-controlling interests | | 318 | 237 | 34.0 |
|
| 399 |
+
| Total equity | | 7,837 | 6,691 | 17.1 |
|
| 400 |
+
| Total liabilities and equity | | 22,137 | 21,053 | 5.1 |
|
| 401 |
|
| 402 |
11
|
| 403 |
|
| 404 |
+
| Additional balance sheet information | | | | |
|
| 405 |
+
| ------------------------------------- | -------- | -------- | -------- | --------- |
|
| 406 |
+
| Operating working capital | | 3,890 | 3,960 | (1.8) |
|
| 407 |
+
| Working capital | | 4,978 | 3,328 | 49.6 |
|
| 408 |
+
| Adjusted net borrowings2 | | 2,963 | 3,148 | (5.9) |
|
| 409 |
+
| Financial leverage3 | 39.4% | 48.8% | | (9.4 pp) |
|
| 410 |
+
| | | | | |
|
| 411 |
+
| | | | | |
|
| 412 |
+
1 2021 figures reflect the reclassification of the Reebok business to assets or liabilities held for sale.
|
| 413 |
+
2 Adjusted net borrowings = short-term borrowings + long-term borrowings and future cash used in lease and pension liabilities – cash and cash equivalents and short-term financial assets.
|
| 414 |
+
3 Based on shareholders' equity.
|
| 415 |
+
Rounding differences may arise.
|
| 416 |
+
|
| 417 |
+
12
|
q131/random_k4/question.json
CHANGED
|
@@ -17,10 +17,10 @@
|
|
| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
"Campaign_038_Introducing_AC_Whitepaper_v5e.pdf",
|
| 20 |
-
"
|
| 21 |
-
"
|
| 22 |
-
"
|
| 23 |
-
"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
|
|
|
|
| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
"Campaign_038_Introducing_AC_Whitepaper_v5e.pdf",
|
| 20 |
+
"resize_r1_37.pdf",
|
| 21 |
+
"web_74331e85a10815bd.pdf",
|
| 22 |
+
"web_d44e9a235a572259.pdf",
|
| 23 |
+
"resize_r2_24.pdf"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
|
q131/random_k4/random_1.md
CHANGED
|
@@ -1,886 +1,539 @@
|
|
| 1 |
-
|
| 2 |
-
with Great In-Store Retail Experiences
|
| 3 |
|
| 4 |
-
|
| 5 |
-
September 2014
|
| 6 |
-
|
| 7 |
-
Table Of Contents
|
| 8 |
-
|
| 9 |
-
Executive Summary ............... 2
|
| 10 |
-
|
| 11 |
-
Key Findings ........................... 3
|
| 12 |
-
|
| 13 |
-
Research Findings
|
| 14 |
-
Investing in People &
|
| 15 |
-
Technology
|
| 16 |
-
to Enhance In-Store
|
| 17 |
-
Experiences ............................... 4
|
| 18 |
-
|
| 19 |
-
The Challenge of
|
| 20 |
-
Cross-Channel Consistency ....... 6
|
| 21 |
-
|
| 22 |
-
Turning In-Store Data
|
| 23 |
-
into Actionable Messaging ........ 9
|
| 24 |
-
|
| 25 |
-
The Future of
|
| 26 |
-
Store Technologies .................. 10
|
| 27 |
-
|
| 28 |
-
Key Recommendations ........ 13
|
| 29 |
-
|
| 30 |
-
Appendices ........................... 14
|
| 31 |
-
|
| 32 |
-
About Future Stores ............ 16
|
| 33 |
-
|
| 34 |
-
About CFI Group .................. 16
|
| 35 |
-
|
| 36 |
-
About WBR & WBR Digital .. 17
|
| 37 |
-
|
| 38 |
-
Register for Next Year’s
|
| 39 |
-
Future Stores Conference .... 17
|
| 40 |
-
|
| 41 |
-
Executive Summary
|
| 42 |
-
How to Engage and Convert Consumers with Great
|
| 43 |
-
In-Store Retail Experiences
|
| 44 |
-
|
| 45 |
-
Technology has had an expansive and multidimensional impact on retail in recent
|
| 46 |
-
years. In particular, the ascendance of multichannel e-commerce platforms has
|
| 47 |
-
challenged brands to reimagine how they interact with consumers. As a result, today’s
|
| 48 |
-
connected consumers have access to a whole host of digital shopping tools, including
|
| 49 |
-
interactive websites with high-definition images and mobile-optimized web and email.
|
| 50 |
-
E-commerce offers variety, convenience, and information, empowering consumers to
|
| 51 |
-
engage with retailers when, where, and how they please.
|
| 52 |
-
|
| 53 |
-
Despite e-commerce’s growing popularity, stores are still the lynchpins of retail strategy.
|
| 54 |
-
The Department of Commerce estimates that e-commerce accounted for approximately
|
| 55 |
-
6.5% of all retail sales in the U.S. during the second quarter of 2014. Although this
|
| 56 |
-
reaffirms that physical stores remain retailers’ most prominent sources of revenue, it
|
| 57 |
-
also suggests that there are great opportunities for synergy between a brand’s physical
|
| 58 |
-
locations and its e-commerce platform.
|
| 59 |
-
|
| 60 |
-
Indeed, many of the technological innovations that have threatened to erode in-store
|
| 61 |
-
sales have turned out to be great assets to retailers. Mobile devices enable businesses
|
| 62 |
-
to send extremely relevant and timely messages to consumers by using location-based
|
| 63 |
-
services and Bluetooth Low Energy (BLE) beacons. Loyalty programs deployed across
|
| 64 |
-
channels encourage repeat business both in-store and online. QR codes and interactive
|
| 65 |
-
displays offer customers new ways to engage with and learn about products and
|
| 66 |
-
services. Omnichannel initiatives (e.g., an option for the consumer to buy online and
|
| 67 |
-
pick up in-store) promote interchannel traffic. Because of these innovations, today’s
|
| 68 |
-
consumers begin shopping before they walk into the store and continue shopping after
|
| 69 |
-
they leave, making their in-store experiences the unifying element.
|
| 70 |
-
|
| 71 |
-
The mission of retail stores has evolved and expanded greatly in recent years, and
|
| 72 |
-
it has been influenced in large part by technological innovation and new consumer
|
| 73 |
-
insights. The most successful retail stores not only leverage new technologies to drive
|
| 74 |
-
in-store conversions, but they also enhance the shopping experience, collect actionable
|
| 75 |
-
customer data, and serve as a physical extension of the brand. This is the store of the
|
| 76 |
-
future: a connected showroom that fuses together multichannel experiences to convert
|
| 77 |
-
and engage customers while also learning from them.
|
| 78 |
-
|
| 79 |
-
What follows is an analysis of the best practices and paradigm-shifting experiences
|
| 80 |
-
retailers are creating in their stores. The analysis is based on survey data collected from
|
| 81 |
-
retail executives and professionals in a variety of industries. This data was collected on-site
|
| 82 |
-
at the 2014 Future Stores Conference and through an online survey. The findings are
|
| 83 |
-
based on the insights and practices of some of the world’s leading retailers and brands.
|
| 84 |
-
|
| 85 |
-
2
|
| 86 |
-
|
| 87 |
-
How to Engage and Convert Consumers with Great In-Store Retail ExperiencesKey Findings
|
| 88 |
-
|
| 89 |
-
Retailers are increasing their investments in
|
| 90 |
-
technology in order to make their in-store
|
| 91 |
-
experiences more relevant and engaging.
|
| 92 |
-
Although associates are still the most important in-store sales
|
| 93 |
-
assets, retailers are investing equally in new store technologies
|
| 94 |
-
and personnel training. Will this shift in emphasis produce a more
|
| 95 |
-
technology-driven in-store sales process?
|
| 96 |
|
| 97 |
-
|
| 98 |
-
shopping experiences across channels.
|
| 99 |
-
In today’s omnichannel commercial world, consistency of experience
|
| 100 |
-
is key to improving conversions and enhancing consumer loyalty.
|
| 101 |
-
Unfortunately, most retailers’ shopping experiences are only somewhat
|
| 102 |
-
consistent across channels, resulting in significant missed opportunities.
|
| 103 |
|
| 104 |
-
|
| 105 |
-
collection in order to create more targeted
|
| 106 |
-
and personalized marketing activities.
|
| 107 |
|
| 108 |
-
|
| 109 |
-
them with an incomplete view of the customer and ineffective
|
| 110 |
-
marketing messages.
|
| 111 |
|
| 112 |
-
|
| 113 |
-
the future will create seamless shopping
|
| 114 |
-
experiences and integrate with other
|
| 115 |
-
technologies and services.
|
| 116 |
|
| 117 |
-
|
| 118 |
-
|
| 119 |
-
|
| 120 |
-
|
| 121 |
-
of solutions and only implement those that enhance conversions while
|
| 122 |
-
providing customers with effortless, engaging experiences.
|
| 123 |
|
| 124 |
-
|
| 125 |
|
| 126 |
-
|
| 127 |
-
more of what they’re
|
| 128 |
-
not getting. They want
|
| 129 |
-
outcomes to be easier to
|
| 130 |
-
achieve, and they would
|
| 131 |
-
like them with greater
|
| 132 |
-
convenience and at a
|
| 133 |
-
higher value.”
|
| 134 |
|
| 135 |
-
|
| 136 |
-
|
| 137 |
-
|
| 138 |
|
| 139 |
-
|
|
|
|
|
|
|
|
|
|
| 140 |
|
| 141 |
-
|
| 142 |
-
Experiences
|
| 143 |
|
| 144 |
-
|
| 145 |
-
generation. Stores have become the standard-bearers for a brand’s customer experience,
|
| 146 |
-
driving consumer loyalty and engagement through innovative interactions and inventive
|
| 147 |
-
campaigns. Stores are also a burgeoning source of data that can be turned into rich insights
|
| 148 |
-
into shoppers’ tendencies and preferences. Add in customers’ lofty expectations for shopping
|
| 149 |
-
experiences and the value of the modern store becomes undeniable. With few exceptions,
|
| 150 |
-
stores continue to be the backbone of retail businesses, even in today’s world of e-commerce
|
| 151 |
-
and digital interconnectedness.
|
| 152 |
|
| 153 |
-
|
| 154 |
-
they are constantly updating designs, technology, and personnel to get the most out of
|
| 155 |
-
each location. Creating a store of the future means seamlessly integrating cutting-edge
|
| 156 |
-
technology with tried and true designs and tactics, providing a strong balance of analog
|
| 157 |
-
and digital elements that help deliver to customers higher value outcomes that are easier
|
| 158 |
-
to achieve. When it comes to technology, electronic point of sale (EPOS) tools have
|
| 159 |
-
become extremely common, with over three quarters of survey respondents indicating
|
| 160 |
-
that they are already utilizing the capability. A robust 72% are leveraging mobile devices
|
| 161 |
-
and tablets in stores, and 60% are making use of digital displays or kiosks.
|
| 162 |
|
| 163 |
-
|
| 164 |
-
of store associates, 91% of those surveyed said that the greatest sales assets in their
|
| 165 |
-
stores are still sales associates. New technologies are providing good value to the in-store
|
| 166 |
-
experience, but they have yet to supplant personnel as key sales elements.
|
| 167 |
|
| 168 |
-
|
|
|
|
| 169 |
|
| 170 |
-
|
|
|
|
| 171 |
|
| 172 |
-
|
|
|
|
| 173 |
|
| 174 |
-
|
|
|
|
| 175 |
|
| 176 |
-
|
| 177 |
-
|
| 178 |
-
displays, etc.)
|
| 179 |
|
| 180 |
-
|
| 181 |
-
|
| 182 |
|
| 183 |
-
|
|
|
|
| 184 |
|
| 185 |
-
|
|
|
|
| 186 |
|
| 187 |
-
|
| 188 |
-
|
| 189 |
|
| 190 |
-
|
|
|
|
| 191 |
|
| 192 |
-
|
| 193 |
-
beacons, etc.)
|
| 194 |
|
| 195 |
-
|
|
|
|
|
|
|
| 196 |
|
| 197 |
-
|
| 198 |
-
|
| 199 |
|
| 200 |
-
|
|
|
|
| 201 |
|
| 202 |
-
|
|
|
|
| 203 |
|
| 204 |
-
|
| 205 |
-
|
| 206 |
-
In-Store Conversions
|
| 207 |
|
| 208 |
-
|
| 209 |
-
|
| 210 |
|
| 211 |
-
|
|
|
|
|
|
|
| 212 |
|
| 213 |
-
|
|
|
|
| 214 |
|
| 215 |
-
|
|
|
|
| 216 |
|
| 217 |
-
|
| 218 |
|
| 219 |
-
|
|
|
|
| 220 |
|
| 221 |
-
|
|
|
|
| 222 |
|
| 223 |
-
|
| 224 |
-
|
| 225 |
-
Common Technologies Being Leveraged to
|
| 226 |
-
Enhance In-Store Experiences
|
| 227 |
|
| 228 |
-
|
|
|
|
| 229 |
|
| 230 |
-
|
|
|
|
| 231 |
|
| 232 |
-
|
|
|
|
| 233 |
|
| 234 |
-
|
|
|
|
| 235 |
|
| 236 |
-
|
|
|
|
| 237 |
|
| 238 |
-
|
|
|
|
| 239 |
|
| 240 |
-
|
|
|
|
|
|
|
| 241 |
|
| 242 |
-
|
| 243 |
|
| 244 |
-
|
|
|
|
| 245 |
|
| 246 |
-
|
|
|
|
| 247 |
|
| 248 |
-
|
| 249 |
-
|
| 250 |
-
experiences, they just
|
| 251 |
-
aren’t always being
|
| 252 |
-
implemented. There is
|
| 253 |
-
a resistance to change,
|
| 254 |
-
because making changes
|
| 255 |
-
costs a lot of time and
|
| 256 |
-
money.”
|
| 257 |
|
| 258 |
-
|
| 259 |
-
|
| 260 |
|
| 261 |
-
|
|
|
|
| 262 |
|
| 263 |
-
|
| 264 |
-
|
| 265 |
-
Today, consumers are increasingly engaging with brands across a variety of diverse media.
|
| 266 |
-
The customer journey has become expansive, dynamic, and multilayered; it permeates
|
| 267 |
-
desktop websites, mobile-optimized sites and apps, social networks, and retail stores
|
| 268 |
-
themselves. For retailers, this has meant a multiplication of consumer touch points and
|
| 269 |
-
an unprecedented demand for innovative digital shopping tools. However, the challenge
|
| 270 |
-
for retailers is not just to develop spectacular omnichannel shopping capabilities but also
|
| 271 |
-
to deliver outstanding experiences across all channels. When it comes to omnichannel
|
| 272 |
-
customer experiences, consistency is key.
|
| 273 |
|
| 274 |
-
|
| 275 |
-
|
| 276 |
-
|
| 277 |
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The majority (60%) of those surveyed noted that their experiences are only somewhat
|
| 278 |
-
consistent. In their quest to provide a great customer experience, these retailers are facing
|
| 279 |
-
many complex challenges, including creating consistency across channels, personalizing
|
| 280 |
-
the experience, capturing and applying relevant customer data, and the implementation
|
| 281 |
-
of customer experience initiatives across store locations.
|
| 282 |
|
| 283 |
-
|
| 284 |
-
|
| 285 |
-
Unfortunately, the way retailers view their shopping experience can differ greatly from
|
| 286 |
-
consumers’ perspectives. For instance, in a Bain & Co. customer experience survey,
|
| 287 |
-
80% of companies stated that they were delivering a “superior experience” to their
|
| 288 |
-
customers. However, consumers in the survey said that only 8% of companies were
|
| 289 |
-
actually delivering high-quality experiences. This discrepancy underlines how critical it is
|
| 290 |
-
for retailers to listen to their customers, especially when it comes to experiences.
|
| 291 |
|
| 292 |
-
|
| 293 |
-
|
| 294 |
-
advances. In part, a successful omnichannel strategy demands that retailers understand
|
| 295 |
-
the key actions that consumers take during their shopping experiences, and retailers
|
| 296 |
-
must then make those actions available across multiple channels. Enabling consumers to
|
| 297 |
-
engage with multiple platforms en route to a purchase not only improves the shopping
|
| 298 |
-
experience but also increases conversion rates and reduces cart abandonment.
|
| 299 |
|
| 300 |
-
|
| 301 |
-
|
| 302 |
-
buying them online, poses a clear threat to traditional retailers, which are susceptible to
|
| 303 |
-
customers using mobile devices to compare prices while in the store. Despite the threat,
|
| 304 |
-
nearly three quarters of respondents reported that they have not seen any sort of impact
|
| 305 |
-
from showrooming. In fact, 19% noted that showrooming has had a positive impact on
|
| 306 |
-
their businesses. This is likely because omnichannel shoppers have been shown to spend
|
| 307 |
-
significantly more than single-channel shoppers. Similarly, “buy online, pick up in store”
|
| 308 |
-
options, which offer the convenience of an online transaction alongside the satisfaction
|
| 309 |
-
of instantly picking up an item, are expanding although only 26% of respondents
|
| 310 |
-
currently have fully-deployed programs.
|
| 311 |
|
| 312 |
-
|
| 313 |
|
| 314 |
-
|
| 315 |
-
between in-store and online?
|
| 316 |
|
| 317 |
-
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|
| 318 |
|
| 319 |
-
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|
| 320 |
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| 321 |
-
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| 322 |
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| 323 |
-
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| 324 |
-
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| 325 |
|
| 326 |
-
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| 327 |
-
|
| 328 |
|
| 329 |
-
|
| 330 |
-
|
| 331 |
-
|
| 332 |
|
| 333 |
-
|
| 334 |
|
| 335 |
-
|
| 336 |
-
|
| 337 |
|
| 338 |
-
|
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|
|
| 339 |
|
| 340 |
-
|
| 341 |
-
|
| 342 |
|
| 343 |
-
|
|
|
|
| 344 |
|
| 345 |
-
|
| 346 |
-
|
| 347 |
-
stores
|
| 348 |
|
| 349 |
-
|
| 350 |
-
|
| 351 |
-
Standing Out Above the Rest
|
| 352 |
|
| 353 |
-
|
|
|
|
| 354 |
|
| 355 |
-
|
|
|
|
| 356 |
|
| 357 |
-
|
|
|
|
| 358 |
|
| 359 |
-
|
|
|
|
| 360 |
|
| 361 |
-
|
| 362 |
-
change
|
| 363 |
|
| 364 |
-
|
| 365 |
|
| 366 |
-
|
| 367 |
-
|
| 368 |
-
drive sales
|
| 369 |
|
| 370 |
-
|
| 371 |
-
|
| 372 |
|
| 373 |
-
|
| 374 |
-
|
| 375 |
|
| 376 |
-
|
| 377 |
-
|
| 378 |
|
| 379 |
-
|
|
|
|
|
|
|
|
|
|
| 380 |
|
| 381 |
-
|
| 382 |
-
|
| 383 |
|
| 384 |
-
|
|
|
|
| 385 |
|
| 386 |
-
|
|
|
|
|
|
|
| 387 |
|
| 388 |
-
|
| 389 |
-
|
| 390 |
-
Products Online and Pick Them Up In-Store
|
| 391 |
|
| 392 |
-
|
|
|
|
| 393 |
|
| 394 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 395 |
|
| 396 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
| 397 |
|
| 398 |
-
|
| 399 |
-
collected in their stores. Using BLE beacons, location-based mobile services, loyalty programs,
|
| 400 |
-
promotions, and sales trends, merchants can uncover valuable data on the in-store customer
|
| 401 |
-
experience. This data can then help them track traffic patterns, evaluate how customers are
|
| 402 |
-
interacting with displays, and determine which promotions and marketing messages are
|
| 403 |
-
having the greatest impact. In other words, these insights lead to optimized stores, improved
|
| 404 |
-
marketing campaigns, and more effective omnichannel commerce interfaces.
|
| 405 |
|
| 406 |
-
|
| 407 |
-
effectively collecting customer data in their stores. Similarly, a third of respondents said that
|
| 408 |
-
their in-store data collection has been ineffective. As a result, just under a fifth of the retailers
|
| 409 |
-
surveyed said that their marketing activities are very targeted and personalized. This lack of
|
| 410 |
-
personalization indicates that most retailers are missing major opportunities to reap the many
|
| 411 |
-
benefits of in-store data insights.
|
| 412 |
|
| 413 |
-
|
| 414 |
-
build processes to capture that information. Those retailers that have processes in place now
|
| 415 |
-
have access to a new age of sophisticated key performance indicators, such as conversion
|
| 416 |
-
rate, shopper yield, Average Transaction Value (ATV), entrance traffic, and sales per square
|
| 417 |
-
foot, as well as a whole host of omnichannel metrics and capabilities.
|
| 418 |
|
| 419 |
-
|
| 420 |
-
data in-store
|
| 421 |
|
| 422 |
-
|
| 423 |
|
| 424 |
-
|
| 425 |
|
| 426 |
-
|
| 427 |
|
| 428 |
-
|
| 429 |
|
| 430 |
-
|
| 431 |
-
Businesses Are Doing a Very Effective Job of
|
| 432 |
-
Collecting Customer Data in Stores
|
| 433 |
|
| 434 |
-
|
| 435 |
|
| 436 |
-
|
| 437 |
-
|
| 438 |
-
|
| 439 |
-
shopping in-store. This
|
| 440 |
-
embrace of mobile
|
| 441 |
-
shopping is where the
|
| 442 |
-
real opportunity lies for
|
| 443 |
-
retailers to make their
|
| 444 |
-
store a better place to
|
| 445 |
-
shop. It is gradually
|
| 446 |
-
becoming clear: the
|
| 447 |
-
stores that make proper
|
| 448 |
-
use of mobile wallets
|
| 449 |
-
are the ones who will
|
| 450 |
-
come out on top in the
|
| 451 |
-
modern retail era.”
|
| 452 |
|
| 453 |
-
|
| 454 |
-
Retail
|
| 455 |
|
| 456 |
-
|
| 457 |
-
|
| 458 |
|
| 459 |
-
|
|
|
|
| 460 |
|
| 461 |
-
and
|
|
|
|
| 462 |
|
| 463 |
-
|
| 464 |
-
|
| 465 |
|
| 466 |
-
|
| 467 |
-
|
| 468 |
|
| 469 |
-
|
|
|
|
| 470 |
|
| 471 |
-
|
| 472 |
-
Targeting Their Marketing Messages, but There
|
| 473 |
-
Is Still Room for Improvement
|
| 474 |
|
| 475 |
-
|
|
|
|
| 476 |
|
| 477 |
-
|
| 478 |
-
|
| 479 |
-
intersections between physical and digital retail channels have become so extensive that
|
| 480 |
-
many companies are no longer differentiating between sales made in stores and those
|
| 481 |
-
made digitally. As Saks Inc. CEO Stephen Sadove has said, “There is so much integration
|
| 482 |
-
between store and online sales that we can’t report the numbers separately. [That just
|
| 483 |
-
doesn’t] make sense, because we are moving inventory from one to another all the time.”
|
| 484 |
|
| 485 |
-
|
| 486 |
-
New devices, online offerings, and digital touch points are the engines of retail growth
|
| 487 |
-
because they streamline shopping experiences across channels and engage consumers on
|
| 488 |
-
their own terms. Novel technologies also enable businesses to gather a massive amount
|
| 489 |
-
of customer data, which can then be used to personalize marketing messages and shift
|
| 490 |
-
inventory to the right places. However, given the abundance of tools and technologies
|
| 491 |
-
available, choosing the right solutions can prove challenging. The best brands are those
|
| 492 |
-
that cut through unessential capabilities and focus only on those that add significant
|
| 493 |
-
value to the customer experience.
|
| 494 |
|
| 495 |
-
|
| 496 |
-
|
| 497 |
-
be at the center of the stores of the future? Despite the relatively wide utilization of QR
|
| 498 |
-
codes in retail stores, 61% of those surveyed said that they believe that QR codes will
|
| 499 |
-
disappear on the next 2-5 years. In contrast, 71% of respondents indicated anticipation
|
| 500 |
-
that mobile wallet capabilities will become standard over the same time period. In many
|
| 501 |
-
cases, the utilization of a given capability will not just depend on how sophisticated a
|
| 502 |
-
technology is but also on how that technology can be leveraged during a customer’s
|
| 503 |
|
| 504 |
-
|
|
|
|
| 505 |
|
| 506 |
-
|
|
|
|
| 507 |
|
| 508 |
-
|
| 509 |
-
|
| 510 |
-
loyalty programs by capturing more data and improving incentives.
|
| 511 |
|
| 512 |
-
|
| 513 |
-
|
| 514 |
-
of the most successful retail technologies are the least intrusive and most intuitive for
|
| 515 |
-
consumers to interact with. This is the principle of Invisible Design: the less intrusive and
|
| 516 |
-
more streamlined a technology is, the more likely it is to become widely adopted.
|
| 517 |
|
| 518 |
-
|
| 519 |
-
next 2-5 years?
|
| 520 |
|
| 521 |
-
|
|
|
|
| 522 |
|
| 523 |
-
|
|
|
|
| 524 |
|
| 525 |
-
|
| 526 |
|
| 527 |
-
|
| 528 |
|
| 529 |
-
|
|
|
|
|
|
|
|
|
|
| 530 |
|
| 531 |
-
|
| 532 |
|
| 533 |
-
|
| 534 |
|
| 535 |
-
|
| 536 |
|
| 537 |
-
|
| 538 |
-
|
| 539 |
-
|
| 540 |
-
|
| 541 |
|
| 542 |
-
|
| 543 |
|
| 544 |
-
|
| 545 |
|
| 546 |
-
|
|
|
|
|
|
|
| 547 |
|
| 548 |
-
|
| 549 |
|
| 550 |
-
|
|
|
|
|
|
|
| 551 |
|
| 552 |
-
|
| 553 |
|
| 554 |
-
|
| 555 |
|
| 556 |
-
|
| 557 |
-
standard practice in the next 2-5 years?
|
| 558 |
|
| 559 |
-
|
| 560 |
|
| 561 |
-
|
| 562 |
|
| 563 |
-
|
| 564 |
|
| 565 |
-
|
| 566 |
|
| 567 |
-
|
| 568 |
|
| 569 |
-
|
| 570 |
-
virtual displays
|
| 571 |
|
| 572 |
-
|
| 573 |
|
| 574 |
-
|
| 575 |
|
| 576 |
-
|
| 577 |
-
70
|
| 578 |
-
50
|
| 579 |
-
Becoming Standard over the next 2-5 Years
|
| 580 |
|
| 581 |
-
|
|
|
|
| 582 |
|
| 583 |
-
|
|
|
|
| 584 |
|
| 585 |
-
|
|
|
|
| 586 |
|
| 587 |
-
|
|
|
|
| 588 |
|
| 589 |
-
|
| 590 |
|
| 591 |
-
|
| 592 |
|
| 593 |
-
|
|
|
|
| 594 |
|
| 595 |
-
|
|
|
|
| 596 |
|
| 597 |
-
|
| 598 |
-
|
| 599 |
-
most exceptional in-store experiences?
|
| 600 |
|
| 601 |
-
|
|
|
|
| 602 |
|
| 603 |
-
|
| 604 |
|
| 605 |
-
|
| 606 |
|
| 607 |
-
|
| 608 |
|
| 609 |
-
|
| 610 |
|
| 611 |
-
|
| 612 |
|
| 613 |
-
|
| 614 |
|
| 615 |
-
|
| 616 |
|
| 617 |
-
|
| 618 |
|
| 619 |
-
|
| 620 |
|
| 621 |
-
|
| 622 |
-
Retailers Providing Exceptional In-Store
|
| 623 |
-
Experiences
|
| 624 |
|
| 625 |
-
|
| 626 |
|
| 627 |
-
|
|
|
|
| 628 |
|
| 629 |
-
|
| 630 |
-
technologies, there may come a time when
|
| 631 |
-
technology is seen as a more critical in-store
|
| 632 |
-
sales asset than associates.
|
| 633 |
|
| 634 |
-
|
| 635 |
-
and enjoyable shopping experience, customers will willingly turn to those technologies.
|
| 636 |
-
As those tools become more sophisticated, they may eventually supersede sales
|
| 637 |
-
associates as the greatest in-store revenue drivers.
|
| 638 |
|
| 639 |
-
|
| 640 |
-
are interacting with their products and
|
| 641 |
-
brands, businesses must prioritize a new set
|
| 642 |
-
of consumer engagement metrics alongside
|
| 643 |
-
traditional measures like conversions.
|
| 644 |
|
| 645 |
-
|
| 646 |
-
metrics, including involvement (i.e., whether or not consumers are relying on the brand
|
| 647 |
-
for information, goods, and services on an ongoing basis) and time of awareness to
|
| 648 |
-
time of satisfaction (i.e., how long it takes for a customer to acquire a good or service
|
| 649 |
-
from the time they become aware of it). Improving involvement and shortening the
|
| 650 |
-
time of awareness to time of satisfaction are becoming central objectives for businesses.
|
| 651 |
|
| 652 |
-
|
| 653 |
-
how well businesses are learning from and
|
| 654 |
-
listening to customers.
|
| 655 |
|
| 656 |
-
|
| 657 |
-
listen to customer feedback and effectively collect customer data. Stores are a great
|
| 658 |
-
source of these inputs, which enable organizations to optimize their offerings and
|
| 659 |
-
create personalized marketing messages.
|
| 660 |
|
| 661 |
-
|
| 662 |
-
the right services to the right places at the right
|
| 663 |
-
times while maintaining a consistent feel.
|
| 664 |
-
Not only must retail organizations become more agile in order to create the capabilities
|
| 665 |
-
customers demand, they must also extend those capabilities across a variety of channels
|
| 666 |
-
without detracting from the overall experience. Many retailers are struggling with this
|
| 667 |
-
cross-channel consistency, highlighting the need for them to critically evaluate how they
|
| 668 |
-
interact with customers on different media.
|
| 669 |
|
| 670 |
-
|
| 671 |
-
leveraging the right technologies and phasing
|
| 672 |
-
out anachronistic elements.
|
| 673 |
|
| 674 |
-
|
| 675 |
-
revenue, companies must replace outmoded elements with the right technologies,
|
| 676 |
-
particularly digital tools that enhance product interactions and capture key data points.
|
| 677 |
-
This requires constant re-evaluation and, occasionally, reinvention of store components
|
| 678 |
|
| 679 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 680 |
|
| 681 |
-
|
| 682 |
|
| 683 |
-
|
| 684 |
-
|
| 685 |
-
of 104 store, operations, IT, cross-channel, and retail customer experience executives
|
| 686 |
-
representing 14 industries (see Appendix B for demographic information). Survey
|
| 687 |
-
participants included decision-makers and executives with responsibility for their
|
| 688 |
-
businesses’ in-store and digital experiences and performance. In-person surveys and
|
| 689 |
-
interviews were conducted on-site at the 2014 Future Stores Conference. Data was
|
| 690 |
-
collected in June of 2014.
|
| 691 |
|
| 692 |
-
|
| 693 |
|
| 694 |
-
|
|
|
|
|
|
|
|
|
|
| 695 |
|
| 696 |
-
|
| 697 |
|
| 698 |
-
|
|
|
|
|
|
|
|
|
|
| 699 |
|
| 700 |
-
|
|
|
|
| 701 |
|
| 702 |
-
|
| 703 |
|
| 704 |
-
|
| 705 |
|
| 706 |
-
|
| 707 |
|
| 708 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 709 |
|
| 710 |
-
|
| 711 |
|
| 712 |
-
|
| 713 |
-
|
| 714 |
|
| 715 |
-
|
| 716 |
|
| 717 |
-
|
| 718 |
|
| 719 |
-
|
| 720 |
|
| 721 |
-
|
|
|
|
| 722 |
|
| 723 |
-
|
| 724 |
-
|
| 725 |
-
2% Supermarkets
|
| 726 |
-
|
| 727 |
-
1% Toys & Hobbies
|
| 728 |
-
|
| 729 |
-
14
|
| 730 |
-
|
| 731 |
-
How to Engage and Convert Consumers with Great In-Store Retail Experiences
|
| 732 |
-
|
| 733 |
-
Roles and Titles
|
| 734 |
-
|
| 735 |
-
Revenue Breakdown
|
| 736 |
-
|
| 737 |
-
15% Marketing
|
| 738 |
-
|
| 739 |
-
15% Executive
|
| 740 |
-
|
| 741 |
-
Management
|
| 742 |
-
|
| 743 |
-
15% Information
|
| 744 |
-
|
| 745 |
-
Technology
|
| 746 |
-
|
| 747 |
-
12% Omni- channel
|
| 748 |
-
|
| 749 |
-
12% Customer
|
| 750 |
-
Experience
|
| 751 |
-
|
| 752 |
-
8% eCommerce
|
| 753 |
-
|
| 754 |
-
6% Operations
|
| 755 |
-
|
| 756 |
-
6% Customer Insights
|
| 757 |
-
|
| 758 |
-
and Analytics
|
| 759 |
-
|
| 760 |
-
6% Consulting & Agency
|
| 761 |
-
|
| 762 |
-
3%
|
| 763 |
-
|
| 764 |
-
Innovation
|
| 765 |
-
|
| 766 |
-
2% Story Design &
|
| 767 |
-
|
| 768 |
-
Management
|
| 769 |
-
|
| 770 |
-
22% Less than $50 million
|
| 771 |
-
|
| 772 |
-
17% $50- ‐150 million
|
| 773 |
-
|
| 774 |
-
61% Greater than $150
|
| 775 |
-
|
| 776 |
-
million
|
| 777 |
-
|
| 778 |
-
15
|
| 779 |
-
|
| 780 |
-
How to Engage and Convert Consumers with Great In-Store Retail Experiences
|
| 781 |
-
|
| 782 |
-
“The event was fantastic.
|
| 783 |
-
It was very well executed,
|
| 784 |
-
and I have taken a lot
|
| 785 |
-
of information from the
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| 786 |
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event that we will be
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| 787 |
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working to implement in
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our stores.”
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- Chanel Chartrand, Visual
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| 791 |
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Merchandiser, Coastal.com
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| 792 |
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| 793 |
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About Future Stores
|
| 794 |
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|
| 795 |
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Future Stores is WBR’s intensive event focused on cutting-edge omnichannel retail
|
| 796 |
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strategies. From omnichannel marketing and customer analytics to retail technology
|
| 797 |
-
and store operations, Future Stores will show you how to design and implement
|
| 798 |
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winning in-store strategies to beat the competition and boost customer loyalty.
|
| 799 |
-
|
| 800 |
-
The conference is centered on the pain points of store, operations, IT, cross-channel
|
| 801 |
-
and customer experience executives to bridge the gap between the store experience
|
| 802 |
-
and the digital experience. Future Stores provides tactical strategies for brick and
|
| 803 |
-
mortar retailers to improve and increase conversion rates in-store as well as make the
|
| 804 |
-
store and cross-channel shopping experiences as seamless and easy as they are online.
|
| 805 |
-
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| 806 |
-
About CFI Group
|
| 807 |
-
|
| 808 |
-
CFI Group is a global leader in providing customer feedback insights through analytics.
|
| 809 |
-
CFI Group provides a technology platform that leverages the science of the American
|
| 810 |
-
Customer Satisfaction Index (ACSI). This platform continuously measures the customer
|
| 811 |
-
experience across multiple channels, benchmarks performance, and prioritizes
|
| 812 |
-
improvements for maximum impact.
|
| 813 |
-
|
| 814 |
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Founded in 1988 and headquartered in Ann Arbor, Michigan, CFI Group serves
|
| 815 |
-
global clients from a network of offices worldwide. Our clients span a variety of
|
| 816 |
-
industries, including financial services, hospitality, manufacturing, telecom, retail, and
|
| 817 |
-
government. Regardless of your industry, we can put the power of our technology and
|
| 818 |
-
the science of the ACSI methodology to work for you.
|
| 819 |
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CFI Group USA, L.L.C.
|
| 821 |
-
625 Avis Drive
|
| 822 |
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Ann Arbor, MI 48108
|
| 823 |
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(734) 930-9090
|
| 824 |
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Askcfi@cfigroup.com
|
| 825 |
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| 826 |
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16
|
| 827 |
-
|
| 828 |
-
How to Engage and Convert Consumers with Great In-Store Retail ExperiencesAbout WBR &
|
| 829 |
-
WBR Digital
|
| 830 |
-
|
| 831 |
-
WBR is the world’s biggest large-scale conference company and part of the PLS group,
|
| 832 |
-
one of the world’s leading providers of strategic business intelligence with 16 offices
|
| 833 |
-
worldwide. Our conference divisions consistently out-perform their industry sector
|
| 834 |
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competitors on the quality of the events we produce and the relationships we nurture
|
| 835 |
-
with both attendees and sponsors.
|
| 836 |
-
|
| 837 |
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Every year, over 10,000 senior executives from Fortune 1,000 companies attend over
|
| 838 |
-
100 of our annual conferences – a true “Who’s Who” of today’s corporate world.
|
| 839 |
-
From Automotive events in Bucharest to Logistics conferences in Arizona to Luxury
|
| 840 |
-
conferences in New York and Finance summits in Hong Kong, WBR is dedicated to
|
| 841 |
-
exceeding the needs of its customers around the world.
|
| 842 |
-
|
| 843 |
-
In addition to our industry leading conferences, our professional services marketing
|
| 844 |
-
division, WBR Digital, connects solutions providers to their target audiences with
|
| 845 |
-
digital branding and engagement services and lead generation campaigns. WBR’s
|
| 846 |
-
marketers act as an extension of your team, relieving strain on your internal resources
|
| 847 |
-
while engaging with customers and prospects on your brand and solutions. Solutions
|
| 848 |
-
providers can target identified accounts or relevant industry/function segments of WBR’s
|
| 849 |
-
global database of senior-level decision makers.
|
| 850 |
-
|
| 851 |
-
Contact:
|
| 852 |
-
Andrew Cole
|
| 853 |
-
Digital Content Manager
|
| 854 |
-
646-200-7541
|
| 855 |
-
Andrew.Cole@wbresearch.com
|
| 856 |
-
|
| 857 |
-
Be a Part of Next Year’s
|
| 858 |
-
Future Stores Conference
|
| 859 |
-
|
| 860 |
-
Be a part of next year’s event and discuss the new trends shaping the retail industry.
|
| 861 |
-
|
| 862 |
-
Click To Register Now
|
| 863 |
-
|
| 864 |
-
Call our customer service team to get the best available discounts for your firm at
|
| 865 |
-
1.888.482.6012, or email us at futurestores@wbresearch.com
|
| 866 |
-
|
| 867 |
-
17
|
| 868 |
-
|
| 869 |
-
How to Engage and Convert Consumers with Great In-Store Retail ExperiencesWhat did you think? Rate this content and help us improve!
|
| 870 |
-
|
| 871 |
-
“An organization’s ability to learn, and translate that learning into
|
| 872 |
-
action rapidly, is the ultimate competitive advantage.” - Jack Welch
|
| 873 |
-
|
| 874 |
-
It is our goal to produce relevant, valuable content to help inform
|
| 875 |
-
your strategic business decisions, so we would love to know what
|
| 876 |
-
you thought of this report. Your feedback goes directly to our
|
| 877 |
-
content team and helps us to improve.
|
| 878 |
-
|
| 879 |
-
CLICK HERE TO TELL
|
| 880 |
-
US WHAT YOU THINK
|
| 881 |
-
|
| 882 |
-
YOU CAN ALSO SUBMIT A RATING HERE WWW.SURVEYMONKEY.COM/S/JTVB7FB
|
| 883 |
-
|
| 884 |
-
18
|
| 885 |
-
|
| 886 |
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How to Engage and Convert Consumers with Great In-Store Retail Experiences
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Here’s how you know
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Here’s how you know
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**Official websites use .gov**
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A
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**.gov**
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website belongs to an official government organization in the
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United States.
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**Secure .gov websites use HTTPS**
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A
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**lock**
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(
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) or
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**https://**
|
| 28 |
+
means you’ve safely connected to the .gov website. Share sensitive
|
| 29 |
+
information only on official, secure websites.
|
| 30 |
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| 31 |
+
[](/ "HealthIt.gov")
|
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+
Menu
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+

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+
[Skip Navigation](#ubermenu-main-36-skipnav)
|
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| 38 |
|
| 39 |
+
* Topics
|
| 40 |
+
+ - Featured
|
| 41 |
|
| 42 |
+
* ## Featured
|
| 43 |
+
* [Certification of Health IT](/certification-health-it/)
|
| 44 |
|
| 45 |
+
Ensures health IT meets standards for functionality, security, and interoperability.
|
| 46 |
+
* [Information Blocking](https://healthit.gov/information-blocking/)
|
| 47 |
|
| 48 |
+
Regulations ensuring health data is shared appropriately without improper barriers.
|
| 49 |
+
* [Interoperability](/interoperability/)
|
| 50 |
|
| 51 |
+
Enables secure and seamless exchange of electronic health information among authorized users.
|
| 52 |
+
* [Health Information Technology Advisory Committee (HITAC)](/hitac/)
|
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| 53 |
|
| 54 |
+
Advises on policies, standards, and implementation specifications for health data and technology.
|
| 55 |
+
* [United States Core Data for Interoperability (USCDI)](https://isp.healthit.gov/united-states-core-data-interoperability-uscdi)
|
| 56 |
|
| 57 |
+
Offers a standardized set of health data classes and constituent data elements for nationwide, interoperable health information exchange.
|
| 58 |
+
* [Trusted Exchange Framework & Common Agreement (TEFCA)](https://healthit.gov/policy/tefca/)
|
| 59 |
|
| 60 |
+
Operates as a nationwide framework for the interoperability of electronic health information.
|
| 61 |
+
- Artificial Intelligence
|
| 62 |
|
| 63 |
+
* ## Artificial Intelligence
|
| 64 |
+
* [Artificial Intelligence (AI) at HHS](https://healthit.gov/artificial-intelligence/)
|
| 65 |
|
| 66 |
+
HHS’ list of AI use cases is publicly available to search and reference. In addition to AI use case summaries, the inventory also includes information on data, IT infrastructure, internal governance, and much more.
|
| 67 |
+
- Care Continuum
|
| 68 |
|
| 69 |
+
* ## Care Continuum
|
|
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|
| 70 |
|
| 71 |
+
Explore the roles of health information and technology in broad healthcare settings, supporting seamless, coordinated patient care from prevention through recovery.
|
| 72 |
+
* ### Care Settings
|
| 73 |
+
* [Behavioral Health](https://healthit.gov/behavioral-health/)
|
| 74 |
|
| 75 |
+
Health information, policies, and technology supporting integrated care for mental health and substance use disorders.
|
| 76 |
+
* [Emergency Medical Services](https://healthit.gov/emergency-medical-services/)
|
| 77 |
|
| 78 |
+
Rapid response and communication during health emergencies through health information and technology.
|
| 79 |
+
* [Long-Term & Post-Acute Care](https://healthit.gov/long-term-and-post-acute-care/)
|
| 80 |
|
| 81 |
+
Health information and technology facilitating coordinated care beyond acute settings.
|
| 82 |
+
* [Maternal & Pediatric Care](https://healthit.gov/maternal-and-pediatric-care/)
|
| 83 |
|
| 84 |
+
Technology addressing unique health needs of mothers and children.
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| 85 |
+
* [Pharmacy & PDMP](/pharmacy-pdmp/)
|
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| 86 |
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| 87 |
+
Electronic tools tracking controlled substance prescriptions to improve patient safety.
|
| 88 |
+
* [Public Health](https://healthit.gov/public-health/)
|
| 89 |
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| 90 |
+
Using health information and technology to prevent disease, diagnose health conditions, and promote population health.
|
| 91 |
+
* ### Clinical Topics
|
| 92 |
+
* [Clinical Quality & Safety](/clinical-quality-and-safety/)
|
| 93 |
|
| 94 |
+
Optimal care through measuring results, prioritizing improvements, and implementing and monitoring results.
|
| 95 |
+
* [Usability & Provider Burden](/usability-and-provider-burden/)
|
| 96 |
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| 97 |
+
Promotes health information and technology usability to reduce clinician burden and enhance patient care.
|
| 98 |
+
- Interoperability
|
| 99 |
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| 100 |
+
* ## Interoperability
|
| 101 |
|
| 102 |
+
Promotes standardized exchange and use of electronic health data to improve patient care, coordination, and public health outcomes.
|
| 103 |
+
* [Health IT Interoperability](/interoperability/)
|
| 104 |
|
| 105 |
+
Enables secure and seamless exchange of electronic health information among authorized users.
|
| 106 |
+
* [Trusted Exchange Framework & Common Agreement (TEFCA)](/interoperability/trusted-exchange-framework-and-common-agreement-tefca/)
|
| 107 |
|
| 108 |
+
Facilitates secure, nationwide electronic health information sharing to connect providers, patients, public health agencies, and payers.
|
| 109 |
+
* [Certification of Health IT](/certification-health-it/)
|
|
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| 110 |
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| 111 |
+
Provides certification criteria for developers of health IT modules that ensures health IT products meet the standards for functionality, security, and interoperability.
|
| 112 |
+
* [Standards & Technology](/standards-and-technology/)
|
| 113 |
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| 114 |
+
Advance healthcare quality and safety through standardized health IT and secure health data exchange.
|
| 115 |
+
* [Information Blocking](https://healthit.gov/information-blocking/)
|
| 116 |
|
| 117 |
+
Prevents practices that interfere with the access, exchange, or use of electronic health information, as defined by the Cures Act.
|
| 118 |
+
* [Interoperability Standards Platform](https://www.healthit.gov/isp/)
|
| 119 |
|
| 120 |
+
Serves as a homepage for tools and resources for understanding and using health IT standards and technologies.
|
| 121 |
+
* [Investments](/investments/)
|
| 122 |
|
| 123 |
+
Support interoperability improvements nationwide.
|
| 124 |
+
* [Health IT & Health Information Exchange Basics](https://healthit.gov/health-it-basics/)
|
| 125 |
|
| 126 |
+
Enable secure electronic sharing and access of patient health information, supporting healthcare providers and patients across care settings.
|
| 127 |
+
* [Patient Access to Health Records](https://healthit.gov/patient-access-to-health-records/)
|
| 128 |
|
| 129 |
+
Ensure patients have secure and convenient access to their health records, supported by healthcare providers and health IT developers under HIPAA.
|
| 130 |
+
- Policy
|
| 131 |
+
* + ## [Policy](/policy/)
|
| 132 |
|
| 133 |
+

|
| 134 |
|
| 135 |
+
Outlines federal regulations and strategic initiatives guiding effective use and secure exchange of electronic health information.
|
| 136 |
+
+ - [Legislation](https://healthit.gov/legislation/)
|
| 137 |
|
| 138 |
+
Delivers improvements in the delivery and experience of health care while enhancing health outcomes by leveraging health information technology.
|
| 139 |
+
- [Regulations](/regulations/)
|
| 140 |
|
| 141 |
+
Supports the adoption and promotion of standards-based health information.
|
| 142 |
+
- [TEFCA](/interoperability/trusted-exchange-framework-and-common-agreement-tefca/)
|
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| 143 |
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| 144 |
+
Operates as a nationwide framework for the interoperability of electronic health information.
|
| 145 |
+
- [HHS Health IT Alignment Program](/hhs-health-it-alignment-program/)
|
| 146 |
|
| 147 |
+
Coordinates health data and technology initiatives across HHS to enhance interoperability and effectiveness.
|
| 148 |
+
- [Health Information Technology Advisory Committee (HITAC)](/hitac/)
|
| 149 |
|
| 150 |
+
Advises on policies, standards, and implementation specifications for health data and technology.
|
| 151 |
+
- [Privacy & Security](/privacy-security/)
|
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| 152 |
|
| 153 |
+
Protects electronic health information security through policy.
|
| 154 |
+
* + ### Rulemaking
|
| 155 |
+
+ [HTI Rules](https://healthit.gov/regulations/hti-rules/)
|
|
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| 156 |
|
| 157 |
+
Health data interoperability regulations ensuring secure, effective technology use.
|
| 158 |
+
+ [Information Blocking](https://healthit.gov/information-blocking/)
|
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| 159 |
|
| 160 |
+
Policies to prevent practices interfering with the access, exchange, and use of electronic health information.
|
| 161 |
+
+ [Certification Program Rules](/certification-program-regulations/)
|
|
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|
| 162 |
|
| 163 |
+
Ensures health IT meets standards for functionality, security, and interoperability.
|
| 164 |
+
- Research & Analysis
|
|
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| 165 |
|
| 166 |
+
* ## [Research & Analysis](/data/)
|
| 167 |
|
| 168 |
+

|
|
|
|
| 169 |
|
| 170 |
+
Interactive datasets related to health IT data analysis, providing insights into adoption and use.
|
| 171 |
+
* [Dashboards](/data/search/?postType=dashboard)
|
| 172 |
|
| 173 |
+
Gives data-driven insight on how dashboards are driving health IT adoption and how they have helped users to meet federal healthcare incentives or programs.
|
| 174 |
+
* [Data Briefs](/data/search/?postType=data-brief)
|
| 175 |
|
| 176 |
+
Provides health IT adoption and use statistics derived from surveys and administrative data and in-depth analysis of health IT policies and programs.
|
| 177 |
+
* [Datasets](/data/search/?postType=dataset)
|
| 178 |
|
| 179 |
+
Grants access to raw datasets from ONC related to health IT adoption, health IT capabilities and other topics.
|
| 180 |
+
* [Quick Stats](/data/search/?postType=quick-stat)
|
| 181 |
|
| 182 |
+
Streamlines data into visualizations of key data and summarizes the latest statistics, facts and figures about health IT.
|
| 183 |
+
* [About Health IT Research & Analysis](https://healthit.gov/data/about/)
|
| 184 |
|
| 185 |
+
Provides information about how health IT data are collected, analyzed, and published.
|
| 186 |
+
* Resources & Tools
|
| 187 |
+
+ - Featured
|
| 188 |
|
| 189 |
+
* ## Featured Resources & Tools
|
| 190 |
|
| 191 |
+
Highlights key tools and guidance supporting effective health IT implementation, interoperability, patient engagement, and compliance with federal standards.
|
| 192 |
+
* [Interoperability Standards](https://www.healthit.gov/isp/)
|
| 193 |
|
| 194 |
+
ONC’s initiatives in health data standards enable secure electronic health data exchange.
|
| 195 |
+
* [TEFCA Resources](https://healthit.gov/resources/?topics=tefca)
|
| 196 |
|
| 197 |
+
Data sheets, videos, and documents to guide users of the TEFCA framework and exchange.
|
| 198 |
+
* [Implementation Resources](https://healthit.gov/resources/?search-text=Implementation+Resources)
|
| 199 |
|
| 200 |
+
Technical resources and tools supporting healthcare providers, clinicians, and developers of health IT products.
|
| 201 |
+
* [Health IT Playbook](https://www.healthit.gov/playbook/)
|
| 202 |
|
| 203 |
+
Strategies, recommendations, and best practices for implementing and using health data and technology.
|
| 204 |
+
* [Security Risk Assessment Tool](https://healthit.gov/privacy-security/security-risk-assessment-tool/)
|
|
|
|
| 205 |
|
| 206 |
+
Desktop application supporting providers conducting HIPAA security risk assessments.
|
| 207 |
+
* [Patient Engagement Playbook](https://www.healthit.gov/playbook/pe/)
|
|
|
|
| 208 |
|
| 209 |
+
Practical reference tool for clinicians, staff, and other innovators around the world to improve patient engagement.
|
| 210 |
+
* [Certified Health IT Product List (CHPL)](https://chpl.healthit.gov/)
|
| 211 |
|
| 212 |
+
A comprehensive and authoritative listing of successfully tested and certified health IT modules.
|
| 213 |
+
* [Conformance Test Tools & Edge Testing Tool](https://healthit.gov/onc-conformance-test-tools/)
|
| 214 |
|
| 215 |
+
Resources for developers implementing standards to enable health information interoperability.
|
| 216 |
+
* [Health IT Feedback Form](https://inquiry.healthit.gov/support/plugins/servlet/desk/portal/2)
|
| 217 |
|
| 218 |
+
Users can submit feedback regarding health data and technology usability, interoperability, and compliance issues.
|
| 219 |
+
- Resources
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| 220 |
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| 221 |
+
* ## [Resources](/resources/)
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| 223 |
+

|
| 224 |
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| 225 |
+
Collection of practical materials, videos, educational tools, and user guides designed to support successful implementation and adoption of health IT systems.
|
| 226 |
+
* [Get It, Check It, Use It Guide](https://healthit.gov/get-it-check-it-use-it/)
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| 227 |
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| 228 |
+
A guide for patients and caregivers who want to access, review, and use their health records.
|
| 229 |
+
* [Video Resources](https://healthit.gov/resources/?resource_types=video)
|
| 230 |
|
| 231 |
+
A repository of informational videos created by ONC.
|
| 232 |
+
* [Health IT Curriculum Resources for Educators](https://healthit.gov/health-it-basics/health-it-curriculum-resources-educators/)
|
| 233 |
|
| 234 |
+
Instructional materials to help healthcare workers stay current in the changing healthcare environment and deliver care more effectively.
|
| 235 |
+
* [Fact Sheets](https://healthit.gov/resources/?resource_types=fact-sheet)
|
| 236 |
|
| 237 |
+
A repository of fact sheets created by ONC.
|
| 238 |
+
- Tools & Technology
|
| 239 |
+
* + ### Implementation
|
| 240 |
+
+ [Certified Health IT Product List](https://chpl.healthit.gov/)
|
| 241 |
|
| 242 |
+
A comprehensive and authoritative listing of successfully tested and certified health IT modules.
|
| 243 |
+
+ [Electronic Clinical Quality Improvement Resource Center](https://ecqi.healthit.gov/)
|
| 244 |
|
| 245 |
+
Provides common standards and shared technologies to monitor and analyze the quality of health care and patient outcomes.
|
| 246 |
+
+ [Security Risk Assessment Tool](https://healthit.gov/privacy-security/security-risk-assessment-tool/)
|
| 247 |
|
| 248 |
+
Desktop application supporting providers conducting HIPAA security risk assessments.
|
| 249 |
+
* + ### Tools
|
| 250 |
+
+ [Edge Testing Tool](https://site.healthit.gov/)
|
| 251 |
|
| 252 |
+
A centralized collection of testing tools and resources supporting health IT developers and users fully evaluating specific technical standards.
|
| 253 |
+
+ [Conformance Test Tools](https://healthit.gov/onc-conformance-test-tools/)
|
|
|
|
| 254 |
|
| 255 |
+
ONC-approved conformance resources supporting developers implementing standards to enable health information interoperability.
|
| 256 |
+
+ [Get It, Check It, Use It Guide](https://healthit.gov/get-it-check-it-use-it/)
|
| 257 |
|
| 258 |
+
A guide for patients and caregivers who want to access, review, and use their health records.
|
| 259 |
+
* + ### Quick Links
|
| 260 |
+
+ [Certification & Testing](https://healthit.gov/onc-health-it-certification-program-test-method/)
|
| 261 |
+
+ [USCDI](https://isp.healthit.gov/united-states-core-data-interoperability-uscdi)
|
| 262 |
+
+ [USCDI+](https://healthit.gov/standards-and-technology/uscdi-plus/)
|
| 263 |
+
+ [Interoperability Standards Platform (ISP)](https://isp.healthit.gov/)
|
| 264 |
+
+ [FHIR](https://healthit.gov/fhir)
|
| 265 |
+
+ [ONC Standards Bulletins](https://healthit.gov/standards-and-technology/onc-standards-bulletin/)
|
| 266 |
+
+ [Patient ID & Matching Adopted Standards for HHS](https://healthit.gov/standards-and-technology/patient-identity-and-patient-record-matching/)
|
| 267 |
+
* News & Events
|
| 268 |
|
| 269 |
+
+ - [Media Center](/media-center)
|
| 270 |
+
- [News](/news)
|
| 271 |
+
- [Events](/events)
|
| 272 |
+
+ - ## Latest News & Events
|
| 273 |
+
- ### Upcoming Event
|
| 274 |
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| 275 |
+
[
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**June 25, 2026**
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| 278 |
|
| 279 |
+
#### Adoption of AI in Clinical Care: Updates from the HHS RFI](https://healthit.gov/event/adoption-of-ai-in-clinical-care-updates-from-the-hhs-rfi/)
|
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+
### Latest Blog
|
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| 282 |
|
| 283 |
+
[
|
| 284 |
|
| 285 |
+
**February 4, 2026**
|
| 286 |
|
| 287 |
+
#### Advancing the Future of Behavioral Health Data Exchange](https://healthit.gov/blog/behavioral-health/advancing-the-future-of-behavioral-health-data-exchange/)
|
| 288 |
|
| 289 |
+
### Recent News
|
| 290 |
|
| 291 |
+
[
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|
| 292 |
|
| 293 |
+
**April 20, 2026**
|
| 294 |
|
| 295 |
+
#### New Data Brief: Electronic Health Record Adoption and Exchange Capabilities Among Substance Use and Mental Health Treatment Facilities, 2024](https://healthit.gov/data/data-briefs/electronic-health-record-adoption-and-exchange-capabilities-among-substance-use-and-mental-health-treatment-facilities-2024/)
|
| 296 |
+
* About
|
| 297 |
+
+ - Overview
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| 298 |
|
| 299 |
+
* [About ONC](https://healthit.gov/about/)
|
|
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|
| 300 |
|
| 301 |
+
Mission, role, and responsibilities of ONC.
|
| 302 |
+
* [Leadership](/about/leadership)
|
| 303 |
|
| 304 |
+
Profiles of ONC’s senior leadership team.
|
| 305 |
+
* [History](https://healthit.gov/about/history/)
|
| 306 |
|
| 307 |
+
Timeline of ONC’s evolution and key milestones.
|
| 308 |
+
* [Budget & Performance](https://healthit.gov/about/onc-budget-and-performance/)
|
| 309 |
|
| 310 |
+
Financial reports and performance accountability.
|
| 311 |
+
* [Investments](https://healthit.gov/interoperability/investments/)
|
| 312 |
|
| 313 |
+
Strategic investments in programs, policies, and technology.
|
| 314 |
+
* [Reports to Congress](/reports-congress/)
|
| 315 |
|
| 316 |
+
Annual health data and technology progress updates to Congress.
|
| 317 |
+
- Careers
|
| 318 |
|
| 319 |
+
* [Careers at ONC](https://healthit.gov/about/careers/)
|
|
|
|
|
|
|
| 320 |
|
| 321 |
+
View opportunities with ONC.
|
| 322 |
+
* [Working at ONC](https://healthit.gov/about/careers/working-at-onc/)
|
| 323 |
|
| 324 |
+
Overview of workplace culture and employee experience.
|
| 325 |
+
- Contact
|
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| 326 |
|
| 327 |
+
* [Contact Us](https://healthit.gov/contact-us/)
|
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|
| 328 |
|
| 329 |
+
Reach ONC with general inquiries.
|
| 330 |
+
* [Health IT Feedback Form](https://www.healthit.gov/feedback)
|
|
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|
| 331 |
|
| 332 |
+
Users can submit feedback regarding health data and technology usability, interoperability, and compliance issues.
|
| 333 |
+
* [Report Issue with Certified Health IT](/certification-health-it/certified-health-it-complaint-process/)
|
| 334 |
|
| 335 |
+
Complaint process to resolve any issues of potential noncompliance with certification requirements.
|
| 336 |
+
* [Information Blocking Claim](https://healthit.gov/report-info-blocking)
|
| 337 |
|
| 338 |
+
Form to report alleged information blocking practices.
|
| 339 |
+
* [Speaker Request](https://healthit.gov/speaker-request-form/)
|
|
|
|
| 340 |
|
| 341 |
+
Form to request ONC experts for speaking engagements.
|
| 342 |
+
- Funding Opportunities
|
|
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|
| 343 |
|
| 344 |
+
* [Funding Announcements](https://healthit.gov/about/funding-announcements/)
|
|
|
|
| 345 |
|
| 346 |
+
ONC’s contractors and grantees play a valuable role in helping promote better health care for Americans by fostering interoperable health data and technology.
|
| 347 |
+
* [Grants Management & Process](https://healthit.gov/about/onc-grants-cooperative-agreements/)
|
| 348 |
|
| 349 |
+
Learn about opportunities for funding through grants and cooperative agreements.
|
| 350 |
+
* [Blog](/blog/)
|
| 351 |
|
| 352 |
+
Search
|
| 353 |
|
| 354 |
+

|
| 355 |
|
| 356 |
+
Popular searches:
|
| 357 |
+
[certification](https://healthit.gov/?swp_form%5Bform_id%5D=1&swps=certification)
|
| 358 |
+
[information blocking](https://healthit.gov/?swp_form%5Bform_id%5D=1&swps=information%20blocking)
|
| 359 |
+
[interoperability](https://healthit.gov/?swp_form%5Bform_id%5D=1&swps=interoperability)
|
| 360 |
|
| 361 |
+
1. Home
|
| 362 |
|
| 363 |
+
# Page *Not Found*
|
| 364 |
|
| 365 |
+
The page you’re looking for is not available on our current site. To look for it, you can:
|
| 366 |
|
| 367 |
+
* Double-check the web address for any mistakes.
|
| 368 |
+
* Use our search.
|
| 369 |
+
* Visit our archives.
|
| 370 |
+
* [Return to our front page](/).
|
| 371 |
|
| 372 |
+

|
| 373 |
|
| 374 |
+
#### Get in Touch
|
| 375 |
|
| 376 |
+
* [Health IT Feedback & Inquiry Form](/feedback)
|
| 377 |
+
* [ONC Speaker Form](/speaker-request-form/)
|
| 378 |
+
* [Contact Us](/about/contact)
|
| 379 |
|
| 380 |
+
#### Get Involved
|
| 381 |
|
| 382 |
+
* [Careers](/about/careers/)
|
| 383 |
+
* [Events](/events/)
|
| 384 |
+
* [Funding Opportunities](/about/funding-announcements/)
|
| 385 |
|
| 386 |
+
[Submit Feedback](#helpful-modal)
|
| 387 |
|
| 388 |
+
## Submit Feedback
|
| 389 |
|
| 390 |
+
Step 1 of 3
|
|
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|
| 391 |
|
| 392 |
+
33%
|
| 393 |
|
| 394 |
+
Facebook
|
| 395 |
|
| 396 |
+
This field is for validation purposes and should be left unchanged.
|
| 397 |
|
| 398 |
+
Name(Required)
|
| 399 |
|
| 400 |
+
First
|
| 401 |
|
| 402 |
+
Last
|
|
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|
| 403 |
|
| 404 |
+
Email(Required)
|
| 405 |
|
| 406 |
+
Please provide your email address for follow-up.
|
| 407 |
|
| 408 |
+
What kind of issue are you experiencing?(Required)
|
|
|
|
|
|
|
|
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|
| 409 |
|
| 410 |
+
[ ]
|
| 411 |
+
Function/Performance
|
| 412 |
|
| 413 |
+
[ ]
|
| 414 |
+
Text & Information
|
| 415 |
|
| 416 |
+
[ ]
|
| 417 |
+
Images & Visuals
|
| 418 |
|
| 419 |
+
[ ]
|
| 420 |
+
Layout & Page Behavior
|
| 421 |
|
| 422 |
+
Select the type of issue you encountered. Select all that apply.
|
| 423 |
|
| 424 |
+
Where did you experience this issue?
|
| 425 |
|
| 426 |
+
[ ]
|
| 427 |
+
Desktop
|
| 428 |
|
| 429 |
+
[ ]
|
| 430 |
+
Tablet
|
| 431 |
|
| 432 |
+
[ ]
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| 433 |
+
Mobile
|
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|
| 434 |
|
| 435 |
+
[ ]
|
| 436 |
+
Not device specific
|
| 437 |
|
| 438 |
+
Select the type of issue you encountered. Select all that apply.
|
| 439 |
|
| 440 |
+
What browser are you using?
|
| 441 |
|
| 442 |
+
Example: Google Chrome on PC or Safari on iPhone.
|
| 443 |
|
| 444 |
+
### Page Information
|
| 445 |
|
| 446 |
+
Page Title(Required)
|
| 447 |
|
| 448 |
+
What page did you find this issue? e.g. Interoperability, ONC Blog
|
| 449 |
|
| 450 |
+
Page URL
|
| 451 |
|
| 452 |
+
e.g. https://healthit.gov/interoperability
|
| 453 |
|
| 454 |
+
Describe the issue you've encountered.(Required)
|
| 455 |
|
| 456 |
+
Please provide a detailed description of the issue you experienced.
|
|
|
|
|
|
|
| 457 |
|
| 458 |
+
Upload Screenshots or Files (optional)
|
| 459 |
|
| 460 |
+
Drop files here or
|
| 461 |
+
Select files
|
| 462 |
|
| 463 |
+
Max. file size: 3 MB, Max. files: 3.
|
|
|
|
|
|
|
|
|
|
| 464 |
|
| 465 |
+
If you have any screenshots or files related to the issue, please upload them here.
|
|
|
|
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|
|
|
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|
| 466 |
|
| 467 |
+
* Cancel
|
|
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|
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|
| 468 |
|
| 469 |
+

|
|
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|
|
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|
| 470 |
|
| 471 |
+
### Subscribe for Email Updates
|
|
|
|
|
|
|
| 472 |
|
| 473 |
+
URL
|
|
|
|
|
|
|
|
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|
| 474 |
|
| 475 |
+
This field is for validation purposes and should be left unchanged.
|
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|
| 476 |
|
| 477 |
+
Email(Required)
|
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|
| 478 |
|
| 479 |
+
#### EXPLORE
|
|
|
|
|
|
|
|
|
|
| 480 |
|
| 481 |
+
* [Certification of Health IT](https://healthit.gov/certification-health-it/)
|
| 482 |
+
* [Information Blocking](https://healthit.gov/information-blocking/)
|
| 483 |
+
* [Interoperability](https://healthit.gov/interoperability/)
|
| 484 |
+
* [Health Information Technology Advisory Committee (HITAC)](https://healthit.gov/hitac/)
|
| 485 |
+
* [Patient Access to Health Records](https://healthit.gov/patient-access-to-health-records/)
|
| 486 |
+
* [TEFCA](https://healthit.gov/policy/tefca/)
|
| 487 |
+
* [Policy](https://healthit.gov/policy/)
|
| 488 |
+
* [Resources](https://healthit.gov/resources/)
|
| 489 |
|
| 490 |
+
#### DATA
|
| 491 |
|
| 492 |
+
* [HealthData.gov](https://healthdata.gov/)
|
| 493 |
+
* [Health IT Research & Analysis](/data/)
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 494 |
|
| 495 |
+
#### NEWS & EVENTS
|
| 496 |
|
| 497 |
+
* [Media Center](https://healthit.gov/media-center)
|
| 498 |
+
* [ONC Blog](/blog/)
|
| 499 |
+
* [News](/news)
|
| 500 |
+
* [Events](/events)
|
| 501 |
|
| 502 |
+
#### ABOUT
|
| 503 |
|
| 504 |
+
* [About ONC](/about/)
|
| 505 |
+
* [Careers](/about/careers/)
|
| 506 |
+
* [Contact](/contact-us/)
|
| 507 |
+
* [Funding Opportunities](/about/funding-announcements/)
|
| 508 |
|
| 509 |
+
[](https://healthit.gov/ "ONC")
|
| 510 |
+
[](https://hhs.gov/ "HHS Link")
|
| 511 |
|
| 512 |
+
[Linkedin](https://www.linkedin.com/company/office-of-the-national-coordinator-for-health-it)
|
| 513 |
|
| 514 |
+
[X](https://x.com/ONC_HealthIT)
|
| 515 |
|
| 516 |
+
[YouTube](http://www.youtube.com/user/HHSONC/)
|
| 517 |
|
| 518 |
+
* [Privacy Policy](https://www.hhs.gov/web/policies-and-standards/hhs-web-policies/privacy/index.html)
|
| 519 |
+
* [Website Disclaimers](/website-disclaimers/)
|
| 520 |
+
* [Viewers & Players](http://www.hhs.gov/plugins.html)
|
| 521 |
+
* [GobiernoUSA.gov](https://gobierno.usa.gov/)
|
| 522 |
+
* [HHS Vulnerability Disclosure Policy](https://www.hhs.gov/vulnerability-disclosure-policy/index.html)
|
| 523 |
+
* [Archived Content](https://healthit.gov/archive/)
|
| 524 |
|
| 525 |
+
### External Link Notice
|
| 526 |
|
| 527 |
+
Continue
|
| 528 |
+
Cancel
|
| 529 |
|
| 530 |
+
×
|
| 531 |
|
| 532 |
+
## Welcome to HealthIT.gov!
|
| 533 |
|
| 534 |
+
Thank you for visiting the HealthIT.gov website! We welcome your feedback using the "Submit Feedback" button at the bottom of the page to help us improve your experience!
|
| 535 |
|
| 536 |
+
* Close
|
| 537 |
+
* Don't show again
|
| 538 |
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+

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if you’re not engaged in social media listening, you’re creating your business
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strategy with blinders on—and you’re missing out on mountains of actionable
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insights from real people who are actively talking about you or your industry online.
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Here’s how to start listening and building your understanding of your
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audience and their needs.
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tKnowing who your audience is and what they want to see on social is key to
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creating content that they will like, comment on, and share. This knowledge
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also critical for planning how to develop your social media fans into
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customers for your business.
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Try creating audience personas. For example, a retail brand might create
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different personas based on demographics, buying motivations, common
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buying objections, and the emotional needs of each type of customer.
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into Twitter or Instagram. You might want to focus on the networks where
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your audience is underserved, rather than trying to win fans away from a
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dominant player.
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Engage in social listening
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Social listening is another way to keep track of the competition.
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As you track your competitors’ accounts and relevant industry keywords, you
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may notice strategic shifts in the way competitors use their social accounts.
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Or you might spot a specific post or campaign that really hits the mark—or
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one that bombs.
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Keep an eye on this information and use to it evaluate your own goals and plans.
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How to conduct a
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competitor audit
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Getting started with
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social listening
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Watch: How to set up
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social listening streams
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Once you gather all this information in one place, you’ll have a good starting
|
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point for planning how to improve your results.
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Your audit should give you a clear picture of what purpose each of your
|
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social accounts serves. If the purpose of an account isn’t clear, think about
|
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whether it’s worth keeping. It may be a valuable account that just needs
|
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a strategic redirection, or it may be an outdated account that’s no longer
|
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worth your while.
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|
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2. If so, how are they using this platform?
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3. Can I use this account to help achieve meaningful business goals?
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Asking these tough questions now will help keep your social media strategy
|
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on track as you grow your social presence.
|
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Look for impostor accounts
|
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During your audit process, you may discover fraudulent accounts using your
|
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business name or the names of your products—that is, accounts that you
|
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and your business don’t own.
|
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|
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These imposter accounts can be harmful to your brand (never mind
|
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capturing followers that should be yours), so be sure to report them. You
|
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may want to get your social accounts verified to ensure your fans and
|
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followers know they are dealing with the real you.
|
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6
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accounts.
|
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| 324 |
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Determine which networks to use (and how to use them)
|
| 325 |
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|
| 326 |
-
As you decide which social channels to use, you’ll also need to define your
|
| 327 |
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strategy for each network. For example, you might decide to use Twitter for
|
| 328 |
-
customer service, Facebook for customer acquisition, and Instagram for
|
| 329 |
-
engaging existing customers.
|
| 330 |
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|
| 331 |
-
It’s a good exercise to create mission statements for each network. These
|
| 332 |
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one-sentence declarations will help you focus on a very specific goal for
|
| 333 |
-
each account on each social network.
|
| 334 |
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|
| 335 |
-
For example, you could decide that:
|
| 336 |
-
|
| 337 |
-
•• Facebook is best for acquiring new customers via paid advertising.
|
| 338 |
-
|
| 339 |
-
••
|
| 340 |
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|
| 341 |
-
Instagram is where you build brand affinity with existing customers.
|
| 342 |
-
|
| 343 |
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•• Twitter is where you engage press and industry influencers.
|
| 344 |
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|
| 345 |
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•• LinkedIn is where you engage existing employees and attract new talent.
|
| 346 |
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| 347 |
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•• YouTube is where you support existing customers with education and
|
| 348 |
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|
| 349 |
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video help content.
|
| 350 |
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|
| 351 |
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•• Snapchat is where you distribute content with the goal of building brand
|
| 352 |
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|
| 353 |
-
awareness with younger consumers.
|
| 354 |
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|
| 355 |
-
If you can’t create a solid mission statement for a particular social network,
|
| 356 |
-
you may want to reconsider whether that network is worth it.
|
| 357 |
-
|
| 358 |
-
Set up (and optimize) your accounts
|
| 359 |
-
|
| 360 |
-
Once you’ve decided which networks to focus on, it’s time to create your
|
| 361 |
-
profiles—or improve existing profiles so they align with your strategic plan.
|
| 362 |
-
|
| 363 |
-
In general, make sure you fill out all profile fields, use keywords people will
|
| 364 |
-
use to search for your business, and use images that are correctly sized for
|
| 365 |
-
each network.
|
| 366 |
-
|
| 367 |
-
GUIDE / Social Media Marketing Strategy
|
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| 369 |
7
|
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|
| 386 |
-
Award-winning accounts and campaigns
|
| 387 |
-
|
| 388 |
-
For examples of brands that are at the top of their social media game, check
|
| 389 |
-
out the winners of The Facebook Awards or The Shorty Awards.
|
| 390 |
-
|
| 391 |
-
Step 7
|
| 392 |
-
|
| 393 |
-
Create a social media content calendar
|
| 394 |
-
|
| 395 |
-
Sharing great content is essential, of course, but it’s equally important to have
|
| 396 |
-
a plan in place for when you’ll share content to get the maximum impact.
|
| 397 |
-
|
| 398 |
-
Your social media content calendar also needs to account for the time you’ll
|
| 399 |
-
spend interacting with your audience (although you need to allow for some
|
| 400 |
-
spontaneous engagement as well).
|
| 401 |
-
|
| 402 |
-
Create a posting schedule
|
| 403 |
-
|
| 404 |
-
Your social media content calendar lists the dates and times at which you will
|
| 405 |
-
publish types of content on each channel. It’s the perfect place to plan all of your
|
| 406 |
-
social media activities—from images and link sharing to blog posts and videos.
|
| 407 |
-
|
| 408 |
-
Your calendar ensures your posts are spaced out appropriately and
|
| 409 |
-
published at the optimal times. It should include both your day-to-day posts
|
| 410 |
-
and your content for social media campaigns.
|
| 411 |
-
|
| 412 |
-
Related resources
|
| 413 |
-
|
| 414 |
-
How to create a social
|
| 415 |
-
media content calendar
|
| 416 |
-
|
| 417 |
-
Watch: How to save time
|
| 418 |
-
with bulk scheduling
|
| 419 |
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|
| 420 |
-
GUIDE / Social Media Marketing Strategy
|
| 421 |
|
| 422 |
8
|
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9
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| 484 |
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|
| 485 |
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use UTM parameters to track visitors as they move through your website, so
|
| 486 |
-
you can see exactly which social posts drive the most traffic to your website.
|
| 487 |
-
|
| 488 |
-
Re-evaluate, test, and do it all again
|
| 489 |
-
|
| 490 |
-
When data starts coming in, use it to reevaluate your strategy regularly.
|
| 491 |
-
You can also use this information to test different posts, campaigns, and
|
| 492 |
-
strategies against one another. Constant testing allows you to understand
|
| 493 |
-
what works and what doesn’t, so you can refine your strategy in real time.
|
| 494 |
-
|
| 495 |
-
Surveys can also be a great way to find out how well your strategy is working.
|
| 496 |
-
Ask your social media followers, email list, and website visitors whether
|
| 497 |
-
you’re meeting their needs and expectations on social media. You can even
|
| 498 |
-
ask them what they’d like to see more of—and then make sure to deliver on
|
| 499 |
-
what they tell you.
|
| 500 |
-
|
| 501 |
-
Things change fast on social media. New networks emerge, while others
|
| 502 |
-
go through significant demographic shifts. Your business will go through
|
| 503 |
-
periods of change as well. All this means that your social media strategy
|
| 504 |
-
should be a living document that you look at regularly and adjust as needed.
|
| 505 |
-
Refer to it often to keep you on track, but don’t be afraid to make changes
|
| 506 |
-
so that it better reflects new goals, tools, or plans.
|
| 507 |
-
|
| 508 |
-
When you update your social strategy, make sure to let everyone on your
|
| 509 |
-
social team know, so they can all work together to help your business make
|
| 510 |
-
the most of your social media accounts.
|
| 511 |
-
|
| 512 |
-
GUIDE / Social Media Marketing Strategy
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10
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11
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|
| 1 |
+
FOR IMMEDIATE RELEASE Herzogenaurach, March 9, 2022
|
| 2 |
+
adidas delivers strong results in 2021 and
|
| 3 |
+
expects double-digit sales growth in 2022
|
| 4 |
+
Major developments FY 2021
|
| 5 |
+
• Currency-neutral revenues up 16% driven by growth in all markets
|
| 6 |
+
• Excellent top-line momentum in EMEA, North America and Latin America with strong
|
| 7 |
+
double-digit increases in each region
|
| 8 |
+
• Double-digit growth in DTC reflecting improvements in both online and offline
|
| 9 |
+
• Gross margin increases to 50.7% driven by higher full-price sales and better inventory
|
| 10 |
+
management
|
| 11 |
+
• Operating margin increases 5.3 percentage points to 9.4%
|
| 12 |
+
• Net income from continuing operations grows more than € 1 billion to € 1.492 billion
|
| 13 |
+
• Executive and Supervisory Boards propose dividend increase of 10% to € 3.30 per share
|
| 14 |
+
Outlook for FY 2022
|
| 15 |
+
• Currency-neutral sales to increase at a rate between 11% and 13%, already reflecting
|
| 16 |
+
up to € 250 million of risk in Russia/CIS business related to the war in Ukraine
|
| 17 |
+
• Gross margin to increase to a level of between 51.5% and 52.0%
|
| 18 |
+
• Operating margin to increase to a level of between 10.5% and 11.0%
|
| 19 |
+
• Net income from continuing operations to grow to between € 1.8 billion and € 1.9 billion
|
| 20 |
+
Kasper Rorsted, CEO of adidas: “Unfortunately, we release our 2021 results in unsettling
|
| 21 |
+
times. Our thoughts and prayers are with the Ukrainian people, our teams on the ground and
|
| 22 |
+
everyone affected by the war. We strongly condemn any form of violence and stand in solidarity
|
| 23 |
+
with all those calling for peace. We also provide immediate humanitarian aid to those in need
|
| 24 |
+
of support. We will continue to follow the situation closely and take future business decisions
|
| 25 |
+
and actions as needed, always prioritizing our employee’s safety and support.”
|
| 26 |
+
“In 2021, we delivered a strong set of results despite several external factors weighing on both
|
| 27 |
+
demand and supply throughout the year”, Kasper Rorsted continued. “Wherever markets
|
| 28 |
+
operated without major disruptions we have been experiencing strong top-line momentum.
|
| 29 |
+
This is reflected in double-digit revenue growth in EMEA, North America and Latin America.
|
| 30 |
+
While we continued to invest heavily into our brand, our direct-to-consumer business, and our
|
| 31 |
+
digital transformation, we improved our bottom-line by more than € 1 billion. Taking it all
|
| 32 |
+
together, 2021 was a successful first year within our new strategic cycle. In 2022, we will build
|
| 33 |
+
1
|
| 34 |
+
|
| 35 |
+
on this momentum and continue to grow both our top- and bottom-line at double-digit rates
|
| 36 |
+
amid heightened uncertainty.”
|
| 37 |
+
Financial Performance in 2021
|
| 38 |
+
Currency-neutral sales grow 16% despite challenging market environment
|
| 39 |
+
In 2021, adidas was able to increase its currency-neutral revenues by 16% despite several
|
| 40 |
+
external factors weighing on both demand and supply throughout the year. In total, the
|
| 41 |
+
challenging market environment in Greater China, extensive covid-19-related lockdowns in
|
| 42 |
+
Asia-Pacific as well as industry-wide supply chain disruptions reduced revenue growth by
|
| 43 |
+
more than € 1.5 billion during the year. From a channel perspective, the company’s top-line
|
| 44 |
+
increase was characterized by a strong recovery from the material revenue decline in its
|
| 45 |
+
physical distribution channels during 2020, when the global coronavirus pandemic had caused
|
| 46 |
+
a large number of temporary store closures. As a result, wholesale revenues as well as sales
|
| 47 |
+
in adidas’ own-retail stores grew at strong double-digit rates in 2021. E-commerce revenues
|
| 48 |
+
increased 4% during the year, on top of the exceptionally high growth in 2020 when e-
|
| 49 |
+
commerce revenues had grown by more than 50%. In euro terms, the company’s revenues
|
| 50 |
+
increased 15% in 2021 to € 21.234 billion (2020: € 18.435 billion).
|
| 51 |
+
Revenue improves in all market segments
|
| 52 |
+
While sales increased in all market segments in 2021, the top-line development in the regions
|
| 53 |
+
differed significantly depending on the impact the various demand and supply challenges had
|
| 54 |
+
on the specific region. While all markets were negatively impacted by industry-wide supply
|
| 55 |
+
chain challenges, the company recorded particularly strong developments in markets that
|
| 56 |
+
operated without major covid-19-related disruptions. Accordingly, currency-neutral sales in
|
| 57 |
+
EMEA, North America, and Latin America increased by 24%, 17%, and 47%, respectively. At
|
| 58 |
+
the same time, the challenging market environment in Greater China (+3%) and the extensive
|
| 59 |
+
covid-19-related restrictions in Asia-Pacific (+8%) weighed on adidas’ results in these
|
| 60 |
+
markets.
|
| 61 |
+
Gross margin at 50.7% driven by higher full-prices sales and better inventory management
|
| 62 |
+
The company’s gross margin increased 0.7 percentage points to 50.7% in 2021 (2020: 50.0%).
|
| 63 |
+
While negative currency developments, higher supply chain costs and a less favorable channel
|
| 64 |
+
and market mix weighed on the development in 2021, higher full-price sales and lower
|
| 65 |
+
inventory allowances as well as the non-recurrence of last year’s purchase order cancellation
|
| 66 |
+
costs were able to overcompensate the negative effects.
|
| 67 |
2
|
| 68 |
|
| 69 |
+
Operating margin improves by 5.3 percentage points
|
| 70 |
+
Other operating expenses increased 4% to € 8.892 billion in 2021 (2020: € 8.580 billion). As a
|
| 71 |
+
percentage of sales, other operating expenses were down 4.7 percentage points to 41.9%
|
| 72 |
+
(2020: 46.5%). Marketing and point-of-sale expenses increased 7% to € 2.547 billion
|
| 73 |
+
(2020: € 2.373 billion) due to increased investments into the brand supporting the introduction
|
| 74 |
+
of new products and to drive consumer experience across both digital and physical platforms.
|
| 75 |
+
As a percentage of sales, marketing and point-of-sale expenses decreased 0.9 percentage
|
| 76 |
+
points to 12.0% (2020: 12.9%). Operating overhead expenses increased 2% to € 6.345 billion
|
| 77 |
+
(2020: € 6.207 billion) including more than € 220 million stranded costs related to the
|
| 78 |
+
divestiture of the Reebok business. As a percentage of sales, operating overhead expenses
|
| 79 |
+
decreased 3.8 percentage points to 29.9% (2020: 33.7%). As a result of the strong top-line
|
| 80 |
+
increase in combination with the improved gross margin and lower operating expenses as a
|
| 81 |
+
percentage of sales, the company’s operating profit increased 166% to € 1.986 billion in 2021
|
| 82 |
+
(2020: € 746 million). Consequently, the operating margin increased 5.3 percentage points to
|
| 83 |
+
9.4% compared to the prior year level of 4.0%.
|
| 84 |
+
Net financial result decreases
|
| 85 |
+
Financial income decreased 32% to € 19 million in 2021 (2020: € 29 million), while financial
|
| 86 |
+
expenses were down 22% to € 153 million (2020: € 196 million). As a result, the company
|
| 87 |
+
recorded a negative net financial result of € 133 million (2020: negative € 167 million). The
|
| 88 |
+
company’s tax rate decreased 0.8 percentage points to 19.4% in 2021 (2020: 20.2%).
|
| 89 |
+
Net income from continuing operations increases by more than € 1 billion
|
| 90 |
+
Net income from continuing operations increased 223% to € 1.492 billion in 2021 (2020:
|
| 91 |
+
€ 461 million). Both basic and diluted EPS from continuing operations also increased 223% to
|
| 92 |
+
€ 7.47 (2020: € 2.31).
|
| 93 |
+
Average operating working capital as percentage of sales decreases 5.3 percentage points
|
| 94 |
+
At the end of December 2021, inventories were down 9% to € 4.009 billion (2020: € 4.397
|
| 95 |
+
billion), or 12% lower on a currency-neutral basis. This development mainly reflects the
|
| 96 |
+
divestiture of the Reebok business. The strong sell-through of the company’s products,
|
| 97 |
+
successful inventory management as well as the impact from industry-wide supply chain
|
| 98 |
+
challenges also contributed to the decline. Accounts receivable increased 11% to € 2.175
|
| 99 |
+
billion at the end of December 2021 (2020: € 1.952 billion) reflecting the company’s strong
|
| 100 |
+
top-line growth. On a currency-neutral basis, accounts receivables were up 6%. Accounts
|
| 101 |
+
payable were down 4% to € 2.294 billion at the end of December 2021 versus € 2.390 billion
|
| 102 |
+
in 2020. This development reflects the normalization of payment terms as well as the
|
| 103 |
+
divestiture of the Reebok business. On a currency-neutral basis, accounts payable decreased
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 104 |
3
|
| 105 |
|
| 106 |
+
6%. Average operating working capital as a percentage of sales decreased 5.3 percentage
|
| 107 |
+
points to 20.0% for the full year (2020: 25.3%).
|
| 108 |
+
Accelerated investments into DTC and digital
|
| 109 |
+
The company’s capital expenditure increased 51% in 2021 to € 667 million (2020: € 442
|
| 110 |
+
million). Investments in new or remodeled own-retail stores, the company’s e-commerce
|
| 111 |
+
business as well as the broader IT infrastructure represented once again the majority of the
|
| 112 |
+
expenditure.
|
| 113 |
+
Executive and Supervisory Boards propose dividend payment of € 3.30 per share
|
| 114 |
+
As a result of the strong operational and financial performance in 2021, the company’s
|
| 115 |
+
financial position as well as Management’s confidence in its long-term growth aspirations,
|
| 116 |
+
the adidas Executive and Supervisory Boards will recommend paying a dividend of € 3.30 per
|
| 117 |
+
dividend-entitled share to shareholders at the Annual General Meeting on May 12, 2022. This
|
| 118 |
+
represents an increase of 10% compared to the prior year dividend (2021: € 3.00).
|
| 119 |
+
Financial Performance in Q4 2021
|
| 120 |
+
Sales in the fourth quarter impacted by supply and demand challenges
|
| 121 |
+
Currency-neutral revenues in the fourth quarter declined 3%. Significant supply shortages as
|
| 122 |
+
a result of the lockdowns in Vietnam last year, the challenging market environment in Greater
|
| 123 |
+
China as well as covid-19-related lockdowns in Asia-Pacific reduced revenue growth by more
|
| 124 |
+
than € 400 million in Q4. In light of the supply shortages the company continued to prioritize
|
| 125 |
+
its own DTC channel. As a result, DTC revenues were stable versus the prior year, reflecting
|
| 126 |
+
a 14% increase compared to the 2019 level. While adidas e-commerce revenues experienced
|
| 127 |
+
a strong increase in full-price sales, revenues in the company’s own digital channel declined
|
| 128 |
+
by 2% during the quarter reflecting the exceptionally high growth in the prior year period.
|
| 129 |
+
Compared to the 2019 level, e-commerce revenues grew 39% in the fourth quarter. In euro
|
| 130 |
+
terms, adidas revenues were flat versus the prior year at € 5.137 billion (2020: € 5.142 billion).
|
| 131 |
+
Revenues in EMEA up strong double-digits in Q4
|
| 132 |
+
From a regional perspective, revenues in North America were most impacted by the supply
|
| 133 |
+
shortages in the fourth quarter with almost half of the total negative impact recorded in this
|
| 134 |
+
particular market. As a result, currency-neutral revenues in North America declined 4%
|
| 135 |
+
during the quarter. Nevertheless, revenues in the company’s direct-to-consumer business
|
| 136 |
+
continued to increase in the market, reflecting the company’s DTC-led strategy. While EMEA
|
| 137 |
+
was also significantly impacted by the supply shortages, revenues still grew 15%, driven by
|
| 138 |
+
double-digit growth in both DTC and wholesale. Fourth quarter revenues in Latin America
|
| 139 |
+
improved 9%, reflecting strong double-digit growth versus the 2019 level. Revenues in Greater
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 140 |
4
|
| 141 |
|
| 142 |
+
China (-24%) and APAC (-6%) declined due to the supply shortages, covid-19-related
|
| 143 |
+
restrictions and – in the case of China – the challenging market environment.
|
| 144 |
+
Gross margin slightly down 0.1 percentage points
|
| 145 |
+
In the fourth quarter of 2021, the gross margin declined slightly by 0.1 percentage points to
|
| 146 |
+
49.0% (2020: 49.1%). Significantly higher supply chain costs – the company recorded
|
| 147 |
+
additional freight costs of more than € 100 million this quarter alone – as well as continued
|
| 148 |
+
headwinds from unfavorable currency developments represented a material drag on gross
|
| 149 |
+
margin in Q4. This impact was almost completely offset by significantly higher full price sales.
|
| 150 |
+
Operating margin below prior year level
|
| 151 |
+
Other operating expenses were up 7% to € 2.501 billion during the fourth quarter (2020:
|
| 152 |
+
€ 2.331 billion). As a percentage of sales, other operating expenses increased 3.3 percentage
|
| 153 |
+
points to 48.7% (2020: 45.3%). Marketing and point-of-sale expenses increased 8% to
|
| 154 |
+
€ 715 million (2020: € 662 million) and as a percentage of sales were up to 13.9% (2020:
|
| 155 |
+
12.9%), reflecting higher investments to support the introduction of new products such as the
|
| 156 |
+
UltraBoost22, NMD S1 and the latest IVY PARK x adidas collection, as well as to elevate the
|
| 157 |
+
consumer experience across all touchpoints. Operating overhead expenses increased 7% to
|
| 158 |
+
€ 1.786 billion (2020: € 1.670 billion) and included stranded costs related to the divestiture of
|
| 159 |
+
the Reebok business in an amount of around € 60 million. As a percentage of sales, operating
|
| 160 |
+
overhead expenses increased to 34.8% (2020: 32.5%). Operating profit amounted to
|
| 161 |
+
€ 66 million (2020: € 225 million), resulting in an operating margin of 1.3% (2020: 4.4%). Net
|
| 162 |
+
income from continuing operations reached € 123 million in the quarter (2020: € 143 million),
|
| 163 |
+
supported by a positive tax benefit related to the divestiture of the Reebok business. Both basic
|
| 164 |
+
and diluted EPS from continuing operations were € 0.58 in Q4 (2020: € 0.70).
|
| 165 |
+
Outlook for 2022
|
| 166 |
+
Currency-neutral sales to increase between 11% and 13%
|
| 167 |
+
After the recovery from the coronavirus pandemic in 2021, adidas expects double-digit top-
|
| 168 |
+
line growth to continue in 2022 amid heightened uncertainty. Driven by the execution of the
|
| 169 |
+
company’s strategy ‘Own the Game’ as well as its strong product pipeline currency-neutral
|
| 170 |
+
revenues are projected to increase at a rate between 11% and 13%. This growth assumption
|
| 171 |
+
already includes a risk of up to € 250 million in the company’s Russia/CIS business – about
|
| 172 |
+
50% of adidas’ total revenues in the region – due to the war in Ukraine and reflects the
|
| 173 |
+
suspension of adidas’ retail and e-commerce operations in Russia. This amount represents
|
| 174 |
+
around 1 percentage point of growth for the total company and explains the difference to the
|
| 175 |
+
initial outlook as provided in the Management Report at the time of the preparation of the
|
| 176 |
+
company’s annual report.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
| 177 |
5
|
| 178 |
|
| 179 |
+
Currency-neutral revenues to increase in all markets
|
| 180 |
+
From a regional perspective, currency-neutral revenues are expected to increase in all
|
| 181 |
+
markets. While currency-neutral sales in North America and Latin America are projected to
|
| 182 |
+
grow at a mid- to high-teens rate, currency-neutral revenues are expected to grow at a rate
|
| 183 |
+
in the mid-teens in EMEA and Asia-Pacific. Greater China is expected to record a sales
|
| 184 |
+
increase in the mid-single digits as the company continues to make progress with its action
|
| 185 |
+
plan aimed at stabilizing the business and re-igniting growth.
|
| 186 |
+
Gross margin expected to expand to a level of between 51.5% and 52.0%
|
| 187 |
+
adidas’ gross margin is expected to continue to increase and reach a level of between 51.5%
|
| 188 |
+
and 52.0%. A positive channel mix effect, significant price increases as well as the positive
|
| 189 |
+
impact from favorable currency developments will drive the gross margin improvement and
|
| 190 |
+
are expected to outweigh significantly higher supply chain costs.
|
| 191 |
+
Operating margin to increase to a level of between 10.5% and 11.0%
|
| 192 |
+
The company’s operating margin is expected to increase significantly to a level of between
|
| 193 |
+
10.5% and 11.0%. In addition to the higher gross margin, lower operating expenses in
|
| 194 |
+
percentage of sales will benefit the company’s operating margin in 2022. This development
|
| 195 |
+
will be supported by the non-recurrence of around 70% of the Reebok-related stranded costs,
|
| 196 |
+
which accounted to more than € 220 million in 2021. Driven by the strong top-line growth in
|
| 197 |
+
combination with the margin improvements net income from continuing operations is
|
| 198 |
+
projected to increase to a level of between € 1.8 billion and € 1.9 billion in 2022.
|
| 199 |
+
***
|
| 200 |
+
Contacts:
|
| 201 |
+
Media Relations Investor Relations
|
| 202 |
+
corporate.press@adidas.com investor.relations@adidas.com
|
| 203 |
+
Tel.: +49 (0) 9132 84-2352 Tel.: +49 (0) 9132 84-2920
|
| 204 |
+
For more information, please visit adidas-group.com or report.adidas-group.com.
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
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|
|
| 205 |
6
|
| 206 |
|
| 207 |
+
| | | | | |
|
| 208 |
+
| --- | ---------------- | ---------------- | --- | --- |
|
| 209 |
+
| | Quarter ending | Quarter ending | | |
|
| 210 |
+
€ in millions December 31, 2021 December 31, 2020 Change
|
| 211 |
+
| Net sales | | 5,137 | 5,142 | (0.1%) |
|
| 212 |
+
| ------------------------------------- | --- | ----------- | -------- | -------- |
|
| 213 |
+
| Cost of sales | | 2,618 | 2,615 | 0.1% |
|
| 214 |
+
| Gross profit | | 2,519 | 2,526 | (0.3%) |
|
| 215 |
+
| (% of net sales) | | 49.0% | 49.1% | (0.1pp) |
|
| 216 |
+
| Royalty and commission income | | 33 | 18 | 86.4% |
|
| 217 |
+
| Other operating income | | 15 | 13 | 16.3% |
|
| 218 |
+
| Other operating expenses | | 2,501 | 2,331 | 7.3% |
|
| 219 |
+
| (% of net sales) | | 48.7% | 45.3% | 3.3pp |
|
| 220 |
+
| Marketing and point-of-sale expenses | | 715 | 662 | 8.2% |
|
| 221 |
+
| (% of net sales) | | 13.9% | 12.9% | 1.1pp |
|
| 222 |
+
| Operating overhead expenses2 | | 1,786 | 1,670 | 6.9% |
|
| 223 |
+
| (% of net sales) | | 34.8% | 32.5% | 2.3pp |
|
| 224 |
+
| Operating profit | | 66 | 225 | (70.9%) |
|
| 225 |
+
| (% of net sales) | | 1.3% | 4.4% | (3.1pp) |
|
| 226 |
+
| Financial income | | 17 | 11 | 59.1% |
|
| 227 |
+
| Financial expenses | | 39 | 76 | (49.4%) |
|
| 228 |
+
| Income before taxes | | 44 | 160 | (72.2%) |
|
| 229 |
+
| (% of net sales) | | 0.9% | 3.1% | (2.2pp) |
|
| 230 |
+
| Income taxes | | (79) | 17 | n.a. |
|
| 231 |
+
| (% of income before taxes) | | (177.6%) | 10.5% | n.a. |
|
| 232 |
+
Net income from continuing operations 123 143 (13.8%)
|
| 233 |
+
| (% of net sales) | | 2.4% | 2.8% | (0.4pp) |
|
| 234 |
+
| ----------------- | --- | ------- | ------- | -------- |
|
| 235 |
+
Gain from discontinued operations, net of tax 89 14 534.2%
|
| 236 |
+
| Net income | | 213 | 157 | 35.3% |
|
| 237 |
+
| ----------------- | --- | ------- | ------- | ------ |
|
| 238 |
+
| (% of net sales) | | 4.1% | 3.1% | 1.1pp |
|
| 239 |
+
Net income attributable to shareholders 202 151 33.6%
|
| 240 |
+
| (% of net sales) | | 3.9% | 2.9% | 1.0pp |
|
| 241 |
+
| ----------------- | --- | ------- | ------- | ------ |
|
| 242 |
+
Net income attributable to non-controlling interests 11 6 74.9%
|
| 243 |
+
| | | | | |
|
| 244 |
+
| --- | --- | --- | --- | --- |
|
| 245 |
+
Basic earnings per share from continuing operations (in €) 0.58 0.70 (16.8%)
|
| 246 |
+
Diluted earnings per share from continuing operations (in €) 0.58 0.70 (16.8%)
|
| 247 |
+
| | | | | |
|
| 248 |
+
| --- | --- | --- | --- | --- |
|
| 249 |
+
Basic earnings per share from continuing and discontinued operations (in €) 1.05 0.77 35.6 %
|
| 250 |
+
Diluted earnings per share from continuing and discontinued operations (in €) 1.05 0.77 35.6 %
|
| 251 |
+
| | | | | |
|
| 252 |
+
| --- | --- | --- | --- | --- |
|
| 253 |
+
1 2021 and 2020 figures reflect continuing operations as a result of the reclassification of the Reebok business to discontinued operations.
|
| 254 |
+
2 Aggregated distribution and selling expenses, general and administration expenses, sundry expenses and impairment losses (net) on accounts receivable and contract assets.
|
| 255 |
+
Rounding differences may arise.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 256 |
|
| 257 |
7
|
| 258 |
|
| 259 |
+
| | | | | | | | |
|
| 260 |
+
| --- | --------------- | --- | --------------- | --- | --- | --- | ------- |
|
| 261 |
+
| | Quarter ending | | Quarter ending | | | | Change |
|
| 262 |
+
€ in millions December 31, 2021 December 31, 2020 Change (currency-neutral)
|
| 263 |
+
| EMEA | | 1,832 | | 1,559 | 17.5% | | 15.2% |
|
| 264 |
+
| ----------------- | --- | -------- | --- | -------- | -------- | --- | -------- |
|
| 265 |
+
| North America | | 1,303 | | 1,317 | (1.1%) | | (3.7%) |
|
| 266 |
+
| Greater China | | 1,037 | | 1,287 | (19.4%) | | (24.3%) |
|
| 267 |
+
| Asia-Pacific | | 541 | | 587 | (7.8%) | | (6.0%) |
|
| 268 |
+
| Latin America | | 397 | | 365 | 8.8% | | 8.7% |
|
| 269 |
+
| Other Businesses | | 28 | | 27 | 3.6% | | 4.1% |
|
| 270 |
+
| | | | | | | | |
|
| 271 |
+
1 2021 and 2020 figures reflect continuing operations as a result of the reclassification of the Reebok business to discontinued operations.
|
| 272 |
+
Rounding differences may arise.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 273 |
|
| 274 |
8
|
| 275 |
|
| 276 |
+
| | | | | |
|
| 277 |
+
| --- | --- | ------------ | ------------ | --- |
|
| 278 |
+
| | | Year ending | Year ending | |
|
| 279 |
+
€ in millions December 31, 2021 December 31, 2020 Change
|
| 280 |
+
| Net sales | | 21,234 | 18,435 | 15.2% |
|
| 281 |
+
| ------------------------------ | --- | --------- | --------- | -------- |
|
| 282 |
+
| Cost of sales | | 10,469 | 9,213 | 13.6% |
|
| 283 |
+
| Gross profit | | 10,765 | 9,222 | 16.7% |
|
| 284 |
+
| (% of net sales) | | 50.7% | 50.0% | 0.7pp |
|
| 285 |
+
| Royalty and commission income | | 86 | 61 | 40.9% |
|
| 286 |
+
| Other operating income | | 28 | 42 | (34.8%) |
|
| 287 |
+
| Other operating expenses | | 8,892 | 8,580 | 3.6% |
|
| 288 |
+
| (% of net sales) | | 41.9% | 46.5% | (4.7pp) |
|
| 289 |
+
Marketing and point-of-sale expenses 2,547 2,373 7.3%
|
| 290 |
+
| (% of net sales) | | 12.0% | 12.9% | (0.9pp) |
|
| 291 |
+
| ----------------------------- | --- | -------- | -------- | -------- |
|
| 292 |
+
| Operating overhead expenses2 | | 6,345 | 6,207 | 2.2% |
|
| 293 |
+
| (% of net sales) | | 29.9% | 33.7% | (3.8pp) |
|
| 294 |
+
| Operating profit | | 1,986 | 746 | 166.3% |
|
| 295 |
+
| (% of net sales) | | 9.4% | 4.0% | 5.3pp |
|
| 296 |
+
| Financial income | | 19 | 29 | (32.1%) |
|
| 297 |
+
| Financial expenses | | 153 | 196 | (22.0%) |
|
| 298 |
+
| Income before taxes | | 1,852 | 578 | 220.2% |
|
| 299 |
+
| (% of net sales) | | 8.7% | 3.1% | 5.6pp |
|
| 300 |
+
| Income taxes | | 360 | 117 | 207.9% |
|
| 301 |
+
| (% of income before taxes) | | 19.4% | 20.2% | (0.8pp) |
|
| 302 |
+
Net income from continuing operations 1,492 461 223.4%
|
| 303 |
+
| (% of net sales) | | 7.0% | 2.5% | 4.5pp |
|
| 304 |
+
| ----------------- | --- | ------- | ------- | ------ |
|
| 305 |
+
Gain/(loss) from discontinued operations, net of tax 666 –19 n.a
|
| 306 |
+
| Net income | | 2,158 | 443 | 387.4% |
|
| 307 |
+
| ----------------- | --- | -------- | ------- | ------- |
|
| 308 |
+
| (% of net sales) | | 10.2% | 2.4% | 7.8pp |
|
| 309 |
+
Net income attributable to shareholders 2,116 432 389.6%
|
| 310 |
+
| (% of net sales) | | 10.0% | 2.3% | 7.6pp |
|
| 311 |
+
| ----------------- | --- | -------- | ------- | ------ |
|
| 312 |
+
Net income attributable to non-controlling interests 42 11 296.5%
|
| 313 |
+
| | | | | |
|
| 314 |
+
| --- | --- | --- | --- | --- |
|
| 315 |
+
Basic earnings per share from continuing operations (in €) 7.47 2.31 223.3%
|
| 316 |
+
Diluted earnings per share from continuing operations (in €) 7.47 2.31 223.3%
|
| 317 |
+
| | | | | |
|
| 318 |
+
| --- | --- | --- | --- | --- |
|
| 319 |
+
Basic earnings per share from continuing and discontinued operations (in €) 10.90 2.21 392.1%
|
| 320 |
+
Diluted earnings per share from continuing and discontinued operations (in €) 10.90 2.21 392.1%
|
| 321 |
+
| | | | | |
|
| 322 |
+
| --- | --- | --- | --- | --- |
|
| 323 |
+
1 2021 and 2020 figures reflect continuing operations as a result of the reclassification of the Reebok business to discontinued operations.
|
| 324 |
+
2 Aggregated distribution and selling expenses, general and administration expenses, sundry expenses and impairment losses (net) on accounts receivable and contract assets.
|
| 325 |
+
Rounding differences may arise.
|
| 326 |
|
| 327 |
9
|
| 328 |
|
| 329 |
+
| | | | | | | |
|
| 330 |
+
| --- | --- | ------------ | ------------ | --- | --- | ------- |
|
| 331 |
+
| | | Year ending | Year ending | | | Change |
|
| 332 |
+
€ in millions December 31, 2021 December 31, 2020 Change (currency-neutral)
|
| 333 |
+
| EMEA | | 7,760 | 6,308 | | 23.0% | 24.0 % |
|
| 334 |
+
| ----------------- | --- | -------- | ------ | ------ | --------- | ------- |
|
| 335 |
+
| North America | | 5,105 | 4,519 | | 13.0% | 16.6 % |
|
| 336 |
+
| Greater China | | 4,597 | 4,342 | | 5.9% | 3.0 % |
|
| 337 |
+
| Asia-Pacific | | 2,180 | 2,083 | | 4.7% | 7.7 % |
|
| 338 |
+
| Latin America | | 1,446 | 1,035 | | 39.8% | 47.2 % |
|
| 339 |
+
| Other Businesses | | 145 | | 149 | (2.6%) | (2.0%) |
|
| 340 |
+
| | | | | | | |
|
| 341 |
+
1 2021 and 2020 figures reflect continuing operations as a result of the reclassification of the Reebok business to discontinued operations.
|
| 342 |
+
Rounding differences may arise.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 343 |
|
| 344 |
10
|
| 345 |
|
| 346 |
+
| | | | | |
|
| 347 |
+
| --- | --- | --- | --- | --- |
|
| 348 |
+
€ in millions December 31, 2021 December 31, 2020 Change in %
|
| 349 |
+
| Cash and cash equivalents | | 3,828 | 3,994 | (4.1) |
|
| 350 |
+
| ------------------------------- | --- | -------- | -------- | ------- |
|
| 351 |
+
| Accounts receivable | | 2,175 | 1,952 | 11.4 |
|
| 352 |
+
| Other current financial assets | | 745 | 702 | 6.1 |
|
| 353 |
+
| Inventories | | 4,009 | 4,397 | (8.8) |
|
| 354 |
+
| Income tax receivables | | 91 | 109 | (16.9) |
|
| 355 |
+
| Other current assets | | 1,062 | 999 | 6.3 |
|
| 356 |
+
Assets classified as held for sale 2,033 0 802,610.8
|
| 357 |
+
| Total current assets | | 13,944 | 12,154 | 14.7 |
|
| 358 |
+
| ---------------------------------------- | --- | --------- | --------- | ------- |
|
| 359 |
+
| Property, plant and equipment | | 2,256 | 2,157 | 4.6 |
|
| 360 |
+
| Right-of-use assets | | 2,569 | 2,430 | 5.7 |
|
| 361 |
+
| Goodwill | | 1,228 | 1,208 | 1.7 |
|
| 362 |
+
| Trademarks | | 16 | 750 | (97.8) |
|
| 363 |
+
| Other intangible assets | | 336 | 252 | 33.6 |
|
| 364 |
+
| Long-term financial assets | | 290 | 353 | (17.8) |
|
| 365 |
+
| Other non-current financial assets | | 160 | 414 | (61.2) |
|
| 366 |
+
| Deferred tax assets | | 1,263 | 1,233 | 2.5 |
|
| 367 |
+
| Other non-current assets | | 74 | 103 | (28.4) |
|
| 368 |
+
| Total non-current assets | | 8,193 | 8,899 | (7.9) |
|
| 369 |
+
| Total assets | | 22,137 | 21,053 | 5.1 |
|
| 370 |
+
| Short-term borrowings | | 29 | 686 | (95.8) |
|
| 371 |
+
| Accounts payable | | 2,294 | 2,390 | (4.0) |
|
| 372 |
+
| Current lease liabilities | | 573 | 563 | 1.8 |
|
| 373 |
+
| Other current financial liabilities | | 363 | 446 | (18.6) |
|
| 374 |
+
| Income taxes | | 536 | 562 | (4.7) |
|
| 375 |
+
| Other current provisions | | 1,458 | 1,609 | (9.4) |
|
| 376 |
+
| Current accrued liabilities | | 2,684 | 2,172 | 23.6 |
|
| 377 |
+
| Other current liabilities | | 434 | 398 | 9.0 |
|
| 378 |
+
| Liabilities classified as held for sale | | 594 | – | n.a. |
|
| 379 |
+
| Total current liabilities | | 8,965 | 8,827 | 1.6 |
|
| 380 |
+
| Long-term borrowings | | 2,466 | 2,482 | (0.7) |
|
| 381 |
+
| Non-current lease liabilities | | 2,263 | 2,159 | 4.8 |
|
| 382 |
+
Other non-current financial liabilities 51 115 (55.4)
|
| 383 |
+
| Pensions and similar obligations | | 267 | 284 | (6.1) |
|
| 384 |
+
| --------------------------------- | --- | -------- | -------- | ------- |
|
| 385 |
+
| Deferred tax liabilities | | 122 | 241 | (49.5) |
|
| 386 |
+
| Other non-current provisions | | 149 | 229 | (34.8) |
|
| 387 |
+
| Non-current accrued liabilities | | 8 | 8 | (3.2) |
|
| 388 |
+
| Other non-current liabilities | | 9 | 17 | (45.8) |
|
| 389 |
+
| Total non-current liabilities | | 5,334 | 5,535 | (3.6) |
|
| 390 |
+
| Share capital | | 192 | 195 | (1.8) |
|
| 391 |
+
Reserves (thereof at Dec. 31st, 2021 € 128 million relating to the Reebok disposal
|
| 392 |
+
| | | 69 | (474) | n.a. |
|
| 393 |
+
| --- | --- | ----- | -------- | ----- |
|
| 394 |
+
group)
|
| 395 |
+
| Retained earnings | | 7,259 | 6,733 | 7.8 |
|
| 396 |
+
| ----------------------------- | --- | --------- | --------- | ----- |
|
| 397 |
+
| Shareholders' equity | | 7,519 | 6,454 | 16.5 |
|
| 398 |
+
| Non-controlling interests | | 318 | 237 | 34.0 |
|
| 399 |
+
| Total equity | | 7,837 | 6,691 | 17.1 |
|
| 400 |
+
| Total liabilities and equity | | 22,137 | 21,053 | 5.1 |
|
| 401 |
|
| 402 |
11
|
| 403 |
|
| 404 |
+
| Additional balance sheet information | | | | |
|
| 405 |
+
| ------------------------------------- | -------- | -------- | -------- | --------- |
|
| 406 |
+
| Operating working capital | | 3,890 | 3,960 | (1.8) |
|
| 407 |
+
| Working capital | | 4,978 | 3,328 | 49.6 |
|
| 408 |
+
| Adjusted net borrowings2 | | 2,963 | 3,148 | (5.9) |
|
| 409 |
+
| Financial leverage3 | 39.4% | 48.8% | | (9.4 pp) |
|
| 410 |
+
| | | | | |
|
| 411 |
+
| | | | | |
|
| 412 |
+
1 2021 figures reflect the reclassification of the Reebok business to assets or liabilities held for sale.
|
| 413 |
+
2 Adjusted net borrowings = short-term borrowings + long-term borrowings and future cash used in lease and pension liabilities – cash and cash equivalents and short-term financial assets.
|
| 414 |
+
3 Based on shareholders' equity.
|
| 415 |
+
Rounding differences may arise.
|
| 416 |
+
|
| 417 |
+
12
|
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| 228 |
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83
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| 230 |
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| 255 |
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| 256 |
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| 257 |
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| 258 |
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| 259 |
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| 260 |
-
time exercised is
|
| 261 |
-
reset to zero at
|
| 262 |
-
midnight. Note: The
|
| 263 |
-
user can select
|
| 264 |
-
between the
|
| 265 |
-
|
| 266 |
-
following four exerciser options.
|
| 267 |
-
1. Running
|
| 268 |
-
2. Badminton
|
| 269 |
-
3. Climbing
|
| 270 |
-
4. Bicycling
|
| 271 |
-
|
| 272 |
-
99
|
| 273 |
-
|
| 274 |
-
Heart rate monitor:
|
| 275 |
-
Measures the
|
| 276 |
-
wearer's current
|
| 277 |
-
resting heart rate
|
| 278 |
-
and displays that
|
| 279 |
-
data as the number
|
| 280 |
-
of heartbeats per
|
| 281 |
-
|
| 282 |
-
minute (BPM). Note: Data will be
|
| 283 |
-
saved in the app
|
| 284 |
-
|
| 285 |
-
87
|
| 286 |
|
| 287 |
131
|
| 288 |
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| 289 |
-
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| 290 |
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| 291 |
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| 306 |
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| 312 |
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| 313 |
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| 316 |
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| 317 |
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(
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| 318 |
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| 319 |
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| 321 |
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| 322 |
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| 326 |
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| 327 |
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| 328 |
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| 329 |
-
(
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| 330 |
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| 331 |
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| 332 |
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| 333 |
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| 334 |
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| 335 |
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| 343 |
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| 349 |
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| 354 |
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| 355 |
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| 356 |
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| 357 |
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| 358 |
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| 359 |
-
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| 360 |
-
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| 361 |
-
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| 362 |
-
The
|
| 363 |
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| 364 |
-
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| 365 |
-
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| 366 |
-
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| 367 |
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| 368 |
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| 369 |
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| 370 |
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| 371 |
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| 372 |
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| 373 |
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| 374 |
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| 375 |
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| 376 |
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| 377 |
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| 378 |
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| 379 |
-
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| 380 |
-
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| 381 |
-
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| 382 |
-
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| 383 |
-
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| 384 |
-
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| 385 |
-
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| 386 |
-
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| 387 |
-
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| 388 |
-
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| 389 |
-
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| 390 |
-
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| 391 |
-
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| 392 |
-
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| 393 |
-
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| 394 |
-
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| 395 |
-
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| 396 |
-
|
| 397 |
-
|
| 398 |
-
|
| 399 |
-
|
| 400 |
-
|
| 401 |
-
|
| 402 |
-
|
| 403 |
-
|
| 404 |
-
|
| 405 |
-
|
| 406 |
-
|
| 407 |
-
|
| 408 |
-
|
| 409 |
-
|
| 410 |
-
|
| 411 |
-
|
| 412 |
-
|
| 413 |
-
|
| 414 |
-
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| 415 |
-
|
| 416 |
-
|
| 417 |
-
|
| 418 |
-
|
| 419 |
-
|
| 420 |
-
|
| 421 |
-
|
| 422 |
-
|
| 423 |
-
|
| 424 |
-
|
| 425 |
-
|
| 426 |
-
|
| 427 |
-
|
| 428 |
-
|
| 429 |
-
|
| 430 |
-
|
| 431 |
-
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| 432 |
-
|
| 433 |
-
|
| 434 |
-
|
| 435 |
-
|
| 436 |
-
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| 437 |
-
|
| 438 |
-
|
| 439 |
-
|
| 440 |
-
|
| 441 |
-
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| 442 |
-
|
| 443 |
-
|
| 444 |
-
|
| 445 |
-
|
| 446 |
-
|
| 447 |
-
|
| 448 |
-
|
| 449 |
-
|
| 450 |
-
|
| 451 |
-
|
| 452 |
-
|
| 453 |
-
|
| 454 |
-
|
| 455 |
-
|
| 456 |
-
|
| 457 |
-
|
| 458 |
-
|
| 459 |
-
|
| 460 |
-
|
| 461 |
-
|
| 462 |
-
|
| 463 |
-
|
| 464 |
-
|
| 465 |
-
|
| 466 |
-
|
| 467 |
-
|
| 468 |
-
|
| 469 |
-
|
| 470 |
-
|
| 471 |
-
|
| 472 |
-
|
| 473 |
-
|
| 474 |
-
|
| 475 |
-
|
| 476 |
-
|
| 477 |
-
|
| 478 |
-
|
| 479 |
-
|
| 480 |
-
|
| 481 |
-
|
| 482 |
-
|
| 483 |
-
|
| 484 |
-
|
| 485 |
-
|
| 486 |
-
|
| 487 |
-
|
| 488 |
-
|
| 489 |
-
|
| 490 |
-
|
| 491 |
-
|
| 492 |
-
|
| 493 |
-
|
| 494 |
-
|
| 495 |
-
|
| 496 |
-
|
| 497 |
-
|
| 498 |
-
|
| 499 |
-
|
| 500 |
-
|
| 501 |
-
|
| 502 |
-
|
| 503 |
-
|
| 504 |
-
|
| 505 |
-
|
| 506 |
-
|
| 507 |
-
|
| 508 |
-
|
| 509 |
-
|
| 510 |
-
|
| 511 |
-
|
| 512 |
-
|
| 513 |
-
|
| 514 |
-
|
| 515 |
-
|
| 516 |
-
|
| 517 |
-
|
| 518 |
-
|
| 519 |
-
|
| 520 |
-
|
| 521 |
-
|
| 522 |
-
|
| 523 |
-
|
| 524 |
-
|
| 525 |
-
|
| 526 |
-
|
| 527 |
-
|
| 528 |
-
|
| 529 |
-
|
| 530 |
-
|
| 531 |
-
|
| 532 |
-
|
| 533 |
-
be
|
| 534 |
-
|
| 535 |
-
|
| 536 |
-
-
|
| 537 |
-
|
| 538 |
-
|
| 539 |
-
-
|
| 540 |
-
|
| 541 |
-
-
|
| 542 |
-
|
| 543 |
-
|
| 544 |
-
|
| 545 |
-
|
| 546 |
-
|
| 547 |
-
|
| 548 |
-
-
|
| 549 |
-
|
| 550 |
-
|
| 551 |
-
|
| 552 |
-
|
| 553 |
-
|
| 554 |
-
|
| 555 |
-
|
| 556 |
-
-
|
| 557 |
-
|
| 558 |
-
-
|
| 559 |
-
|
| 560 |
-
-
|
| 561 |
-
|
| 562 |
-
|
| 563 |
-
|
| 564 |
-
|
| 565 |
-
-
|
| 566 |
-
|
| 567 |
-
|
| 568 |
-
|
| 569 |
-
|
| 570 |
-
|
| 571 |
-
-
|
| 572 |
-
|
| 573 |
-
---
|
| 574 |
-
|
| 575 |
-
|
| 576 |
-
|
| 577 |
-
|
| 578 |
-
|
| 579 |
-
-
|
| 580 |
-
|
| 581 |
-
|
| 582 |
-
|
| 583 |
-
|
| 584 |
-
|
| 585 |
-
|
| 586 |
-
|
| 587 |
-
|
| 588 |
-
|
| 589 |
-
|
| 590 |
-
|
| 591 |
-
|
| 592 |
-
|
| 593 |
-
|
| 594 |
-
|
| 595 |
-
-
|
| 596 |
-
|
| 597 |
-
|
| 598 |
-
|
| 599 |
-
|
| 600 |
-
|
| 601 |
-
|
| 602 |
-
|
| 603 |
-
|
| 604 |
-
|
|
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| 605 |
|
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|
|
| 1 |
+
DOI: 10.1111/polp.12517
|
| 2 |
+
|
| 3 |
+
O R I G I N A L A R T I C L E
|
| 4 |
+
|
| 5 |
+
The fluid voter: Exploring independent voting patterns
|
| 6 |
+
over time
|
| 7 |
+
|
| 8 |
+
Thom Reilly1
|
| 9 |
+
|
| 10 |
+
| Dan Hunting2
|
| 11 |
+
|
| 12 |
+
1School of Public Affairs, Arizona State
|
| 13 |
+
University, Phoenix, Arizona, USA
|
| 14 |
+
|
| 15 |
+
2Lodestar Center for Philanthropy and
|
| 16 |
+
Nonprofit Innovation, Arizona State
|
| 17 |
+
University, Phoenix, Arizona, USA
|
| 18 |
+
|
| 19 |
+
Correspondence
|
| 20 |
+
|
| 21 |
+
Thom Reilly, School of Public Affairs, Arizona
|
| 22 |
+
State University, 411 N Central Ave. Office 422K,
|
| 23 |
+
Mail Code 3720, Phoenix, AZ 85005, USA.
|
| 24 |
+
Email: thom.reilly@asu.edu
|
| 25 |
+
|
| 26 |
+
Abstract
|
| 27 |
+
Independents remain hard to categorize because they are, by
|
| 28 |
+
their choice of self-identification, resisting the standard cate-
|
| 29 |
+
gories of political classification. Despite the growth in inde-
|
| 30 |
+
pendent voter identity, many political strategists still view
|
| 31 |
+
independents as partisans. In this article, we contribute to the
|
| 32 |
+
academic literature on independent voting behavior by explor-
|
| 33 |
+
ing whether those who identify as politically independent
|
| 34 |
+
function as true independents by accounting for their voting
|
| 35 |
+
patterns over time. We do this by analyzing data produced by
|
| 36 |
+
the American National Election Studies (ANES) on political
|
| 37 |
+
identification and voting choices from 1972 to 2020 on each
|
| 38 |
+
of the three ANES measures of party affiliation. Our findings
|
| 39 |
+
show when tracking independent voting behavior over more
|
| 40 |
+
than one election, there is a significant volatility in voting
|
| 41 |
+
loyalty and independents as a group are distinct from parti-
|
| 42 |
+
sans. This volatility was observed in all three measures of party
|
| 43 |
+
affiliation used by the ANES survey data. The research also
|
| 44 |
+
finds evidence that a sizeable number of independents move
|
| 45 |
+
in and out of independent status from one election to another.
|
| 46 |
+
|
| 47 |
+
K E Y W O R D S
|
| 48 |
+
ANES, elections, fluid voter, independent voter, over time, partisanship,
|
| 49 |
+
political behavior, political parties, United States, volatility, voter identifi-
|
| 50 |
+
cation, voting behavior, voting loyalty
|
| 51 |
+
|
| 52 |
+
Related Articles
|
| 53 |
+
Grossmann, Matt. 2014. “The Varied Effects of Policy Cues
|
| 54 |
+
on Partisan Opinions.” Politics & Policy 42(6): 881–904.
|
| 55 |
+
https://doi.org/10.1111/polp.12102.
|
| 56 |
+
Reilly, Thom, and E. C. Hedberg. 2022. “Social Networks
|
| 57 |
+
of Independents and Partisans: Are Independents a Moder-
|
| 58 |
+
ating Forcer?” Politics & Policy 50(2): 225–43. https://doi.
|
| 59 |
+
org/10.1111/polp.12460.
|
| 60 |
+
Saeki, Manabu. 2019. “Anatomy of Party Sorting: Parti-
|
| 61 |
+
san Polarization of Voters and Party Switching.” Politics &
|
| 62 |
+
Policy 47(4): 699–747. https://doi.org/10.1111/polp.12318.
|
| 63 |
+
|
| 64 |
+
Politics & Policy. 2023;00:1–22.
|
| 65 |
+
|
| 66 |
+
wileyonlinelibrary.com/journal/polp
|
| 67 |
+
|
| 68 |
+
1
|
| 69 |
+
|
| 70 |
+
© 2023 Policy Studies Organization.
|
| 71 |
+
2
|
| 72 |
+
|
| 73 |
+
THE FLUID VOTER
|
| 74 |
+
|
| 75 |
+
Americans are increasingly declaring independence from the political parties. The rise in political
|
| 76 |
+
independence is likely an outgrowth of Americans' record or near-record negative views of the
|
| 77 |
+
U.S. two-party system (Ingraham, 2021) and their low level of trust in government (PEW, 2022).
|
| 78 |
+
Self-defined independent voters now number between 40% and 46% of the U.S. electorate
|
| 79 |
+
(Gallup, 2022) and currently constitute either the largest or second-largest group of registered
|
| 80 |
+
voters in half the states (Gruber & Opdycke, 2020). Despite the historical increase in independ-
|
| 81 |
+
ent voter identification, many political strategists still view independents as partisans (Magleby
|
| 82 |
+
et al., 2011; Petrocik, 2009) and contend that the overwhelming majority of Americans who say
|
| 83 |
+
they are “independent” really lean toward one party or the other. However, other scholars have
|
| 84 |
+
disputed the findings that most independents are leaners and suggest that there is no conclusive
|
| 85 |
+
evidence for this position (Abrams & Fiorina, 2011).
|
| 86 |
+
|
| 87 |
+
Our study seeks to contribute to the academic literature by exploring whether those who are
|
| 88 |
+
identified as politically independent function as true independents by accounting for their voting
|
| 89 |
+
patterns over time. We are interested in determining whether independents move in and out of
|
| 90 |
+
independent status. We do this by reviewing the voting behavior of Democrats, Republicans,
|
| 91 |
+
and independents over multiple election cycles. Our research seeks to address the following three
|
| 92 |
+
questions:
|
| 93 |
+
|
| 94 |
+
1. Does political identification change across time?
|
| 95 |
+
2. How do respondents allocate their votes across parties?
|
| 96 |
+
3. Do voting choices change over time?
|
| 97 |
+
|
| 98 |
+
LITERATURE REVIEW
|
| 99 |
+
|
| 100 |
+
The classification of voters as independent dates back to the seminal work of Angus Campbell
|
| 101 |
+
and his colleagues, who first published The American Voter in 1960 (Campbell et al., 1960).
|
| 102 |
+
Analyzing data collected under the University of Michigan Survey Research Center (and later
|
| 103 |
+
aggregated by the American National Election Studies; ANES Data Center, 2021), the authors
|
| 104 |
+
describe the identity of party affiliation as a central characteristic explaining voting behavior
|
| 105 |
+
and other political attitudes and behaviors. The surveys that The American Voter analyzed have
|
| 106 |
+
been considered by many to be the gold standard in the field. Though officially founded in 1978,
|
| 107 |
+
the American National Election Studies (ANES) program has continuous survey data on the
|
| 108 |
+
electorate since 1948. The survey is usually administered every other year, but occasionally every
|
| 109 |
+
fourth year. ANES is a comprehensive survey which provides much information on respondents'
|
| 110 |
+
background and political attitude.
|
| 111 |
+
|
| 112 |
+
The American Voter authors acknowledged that some kind of “independent” existed but
|
| 113 |
+
characterized the independent as having little interest in campaigns and outcomes and suggested
|
| 114 |
+
their choice between competing candidates is uninformed. Most of what we know about inde-
|
| 115 |
+
pendents comes from survey data, and most surveys predispose the majority of independents as
|
| 116 |
+
leaners toward either of the two political parties. Since 1952, when individuals identified them-
|
| 117 |
+
selves as an independent, researchers and pollsters have asked a follow-up question on whether
|
| 118 |
+
respondents prefer one party over the other if they had to vote then and there.
|
| 119 |
+
|
| 120 |
+
In addition to asking respondents to identify themselves from a three-point scale: Democrat,
|
| 121 |
+
Republican, and independent, respondents were asked to self-identify on the ANES seven-point
|
| 122 |
+
political spectrum (ANES Data Center, 2015):
|
| 123 |
+
|
| 124 |
+
1. Strong Democrat
|
| 125 |
+
2. Democrat
|
| 126 |
+
3. Independent, leans Democrat
|
| 127 |
+
4. Independent
|
| 128 |
+
|
| 129 |
+
REILLY anD HUnTInG
|
| 130 |
+
|
| 131 |
+
3
|
| 132 |
+
|
| 133 |
+
5. Independent, leans Republican
|
| 134 |
+
6. Republican
|
| 135 |
+
7. Strong Republican
|
| 136 |
+
|
| 137 |
+
Since the seven-point measure was introduced in the 1952 survey, researchers accessing the ANES
|
| 138 |
+
data were able to use several measures. They could use the seven-point measure, a five-point
|
| 139 |
+
measure by collapsing the three independent categories into one (as the authors of the Amer-
|
| 140 |
+
ican Voter did), a three-point measure with leaners classed as independents, or a three-point
|
| 141 |
+
measure with leaners classified as partisans. Researchers used any or all of these measures often
|
| 142 |
+
depending on which coding decision gave them big enough cell sizes for analysis by re-coding the
|
| 143 |
+
data or not (DeBell, 2010).
|
| 144 |
+
|
| 145 |
+
Viewing the majority of independents as partisans originates from the formative research
|
| 146 |
+
popularized in The Myth of the Independent Voter (Keith et al., 1992), which claimed that the
|
| 147 |
+
ANES' “Seven-Point Scale” should only include three actual categories (Democrat, Repub-
|
| 148 |
+
lican, and Independent). After the Petrocik (2009) and Keith and others' (1992) articles, it
|
| 149 |
+
became more common to use a five-point or three-point measure with leaners classified as
|
| 150 |
+
independents.
|
| 151 |
+
|
| 152 |
+
Most independents indicated a lean toward one of the two major political parties' candi-
|
| 153 |
+
dates. Political scientists have labeled these individuals as “independent leaners” and have argued
|
| 154 |
+
that the number of pure independents is actually quite small—below 10%. This percentage has
|
| 155 |
+
remained constant since the 1950s (Mayer, 2008; PEW, 2019; Sides, 2013), and many political
|
| 156 |
+
scientists assert that the overwhelming majority of Americans who say there are “independent”
|
| 157 |
+
lean toward one party or the other (Teixiera, 2012).
|
| 158 |
+
|
| 159 |
+
Klar and Krupnikov (2016) have recently added some important research on the independent
|
| 160 |
+
voter. They explored the social significance of the growth in people refusing to identify them-
|
| 161 |
+
selves with a political party and suggested that independents and partisans differ psychologically
|
| 162 |
+
(Klar & Krupnikov, 2016). They do not dispute the notion that independents may be “closet
|
| 163 |
+
partisans” (they call them “undercover partisans”); but they do dispute the bias that independ-
|
| 164 |
+
ents are not politically engaged, stating that “engagement levels are comparable across independ-
|
| 165 |
+
ents and partisans” (Klar, 2014). They assert that many Americans are embarrassed by their
|
| 166 |
+
political party and do not wish to be associated with either side. Instead, they intentionally mask
|
| 167 |
+
their party preference, especially in social situations (Klar & Krupnikov, 2016). Nonetheless, they
|
| 168 |
+
contend that the refusal to publicly identify with a party must be revealing something important.
|
| 169 |
+
And they believe the predictors of independent political engagement differ substantially from
|
| 170 |
+
partisans.
|
| 171 |
+
|
| 172 |
+
However, there are some researchers that disagree with the assertion that independents
|
| 173 |
+
are leaners and suggest there is more volatility in their voter patterns, and that a sizeable
|
| 174 |
+
number of independents move in and out of independent status in ways that impact inde-
|
| 175 |
+
pendent voting over time (Abrams & Fiorina, 2011; Fiorina, 1977, 2016; Jackson, 1975;
|
| 176 |
+
Page & Jones, 1979). Their identification may depend on specific candidates or issues on the
|
| 177 |
+
ballot (Reilly et al., 2023) or may derive from short-term interest rather than a long-standing
|
| 178 |
+
loyalty (Miller, 1991). Fiorina (2017), professor of political science at Stanford University and
|
| 179 |
+
former chairman of the board of the ANES, contends that following independent leaners
|
| 180 |
+
over several elections is key to understanding their voting patterns. Along with his colleague
|
| 181 |
+
Samuel J. Abrams, they conducted such an analysis and found that, following independent
|
| 182 |
+
leaners across multiple elections, their partisan stability is closer to pure independents than
|
| 183 |
+
weak partisans (Fiorina, 2017). They also noted that “classifying all leaners as weak partisans
|
| 184 |
+
mis-characterizes the partisanship of Americans and overestimates the rate of party voting”
|
| 185 |
+
(Abrams & Fiorina, 2011). Other researchers have argued that responses to survey question
|
| 186 |
+
probes asking independents if they lean toward the Democratic or Republican Party are
|
| 187 |
+
significantly contaminated by short-term electoral elements operating in the campaign, such
|
| 188 |
+
|
| 189 |
+
4
|
| 190 |
+
|
| 191 |
+
THE FLUID VOTER
|
| 192 |
+
|
| 193 |
+
as the candidates and specific issues (Abrams & Fiorina, 2011; Brody, 1978, 1991; Brody &
|
| 194 |
+
Rothenberg, 1988; Miller, 1991).
|
| 195 |
+
|
| 196 |
+
Finally, given the lack of data on voting patterns of independents in state races and
|
| 197 |
+
down-ballot (other than for president, governor, and Congress), there is growing interest in
|
| 198 |
+
examining the characteristics and attitudes of unaffiliated or independent voters as they
|
| 199 |
+
compare to voters from the two major parties. Bitzer and others (2022) researched down-ballot
|
| 200 |
+
voters in North Carolina and found unaffiliated voters were not simply shadow partisans but
|
| 201 |
+
varied from Democrats and Republicans in terms of demographics, political behavior, and polit-
|
| 202 |
+
ical attitudes.
|
| 203 |
+
|
| 204 |
+
OUR EXPECTATIONS
|
| 205 |
+
|
| 206 |
+
Our study seeks to contribute to the academic literature by exploring whether those who are
|
| 207 |
+
identified as politically independent function as true independents by accounting for their voting
|
| 208 |
+
patterns over time. The study also explores whether independents move in and out of independ-
|
| 209 |
+
ent status.
|
| 210 |
+
|
| 211 |
+
We begin with a description of ANES data and the three measures of party affiliation used
|
| 212 |
+
by the survey. Analysis then begins with a look at how the political identification of voters
|
| 213 |
+
changes over multiple survey waves using each of the three ANES scales to be described in the
|
| 214 |
+
next section. This analysis includes a parallel review of respondents who voted in both waves and
|
| 215 |
+
those who voted in neither wave. We next investigate how frequently respondents to the ANES
|
| 216 |
+
vote “straight tickets”—always choosing candidates from the same party—or “mixed tickets”
|
| 217 |
+
where some Republican and some Democrat candidates are chosen. It is expected that those
|
| 218 |
+
identifying as Democrat or Republican will mostly choose candidates from their own party,
|
| 219 |
+
while independents will show more variety in their choices. These results will also be reported on
|
| 220 |
+
each of the three political identification scales discussed below. Finally, we explore the degree to
|
| 221 |
+
which individuals change their voting choices over time.
|
| 222 |
+
|
| 223 |
+
METHODOLOGY
|
| 224 |
+
|
| 225 |
+
The ANES Cumulative Data File (CDF) is used to examine political identification and voting
|
| 226 |
+
choices from 1972 to 2020 (ANES Data Center, n.d.). Although the CDF contains data dating
|
| 227 |
+
back to 1948, restricting the analysis to data from 1972 onward provided the best balance of: (a)
|
| 228 |
+
providing a large enough sample to be useful and (b) capturing attitudes and trends that are rele-
|
| 229 |
+
vant in the current social and political climate. There have been substantial demographic changes
|
| 230 |
+
in the United States over the 72 years of ANES data. Additionally, prior to the passage of the
|
| 231 |
+
Voting Rights Act of 1965, large portions of the population were effectively disenfranchised.
|
| 232 |
+
These changes become evident when pre-1972 ANES data are compared to 1972–2020 data.
|
| 233 |
+
Prior to 1972, 6.4% of ANES respondents who reported voting were non-White, but the figure
|
| 234 |
+
jumps to 22.4% when looking at voters between 1972 and 2020. This percentage is much more in
|
| 235 |
+
line with current voter profiles. Smaller, but still important, changes are evident in the age distri-
|
| 236 |
+
bution and gender of respondents across the two time periods. Eighteen- to twenty-year-olds
|
| 237 |
+
made up 1.5% of the pre-1972 respondents and 5.9% after that. Females made up 52.4% of
|
| 238 |
+
the pre-1972 respondents and 53.8% from 1972 to 2020. The 1972–2020 data are more closely
|
| 239 |
+
aligned with current voter demographics, making this analysis more applicable to today's voters.
|
| 240 |
+
This dataset includes political identification information for respondents and self-reported
|
| 241 |
+
voting choices for president, Senate, Congress, and governor races. Since the ANES does not
|
| 242 |
+
show 2020 election preference data in the CDF, these data were linked to the CDF using the
|
| 243 |
+
Respondent ID from the ANES 2020 timeseries file. The resulting file was then formatted so that
|
| 244 |
+
|
| 245 |
+
REILLY anD HUnTInG
|
| 246 |
+
|
| 247 |
+
5
|
| 248 |
+
|
| 249 |
+
each record represented a unique respondent, capturing party identification on three scales and
|
| 250 |
+
reported voting choices for all survey waves that each respondent answered.
|
| 251 |
+
|
| 252 |
+
We examine three questions, looking at each on three different political identification scales:
|
| 253 |
+
|
| 254 |
+
1. Does political identification change across time?
|
| 255 |
+
2. How do respondents allocate their votes across parties?
|
| 256 |
+
3. Do voting choices change over time?
|
| 257 |
+
|
| 258 |
+
To probe these areas, we look at political identification with three different scales commonly used
|
| 259 |
+
by the ANES. First, with the initial party identification queried in question VCF0302, which
|
| 260 |
+
asks, “Generally speaking, do you usually think of yourself as a Democrat, a Republican, an
|
| 261 |
+
Independent, or what?” This “Initial Party ID Response” gives a three-point scale with Demo-
|
| 262 |
+
crats and Republicans, and all minor-party and independent respondents grouped under the
|
| 263 |
+
independent umbrella. Second, we use the ANES Seven-Point Scale (VCF0301, “Seven Point
|
| 264 |
+
Scale”) that divides Democrats and Republicans into “strong” and “weak” supporters of their
|
| 265 |
+
parties, and divides independents into Democrat-leaners, Republican-leaners, and true independ-
|
| 266 |
+
ents. Finally, we use the modified three-point scale from VCF0303 “Summary 3-Category.” The
|
| 267 |
+
Summary 3-Category measure collapses the Seven-Point Scale by counting Democrat-leaning
|
| 268 |
+
independents as Democrats and Republican-leaning independents as Republicans. This leaves
|
| 269 |
+
only a small fraction of the respondents as independents.
|
| 270 |
+
|
| 271 |
+
American National Election Studies Survey
|
| 272 |
+
|
| 273 |
+
The CDF was downloaded in SPSS format and filtered to include responses from 1972 to 2020.
|
| 274 |
+
Since 2020 post-election voting information is not currently in the CDF, data from the 2020
|
| 275 |
+
time-series file were joined to the CDF to provide complete information on the 2016–2020 panel.
|
| 276 |
+
The resulting file contains responses from 43,423 individuals, of whom 27,832 voted in at least
|
| 277 |
+
one election (Table 1).
|
| 278 |
+
|
| 279 |
+
The ANES contains data on how respondents reported voting on four different contests,
|
| 280 |
+
giving the party choice for president, Congress, Senate, and governor. Respondents do not neces-
|
| 281 |
+
sarily vote in each of these races due to the timing of elections. Choices for a total of 77,729
|
| 282 |
+
contests are recorded for the 27,832 voters in the data. For each election cycle, the total number
|
| 283 |
+
of votes for Democratic, Republican, and third-party candidates were totaled for each respond-
|
| 284 |
+
ent, along with their party identification at that time. The survey has also included time-series
|
| 285 |
+
panel data from time to time, where respondents are contacted multiple times over the years. For
|
| 286 |
+
respondents that appeared in multiple waves of the survey, their votes and party identification
|
| 287 |
+
were tallied at each survey point.
|
| 288 |
+
|
| 289 |
+
Since 1970, there have been seven panels as shown in Table 2, each covering a single presi-
|
| 290 |
+
dential election. Of the 13,399 respondents to the survey in these panels, 4770 voted in all waves
|
| 291 |
+
available to them. These voters reported their voting choice on a total of 25,024 races for pres-
|
| 292 |
+
ident, Congress, Senate, and governor. Due to the timing of election cycles, not all respondents
|
| 293 |
+
reported voting in each of these races in each wave of the survey.
|
| 294 |
+
|
| 295 |
+
Party identification on three scales
|
| 296 |
+
|
| 297 |
+
ANES CDF classifies the political identification of respondents according to their answers to
|
| 298 |
+
questions VCF0302, VCF0301, and VCF0303.
|
| 299 |
+
|
| 300 |
+
VCF0302 is the initial party identification response and asks:
|
| 301 |
+
|
| 302 |
+
6
|
| 303 |
+
|
| 304 |
+
THE FLUID VOTER
|
| 305 |
+
|
| 306 |
+
T A B L E 1 ANES respondents by year
|
| 307 |
+
|
| 308 |
+
Total respondents
|
| 309 |
+
|
| 310 |
+
Respondents who voted
|
| 311 |
+
|
| 312 |
+
Total votes tallied
|
| 313 |
+
|
| 314 |
+
Year
|
| 315 |
+
|
| 316 |
+
1972
|
| 317 |
+
|
| 318 |
+
1974
|
| 319 |
+
|
| 320 |
+
1976
|
| 321 |
+
|
| 322 |
+
1978
|
| 323 |
+
|
| 324 |
+
1980
|
| 325 |
+
|
| 326 |
+
1982
|
| 327 |
+
|
| 328 |
+
1984
|
| 329 |
+
|
| 330 |
+
1986
|
| 331 |
+
|
| 332 |
+
1988
|
| 333 |
+
|
| 334 |
+
1990
|
| 335 |
+
|
| 336 |
+
1992
|
| 337 |
+
|
| 338 |
+
1994
|
| 339 |
+
|
| 340 |
+
1996
|
| 341 |
+
|
| 342 |
+
1998
|
| 343 |
+
|
| 344 |
+
2000
|
| 345 |
+
|
| 346 |
+
2002
|
| 347 |
+
|
| 348 |
+
2004
|
| 349 |
+
|
| 350 |
+
2008
|
| 351 |
+
|
| 352 |
+
2012
|
| 353 |
+
|
| 354 |
+
2016
|
| 355 |
+
|
| 356 |
+
2020
|
| 357 |
+
|
| 358 |
+
2705
|
| 359 |
+
|
| 360 |
+
475
|
| 361 |
+
|
| 362 |
+
1323
|
| 363 |
+
|
| 364 |
+
2304
|
| 365 |
+
|
| 366 |
+
1614
|
| 367 |
+
|
| 368 |
+
1418
|
| 369 |
+
|
| 370 |
+
2257
|
| 371 |
+
|
| 372 |
+
2176
|
| 373 |
+
|
| 374 |
+
2040
|
| 375 |
+
|
| 376 |
+
1980
|
| 377 |
+
|
| 378 |
+
1126
|
| 379 |
+
|
| 380 |
+
1036
|
| 381 |
+
|
| 382 |
+
398
|
| 383 |
+
|
| 384 |
+
1281
|
| 385 |
+
|
| 386 |
+
1807
|
| 387 |
+
|
| 388 |
+
324
|
| 389 |
+
|
| 390 |
+
1212
|
| 391 |
+
|
| 392 |
+
2322
|
| 393 |
+
|
| 394 |
+
5914
|
| 395 |
+
|
| 396 |
+
4270
|
| 397 |
+
|
| 398 |
+
5441
|
| 399 |
+
|
| 400 |
+
1718
|
| 401 |
+
|
| 402 |
+
237
|
| 403 |
+
|
| 404 |
+
691
|
| 405 |
+
|
| 406 |
+
1167
|
| 407 |
+
|
| 408 |
+
989
|
| 409 |
+
|
| 410 |
+
798
|
| 411 |
+
|
| 412 |
+
1427
|
| 413 |
+
|
| 414 |
+
1087
|
| 415 |
+
|
| 416 |
+
1226
|
| 417 |
+
|
| 418 |
+
1236
|
| 419 |
+
|
| 420 |
+
807
|
| 421 |
+
|
| 422 |
+
693
|
| 423 |
+
|
| 424 |
+
239
|
| 425 |
+
|
| 426 |
+
648
|
| 427 |
+
|
| 428 |
+
1240
|
| 429 |
+
|
| 430 |
+
160
|
| 431 |
+
|
| 432 |
+
829
|
| 433 |
+
|
| 434 |
+
1580
|
| 435 |
+
|
| 436 |
+
4355
|
| 437 |
+
|
| 438 |
+
3124
|
| 439 |
+
|
| 440 |
+
3581
|
| 441 |
+
|
| 442 |
+
7215
|
| 443 |
+
|
| 444 |
+
760
|
| 445 |
+
|
| 446 |
+
1731
|
| 447 |
+
|
| 448 |
+
2463
|
| 449 |
+
|
| 450 |
+
2572
|
| 451 |
+
|
| 452 |
+
1860
|
| 453 |
+
|
| 454 |
+
3314
|
| 455 |
+
|
| 456 |
+
2549
|
| 457 |
+
|
| 458 |
+
3104
|
| 459 |
+
|
| 460 |
+
4294
|
| 461 |
+
|
| 462 |
+
3888
|
| 463 |
+
|
| 464 |
+
2575
|
| 465 |
+
|
| 466 |
+
562
|
| 467 |
+
|
| 468 |
+
1509
|
| 469 |
+
|
| 470 |
+
3838
|
| 471 |
+
|
| 472 |
+
247
|
| 473 |
+
|
| 474 |
+
2058
|
| 475 |
+
|
| 476 |
+
3624
|
| 477 |
+
|
| 478 |
+
11,322
|
| 479 |
+
|
| 480 |
+
12,981
|
| 481 |
+
|
| 482 |
+
5263
|
| 483 |
+
|
| 484 |
+
77,729
|
| 485 |
+
|
| 486 |
+
Total
|
| 487 |
+
|
| 488 |
+
43,423
|
| 489 |
+
|
| 490 |
+
27,832
|
| 491 |
+
|
| 492 |
+
T A B L E 2 Multiple-wave voters in ANES data, 1972–2000
|
| 493 |
+
|
| 494 |
+
Year of 1st wave
|
| 495 |
+
|
| 496 |
+
Year of 2nd wave
|
| 497 |
+
|
| 498 |
+
Total respondents
|
| 499 |
+
|
| 500 |
+
Voted in both waves
|
| 501 |
+
|
| 502 |
+
Total votes in
|
| 503 |
+
Wave 1
|
| 504 |
+
|
| 505 |
+
Total votes
|
| 506 |
+
in Wave 2
|
| 507 |
+
|
| 508 |
+
1972
|
| 509 |
+
|
| 510 |
+
1974
|
| 511 |
+
|
| 512 |
+
1990
|
| 513 |
+
|
| 514 |
+
1992
|
| 515 |
+
|
| 516 |
+
1994
|
| 517 |
+
|
| 518 |
+
2000
|
| 519 |
+
|
| 520 |
+
2016
|
| 521 |
+
|
| 522 |
+
Grand total
|
| 523 |
+
|
| 524 |
+
1974
|
| 525 |
+
|
| 526 |
+
1976
|
| 527 |
+
|
| 528 |
+
1992
|
| 529 |
+
|
| 530 |
+
1994
|
| 531 |
+
|
| 532 |
+
1996
|
| 533 |
+
|
| 534 |
+
2002
|
| 535 |
+
|
| 536 |
+
2020
|
| 537 |
+
|
| 538 |
+
2705
|
| 539 |
+
|
| 540 |
+
475
|
| 541 |
+
|
| 542 |
+
1980
|
| 543 |
+
|
| 544 |
+
1126
|
| 545 |
+
|
| 546 |
+
1036
|
| 547 |
+
|
| 548 |
+
1807
|
| 549 |
+
|
| 550 |
+
4270
|
| 551 |
+
|
| 552 |
+
13,399
|
| 553 |
+
|
| 554 |
+
658
|
| 555 |
|
| 556 |
83
|
| 557 |
|
| 558 |
+
582
|
| 559 |
+
|
| 560 |
+
444
|
| 561 |
+
|
| 562 |
+
367
|
| 563 |
+
|
| 564 |
+
604
|
| 565 |
+
|
| 566 |
+
2032
|
| 567 |
+
|
| 568 |
+
4770
|
| 569 |
+
|
| 570 |
+
1644
|
| 571 |
+
|
| 572 |
+
189
|
| 573 |
+
|
| 574 |
+
902
|
| 575 |
+
|
| 576 |
+
763
|
| 577 |
+
|
| 578 |
+
560
|
| 579 |
+
|
| 580 |
+
1171
|
| 581 |
+
|
| 582 |
+
2858
|
| 583 |
+
|
| 584 |
+
8087
|
| 585 |
+
|
| 586 |
+
701
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 587 |
|
| 588 |
131
|
| 589 |
|
| 590 |
+
916
|
| 591 |
+
|
| 592 |
+
463
|
| 593 |
+
|
| 594 |
+
500
|
| 595 |
+
|
| 596 |
+
673
|
| 597 |
+
|
| 598 |
+
2298
|
| 599 |
+
|
| 600 |
+
5682
|
| 601 |
+
|
| 602 |
+
Generally speaking, do you usually think of yourself as a Democrat, a Republican,
|
| 603 |
+
an Independent, or what?
|
| 604 |
+
|
| 605 |
+
VCF0301 is party identification on a Seven-Point Scale and is constructed by combining the
|
| 606 |
+
VCF0302 question with one of two follow-up questions. Respondents who identify as either
|
| 607 |
+
Republicans or Democrats in their initial response are asked a follow-up question:
|
| 608 |
+
|
| 609 |
+
REILLY anD HUnTInG
|
| 610 |
+
|
| 611 |
+
7
|
| 612 |
+
|
| 613 |
+
Would you call yourself a strong [Democrat/Republican] or a not very strong
|
| 614 |
+
[Democrat/Republican]?
|
| 615 |
+
|
| 616 |
+
These responses form the two ends of the Seven-Point Scale, with Strong Democrats coded as 1,
|
| 617 |
+
Weak Democrats coded as 2, Weak Republicans coded as 6, and Strong Republicans as 7. A small
|
| 618 |
+
number (92) of those who expressed partisan affiliation in VCF0302 were coded as DK, NA,
|
| 619 |
+
Other at this point in the survey.
|
| 620 |
+
|
| 621 |
+
Those who did not identify as either Democrats or Republicans are given this follow-up
|
| 622 |
+
|
| 623 |
+
question:
|
| 624 |
+
|
| 625 |
+
Do you think of yourself as closer to the Republican Party or to the Democratic
|
| 626 |
+
Party?
|
| 627 |
+
|
| 628 |
+
These responses are used to construct the middle three categories of the Seven-Point Scale. Those
|
| 629 |
+
answering “Democratic” are assigned to Independent-Democrats (3), with “Republican” coded as
|
| 630 |
+
Independent-Republican (5). Respondents who choose “Neither” are Independent-Independents at
|
| 631 |
+
scale point 4. Note that although the above question is asked in the ANES time series surveys,
|
| 632 |
+
it does not appear in the CDF data. The results of this question are captured in CDF item
|
| 633 |
+
VCF0301. Also note that a small number of respondents answered “do not know” or refused
|
| 634 |
+
to answer VCF0302 but indicated a party preference in the follow-up. These were moved to the
|
| 635 |
+
Independent-Republican and Independent-Democrat categories for VCF0301.
|
| 636 |
+
|
| 637 |
+
Finally, the Seven-Point Scale of VCF0301 is collapsed to three categories for VCF0303.
|
| 638 |
+
This is done by combining the strong and weak Democrats with Independent-Democrats under
|
| 639 |
+
Democrats (including leaners) and ANES political identification data on 43,423 respondents
|
| 640 |
+
from 1972 through 2020 is shown on these three scales in Table 3. Independents make up 36%
|
| 641 |
+
of the total respondents over these surveys, with 13% identified as having no party leaning or
|
| 642 |
+
Independent-Independents.
|
| 643 |
+
|
| 644 |
+
RESULTS
|
| 645 |
+
|
| 646 |
+
Change in political identification over time—voters
|
| 647 |
+
|
| 648 |
+
We now use ANES data from multiple waves to look at how political identification changes for
|
| 649 |
+
voters over time. Between 1972 and 2020, ANES has data on 4770 respondents who voted in
|
| 650 |
+
two consecutive waves of the survey (Table 2). The following section looks at how these voters
|
| 651 |
+
changed their party identification from one survey cycle to the next. A small portion of this
|
| 652 |
+
number did not report party identification on one of the three scales analyzed below.
|
| 653 |
+
|
| 654 |
+
Initial Party ID Response (VCF0302)
|
| 655 |
+
|
| 656 |
+
Of the 4745 respondents shown in Figure 1, 22% changed their initial-response party ID from
|
| 657 |
+
one wave to another. Independents were more fluid on this metric than party-affiliated respond-
|
| 658 |
+
ents: 16% of both Democrats and Republicans were changed at the second survey wave, while
|
| 659 |
+
36% of Independents changed.
|
| 660 |
+
|
| 661 |
+
In each major party, 13% of the wave-one respondents changed their position and identi-
|
| 662 |
+
fied as independents at wave two, while 3% went to the opposite party. Independents saw 17%
|
| 663 |
+
of the wave-one respondents move to Democrat and 19% move to Republican. The absolute
|
| 664 |
+
number of voters switching from party-affiliated to independent (426) and from independent to
|
| 665 |
+
party-affiliated (520) are similar, but the percentage of independents becoming party-affiliated
|
| 666 |
+
|
| 667 |
+
8
|
| 668 |
+
|
| 669 |
+
THE FLUID VOTER
|
| 670 |
+
|
| 671 |
+
T A B L E 3 Three political ID scales: 1972–2020 ANES data
|
| 672 |
+
|
| 673 |
+
Democrat
|
| 674 |
+
|
| 675 |
+
Republican
|
| 676 |
+
|
| 677 |
+
Independent
|
| 678 |
+
|
| 679 |
+
Other
|
| 680 |
+
|
| 681 |
+
DK/NA Total
|
| 682 |
+
|
| 683 |
+
VCF0302 (initial
|
| 684 |
+
response)
|
| 685 |
+
|
| 686 |
+
Percent
|
| 687 |
+
|
| 688 |
+
16,263
|
| 689 |
+
|
| 690 |
+
37%
|
| 691 |
+
|
| 692 |
+
10,976
|
| 693 |
+
|
| 694 |
+
25%
|
| 695 |
+
|
| 696 |
+
VCF0301 (7-Point
|
| 697 |
+
|
| 698 |
+
Scale)
|
| 699 |
+
|
| 700 |
+
Strong
|
| 701 |
+
Dem
|
| 702 |
+
|
| 703 |
+
Weak
|
| 704 |
+
|
| 705 |
+
Weak
|
| 706 |
+
|
| 707 |
+
Dem
|
| 708 |
+
|
| 709 |
+
Rep
|
| 710 |
+
|
| 711 |
+
Strong
|
| 712 |
+
Rep
|
| 713 |
+
|
| 714 |
+
12,772
|
| 715 |
+
|
| 716 |
+
29%
|
| 717 |
+
|
| 718 |
+
3085
|
| 719 |
+
|
| 720 |
+
7%
|
| 721 |
+
|
| 722 |
+
327
|
| 723 |
+
|
| 724 |
+
1%
|
| 725 |
+
|
| 726 |
+
43,423
|
| 727 |
+
|
| 728 |
+
Ind-Dem Ind-Ind Ind-Rep DK/NA Total
|
| 729 |
+
|
| 730 |
+
Percent
|
| 731 |
+
|
| 732 |
+
VCF0303
|
| 733 |
+
|
| 734 |
+
(Summary
|
| 735 |
+
3-Category)
|
| 736 |
+
|
| 737 |
+
Percent
|
| 738 |
+
|
| 739 |
+
8523
|
| 740 |
+
|
| 741 |
+
20%
|
| 742 |
+
|
| 743 |
+
7677
|
| 744 |
+
|
| 745 |
+
18%
|
| 746 |
+
|
| 747 |
+
5354
|
| 748 |
+
|
| 749 |
+
12%
|
| 750 |
+
|
| 751 |
+
5592
|
| 752 |
+
|
| 753 |
+
13%
|
| 754 |
+
|
| 755 |
+
5515
|
| 756 |
+
|
| 757 |
+
13%
|
| 758 |
+
|
| 759 |
+
5677
|
| 760 |
+
|
| 761 |
+
13%
|
| 762 |
+
|
| 763 |
+
4726
|
| 764 |
+
|
| 765 |
+
11%
|
| 766 |
+
|
| 767 |
+
359
|
| 768 |
+
|
| 769 |
+
1%
|
| 770 |
+
|
| 771 |
+
43,423
|
| 772 |
+
|
| 773 |
+
100%
|
| 774 |
+
|
| 775 |
+
Democrat (incl.
|
| 776 |
+
leaners)
|
| 777 |
+
|
| 778 |
+
21,715
|
| 779 |
+
|
| 780 |
+
50%
|
| 781 |
+
|
| 782 |
+
Republican (incl.
|
| 783 |
+
|
| 784 |
+
Independent
|
| 785 |
+
|
| 786 |
+
DK/NA Total
|
| 787 |
+
|
| 788 |
+
leaners)
|
| 789 |
+
|
| 790 |
+
15,672
|
| 791 |
+
|
| 792 |
+
36%
|
| 793 |
+
|
| 794 |
+
5677
|
| 795 |
+
|
| 796 |
+
13%
|
| 797 |
+
|
| 798 |
+
359
|
| 799 |
+
|
| 800 |
+
1%
|
| 801 |
+
|
| 802 |
+
43,423
|
| 803 |
+
|
| 804 |
+
100%
|
| 805 |
+
|
| 806 |
+
F I G U R E 1 Change in initial response (VCF0302) voters, 1972–2020
|
| 807 |
+
|
| 808 |
+
is nearly three times that of party-affiliates becoming independent. Respondents coded as Inde-
|
| 809 |
+
pendent, No Preference, and Other are included in the independent category. This flow is illus-
|
| 810 |
+
trated in Figure 1.
|
| 811 |
+
|
| 812 |
+
Seven-Point Scale (VCF0301)
|
| 813 |
+
|
| 814 |
+
When the Seven-Point Scale of variable VCF0301 is analyzed across two survey waves, more
|
| 815 |
+
fluidity in political identification becomes apparent. Of the 4735 respondents who voted in two
|
| 816 |
+
waves of the survey and recorded scores on this scale in both waves, 43% changed their identifi-
|
| 817 |
+
cation at the second wave. This is nearly double the 22% rate seen in the initial response variable
|
| 818 |
+
above.
|
| 819 |
+
|
| 820 |
+
Partisan respondents at the extremes of the scale were more consistent in their identification,
|
| 821 |
+
with 21% of Strong Democrats and 22% of Strong Republicans changing at the second wave.
|
| 822 |
+
Fifty-seven percent of Weak Democrats and 55% of Weak Republicans changed their identifica-
|
| 823 |
+
tion at wave two. Overall, 36% of Democrats and 36% of Republicans changed their party iden-
|
| 824 |
+
tification by at least one point on this scale between wave one and wave two; this is substantially
|
| 825 |
+
higher than the 36% of party-identified respondents who changed their position.
|
| 826 |
+
|
| 827 |
+
REILLY anD HUnTInG
|
| 828 |
+
|
| 829 |
+
9
|
| 830 |
+
|
| 831 |
+
F I G U R E 2 Change in 7-point scale (VCF0301) voters, 1972–2020
|
| 832 |
+
|
| 833 |
+
The complex flow of the three independent classifications is shown in Figure 2. As noted
|
| 834 |
+
above, 36% of those reporting to be independent at the first wave interview were identifying with
|
| 835 |
+
one of the two parties at the second wave. In addition, another 22% of independents remained
|
| 836 |
+
independent at wave two, but shifted their position within the three independent categories on
|
| 837 |
+
this scale. Overall, 57% of those in one of the three independent categories of the Seven-Point
|
| 838 |
+
Scale changed their identification at wave two. This flow is illustrated in Figure 2.
|
| 839 |
+
|
| 840 |
+
Summary 3-Category Scale (VCF0303)
|
| 841 |
+
|
| 842 |
+
The collapsed categories of the Summary 3-Category Scale presented in VCF0303 necessarily
|
| 843 |
+
suppress much of the change in party identification seen in the previous two scales. By this
|
| 844 |
+
measure, 10% of Democrats (including leaners) and 12% of Republicans (including leaners)
|
| 845 |
+
changed their identification between the two survey waves. The independents represent just 7%
|
| 846 |
+
of respondents on this scale, as those who identify as independent but leaning toward a party are
|
| 847 |
+
grouped with their respective parties. The 328 remaining “true” independents fractured nearly
|
| 848 |
+
in thirds when queried at the second wave: 36% remained Independent while 30% switched to
|
| 849 |
+
Democrat and 34% to Republican. A total of 64% of the Independents from wave one were clas-
|
| 850 |
+
sified as partisans at wave two. Among those classified as either Democrats or Republicans at
|
| 851 |
+
wave one, just 11% changed their identification on this scale at wave two (Figure 3).
|
| 852 |
+
|
| 853 |
+
10
|
| 854 |
+
|
| 855 |
+
THE FLUID VOTER
|
| 856 |
+
|
| 857 |
+
F I G U R E 3 Change in Summary 3-Category Scale (VCF0303) voters, 1972–2020
|
| 858 |
+
|
| 859 |
+
F I G U R E 4 Change in initial response (VCF0302) non-voters, 1972–2020
|
| 860 |
+
|
| 861 |
+
Change in political identification over time—Non-voters
|
| 862 |
+
|
| 863 |
+
ANES data 1972–2020 also contain information on political identification for respondents
|
| 864 |
+
who did not vote. In this section we examine changes in political identification in the 15,292
|
| 865 |
+
respondents who answered two consecutive waves of the survey but voted in neither election.
|
| 866 |
+
For the purposes of this article, we use the term non-voters to identify those respondents who
|
| 867 |
+
did not vote in either wave of this analysis. It is unknown what portion of this population votes
|
| 868 |
+
on occasion.
|
| 869 |
+
|
| 870 |
+
Initial party response (VCF0302)
|
| 871 |
+
|
| 872 |
+
Of the 15,592 respondents shown in Figure 4, 60% changed their initial response party identifi-
|
| 873 |
+
cation from one wave to the next. This is nearly three times the 22% rate seen among those who
|
| 874 |
+
voted in both waves. Fifty-seven percent of the non-voting Democrat-identified respondents and
|
| 875 |
+
|
| 876 |
+
REILLY anD HUnTInG
|
| 877 |
+
|
| 878 |
+
11
|
| 879 |
+
|
| 880 |
+
69% of Republicans changed their identification. Taken together, 62% of the party-identified
|
| 881 |
+
non-voters changed their identification at wave two. This compares with 59% of the independ-
|
| 882 |
+
ents who changed.1
|
| 883 |
+
|
| 884 |
+
Of the 5201 who identified with Democrats at wave one, just 43% identified as such at wave
|
| 885 |
+
two, with 34% now seeing themselves as independents, and 23% crossing over to be Republicans.
|
| 886 |
+
This contrasts with just three percent of voting Democrats crossing over to the other party at
|
| 887 |
+
wave two. Non-voting Republicans showed even more fluidity between the two survey waves.
|
| 888 |
+
Just 31% of those who said they were Republican at wave one maintained that identification
|
| 889 |
+
at wave two, with a third of the respondents switching to Democratic identification and 36%
|
| 890 |
+
now calling themselves Independent. Non-voting independents switched to Democrat in 36% of
|
| 891 |
+
the cases, and to Republican 23%, with 41% remaining independent. This flow is illustrated in
|
| 892 |
+
Figure 4.
|
| 893 |
+
|
| 894 |
+
Seven-Point Scale (VCF0301)
|
| 895 |
+
|
| 896 |
+
Non-voting respondents to ANES changed their political identification on the Seven-Point Scale
|
| 897 |
+
between wave one and wave two in 81% of the cases. This fluidity was relatively consistent across
|
| 898 |
+
the scale, ranging from 76% of Strong Democrats changing identification by at least one scale
|
| 899 |
+
point to 87% of Independent-Republicans.
|
| 900 |
+
|
| 901 |
+
Changes in party identification for the three independent categories are shown in Figure 5.
|
| 902 |
+
A total of 5923 (83%) of those who identified as one of the three independent categories at wave
|
| 903 |
+
one had moved by at least one scale point at wave two. Of this amount, 1722 (29%) remained
|
| 904 |
+
within the independent domain while 4201 (81%) moved to one of the parties. Changes in inde-
|
| 905 |
+
pendent non-voter identification are shown in Figure 5.
|
| 906 |
+
|
| 907 |
+
Summary 3-Category Scale (VCF0303)
|
| 908 |
+
|
| 909 |
+
When non-voting ANES respondents are examined on the summary 3-category scale of
|
| 910 |
+
VCF0303, 58% are seen to change categories. Democrats (including leaners) moved to another
|
| 911 |
+
point on the scale 46% of the time, with 32% identifying as Republicans at wave 2 and 13%
|
| 912 |
+
as independents. Well over half (60%) of the non-voters identified as Republicans at wave one
|
| 913 |
+
changed identification at wave two, with 47% later identifying as Democrat and 13% as inde-
|
| 914 |
+
pendent. Independent non-voters changed identification 81% of the time, with 48% moving to
|
| 915 |
+
Democrat at wave two and 33% to Republican. These flows are illustrated in Figure 6.
|
| 916 |
+
|
| 917 |
+
Voting patterns: Straight and split-ticket voters
|
| 918 |
+
|
| 919 |
+
ANES asks respondents to state how they voted in four contests: president, Congress, Senate7,
|
| 920 |
+
and governor. Respondents may not have the opportunity to vote in each of these races, depend-
|
| 921 |
+
ing on the timing of the election cycle. There are 27,832 respondents in the ANES data that said
|
| 922 |
+
they voted in at least one election, and these respondents give us information on a total of 77,729
|
| 923 |
+
races.
|
| 924 |
+
|
| 925 |
+
Of the ANES respondents who reported voting from 1972 to 2010, Figure 7 shows that 20,521
|
| 926 |
+
(73.7%) always voted a straight ticket for either Democrats (11,638 respondents) or Republicans
|
| 927 |
+
(8883). Conversely, 9316 respondents never voted for a Democrat and 12,201 never voted Repub-
|
| 928 |
+
|
| 929 |
+
1 Z-test for proportions <.01.
|
| 930 |
+
|
| 931 |
+
12
|
| 932 |
+
|
| 933 |
+
THE FLUID VOTER
|
| 934 |
+
|
| 935 |
+
F I G U R E 5 Change in 7-Point Scale (VCF0301) non-voters, 1972–2020
|
| 936 |
+
|
| 937 |
+
lican (Figure 7) in the races surveyed. Note that the 0% and 100% columns do not exactly mirror
|
| 938 |
+
each other due to the number of votes for minor parties.
|
| 939 |
+
|
| 940 |
+
The great majority of voters surveyed by ANES exclusively vote for one of the major parties,
|
| 941 |
+
with only a small percentage splitting their votes between Republicans and Democrats. The
|
| 942 |
+
40%–59% bracket in Figure 7 shows that 4655 people (16.7%) divided their votes evenly between
|
| 943 |
+
the two parties. Considering both the small number of election contests available for analysis
|
| 944 |
+
and the polarized nature of voting noted above, further analysis divides voters into three groups:
|
| 945 |
+
those who voted for Democrats in 100% of the contests, those who voted for Republicans in
|
| 946 |
+
100% of the contests, and those who voted for some mix of Democrats and Republicans. With
|
| 947 |
+
this information, we can see what portion of the sample consistently vote for one party and what
|
| 948 |
+
portion switch their votes between parties (Figure 7).
|
| 949 |
+
|
| 950 |
+
Initial Party ID Response (VCF0302)
|
| 951 |
+
|
| 952 |
+
As expected, Democrats generally vote a straight ticket for Democrats, at a rate of 74% while 71%
|
| 953 |
+
of Republicans, 5678 of the total 7990 Republican voters, always vote Republican (Figure 8).
|
| 954 |
+
Incongruously, 5% of Democrats and 5% of Republicans report that they always vote for the
|
| 955 |
+
opposite party.
|
| 956 |
+
|
| 957 |
+
Independents are much more evenly divided in their vote choices. A significant portion still
|
| 958 |
+
vote straight tickets for one party or the other, with 34.8% always voting for Democrats and
|
| 959 |
+
30% always voting Republican. A plurality of independents (35.2%) split their votes between
|
| 960 |
+
Democrats and Republicans at least occasionally. This compares with the combined figures for
|
| 961 |
+
|
| 962 |
+
REILLY anD HUnTInG
|
| 963 |
+
|
| 964 |
+
13
|
| 965 |
+
|
| 966 |
+
F I G U R E 6 Change in Summary 3-Category Scale (VCF0303) non-voters, 1972–2020
|
| 967 |
+
|
| 968 |
+
12,000
|
| 969 |
+
|
| 970 |
+
12,101
|
| 971 |
+
|
| 972 |
+
10,000
|
| 973 |
+
|
| 974 |
+
9,316
|
| 975 |
+
|
| 976 |
+
11,638
|
| 977 |
+
|
| 978 |
+
8,883
|
| 979 |
+
|
| 980 |
+
s
|
| 981 |
+
t
|
| 982 |
+
n
|
| 983 |
+
e
|
| 984 |
+
d
|
| 985 |
+
n
|
| 986 |
+
o
|
| 987 |
+
p
|
| 988 |
+
s
|
| 989 |
+
e
|
| 990 |
+
R
|
| 991 |
+
S
|
| 992 |
+
E
|
| 993 |
+
N
|
| 994 |
+
A
|
| 995 |
+
|
| 996 |
+
8,000
|
| 997 |
+
|
| 998 |
+
6,000
|
| 999 |
+
|
| 1000 |
+
4,000
|
| 1001 |
+
|
| 1002 |
+
2,000
|
| 1003 |
+
|
| 1004 |
+
-
|
| 1005 |
+
|
| 1006 |
+
1,882
|
| 1007 |
+
|
| 1008 |
+
2,086
|
| 1009 |
+
|
| 1010 |
+
2,327
|
| 1011 |
+
|
| 1012 |
+
2,328
|
| 1013 |
+
|
| 1014 |
+
2,061
|
| 1015 |
+
|
| 1016 |
+
1,869
|
| 1017 |
+
|
| 1018 |
+
165
|
| 1019 |
+
|
| 1020 |
+
191
|
| 1021 |
+
|
| 1022 |
+
443
|
| 1023 |
+
|
| 1024 |
+
374
|
| 1025 |
+
|
| 1026 |
+
0%
|
| 1027 |
+
|
| 1028 |
+
1%-19% 20%-39% 40%-59% 60%-79% 80%-99%
|
| 1029 |
+
|
| 1030 |
+
100%
|
| 1031 |
+
|
| 1032 |
+
Dem Votes
|
| 1033 |
+
|
| 1034 |
+
Rep Votes
|
| 1035 |
+
|
| 1036 |
+
F I G U R E 7 Percent of each respondent's votes by party, 1972–2020
|
| 1037 |
+
|
| 1038 |
+
Democrats and Republicans showing that 22% of the party-identified voters voted a mixed ticket
|
| 1039 |
+
at least once.2 Respondents coded as Independent, No Preference, and Other are included in the
|
| 1040 |
+
Independent category (Figure 8).
|
| 1041 |
+
|
| 1042 |
+
Seven-Point Scale (VCF0301)
|
| 1043 |
+
|
| 1044 |
+
With the Independent-Democrats and Independent-Republicans broken out on the
|
| 1045 |
+
7-Point Scale of VCF0301, we see a steady progression from left-to-right, with decreas-
|
| 1046 |
+
ing Democratic straight-ticket voting and increasing Republican support (Figure 9). The
|
| 1047 |
+
Independent-Independents at the middle of the scale have truly mixed voting choices: 31% only
|
| 1048 |
+
voting for Democrats, 27% on voting for Republicans, and 43% choosing a mixture of Democrat
|
| 1049 |
+
and Republican candidates. The votes reported by Independent-Independents represent 8% of
|
| 1050 |
+
the 27,704 reported to ANES by respondents (Figure 9).
|
| 1051 |
+
|
| 1052 |
+
2 Z-test for proportions <.01.
|
| 1053 |
+
|
| 1054 |
+
14
|
| 1055 |
+
|
| 1056 |
+
THE FLUID VOTER
|
| 1057 |
+
|
| 1058 |
+
8,160
|
| 1059 |
+
|
| 1060 |
+
s
|
| 1061 |
+
t
|
| 1062 |
+
n
|
| 1063 |
+
e
|
| 1064 |
+
d
|
| 1065 |
+
n
|
| 1066 |
+
o
|
| 1067 |
+
p
|
| 1068 |
+
s
|
| 1069 |
+
e
|
| 1070 |
+
R
|
| 1071 |
+
S
|
| 1072 |
+
E
|
| 1073 |
+
N
|
| 1074 |
+
A
|
| 1075 |
+
|
| 1076 |
+
9,000
|
| 1077 |
+
|
| 1078 |
+
8,000
|
| 1079 |
+
|
| 1080 |
+
7,000
|
| 1081 |
+
|
| 1082 |
+
6,000
|
| 1083 |
+
|
| 1084 |
+
5,000
|
| 1085 |
+
|
| 1086 |
+
4,000
|
| 1087 |
+
|
| 1088 |
+
3,000
|
| 1089 |
+
|
| 1090 |
+
2,000
|
| 1091 |
+
|
| 1092 |
+
1,000
|
| 1093 |
+
|
| 1094 |
+
-
|
| 1095 |
+
|
| 1096 |
+
5,678
|
| 1097 |
+
|
| 1098 |
+
3,026
|
| 1099 |
+
|
| 1100 |
+
3,056
|
| 1101 |
+
|
| 1102 |
+
2,610
|
| 1103 |
+
|
| 1104 |
+
2,324
|
| 1105 |
+
|
| 1106 |
+
1,906
|
| 1107 |
+
|
| 1108 |
+
560
|
| 1109 |
+
|
| 1110 |
+
406
|
| 1111 |
+
|
| 1112 |
+
Democrat
|
| 1113 |
+
|
| 1114 |
+
Republican
|
| 1115 |
+
|
| 1116 |
+
Independent
|
| 1117 |
+
|
| 1118 |
+
Always Votes DEM
|
| 1119 |
+
|
| 1120 |
+
Mixed Votes
|
| 1121 |
+
|
| 1122 |
+
Always Votes REP
|
| 1123 |
+
|
| 1124 |
+
F I G U R E 8
|
| 1125 |
+
|
| 1126 |
+
Straight-ticket and mixed voting by Initial Party ID Response, 1972–2020
|
| 1127 |
+
|
| 1128 |
+
s
|
| 1129 |
+
t
|
| 1130 |
+
n
|
| 1131 |
+
e
|
| 1132 |
+
d
|
| 1133 |
+
n
|
| 1134 |
+
o
|
| 1135 |
+
p
|
| 1136 |
+
s
|
| 1137 |
+
e
|
| 1138 |
+
R
|
| 1139 |
+
S
|
| 1140 |
+
E
|
| 1141 |
+
N
|
| 1142 |
+
A
|
| 1143 |
+
|
| 1144 |
+
6,000
|
| 1145 |
+
|
| 1146 |
+
5,000
|
| 1147 |
+
|
| 1148 |
+
4,000
|
| 1149 |
+
|
| 1150 |
+
3,000
|
| 1151 |
+
|
| 1152 |
+
2,000
|
| 1153 |
+
|
| 1154 |
+
1,000
|
| 1155 |
+
|
| 1156 |
+
-
|
| 1157 |
+
|
| 1158 |
+
Strong Dem Weak Dem Ind-Dem
|
| 1159 |
+
|
| 1160 |
+
Ind-Ind
|
| 1161 |
+
|
| 1162 |
+
Ind-Rep Weak Rep Strong Rep
|
| 1163 |
+
|
| 1164 |
+
Always vote DEM
|
| 1165 |
+
|
| 1166 |
+
Mixed Votes
|
| 1167 |
+
|
| 1168 |
+
Always vote REP
|
| 1169 |
+
|
| 1170 |
+
F I G U R E 9
|
| 1171 |
+
|
| 1172 |
+
Straight-ticket and mixed voting by 7-point scale, 1972–2010
|
| 1173 |
+
|
| 1174 |
+
Interestingly, Independent-Democrats show a higher percentage of straight-ticket support of
|
| 1175 |
+
Democratic candidates (63%) than the Weak Democrats who explicitly declare support for the
|
| 1176 |
+
party (60%).3
|
| 1177 |
+
|
| 1178 |
+
Summary 3-Category Scale (VCF0303)
|
| 1179 |
+
|
| 1180 |
+
With the Independent-Democrats and Independent-Republicans of VCF0301 included as “lean-
|
| 1181 |
+
ers” in their respective partisan buckets for VCF0303, the Independent-Independents are high-
|
| 1182 |
+
lighted (Figure 10). Combining the straight-ticket Democrat and Republican votes shows that
|
| 1183 |
+
|
| 1184 |
+
3 Z-test for proportions p < .05.
|
| 1185 |
+
|
| 1186 |
+
REILLY anD HUnTInG
|
| 1187 |
+
|
| 1188 |
+
15
|
| 1189 |
+
|
| 1190 |
+
s
|
| 1191 |
+
t
|
| 1192 |
+
n
|
| 1193 |
+
e
|
| 1194 |
+
d
|
| 1195 |
+
n
|
| 1196 |
+
o
|
| 1197 |
+
p
|
| 1198 |
+
s
|
| 1199 |
+
e
|
| 1200 |
+
R
|
| 1201 |
+
S
|
| 1202 |
+
E
|
| 1203 |
+
N
|
| 1204 |
+
A
|
| 1205 |
+
|
| 1206 |
+
12,000
|
| 1207 |
+
|
| 1208 |
+
10,000
|
| 1209 |
+
|
| 1210 |
+
8,000
|
| 1211 |
+
|
| 1212 |
+
6,000
|
| 1213 |
+
|
| 1214 |
+
4,000
|
| 1215 |
+
|
| 1216 |
+
2,000
|
| 1217 |
+
|
| 1218 |
+
-
|
| 1219 |
+
|
| 1220 |
+
10,207
|
| 1221 |
+
|
| 1222 |
+
7,412
|
| 1223 |
+
|
| 1224 |
+
3,284
|
| 1225 |
+
|
| 1226 |
+
3,019
|
| 1227 |
+
|
| 1228 |
+
817
|
| 1229 |
+
|
| 1230 |
+
665
|
| 1231 |
+
|
| 1232 |
+
705
|
| 1233 |
+
|
| 1234 |
+
984
|
| 1235 |
+
|
| 1236 |
+
611
|
| 1237 |
+
|
| 1238 |
+
Democrat (incl. leaners)
|
| 1239 |
+
|
| 1240 |
+
Republican (incl. leaners)
|
| 1241 |
+
|
| 1242 |
+
Independent
|
| 1243 |
+
|
| 1244 |
+
Always Votes DEM
|
| 1245 |
+
|
| 1246 |
+
Mixed Votes
|
| 1247 |
+
|
| 1248 |
+
Always Votes REP
|
| 1249 |
+
|
| 1250 |
+
F I G U R E 1 0
|
| 1251 |
+
|
| 1252 |
+
Straight-ticket and mixed voting by Summary 3-Category scale, 1972–2010
|
| 1253 |
+
|
| 1254 |
+
77% of the Democrat (including leaners) category always votes a straight ticket, 73% of Repub-
|
| 1255 |
+
licans (including leaners), and 57% of independents (Figure 10).
|
| 1256 |
+
|
| 1257 |
+
Voting change over time
|
| 1258 |
+
|
| 1259 |
+
Changes in voting behavior for ANES two-wave voters are summarized in Table 4. The 1464
|
| 1260 |
+
respondents reported voting a straight Democrat ticket both the first and second time they were
|
| 1261 |
+
interviewed, with 1239 voting straight Republican both times, and 434 casting mixed votes at
|
| 1262 |
+
each wave. This total of 3137 represents 66% of the total 4770 who voted in two waves of the
|
| 1263 |
+
survey. This leaves 34% who altered their behavior across the election cycles.
|
| 1264 |
+
|
| 1265 |
+
The 4754 respondents who voted in two waves of the ANES survey and stated their political
|
| 1266 |
+
identification are summarized in Table 5.4 Respondents who identified as Republicans or Demo-
|
| 1267 |
+
crats as their Initial Party ID Response for VCF0302 are grouped together as Party Affiliated in
|
| 1268 |
+
this table, for comparison to independent voters. Respondents coded as Independent, No Prefer-
|
| 1269 |
+
ence, and Other are included in the independent category.
|
| 1270 |
+
|
| 1271 |
+
Party-affiliated voters exhibited the same voting behavior, either straight-ticket or mixed
|
| 1272 |
+
voting in each wave, in 70% of the cases. For Independents, this percentage drops to 57%.
|
| 1273 |
+
Conversely, 30% of party affiliates changed their voting patterns across two elections, while 43%
|
| 1274 |
+
of Independents changed.
|
| 1275 |
+
|
| 1276 |
+
Party-affiliated voters voted a straight ticket for the same party at a rate of 62%. Independ-
|
| 1277 |
+
ents, while still voting consistently for a single party at a significant rate (44%), were still more
|
| 1278 |
+
likely to change their voting behavior at the second wave of the survey. A small number of voters
|
| 1279 |
+
voted a straight ticket for one party at Wave 1 and then switched to the other party at Wave 2.
|
| 1280 |
+
Here we see that independents were twice as likely to make this large shift than party affiliates.
|
| 1281 |
+
There is a small difference between the two groups on percentages that went from straight ticket
|
| 1282 |
+
at Wave 1 to mixed at Wave 2. Independents were more likely to go from mixed to straight voting
|
| 1283 |
+
and much more likely to vote for a mix of the two parties in both waves.
|
| 1284 |
+
|
| 1285 |
+
4 Sixteen of the 4770 ANES respondents who reported voting in two waves of the survey are coded as DK or NA, refused in VCF0302,
|
| 1286 |
+
leaving 4754 who could have their political identification classified.
|
| 1287 |
+
|
| 1288 |
+
16
|
| 1289 |
+
|
| 1290 |
+
THE FLUID VOTER
|
| 1291 |
+
|
| 1292 |
+
T A B L E 4 Changes in voting behavior, all respondents
|
| 1293 |
+
|
| 1294 |
+
Wave 2
|
| 1295 |
+
|
| 1296 |
+
Wave 1
|
| 1297 |
+
|
| 1298 |
+
Straight REP
|
| 1299 |
+
|
| 1300 |
+
Mixed vote
|
| 1301 |
+
|
| 1302 |
+
Straight DEM
|
| 1303 |
+
|
| 1304 |
+
Total
|
| 1305 |
+
|
| 1306 |
+
Straight REP
|
| 1307 |
+
|
| 1308 |
+
Mixed Vote
|
| 1309 |
+
|
| 1310 |
+
Straight DEM
|
| 1311 |
+
|
| 1312 |
+
1239
|
| 1313 |
+
|
| 1314 |
+
399
|
| 1315 |
+
|
| 1316 |
+
55
|
| 1317 |
+
|
| 1318 |
+
1693
|
| 1319 |
+
|
| 1320 |
+
285
|
| 1321 |
+
|
| 1322 |
+
434
|
| 1323 |
+
|
| 1324 |
+
264
|
| 1325 |
+
|
| 1326 |
+
983
|
| 1327 |
+
|
| 1328 |
+
123
|
| 1329 |
+
|
| 1330 |
+
507
|
| 1331 |
+
|
| 1332 |
+
1464
|
| 1333 |
+
|
| 1334 |
+
2094
|
| 1335 |
+
|
| 1336 |
+
T A B L E 5 Voting changes over two waves of ANES data
|
| 1337 |
+
|
| 1338 |
+
Party affiliated
|
| 1339 |
+
|
| 1340 |
+
Independent
|
| 1341 |
+
|
| 1342 |
+
Initial Party ID Response (VCF0302)
|
| 1343 |
+
|
| 1344 |
+
Straight ticket Wave 1 & Wave 2: same party both waves*
|
| 1345 |
+
|
| 1346 |
+
Mixed ticket, both Wave 1 & Wave 2*
|
| 1347 |
+
|
| 1348 |
+
Subtotal: Same voting behavior in Wave 1 & 2*
|
| 1349 |
+
|
| 1350 |
+
Straight ticket Wave 1 & Wave 2: switched parties*
|
| 1351 |
+
|
| 1352 |
+
Straight ticket in Wave 1, mixed ticket in Wave 2**
|
| 1353 |
+
|
| 1354 |
+
Mixed ticket in Wave 1, straight ticket in Wave 2*
|
| 1355 |
+
|
| 1356 |
+
Subtotal: Different voting behavior in Wave 1 & 2*
|
| 1357 |
+
|
| 1358 |
+
n
|
| 1359 |
+
|
| 1360 |
+
2056
|
| 1361 |
+
|
| 1362 |
+
237
|
| 1363 |
+
|
| 1364 |
+
2293
|
| 1365 |
+
|
| 1366 |
+
96
|
| 1367 |
+
|
| 1368 |
+
355
|
| 1369 |
+
|
| 1370 |
+
547
|
| 1371 |
+
|
| 1372 |
+
998
|
| 1373 |
+
|
| 1374 |
+
%
|
| 1375 |
+
|
| 1376 |
+
62%
|
| 1377 |
+
|
| 1378 |
+
7%
|
| 1379 |
+
|
| 1380 |
+
70%
|
| 1381 |
+
|
| 1382 |
+
3%
|
| 1383 |
+
|
| 1384 |
+
11%
|
| 1385 |
+
|
| 1386 |
+
17%
|
| 1387 |
+
|
| 1388 |
+
30%
|
| 1389 |
+
|
| 1390 |
+
n
|
| 1391 |
+
|
| 1392 |
+
640
|
| 1393 |
+
|
| 1394 |
+
196
|
| 1395 |
+
|
| 1396 |
+
836
|
| 1397 |
+
|
| 1398 |
+
81
|
| 1399 |
+
|
| 1400 |
+
191
|
| 1401 |
+
|
| 1402 |
+
355
|
| 1403 |
+
|
| 1404 |
+
627
|
| 1405 |
+
|
| 1406 |
+
Total
|
| 1407 |
+
|
| 1408 |
+
1647
|
| 1409 |
+
|
| 1410 |
+
1340
|
| 1411 |
+
|
| 1412 |
+
1783
|
| 1413 |
+
|
| 1414 |
+
4770
|
| 1415 |
+
|
| 1416 |
+
%
|
| 1417 |
+
|
| 1418 |
+
44%
|
| 1419 |
+
|
| 1420 |
+
13%
|
| 1421 |
+
|
| 1422 |
+
57%
|
| 1423 |
+
|
| 1424 |
+
6%
|
| 1425 |
+
|
| 1426 |
+
13%
|
| 1427 |
+
|
| 1428 |
+
24%
|
| 1429 |
+
|
| 1430 |
+
43%
|
| 1431 |
+
|
| 1432 |
+
Total
|
| 1433 |
+
|
| 1434 |
+
*Z-test for proportions p < .01.
|
| 1435 |
+
**Z-test for proportions p < .05.
|
| 1436 |
+
|
| 1437 |
+
Initial Party ID Response (VCF0302)
|
| 1438 |
+
|
| 1439 |
+
3291
|
| 1440 |
+
|
| 1441 |
+
100%
|
| 1442 |
+
|
| 1443 |
+
1463
|
| 1444 |
+
|
| 1445 |
+
100%
|
| 1446 |
+
|
| 1447 |
+
When the party-affiliated category shown in Table 5 is broken out to show the two parties, we see
|
| 1448 |
+
the results are largely the same. Democrats continued their pattern from Wave 1, either voting
|
| 1449 |
+
a straight ticket for a particular party or voting a mixed ticket, in 71% of the cases. This left
|
| 1450 |
+
29% of self-identified Democrats changing their voting behavior in some fashion, with 32% of
|
| 1451 |
+
Republicans exhibiting changed behavior. The p-value for a comparison of these percentages is
|
| 1452 |
+
.176, suggesting that there is little meaningful difference between Democrats and Republicans on
|
| 1453 |
+
this measure.
|
| 1454 |
+
|
| 1455 |
+
As noted above, 43% of independents showed changed behavior between Wave 1 and Wave 2,
|
| 1456 |
+
|
| 1457 |
+
with a p-value of <.01 compared to party-affiliated respondents (Table 6).
|
| 1458 |
+
|
| 1459 |
+
Seven-Point Scale (VCF0301)
|
| 1460 |
+
|
| 1461 |
+
When this same measure of voting change over time is applied to the Seven-Point Scale of
|
| 1462 |
+
VCF0301, we see that, unsurprisingly, the Strong Democrats and Strong Republicans are most
|
| 1463 |
+
consistent in their behavior, with less than a quarter of these groups changing their voting profile
|
| 1464 |
+
from one wave to the next (Table 7). Independent-Independents were the most likely to change their
|
| 1465 |
+
voting profile at 48%, followed by Independent-Republicans at 45%. Independent-Democrats
|
| 1466 |
+
again seem to be as committed to Democratic candidates as the Weak Democrats with the party
|
| 1467 |
+
in the question posed in VCF0301. Weak Democrats voted for a straight Democratic ticked at a
|
| 1468 |
+
|
| 1469 |
+
REILLY anD HUnTInG
|
| 1470 |
+
|
| 1471 |
+
T A B L E 6 Changes in voting behavior by Initial Party ID Response
|
| 1472 |
+
|
| 1473 |
+
VCF0302
|
| 1474 |
+
|
| 1475 |
+
Democrat
|
| 1476 |
+
|
| 1477 |
+
Republican
|
| 1478 |
+
|
| 1479 |
+
Subtotal: Party-identified
|
| 1480 |
+
|
| 1481 |
+
Independent, Other, No Pref.
|
| 1482 |
+
|
| 1483 |
+
Total
|
| 1484 |
+
|
| 1485 |
+
Voted in two waves
|
| 1486 |
+
|
| 1487 |
+
Percent that changed voting behavior
|
| 1488 |
+
|
| 1489 |
+
1803
|
| 1490 |
+
|
| 1491 |
+
1488
|
| 1492 |
+
|
| 1493 |
+
3291
|
| 1494 |
+
|
| 1495 |
+
1463
|
| 1496 |
+
|
| 1497 |
+
4754
|
| 1498 |
+
|
| 1499 |
+
29%
|
| 1500 |
+
|
| 1501 |
+
32%
|
| 1502 |
+
|
| 1503 |
+
30%
|
| 1504 |
+
|
| 1505 |
+
43%
|
| 1506 |
+
|
| 1507 |
+
34%
|
| 1508 |
+
|
| 1509 |
+
17
|
| 1510 |
+
|
| 1511 |
+
Percent that
|
| 1512 |
+
did not change
|
| 1513 |
+
|
| 1514 |
+
71%
|
| 1515 |
+
|
| 1516 |
+
68%
|
| 1517 |
+
|
| 1518 |
+
70%
|
| 1519 |
+
|
| 1520 |
+
57%
|
| 1521 |
+
|
| 1522 |
+
66%
|
| 1523 |
+
|
| 1524 |
+
T A B L E 7 Changes in voting behavior by 7-Point Scale
|
| 1525 |
+
|
| 1526 |
+
VCF0301
|
| 1527 |
+
|
| 1528 |
+
Voted in two waves
|
| 1529 |
+
|
| 1530 |
+
Percent that changed voting behavior
|
| 1531 |
+
|
| 1532 |
+
Percent that did not change
|
| 1533 |
+
|
| 1534 |
+
Strong Democrat
|
| 1535 |
+
|
| 1536 |
+
1045
|
| 1537 |
+
|
| 1538 |
+
Weak Democrat
|
| 1539 |
+
|
| 1540 |
+
Independent-Democrat
|
| 1541 |
+
|
| 1542 |
+
Independent-Independent
|
| 1543 |
+
|
| 1544 |
+
Independent-Republican
|
| 1545 |
+
|
| 1546 |
+
Weak Republican
|
| 1547 |
+
|
| 1548 |
+
Strong Republican
|
| 1549 |
+
|
| 1550 |
+
Total
|
| 1551 |
+
|
| 1552 |
+
757
|
| 1553 |
+
|
| 1554 |
+
547
|
| 1555 |
+
|
| 1556 |
+
332
|
| 1557 |
+
|
| 1558 |
+
588
|
| 1559 |
+
|
| 1560 |
+
637
|
| 1561 |
+
|
| 1562 |
+
850
|
| 1563 |
+
|
| 1564 |
+
4756
|
| 1565 |
+
|
| 1566 |
+
22%
|
| 1567 |
+
|
| 1568 |
+
40%
|
| 1569 |
+
|
| 1570 |
+
38%
|
| 1571 |
+
|
| 1572 |
+
48%
|
| 1573 |
+
|
| 1574 |
+
45%
|
| 1575 |
+
|
| 1576 |
+
42%
|
| 1577 |
+
|
| 1578 |
+
24%
|
| 1579 |
+
|
| 1580 |
+
34%
|
| 1581 |
+
|
| 1582 |
+
78%
|
| 1583 |
+
|
| 1584 |
+
60%
|
| 1585 |
+
|
| 1586 |
+
62%
|
| 1587 |
+
|
| 1588 |
+
52%
|
| 1589 |
+
|
| 1590 |
+
55%
|
| 1591 |
+
|
| 1592 |
+
58%
|
| 1593 |
+
|
| 1594 |
+
76%
|
| 1595 |
+
|
| 1596 |
+
66%
|
| 1597 |
+
|
| 1598 |
+
rate of 45%, while Independent-Democrats did so at a rate of 47% with a p-value of .472 between
|
| 1599 |
+
the two rates, indicating little actual difference between the two groups.
|
| 1600 |
+
|
| 1601 |
+
Summary 3-Category Scale (VCF0303)
|
| 1602 |
+
|
| 1603 |
+
The Summary 3-Category Scale once again shrinks the size of the independent category but
|
| 1604 |
+
maximizes its difference from the enlarged party-identified categories. Democrats (including
|
| 1605 |
+
leaners) were slightly less likely to change their behavior (31%) than Republicans (including lean-
|
| 1606 |
+
ers) at 35%.5 True independents, as above, changed their voting profile 48% of the time between
|
| 1607 |
+
the first and second survey waves (Table 8).
|
| 1608 |
+
|
| 1609 |
+
DISCUSSION
|
| 1610 |
+
|
| 1611 |
+
Analyzing each of the three ANES measures of party affiliation (Initial Party ID, Seven-Point
|
| 1612 |
+
Scale, and Summary 3 Category) over multiple elections provides some important findings on
|
| 1613 |
+
the voting patterns of independents. We find evidence that, when tracking independent voting
|
| 1614 |
+
behavior over more than one election, there is a significant volatility in voting loyalty and as
|
| 1615 |
+
a group, independents are distinct from partisans. The research also confirms that a sizeable
|
| 1616 |
+
number of independents move in and out of independent status from one election to another.
|
| 1617 |
+
|
| 1618 |
+
In the first analysis on how political identification of voters changes over multiple survey
|
| 1619 |
+
waves, we explored how these respondents changed their party identification from one survey
|
| 1620 |
+
cycle to the next. The Initial Party ID scale found that independents were more fluid on this metric
|
| 1621 |
+
than party-affiliated respondents with the percent of independents changing at the second wave
|
| 1622 |
+
|
| 1623 |
+
5 Z-test for proportions <.01.
|
| 1624 |
+
|
| 1625 |
+
18
|
| 1626 |
+
|
| 1627 |
+
THE FLUID VOTER
|
| 1628 |
+
|
| 1629 |
+
T A B L E 8 Changes in voting behavior by Summary 3-Category Scale
|
| 1630 |
+
|
| 1631 |
+
VCF0303
|
| 1632 |
+
|
| 1633 |
+
Voted in two waves
|
| 1634 |
+
|
| 1635 |
+
Percent that changed voting behavior
|
| 1636 |
+
|
| 1637 |
+
Democrat (including leaners)
|
| 1638 |
+
|
| 1639 |
+
Republican (including leaners)
|
| 1640 |
+
|
| 1641 |
+
Subtotal: Party-Identified
|
| 1642 |
+
|
| 1643 |
+
Independent
|
| 1644 |
+
|
| 1645 |
+
Total
|
| 1646 |
+
|
| 1647 |
+
2349
|
| 1648 |
+
|
| 1649 |
+
2075
|
| 1650 |
+
|
| 1651 |
+
4424
|
| 1652 |
+
|
| 1653 |
+
332
|
| 1654 |
+
|
| 1655 |
+
4756
|
| 1656 |
+
|
| 1657 |
+
31%
|
| 1658 |
+
|
| 1659 |
+
35%
|
| 1660 |
+
|
| 1661 |
+
33%
|
| 1662 |
+
|
| 1663 |
+
48%
|
| 1664 |
+
|
| 1665 |
+
34%
|
| 1666 |
+
|
| 1667 |
+
Percent that
|
| 1668 |
+
did not change
|
| 1669 |
+
|
| 1670 |
+
69%
|
| 1671 |
+
|
| 1672 |
+
65%
|
| 1673 |
+
|
| 1674 |
+
67%
|
| 1675 |
+
|
| 1676 |
+
52%
|
| 1677 |
+
|
| 1678 |
+
66%
|
| 1679 |
+
|
| 1680 |
+
by more than double that of partisans. Additionally, the percentage of independents becoming
|
| 1681 |
+
party affiliated was nearly three times that of party affiliates becoming independent. Moving to
|
| 1682 |
+
the analysis of the Seven-Point Scale, even more fluidity was found with an overall 57% of those
|
| 1683 |
+
in one of the three independent categories of the Seven-Point Scale changing their identification
|
| 1684 |
+
at wave two. The last analysis collapsed categories of the Summary 3-Category Scale in party
|
| 1685 |
+
identification seen in the previous two scales and resulted in a significantly reduced (7%) number
|
| 1686 |
+
of independent respondents. Despite this small percentage of independent respondents, almost
|
| 1687 |
+
two-thirds or 64% of the independents changed classification to partisans at Wave 2.
|
| 1688 |
+
|
| 1689 |
+
ANES participants who responded to two consecutive waves of the survey but voted in
|
| 1690 |
+
neither of the corresponding elections showed much greater fluidity in their political identifica-
|
| 1691 |
+
tion between waves. Overall, 60% of respondents changed their Initial Party Identification. In
|
| 1692 |
+
contrast with the voting respondents, non-voting Independents were substantially the same as
|
| 1693 |
+
party affiliates, 59% making a switch to party affiliation. Non-voting independents were more
|
| 1694 |
+
likely to move by at least one point on the Seven-Point Scale (64%) than either Democrats (50%)
|
| 1695 |
+
or Republicans (49%). Thirty-nine percent of non-voters who identified as Independent in the
|
| 1696 |
+
first survey wave chose party affiliation at wave two. When the Summary 3-Category Scale is
|
| 1697 |
+
analyzed, we see that 81% of the non-voting independents identified with one of the major
|
| 1698 |
+
parties at wave two, compared with 58% of all respondents.
|
| 1699 |
+
|
| 1700 |
+
Our analysis on how independent voters and non-voters changed their party identification
|
| 1701 |
+
from one cycle to the next showed a significant amount of fluidity with non-voters being espe-
|
| 1702 |
+
cially unpredictable. On all three political identification scales, independent respondents changed
|
| 1703 |
+
their political identification over time more often than partisans (ranging from 36% to 64% for
|
| 1704 |
+
voters and 59% to 83% for non-voters) with the exception of non-voting Republicans on the
|
| 1705 |
+
Initial Party ID Scale. These findings suggest that independent voters and non-voters who iden-
|
| 1706 |
+
tify in one political classification in one election are less likely to identify themselves in the same
|
| 1707 |
+
manner in the next election. Their identification may depend on specific candidates or issues on
|
| 1708 |
+
the ballot (Reilly et al., 2023) or may derive from short-term interest rather than a long-standing
|
| 1709 |
+
loyalty (Miller, 1991). This finding supports Fiorina's (2016) assertion about independent voting
|
| 1710 |
+
behavior: “whatever they are, they are an important component of the electoral instability that
|
| 1711 |
+
characterizes the contemporary era. Their critical contribution to contemporary elections lies in
|
| 1712 |
+
their volatility” (p. 10).
|
| 1713 |
+
|
| 1714 |
+
We next investigated how frequently respondents to the ANES scales vote “straight tickets,”
|
| 1715 |
+
always choosing candidates from the same party or “mixed tickets” where some Republican
|
| 1716 |
+
and some Democrat candidates are chosen. Our expectation that those identifying as Demo-
|
| 1717 |
+
crat or Republican would mostly choose candidates from their own party was confirmed, while
|
| 1718 |
+
independents demonstrated more variety in their choices. For the Initial Party ID scale, over
|
| 1719 |
+
70% of partisans voted straight ticket, while 65% of independent respondents did, with the
|
| 1720 |
+
independent straight-ticket voters divided; 35% voting for Democrats and 30% for Republi-
|
| 1721 |
+
cans. While the Seven-Point Scale showed similar results, Independent-Democrats showed a
|
| 1722 |
+
|
| 1723 |
+
REILLY anD HUnTInG
|
| 1724 |
+
|
| 1725 |
+
19
|
| 1726 |
+
|
| 1727 |
+
higher percentage of straight-ticket support of Democratic candidates than the Weak Demo-
|
| 1728 |
+
crats, while Independent Republicans were slightly less likely to vote a straight ticket than Weak
|
| 1729 |
+
Republicans.
|
| 1730 |
+
|
| 1731 |
+
Finally, we explored the degree to which individuals change their voting choices over time
|
| 1732 |
+
(two-wave voters). Partisan voters exhibited the same voting behavior, either straight-ticket
|
| 1733 |
+
or mixed voting in each wave, in 70% of the cases. For independents, this percentage drops
|
| 1734 |
+
to 57%. The Initial Party ID analysis found that approximately 30% of partisans changed
|
| 1735 |
+
between waves compared to 43% of independents; while the Seven-Point Scale showed
|
| 1736 |
+
Independent-Independents were the most likely to change their voting profile at 48%, followed
|
| 1737 |
+
by Independent-Republicans at 45%. Weak Democrats voted for a straight Democratic ticket at
|
| 1738 |
+
a rate of 45%, while Independent-Democrats did so at a rate of 47%. Independents were more
|
| 1739 |
+
likely to go from mixed to straight voting and much more likely to vote for a mix of the two
|
| 1740 |
+
parties in both waves. For the Summary 3-Category, approximately a third of partisans changed
|
| 1741 |
+
their voting patterns over the two waves compared to 48% of independents.
|
| 1742 |
+
|
| 1743 |
+
Our research on independent voting behavior included analyses of voting patterns over time.
|
| 1744 |
+
The findings confirm that independents do indeed move in and out of independent status when
|
| 1745 |
+
tracked over multiple elections. Further, this study lends support to the notion that there is a
|
| 1746 |
+
good deal more fluidity in voting patterns of independents. This was the case when analyzing
|
| 1747 |
+
data across all three ANES scales. Our analysis of the ANES Seven-Point Scale showed that
|
| 1748 |
+
Independent-Republicans and Weak-Republicans resembled each other's voting patterns on
|
| 1749 |
+
straight/split ticket and voting change over time analyses (Mayer, 2008; Petrocik, 2009; Smith
|
| 1750 |
+
et al., 1995); however, this was not the case with Independent-Democrats and Weak-Democrats.
|
| 1751 |
+
Independent-Democrats, who did not affiliate with any party in the Initial Party Response ID
|
| 1752 |
+
question, were more likely to vote only for Democrats than Weak-Democrats that specifically
|
| 1753 |
+
identified as Democrat. Similarly, Independent-Republicans were as likely to vote a straight
|
| 1754 |
+
Republican ticket in both waves than Weak Republicans. Respondents who were coded as either
|
| 1755 |
+
5 (Independent-Republican) or 6 (Weak Republican) showed essentially the same voting behav-
|
| 1756 |
+
ior, while those coded as 3 (Independent-Democrat) were more Democratic in their behavior
|
| 1757 |
+
than the supposedly more liberal Weak Democrats at scale point 2. This indicates that caution
|
| 1758 |
+
needs to be exercised when treating the Seven-Point Scale (VCF0301) as a continuous variable.
|
| 1759 |
+
|
| 1760 |
+
It may be that traditional ways of measuring voter identification do not capture the independ-
|
| 1761 |
+
ent voter due to voter composition of the electorate and our hyperpolarized political environ-
|
| 1762 |
+
ment. Due to the research of Keith and others (1992), it became most common for researchers
|
| 1763 |
+
with the ANES to utilize a three-point or five-point scale that classified independent-leaning
|
| 1764 |
+
Democrats, or independent-leaning Republicans, as partisans (VCF0302, Initial Party ID
|
| 1765 |
+
response). This resulted in a significant reduction in the number of self-described independ-
|
| 1766 |
+
ents. Reilly and Hedberg (2022) have argued that in light of the more recent work of Klar and
|
| 1767 |
+
Krupnikov (2016) and Zschirnt (2011), which showed the importance of the independent iden-
|
| 1768 |
+
tity, classifying self-identified independents as partisans seems counterproductive in examining
|
| 1769 |
+
their influence on partisans, especially when respondents elected to self-identify as leaners. The
|
| 1770 |
+
authors collapsed three groups—respondents who selected option 3, 4, or 5—as independ-
|
| 1771 |
+
ent, thus treating leaners as Independents (VCF0303, Summary 3-category scale). Similarly,
|
| 1772 |
+
Fiorina (2016) has long been an opponent of classifying leaning independents as partisans and
|
| 1773 |
+
leaving pure independents in the middle ID category arguing that “We can think of no other case
|
| 1774 |
+
in political science where analysts change a respondent's explicit response to a survey item on
|
| 1775 |
+
the basis of information from other items—especially one generally used as the dependent varia-
|
| 1776 |
+
ble” (Abrams & Fiorina, 2011, p. 5). Perhaps it is time to develop new explanatory constructs to
|
| 1777 |
+
capture independent voter classification.
|
| 1778 |
+
|
| 1779 |
+
20
|
| 1780 |
+
|
| 1781 |
+
CONCLUSION
|
| 1782 |
+
|
| 1783 |
+
THE FLUID VOTER
|
| 1784 |
+
|
| 1785 |
+
Our study contributes to previous literature on the independent voter by showing their voting
|
| 1786 |
+
patterns are volatile, unpredictable, and distinct from partisans. Additionally, when analyz-
|
| 1787 |
+
ing voting behavior over time, our research confirmed that a sizeable number of independ-
|
| 1788 |
+
ents move in and out of independent status from one election to another. This volatility was
|
| 1789 |
+
observed in all three measures of party affiliation used by the ANES survey data. When inde-
|
| 1790 |
+
pendents are followed over multiple elections, they have been found to have no firm partisan
|
| 1791 |
+
loyalties.
|
| 1792 |
+
|
| 1793 |
+
Despite our contributions, our study has several limitations. First, as with any survey, the
|
| 1794 |
+
voting classification and behavior details are all based on self-reports, which are suspectable to
|
| 1795 |
+
response bias. Second, although ANES is a rich dataset with a long history to draw from, it does
|
| 1796 |
+
have limitations for this sort of analysis. There is limited information about voter choices in the
|
| 1797 |
+
data. The survey asks for party choices on just four races: president, Congress, Senate, and gover-
|
| 1798 |
+
nor. With the survey waves spaced two years apart (except for the 2016–2020 waves), respondents
|
| 1799 |
+
will not be able to provide answers to presidential, senatorial, and most governor's races in both
|
| 1800 |
+
waves, which limits the data available for analysis. These four races, especially at the presidential
|
| 1801 |
+
level, are susceptible to a “celebrity effect” where a high-profile candidate's perceived charm
|
| 1802 |
+
(or repulsiveness) may overwhelm a voter's policy-based preferences when selecting a candidate.
|
| 1803 |
+
Data that included more frequent and down-ballot races would provide a better picture of the
|
| 1804 |
+
relationship between the stated political identification of voters and their voting choices (Bitzer
|
| 1805 |
+
et al., 2021). Finally, it is also difficult to draw solid conclusions about the behavior of non-voters
|
| 1806 |
+
from these data. These non-voters may be latent voters who generally lie dormant but turn out
|
| 1807 |
+
at the polls when there is an issue or candidate that particularly motivates them. Without a very
|
| 1808 |
+
long time-series survey, it is difficult to say with what frequency these latent voters are activated
|
| 1809 |
+
or what motivates changes in their political identification.
|
| 1810 |
+
|
| 1811 |
+
There is a lot that still needs to be learned about this emerging group of voters. Future
|
| 1812 |
+
research should explore the fluidity of Black and Latino voters as well as the increasing genera-
|
| 1813 |
+
tional divide. Most importantly, there is a need to continue to track independent voting behavior
|
| 1814 |
+
over time and more analysis on the voting patterns of independents is needed down ballot at the
|
| 1815 |
+
state and local level.
|
| 1816 |
+
|
| 1817 |
+
ORCID
|
| 1818 |
+
Thom Reilly
|
| 1819 |
+
|
| 1820 |
+
https://orcid.org/0000-0001-8614-0482
|
| 1821 |
+
|
| 1822 |
+
REFERENCES
|
| 1823 |
+
Abrams, Samuel J., and Morris P. Fiorina. 2011. “Are Leaning Independents Deluded or Dishonest Weak Partisans?”
|
| 1824 |
+
|
| 1825 |
+
https://cise.luiss.it/cise/wp-content/uploads/2011/10/Are-Leaners-Partisans.pdf.
|
| 1826 |
+
|
| 1827 |
+
ANES Data Center. 2015. “Party Identification 3-Point Scale (Revised in 2008) 1952-2012.” American National Election
|
| 1828 |
+
|
| 1829 |
+
Studies. https://electionstudies.org/resources/anes-guide/top-tables/?id=22.
|
| 1830 |
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|
| 1831 |
+
ANES Data Center. 2021. “American National Election Studies.” https://electionstudies.org/data-center/.
|
| 1832 |
+
ANES Data Center. n.d. “Time Series Cumulative Data File.” American National Election Studies. https://electionstud-
|
| 1833 |
+
|
| 1834 |
+
ies.org/data-center/anes-time-series-cumulative-data-file/.
|
| 1835 |
+
|
| 1836 |
+
Bitzer, J. Michael, Christopher A. Cooper, Whitney Ross Manzo, and Susan Roberts. 2021, November 4–5. “The Rise
|
| 1837 |
+
of the Unaffiliated Voter in North Carolina.” Prepared for Presentation at the State if the Parties 2020 and Beyond
|
| 1838 |
+
Virtual Conference. Ray C. Bliss Institute of Applied Politics, University of Akron.
|
| 1839 |
+
|
| 1840 |
+
Bitzer, J. Michael, Christopher A. Cooper, Whitney Ross Manzo, and Susan Roberts. 2022. “Growing and Distinct:
|
| 1841 |
+
The Unaffiliated Voter as Unmoored Voter.” Social Science Quarterly 103(7): 1587–601. https://doi.org/10.1111/
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+
ssqu.13225
|
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+
|
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+
Brody, Richard A. 1978. “Change and Stability in the Components of Partisan Identification” Paper Prepared for the
|
| 1845 |
+
|
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+
NES Conference on Party Identification.
|
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+
|
| 1848 |
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21
|
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+
Brody, Richard A. 1991. “Stability and Change in Party Identification: Presidential Off-Years.” In Reasoning and Choice,
|
| 1853 |
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edited by Paul A. Sniderman, Philip E. Tetlock, and Richard A. Brody, 179–205. Cambridge: Cambridge Univer-
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Brody, Richard A., and Lawrence S. Rothenberg. 1988. “The Instability of Partisanship: An Analysis of the 1980 Pres-
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idential Election.” British Journal of Political Science 18(4): 445–65. https://doi.org/10.1017/S0007123400005214.
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Campbell, Angus, Philip E. Converse, Warren E. Miller, and Donald E. Stokes. 1960. The American Voter. Hoboken,
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NJ: Wiley.
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DeBell, Matthew. 2010. How to Analyze ANES Survey Data. ANES Technical Report Series no.nes012492. Palo Alto,
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CA, and Ann Arbor, MI: Stanford University and the University of Michigan.
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Fiorina, Morris P. 1977. “An Outline for a Model of Party Choice.” American Journal of Political Science 21(3): 601–25.
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https://doi.org/10.2307/2110583.
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Fiorina, Morris P. 2016. “Independents: The Marginal Members of an Electoral Coalition.” Washington, DC: Hoover
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Institution. https://www.hoover.org/research/independents-marginal-members-electoral-coalition.
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Fiorina, Morris P. 2017. Unstable Majorities: Polarization, Party Sorting, and Political Stalemate. Washington, DC:
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Hoover Institution Press.
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+
Gallup. 2022. “Party Affiliation.” Gallup Polls. https://news.gallup.com/poll/15370/party-affiliation.aspx.
|
| 1881 |
+
Gruber, Jeremy, and John Opdycke. 2020. “The Next Great Migration: The Rise of Independent Voters.” Open Prima-
|
| 1882 |
+
|
| 1883 |
+
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Ingraham, Christopher. 2021. “How to Fix Democracy: More Beyond the Two-Party System, Experts Say.” The Wash-
|
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+
|
| 1887 |
+
ington Post. https://www.washingtonpost.com/business/2021/03/01/break-up-two-party-system/.
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+
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+
Jackson, John E. 1975. “Issues, Party Choices, and Presidential Votes.” American Journal of Political Science 19(2):
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+
|
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+
161–85. https://doi.org/10.2307/2110431.
|
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+
|
| 1893 |
+
Keith, Bruce E., David B. Magleby, Candice J. Nelson, Elizabeth Orr, Mark C. Westlye, and Raymond E. Wolfinger.
|
| 1894 |
+
|
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+
1992. The Myth of the Independent Voter. Oakland, CA: University of California Press.
|
| 1896 |
+
|
| 1897 |
+
Klar, Samara. 2014. “Partisanship in a Social Setting.” American Journal of Political Science 58(3): 687–704. https://doi.
|
| 1898 |
+
|
| 1899 |
+
org/10.1111/ajps.12087.
|
| 1900 |
+
|
| 1901 |
+
Klar, Samara, and Yanna Krupnikov. 2016. Independent Politics: How American Disdain for Parties Leads to Political
|
| 1902 |
+
|
| 1903 |
+
Inaction. New York: Cambridge University Press.
|
| 1904 |
+
|
| 1905 |
+
Magleby, David, Candice Nelson, and Mark Westlye. 2011. “The Myth of the Indepedent Voter Revisited.” In Facing the
|
| 1906 |
+
Challenge of Democracy: Explorations in the Analysis of Public Opinion and Political Particiaption, edited by Paul
|
| 1907 |
+
M. Sniderman and Benjamin Highton, pp. 238–63. Princeton, NJ: Princeton University Press.
|
| 1908 |
+
|
| 1909 |
+
Mayer, William G. 2008. The Swing Voter in American Politics. Washington, DC: Brookings Institution Press.
|
| 1910 |
+
Miller, Warren E. 1991. “Party Identification, Realignment and Party Voting: Back to Basics.” American Political Science
|
| 1911 |
+
|
| 1912 |
+
Review 85(2): 557–68. https://doi.org/10.2307/1963175.
|
| 1913 |
+
|
| 1914 |
+
Page, Benjamin I., and Calvin C. Jones. 1979. “Reciprocal Effects of Policy Preferences, Party Loyalties, and the Vote.”
|
| 1915 |
+
|
| 1916 |
+
The American Political Science Review 73(4): 1071–89. https://doi.org/10.2307/1953990.
|
| 1917 |
+
|
| 1918 |
+
Petrocik, John R. 2009. “Measuring Party Support: Leaners Are Not Independents.” Electoral Studies 28(4): 562–72.
|
| 1919 |
+
|
| 1920 |
+
https://doi.org/10.1016/j.electstud.2009.05.022.
|
| 1921 |
+
|
| 1922 |
+
PEW Research Center. 2019. Political Independents: Who They Are, What They Think. U.S. Politics & Policy. https://
|
| 1923 |
+
|
| 1924 |
+
www.pewresearch.org/politics/2019/03/14/political-independents-who-they-are-what-they-think/.
|
| 1925 |
+
|
| 1926 |
+
PEW Research Center. 2022. Americans’ Views of Government: Decades of Distrust, Enduring Support for Its Role U.S.
|
| 1927 |
+
Politics & Policy. https://www.pewresearch.org/politics/2022/06/06/americans-views-of-government-decades-of-dist
|
| 1928 |
+
rust-enduring-support-for-its-role/.
|
| 1929 |
+
|
| 1930 |
+
Reilly, Thom, and E. C. Hedberg. 2022. “Social Networks of Independents and Partisans: Are Independents a Moderat-
|
| 1931 |
+
|
| 1932 |
+
ing Force?” Politics & Policy 50(2): 225–43. https://doi.org/10.1111/polp.12460.
|
| 1933 |
+
|
| 1934 |
+
Reilly, Thom, Jacqueline S. Salit, and Omar H. Ali. 2023. The Independent Voter. London: Routledge.
|
| 1935 |
+
Sides, John. 2013. “Three Myths about Political Independents.” The Monkey Cage. https://themonkeycage.org/2009/12/
|
| 1936 |
+
|
| 1937 |
+
three_myths_about_political_in/.
|
| 1938 |
+
|
| 1939 |
+
Smith, Andrew E., Alfred J. Tuchfarber, Eric W. Rademacher, and Stephen E. Bennett. 1995. “Partisan Leaners Are NOT
|
| 1940 |
+
|
| 1941 |
+
Independents.” The Public Perspective. https://ropercenter.cornell.edu/sites/default/files/2018-07/66009.pdf.
|
| 1942 |
+
|
| 1943 |
+
Teixiera, Ruy. 2012. “The Great Illusion.” The New Republic. https://newrepublic.com/article/100799/swing-vote-untapp
|
| 1944 |
+
|
| 1945 |
+
ed-power-independents-linda-killian.
|
| 1946 |
+
|
| 1947 |
+
Zschirnt, Simon. 2011. “The Origins & Meaning of Liberal/Conservative Self-Identifications Revisited.” Political Behav-
|
| 1948 |
+
|
| 1949 |
+
ior 33(4): 685–701. https://doi.org/10.1007/s11109-010-9145-6.
|
| 1950 |
+
|
| 1951 |
+
22
|
| 1952 |
+
|
| 1953 |
+
THE FLUID VOTER
|
| 1954 |
+
|
| 1955 |
+
AUT HOR BI OG RAP HIES
|
| 1956 |
+
|
| 1957 |
+
Thom Reilly is a Professor and Co-Director for the Center for an Independent and Sustaina-
|
| 1958 |
+
ble Democracy in the School of Public Affairs at Arizona State University. He is the former
|
| 1959 |
+
Chancellor of the Nevada System of Higher Education and County Manager for Clark
|
| 1960 |
+
County, Nevada. Reilly's research focuses on public pay and benefit schemes, nonpartisan
|
| 1961 |
+
governance, the independent voter, and child welfare. He is the author of several books
|
| 1962 |
+
including The Independent Voter (Routledge Press, 2023) with co-authors Jacqueline Salit and
|
| 1963 |
+
Omar Ali, The Failure of Governance in Bell, California (Lexington Press, 2016), and Rethink-
|
| 1964 |
+
ing Public Sector Compensation (M.E. Sharpe, 2012).
|
| 1965 |
+
|
| 1966 |
+
Dan Hunting is Senior Researcher at Arizona State University's Lodestar Center for Philan-
|
| 1967 |
+
thropy & Nonprofit Innovation. His research interests include economic impacts of the
|
| 1968 |
+
nonprofit sector, voter dynamics, workforce development, education funding, and urban
|
| 1969 |
+
growth. Hunting has authored several foundational works that have informed Arizona policy
|
| 1970 |
+
discussions including Finding & Keeping: Educators for Arizona's Classrooms an analysis
|
| 1971 |
+
of the state's teacher shortage, and Sun Corridor: A Competitive Mindset (co-authored with
|
| 1972 |
+
Grady Gammage, Jr.) which described the complex connections between the economies of
|
| 1973 |
+
Phoenix and Tucson.
|
| 1974 |
+
|
| 1975 |
+
How to cite this article: Reilly, Thom, and Dan Hunting. 2023. “The fluid voter:
|
| 1976 |
+
Exploring independent voting patterns over time.” Politics & Policy 00: 1–22. https://doi.
|
| 1977 |
+
org/10.1111/polp.12517.
|
| 1978 |
|
q136/random_k2/question.json
CHANGED
|
@@ -15,8 +15,8 @@
|
|
| 15 |
],
|
| 16 |
"original_filenames": [
|
| 17 |
"f1f5242528411b262be447e61e2eb10f.pdf",
|
| 18 |
-
"
|
| 19 |
-
"
|
| 20 |
],
|
| 21 |
"modality": "markdown"
|
| 22 |
}
|
|
|
|
| 15 |
],
|
| 16 |
"original_filenames": [
|
| 17 |
"f1f5242528411b262be447e61e2eb10f.pdf",
|
| 18 |
+
"web_cb05559b91321f82.pdf",
|
| 19 |
+
"web_f77c9a6a0c40e754.pdf"
|
| 20 |
],
|
| 21 |
"modality": "markdown"
|
| 22 |
}
|
q136/random_k2/random_1.md
CHANGED
|
@@ -1,224 +1,750 @@
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INTERNATIONAL VISITORS
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review the official payment guidelines from the People's Bank of China:
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international visitors may use UnionPay chip-enabled cards,
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internationally issued Visa, Mastercard, and American Express chip-enabled cards to
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take Chengdu Metro.
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directly through the app.
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outlets at the airport).
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(passport/visa, etc.).
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quickly.
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functions properly.
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International Airport.
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that connects 80%+ high-speed routes), Chengdu South Railway Station (regional
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services that link to Leshan City, Mianyang City, Yibin City...), and Chengdu West
|
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Railway Station (serves western routes, e.g., Pujiang, Dujiangyan).
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Convention Center
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International Convention Center
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| 150 |
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transportation to other destinations, please check the official airport shuttle schedule upon
|
| 151 |
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arrival.
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complies with the rules below:
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QR code at gates
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scanning “Transport → Select Chengdu Bus”
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Chengdu:
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regulations.
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|
| 1 |
+
PREPARED REMARKS
|
|
|
|
| 2 |
|
| 3 |
+
Q1 FISCAL 2020
|
| 4 |
|
| 5 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 6 |
|
| 7 |
+
FY20Q1
|
| 8 |
|
| 9 |
+
CHRIS:
|
| 10 |
|
| 11 |
+
Thank you.
|
| 12 |
|
| 13 |
+
Welcome to EA’s first quarter fiscal 2020 earnings call. With me on the call today are Andrew
|
| 14 |
|
| 15 |
+
Wilson, our CEO, and Blake Jorgensen, our CFO and COO.
|
| 16 |
|
| 17 |
+
Please note that our SEC filings and our earnings release are available at ir.ea.com. In addition,
|
| 18 |
|
| 19 |
+
we have posted earnings slides to accompany our prepared remarks. Lastly, after the call, we
|
| 20 |
|
| 21 |
+
will post our prepared remarks, an audio replay of this call, our financial model, a transcript, and
|
|
|
|
| 22 |
|
| 23 |
+
an updated accounting FAQ.
|
| 24 |
|
| 25 |
+
With regards to our calendar: our annual shareholder meeting will take place on Thursday,
|
| 26 |
|
| 27 |
+
August 8, here in Redwood Shores; and our Q2 fiscal 2020 earnings call is scheduled for
|
| 28 |
|
| 29 |
+
Tuesday, October 29.
|
|
|
|
|
|
|
|
|
|
| 30 |
|
| 31 |
+
This presentation and our comments include forward-looking statements regarding future events
|
| 32 |
|
| 33 |
+
and the future financial performance of the Company. Actual events and results may differ
|
| 34 |
|
| 35 |
+
materially from our expectations. We refer you to our most recent Form 10-K for a discussion of
|
| 36 |
+
|
| 37 |
+
risks that could cause actual results to differ materially from those discussed today. Electronic
|
| 38 |
+
|
| 39 |
+
Arts makes these statements as of today, July 30, 2019, and disclaims any duty to update
|
| 40 |
+
|
| 41 |
+
them.
|
| 42 |
+
|
| 43 |
+
During this call, the financial metrics, with the exception of free cash flow, will be presented on a
|
| 44 |
+
|
| 45 |
+
GAAP basis. All comparisons made in the course of this call are against the same period in the
|
| 46 |
+
|
| 47 |
+
prior year unless otherwise stated.
|
| 48 |
+
|
| 49 |
+
Now, I’ll turn the call over to Andrew.
|
| 50 |
|
| 51 |
1
|
| 52 |
|
| 53 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 54 |
+
|
| 55 |
+
FY20Q1
|
| 56 |
+
|
| 57 |
+
ANDREW:
|
| 58 |
+
|
| 59 |
+
Thanks, Chris.
|
| 60 |
+
|
| 61 |
+
We delivered a strong start to FY20. Players were deeply engaged in our top franchises, with
|
| 62 |
+
|
| 63 |
+
growing communities reaching new peaks of engagement fueled by new content and in-game
|
| 64 |
+
|
| 65 |
+
events in our live services. As a result, our operating results significantly exceeded our
|
| 66 |
+
|
| 67 |
+
expectations for the first quarter. We’re thrilled by the great experiences that players are having
|
| 68 |
+
|
| 69 |
+
in our games, and we’re looking forward to delivering a lot more throughout the fiscal year.
|
| 70 |
+
|
| 71 |
+
Interactive entertainment continues to grow. An expanding global player base, new platforms,
|
| 72 |
+
|
| 73 |
+
new business models and more ways to play and watch are fueling tailwinds for the
|
| 74 |
+
|
| 75 |
+
industry. With this backdrop, the core drivers of growth for EA are: the depth and breadth of our
|
| 76 |
|
| 77 |
+
portfolio and IP; our expertise in live services; our leadership in subscriptions; and competitive
|
|
|
|
| 78 |
|
| 79 |
+
gaming that expands our reach and drives deeper engagement. We’re also continually
|
|
|
|
| 80 |
|
| 81 |
+
strengthening our foundation of great talent and technology. I’ll touch on some of these drivers
|
| 82 |
|
| 83 |
+
with a few highlights here.
|
| 84 |
|
| 85 |
+
Let’s start with Apex Legends. We have a massive global audience continuing to engage in this
|
|
|
|
| 86 |
|
| 87 |
+
high-quality, free-to-play experience. Apex has tremendous gameplay at its core, and we’ve
|
| 88 |
|
| 89 |
+
built it to have longevity as a live service that will continue to drive engagement over time. In
|
|
|
|
| 90 |
|
| 91 |
+
our live service, we’re delivering Seasons of new content – a collection of new content and
|
|
|
|
| 92 |
|
| 93 |
+
updates that begin to roll out at the start of each season, and continue throughout the course of
|
| 94 |
|
| 95 |
+
several weeks and months. We launched Season 2 in early July, including a robust Battle Pass
|
| 96 |
|
| 97 |
+
offering, a new character, and additions to the environment – and to date, it has outperformed
|
|
|
|
| 98 |
|
| 99 |
+
our expectations with significant growth in daily and weekly active players. In each season,
|
|
|
|
|
|
|
|
|
|
| 100 |
|
| 101 |
+
there are in-game events that are additional drivers of engagement – such as the event coming
|
| 102 |
+
|
| 103 |
+
in the next few weeks that will bring new content and deliver one of the most fan-requested
|
| 104 |
|
| 105 |
2
|
| 106 |
|
| 107 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 108 |
+
|
| 109 |
+
FY20Q1
|
| 110 |
+
|
| 111 |
+
features since the launch of Apex. There will be more updates and in-game experiences in the
|
| 112 |
+
|
| 113 |
+
weeks to come for Season 2, and Season 3 is shaping up to be even bigger. All of these
|
| 114 |
+
|
| 115 |
+
elements – the fantastic core gameplay, Seasons of new content, and additional in-game events
|
| 116 |
+
|
| 117 |
+
– are designed to continually excite and engage the Apex community over the long-term.
|
| 118 |
+
|
| 119 |
+
We’re also expanding into additional growth opportunities for Apex Legends. Esports will bring
|
| 120 |
+
|
| 121 |
+
new drivers of social interaction and competition to the Apex ecosystem. Interest from teams,
|
| 122 |
+
|
| 123 |
+
broadcast partners and sponsors is strong, and we’ve had great success with our first exhibition
|
| 124 |
+
|
| 125 |
+
events, including a competition at the ESPYS that was broadcast on ESPN and ABC. We’ll
|
| 126 |
+
|
| 127 |
+
have 80 teams from around the world participating in our first official competition in September.
|
| 128 |
+
|
| 129 |
+
Our plans to bring Apex Legends to China and a worldwide mobile launch are also on course,
|
| 130 |
+
|
| 131 |
+
and we will share more on our plans in the future.
|
| 132 |
+
|
| 133 |
+
In our EA SPORTS portfolio, our franchises like Madden NFL and FIFA are delivering for core
|
| 134 |
+
|
| 135 |
+
fans, innovating to reach new players, and leading our growth in esports. Looking first at
|
| 136 |
+
|
| 137 |
+
Madden NFL, we continue to see deep year-round engagement in the franchise. Live service
|
| 138 |
+
|
| 139 |
+
events and tie-in content with the NFL Draft drove growth in new players joining Madden NFL
|
| 140 |
|
| 141 |
+
19 in Q1, and also deepened engagement in Madden Ultimate Team. We’re now just days
|
|
|
|
| 142 |
|
| 143 |
+
away from launching Madden NFL 20. The innovations in this year’s game, like the new
|
| 144 |
|
| 145 |
+
superstar X-Factor abilities, new personalized Career Campaign, and the more fluid core
|
| 146 |
+
|
| 147 |
+
gameplay, are all designed to appeal to new and existing football fans. Madden NFL esports
|
| 148 |
+
|
| 149 |
+
also continues to drive growing viewership. Players in our Madden NFL competitive
|
| 150 |
+
|
| 151 |
+
ecosystem engaged four times more than non-competitors last season, and our events drove
|
| 152 |
+
|
| 153 |
+
record broadcast and digital viewership. We’re now looking to build on that success with the
|
| 154 |
+
|
| 155 |
+
Madden NFL 20 Championship Series. We’re partnered with all 32 NFL teams, our
|
| 156 |
+
|
| 157 |
+
competitions are aligned with key beats in the NFL season, and we’re welcoming major
|
| 158 |
|
| 159 |
3
|
| 160 |
|
| 161 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 162 |
+
|
| 163 |
+
FY20Q1
|
| 164 |
+
|
| 165 |
+
sponsors including Pizza Hut, Snickers and Starbucks. Finally, the latest season of our fan-
|
| 166 |
+
|
| 167 |
+
favorite Madden NFL Mobile game launches tomorrow, and this year the game is bringing back
|
| 168 |
+
|
| 169 |
+
some of the classic modes that fans love, as well as new innovation in social co-op play and
|
| 170 |
+
|
| 171 |
+
customization. Through great experiences on console and PC, the ever-popular Madden NFL
|
| 172 |
+
|
| 173 |
+
Mobile game, and our leading esports programming, Madden NFL continues to reach and
|
| 174 |
+
|
| 175 |
+
engage a wide audience of fans.
|
| 176 |
+
|
| 177 |
+
Our FIFA franchise had a very strong Q1, with players deeply engaged in our Ultimate Team
|
| 178 |
+
|
| 179 |
+
live service. Our biggest in-game event, Team of the Season, had more than 3 million players
|
| 180 |
+
|
| 181 |
+
logging into FUT daily to play – the highest daily levels we’ve ever seen for this event. Esports
|
| 182 |
+
|
| 183 |
+
for FIFA is exploding as well, with our competitive modes growing faster than any other mode in
|
| 184 |
+
|
| 185 |
+
FUT. Momentum is strong across our entire FIFA esports ecosystem, and next week’s FIFA
|
| 186 |
|
| 187 |
+
eWorld Cup Finals will be the culmination of a season that has engaged 17 official league
|
| 188 |
|
| 189 |
+
partners, players from 20 different nations, more than 30 live events, and more than 60 million
|
| 190 |
|
| 191 |
+
total views to date. Looking ahead to September, FIFA 20 is set to expand our FIFA platform
|
| 192 |
|
| 193 |
+
with a brand new dimension of the game for players who want more personalization,
|
| 194 |
|
| 195 |
+
customization and community. VOLTA Football brings a street soccer experience to the
|
| 196 |
|
| 197 |
+
franchise, where players can build their own characters, express themselves, and play different
|
| 198 |
|
| 199 |
+
forms of the sport in different environments around the world. That’s in addition to major
|
|
|
|
| 200 |
|
| 201 |
+
advancements in the core experience designed to deliver the most authentic football gameplay
|
| 202 |
|
| 203 |
+
we’ve ever produced. FIFA 20 will have an unmatched breadth of top leagues, teams and
|
| 204 |
|
| 205 |
+
players included in the game – a continuing differentiator of the authenticity in our FIFA
|
| 206 |
|
| 207 |
+
franchise. Our licensing program is built on the strength of multi-year relationships and careful
|
| 208 |
+
|
| 209 |
+
consideration of the most important players, teams and leagues that our fans love to see in the
|
| 210 |
+
|
| 211 |
+
game. From console to PC, to our FIFA Mobile games in the west and China, to our FIFA
|
| 212 |
+
|
| 213 |
+
Online offerings in Asia, FIFA continues to be the way that hundreds of millions of players
|
| 214 |
+
|
| 215 |
+
around the world come together in their shared passion for soccer.
|
| 216 |
|
| 217 |
4
|
| 218 |
|
| 219 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 220 |
+
|
| 221 |
+
FY20Q1
|
| 222 |
+
|
| 223 |
+
Our Sims 4 live service also continues to be a rich and rewarding experience for our players,
|
| 224 |
+
|
| 225 |
+
and a strong platform for growth. The Sims 4 continues to be one of the great owned IP
|
| 226 |
+
|
| 227 |
+
success stories of our portfolio, and we’re planning for FY20 to be our biggest year yet of new
|
| 228 |
+
|
| 229 |
+
content. Knowing that, we gave more fans a chance to get into the game through a one-week
|
| 230 |
+
|
| 231 |
+
promotion in May to download the base game for free. Almost 7 million players downloaded the
|
| 232 |
+
|
| 233 |
+
game during that time. In addition to the base game promotion, total expansion and game pack
|
| 234 |
+
|
| 235 |
+
downloads also increased 55% year-over-year in Q1. We launched our seventh expansion
|
| 236 |
+
|
| 237 |
+
pack – Island Living – in late June, and it has already become one of our best-selling packs for
|
| 238 |
+
|
| 239 |
+
The Sims 4. We are fortunate to have an incredibly vibrant and creative Sims community on
|
| 240 |
+
|
| 241 |
+
console, PC and mobile, and we are continuing to double down on this amazing franchise to
|
| 242 |
+
|
| 243 |
+
reach new players and open up exciting new dimensions of The Sims this year.
|
| 244 |
+
|
| 245 |
+
Subscription services are expanding across the industry, as well. We’re a pioneer and a leader
|
| 246 |
+
|
| 247 |
+
in this space, having just launched our subscription on a third major platform with EA Access on
|
| 248 |
+
|
| 249 |
+
the Sony PlayStation 4. We believe subscriptions can be transformative to the player
|
| 250 |
+
|
| 251 |
+
experience and the gaming industry over the long term, as they offer tremendous value and
|
| 252 |
+
|
| 253 |
+
choice to players, and greater flexibility in the games we bring to market. Our PC subscription
|
| 254 |
+
|
| 255 |
+
already includes more than 220 games, 140 of which are from third party developers. We’re
|
| 256 |
+
|
| 257 |
+
continually adding to this with new games from EA, from indie developers seeking to expand
|
| 258 |
+
|
| 259 |
+
their reach through our EA Originals program, and from other third-party partners ready to reach
|
| 260 |
+
|
| 261 |
+
more players through our services. We’re also working to expand our subscriptions to even
|
| 262 |
+
|
| 263 |
+
more platforms.
|
| 264 |
+
|
| 265 |
+
Mobile continues to be a growth opportunity for us. Live services are a key aspect of our mobile
|
| 266 |
+
|
| 267 |
+
business, with franchises like Madden Mobile, FIFA Mobile and The Sims continuing to drive
|
| 268 |
+
|
| 269 |
+
strong ongoing engagement. Star Wars Galaxy of Heroes has grown to nearly 80 million
|
| 270 |
+
|
| 271 |
+
players life-to-date. Galaxy of Heroes has the most deeply engaged community of all our
|
| 272 |
|
| 273 |
5
|
| 274 |
|
| 275 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 276 |
+
|
| 277 |
+
FY20Q1
|
| 278 |
+
|
| 279 |
+
mobile games, and we plan to continue delivering great new content and in-game events to
|
| 280 |
+
|
| 281 |
+
grow the audience this year. We’ve also just started pre-alpha testing for Plants vs. Zombies 3.
|
| 282 |
+
|
| 283 |
+
In a market where discovery and acquisition can be challenging, Plants vs. Zombies is one of
|
| 284 |
+
|
| 285 |
+
the most beloved brands in gaming. To date, we’ve had more than a billion downloads
|
| 286 |
|
| 287 |
+
worldwide of PvZ games on mobile, and we’re looking forward to bringing something new to
|
| 288 |
|
| 289 |
+
fans around the world. We’re continuing to prototype and develop more bespoke mobile
|
| 290 |
|
| 291 |
+
projects, as well as new concepts for cross-platform play. The mobile space is complex and
|
| 292 |
|
| 293 |
+
competitive, and our focus is on bringing more innovation and unique new experiences to
|
| 294 |
|
| 295 |
+
mobile players.
|
| 296 |
|
| 297 |
+
In addition to the franchises and live services that I’ve already mentioned, we’ll be delivering
|
| 298 |
|
| 299 |
+
many other new experiences to players throughout the remainder of this fiscal year. NHL 20 is
|
| 300 |
|
| 301 |
+
launching in Q2, with hundreds of gameplay advancements, as well as new competitive and
|
| 302 |
|
| 303 |
+
multiplayer modes. We’ll take the wraps off our new Need for Speed game heading into
|
|
|
|
|
|
|
| 304 |
|
| 305 |
+
Gamescom in a few weeks. We have a Plants vs. Zombies shooter title coming to console and
|
| 306 |
|
| 307 |
+
PC later this year. And the excitement and anticipation for Star Wars Jedi: Fallen Order has
|
| 308 |
|
| 309 |
+
been strong coming out of EA PLAY and E3, where the game received 45 award nominations
|
| 310 |
|
| 311 |
+
and great buzz from the player community. Respawn’s track record speaks for the high-quality
|
|
|
|
| 312 |
|
| 313 |
+
games they develop, and they have created a brand new Star Wars story that will be a lot of fun
|
| 314 |
|
| 315 |
+
to play when it launches this holiday.
|
| 316 |
+
|
| 317 |
+
From the core game to live services that extend and enhance the experience, to new ways to
|
| 318 |
+
|
| 319 |
+
engage through subscriptions and competitive gaming, our focus continues to be on strong
|
| 320 |
+
|
| 321 |
+
execution and delivering innovation, quality and fun for players at every turn. We’re fortunate to
|
| 322 |
+
|
| 323 |
+
have some of the greatest and most creative talent in the industry, driving our efforts to
|
| 324 |
+
|
| 325 |
+
continually learn and improve. With robust, best-in-class technology powering our efforts, we’re
|
| 326 |
+
|
| 327 |
+
also in position to scale and evolve with the changing needs of our players.
|
| 328 |
|
| 329 |
6
|
| 330 |
|
| 331 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 332 |
+
|
| 333 |
+
FY20Q1
|
| 334 |
+
|
| 335 |
+
Now I’ll hand the call over to Blake.
|
| 336 |
+
|
| 337 |
+
BLAKE:
|
| 338 |
|
| 339 |
+
Thanks, Andrew.
|
| 340 |
|
| 341 |
+
We delivered operating results significantly above our expectations this quarter. At a high level,
|
| 342 |
|
| 343 |
+
those results were driven by broad strength across our core franchises. Apex Legends
|
| 344 |
|
| 345 |
+
continues to delight players and we are pleased with the impact of Season 2 since its launch on
|
|
|
|
| 346 |
|
| 347 |
+
July 2. This quarter’s results demonstrate how the power of our portfolio strategy, combined
|
| 348 |
|
| 349 |
+
with extra content, delivers strong results - even in relatively quiet quarters.
|
| 350 |
|
| 351 |
+
I’ll report the specifics of our results on a GAAP basis, then use our operational measure of net
|
| 352 |
|
| 353 |
+
bookings to discuss the dynamics of our business. To compare this quarter’s results to
|
| 354 |
|
| 355 |
+
historically-reported non-GAAP measures, please refer to the relevant tabs in our downloadable
|
|
|
|
| 356 |
|
| 357 |
+
financial model.
|
| 358 |
|
| 359 |
+
EA’s net revenue was $1.21 billion, compared to $1.14 billion a year ago, and above our
|
| 360 |
|
| 361 |
+
guidance by $79 million. Operating expenses were $607 million, compared to $622 million a
|
| 362 |
|
| 363 |
+
year ago, primarily driven by lower sales and marketing partially offset by continued investment
|
| 364 |
+
|
| 365 |
+
in new IP. This was significantly below our forecast, driven by timing of advertising
|
| 366 |
+
|
| 367 |
+
spend. Operating income was $415 million, compared to $300 million a year ago and above
|
| 368 |
+
|
| 369 |
+
our expectations. Diluted earnings per share was $4.75, up over 400% year on
|
| 370 |
+
|
| 371 |
+
year. Underlying EPS was well above our expectations, driven by net bookings, gross profit and
|
| 372 |
+
|
| 373 |
+
operating expenses.
|
| 374 |
+
|
| 375 |
+
Operating cash flow for the quarter was $158 million, up $38 million from last year. Capital
|
| 376 |
+
|
| 377 |
+
expenditures for the quarter were $45 million, resulting in a free cash flow of
|
| 378 |
|
| 379 |
7
|
| 380 |
|
| 381 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 382 |
+
|
| 383 |
+
FY20Q1
|
| 384 |
|
| 385 |
+
$113 million. Operating cash flow for the last twelve months was $1.59 billion. See our
|
| 386 |
|
| 387 |
+
earnings slides for further cash flow information.
|
| 388 |
|
| 389 |
+
During the quarter, we also repurchased 3.2 million shares at a cost of $305 million, leaving
|
| 390 |
|
| 391 |
+
$979 million available in our buyback program.
|
| 392 |
|
| 393 |
+
Our cash and short-term investments at the end of the quarter were $5.19 billion, up 4% year
|
|
|
|
| 394 |
|
| 395 |
+
on year.
|
|
|
|
| 396 |
|
| 397 |
+
Now, I’d like to turn to the key drivers of our business this quarter.
|
| 398 |
|
| 399 |
+
Net bookings for the quarter were $743 million, approximately flat year on year. It was
|
| 400 |
|
| 401 |
+
$53 million above our guidance, driven by strength across the board, with strong performance
|
| 402 |
+
|
| 403 |
+
from our core franchises and live services.
|
| 404 |
+
|
| 405 |
+
Digital net bookings were $701 million, up $8 million on the year-ago period. On a trailing
|
| 406 |
+
|
| 407 |
+
twelve-month basis, digital net bookings now represent 76% of our business, compared to 69%
|
| 408 |
+
|
| 409 |
+
a year ago.
|
| 410 |
+
|
| 411 |
+
Looking at each of the components of this quarter’s digital bookings in turn:
|
| 412 |
+
|
| 413 |
+
• Live services net bookings were up 12% year on year, to $504 million, led by Apex
|
| 414 |
+
|
| 415 |
+
Legends and The Sims 4. FIFA Ultimate Team was up 11% year on year at constant
|
| 416 |
+
|
| 417 |
+
currency, 5% at actual exchange rates.
|
| 418 |
+
|
| 419 |
+
Diving into the details: Season 2 launched for Apex Legends at the beginning of Q2, and
|
| 420 |
+
|
| 421 |
+
we’re pleased with its performance, with regards to both sales and engagement. We will
|
| 422 |
+
|
| 423 |
+
continue to add content during the quarter, with a major event in mid-August, and Season 3
|
| 424 |
+
|
| 425 |
+
will begin next quarter. We are increasing investment in content development and
|
| 426 |
+
|
| 427 |
+
marketing to continue to drive growth in Apex Legends.
|
| 428 |
|
| 429 |
8
|
| 430 |
|
| 431 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 432 |
+
|
| 433 |
+
FY20Q1
|
| 434 |
+
|
| 435 |
+
FIFA Online outperformed our expectations. FIFA Online 4 performed well in Korea, where
|
| 436 |
+
|
| 437 |
+
we have fully transitioned from FIFA Online 3 to FIFA Online 4. Meanwhile, FIFA Online 3
|
| 438 |
+
|
| 439 |
+
outperformed our expectations in China, and we are positioned well for switching over to
|
| 440 |
+
|
| 441 |
+
FIFA Online 4.
|
| 442 |
+
|
| 443 |
+
Finally, as Andrew mentioned, The Sims 4 base game promotion delivered nearly 7 million
|
| 444 |
+
|
| 445 |
+
new installs and we remain on track to have the fifth consecutive year of growth in
|
| 446 |
+
|
| 447 |
+
The Sims 4, following its launch in 2014.
|
| 448 |
+
|
| 449 |
+
• Mobile delivered net bookings of $122 million, down 17% year on year, driven by aging
|
| 450 |
+
|
| 451 |
+
titles. Although down year on year, Star Wars Galaxy of Heroes outperformed our
|
| 452 |
+
|
| 453 |
+
expectations and maintains a highly engaged user base, leading us to be optimistic about
|
| 454 |
+
|
| 455 |
+
performance in a huge year for Star Wars, with new TV show, movie and theme park
|
| 456 |
+
|
| 457 |
+
launches.
|
| 458 |
+
|
| 459 |
+
• Full game PC and console downloads generated net bookings of $75 million, down 22%
|
| 460 |
+
|
| 461 |
+
year on year, due to last year’s launch of A Way Out and FIFA 18 World Cup
|
| 462 |
+
|
| 463 |
+
promotions. 47% of our unit sales are now digital rather than physical, measured on Xbox
|
| 464 |
+
|
| 465 |
+
One and PlayStation 4 over the last twelve months. Although this is up 7 percentage points
|
| 466 |
+
|
| 467 |
+
year on year, we continue to model an annual shift of 5 percentage points, given how
|
| 468 |
+
|
| 469 |
+
strongly digital Anthem was at its launch last quarter.
|
| 470 |
+
|
| 471 |
+
Before discussing guidance, I would like to highlight that there were three income tax events
|
| 472 |
+
|
| 473 |
+
in the quarter that impacted our GAAP Q1 results and our full year GAAP guidance. Please
|
| 474 |
+
|
| 475 |
+
refer to our press release for the details. As a result, we expect to recognize a $1.700 billion
|
| 476 |
+
|
| 477 |
+
benefit in the fiscal year, which is $200 million better than we had included in our guidance last
|
| 478 |
+
|
| 479 |
+
quarter, although the phasing of the benefit between Q1 and Q2 has changed since we gave
|
| 480 |
+
|
| 481 |
+
that guidance. $1.080 billion of this amount was recognized in the first quarter and the
|
| 482 |
+
|
| 483 |
+
9
|
| 484 |
+
|
| 485 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 486 |
+
|
| 487 |
+
FY20Q1
|
| 488 |
+
|
| 489 |
+
remaining $620 million will be recognized when the Swiss tax rates change, which we expect to
|
| 490 |
+
|
| 491 |
+
occur in the second quarter. We do not expect the above events to impact our FY20 operating
|
| 492 |
+
|
| 493 |
+
cash flow or our management tax rate for fiscal 2020.
|
| 494 |
+
|
| 495 |
+
Now, turning to guidance: Except for the increase in our tax benefit of $200 million or $0.66
|
| 496 |
+
|
| 497 |
+
on GAAP EPS, we are reiterating our guidance for the full year.
|
| 498 |
+
|
| 499 |
+
We continue to expect The Sims 4 and Apex Legends to each deliver net bookings in the
|
| 500 |
+
|
| 501 |
+
$300 million to $400 million range.
|
| 502 |
+
|
| 503 |
+
We are holding our operating cash flow guidance at approximately $1.575 billion, with capex
|
| 504 |
+
|
| 505 |
+
still expected to be $125 million and free cash flow of about $1.45 billion.
|
| 506 |
+
|
| 507 |
+
For the second quarter, we continue to expect net revenue of $1.315 billion, cost of revenue
|
| 508 |
+
|
| 509 |
+
to be $407 million, and operating expenses of $679 million. This results in earnings per
|
| 510 |
+
|
| 511 |
+
share of $2.60 for the second quarter.
|
| 512 |
+
|
| 513 |
+
We anticipate net bookings for the quarter to be $1.23 billion. We’re excited about the Madden
|
| 514 |
+
|
| 515 |
+
NFL launch and upcoming Apex Legends event, and the launch of FIFA 20 with VOLTA
|
| 516 |
+
|
| 517 |
+
Football at the end of the quarter.
|
| 518 |
+
|
| 519 |
+
We over delivered this quarter as a result of the performance of our core franchises. These
|
| 520 |
+
|
| 521 |
+
evergreen live services provide a tremendously solid base for our business and enable us to
|
| 522 |
+
|
| 523 |
+
invest in new opportunities, to innovate and to take risks. We are unique among our peers in
|
| 524 |
+
|
| 525 |
+
this, and it is no coincidence that we are a leader in cloud gaming, subscriptions and in the
|
| 526 |
+
|
| 527 |
+
strength of our player networks.
|
| 528 |
+
|
| 529 |
+
People will only engage with our games if they have fun playing them. And we continue to
|
| 530 |
+
|
| 531 |
+
invest in keeping them fun – whether it’s the major innovation of VOLTA Football in FIFA, or
|
| 532 |
+
|
| 533 |
+
new modes, events and legends in Apex Legends, or even adding laundry to The Sims 4, we
|
| 534 |
+
|
| 535 |
+
10
|
| 536 |
+
|
| 537 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 538 |
+
|
| 539 |
+
FY20Q1
|
| 540 |
+
|
| 541 |
+
aim to give players content they want to play. If we’re successful in that, we’re successful as a
|
| 542 |
+
|
| 543 |
+
business.
|
| 544 |
+
|
| 545 |
+
This combination of core plus innovation plus fun will drive our success through the
|
| 546 |
+
|
| 547 |
+
year. Coming up in August we have more live services for our newest franchise, Apex
|
| 548 |
+
|
| 549 |
+
Legends, and the latest installment in one of our most storied, Madden NFL. FIFA 20 launches
|
| 550 |
+
|
| 551 |
+
right at the end of the quarter. The following quarter we have a new IP, Star Wars Jedi: Fallen
|
| 552 |
+
|
| 553 |
+
Order. Simultaneously, we continue to invest in more new IP, new technologies and new
|
| 554 |
+
|
| 555 |
+
business models.
|
| 556 |
+
|
| 557 |
+
We believe we have the right ingredients in place to deliver fun for our players and success for
|
| 558 |
+
|
| 559 |
+
our business, and I look forward to reporting our progress to you next quarter.
|
| 560 |
+
|
| 561 |
+
Now, I’ll turn the call back to Andrew.
|
| 562 |
+
|
| 563 |
+
ANDREW CLOSING:
|
| 564 |
+
|
| 565 |
+
Thanks, Blake.
|
| 566 |
+
|
| 567 |
+
The world loves to play games. As the global gaming audience continues to grow and spend
|
| 568 |
+
|
| 569 |
+
more time with the games they love, interactive entertainment is an increasingly important part
|
| 570 |
+
|
| 571 |
+
of our daily lives. At the heart of this is social connection – the unique ability that games have to
|
| 572 |
+
|
| 573 |
+
connect and inspire players to be part of a shared experience. New platforms, new
|
| 574 |
+
|
| 575 |
+
technologies and new ways to engage will continue to fuel growth for the industry, and through
|
| 576 |
+
|
| 577 |
+
these opportunities we are positioning EA to lead.
|
| 578 |
+
|
| 579 |
+
It begins with great games that can fulfill the motivations of a diverse global player base. We
|
| 580 |
+
|
| 581 |
+
continue to invest across our portfolio to deliver the depth, breadth and quality of experiences
|
| 582 |
+
|
| 583 |
+
that players seek. Our top titles across sports, simulation, shooters, and racing connect
|
| 584 |
+
|
| 585 |
+
11
|
| 586 |
+
|
| 587 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 588 |
+
|
| 589 |
+
FY20Q1
|
| 590 |
+
|
| 591 |
+
hundreds of millions of players on console, PC and mobile. We create experiences in some of
|
| 592 |
+
|
| 593 |
+
the most popular owned IP in the industry, including The Sims, Battlefield, Need for Speed and
|
| 594 |
+
|
| 595 |
+
Plants vs. Zombies. We’ve introduced powerful new IP like Apex Legends, and we’re building
|
| 596 |
+
|
| 597 |
+
new licensed experiences like Star Wars Jedi: Fallen Order. Our pipeline is full of innovative
|
| 598 |
+
|
| 599 |
+
new projects for our current franchises, new IP, and plans to revisit some of our fan-favorite
|
| 600 |
+
|
| 601 |
+
brands, as we continually work to bring more high-quality games to players across a growing
|
| 602 |
+
|
| 603 |
+
number of platforms and devices.
|
| 604 |
+
|
| 605 |
+
Live services enable us to build powerful communities, where players come together and
|
| 606 |
+
|
| 607 |
+
continue to share in the experiences they love. We’ve had great success building deeply-
|
| 608 |
+
|
| 609 |
+
engaged, long-term communities in Ultimate Team, The Sims, Battlefield, Star Wars and more –
|
| 610 |
+
|
| 611 |
+
and now we’re adding to that with our massive player base in Apex Legends. Each live service
|
| 612 |
+
|
| 613 |
+
is different, designed uniquely for the community it serves. They also enable us to continually
|
| 614 |
+
|
| 615 |
+
learn from our players – their feedback and their motivations – so we can drive more innovation
|
| 616 |
+
|
| 617 |
+
and creative exploration for the future.
|
| 618 |
+
|
| 619 |
+
Interactive entertainment today transcends the act of playing a game. New ways to engage like
|
| 620 |
+
|
| 621 |
+
esports are becoming just as important. With FIFA and Madden, we have the largest esports
|
| 622 |
+
|
| 623 |
+
ecosystems in sports games, and Apex Legends is going to be a major new addition to the
|
| 624 |
+
|
| 625 |
+
global competitive gaming scene this year. We believe that our games can make competition
|
| 626 |
+
|
| 627 |
+
accessible to anyone. We see opportunities to bring competitive play to more of our franchises,
|
| 628 |
+
|
| 629 |
+
and we look forward to delivering for more players, viewers, sponsors and broadcasters around
|
| 630 |
+
|
| 631 |
+
the world.
|
| 632 |
+
|
| 633 |
+
With games becoming an increasingly important part of our lives, subscriptions offer a
|
| 634 |
+
|
| 635 |
+
compelling new value proposition for players. Other industries have demonstrated how
|
| 636 |
+
|
| 637 |
+
12
|
| 638 |
+
|
| 639 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 640 |
+
|
| 641 |
+
FY20Q1
|
| 642 |
+
|
| 643 |
+
subscriptions fundamentally shift consumer behavior. We consume more television content in
|
| 644 |
+
|
| 645 |
+
different ways because of video subscriptions. We consume more music in different ways
|
| 646 |
+
|
| 647 |
+
because of music subscription services. We believe the same is happening with games, where
|
| 648 |
+
|
| 649 |
+
subscriptions can offer access to great content, at great value, with tremendously low
|
| 650 |
+
|
| 651 |
+
friction. When combined with cloud streaming, the barriers are lowered even further, making it
|
| 652 |
+
|
| 653 |
+
even more compelling to jump into new games and connect with new communities. The
|
| 654 |
+
|
| 655 |
+
subscription opportunity is powerful for both players and game creators, and we’re continuing to
|
| 656 |
+
|
| 657 |
+
invest in our leading services on console and PC.
|
| 658 |
+
|
| 659 |
+
In addition to more great games, passionate global communities, and new ways to engage,
|
| 660 |
+
|
| 661 |
+
there will be more transformative shifts on the horizon. The constant push of progress and
|
| 662 |
+
|
| 663 |
+
innovation is what sets this industry apart from every other form of entertainment. With our
|
| 664 |
+
|
| 665 |
+
teams of incredibly talented developers, artists and engineers, we are working to drive creativity,
|
| 666 |
+
|
| 667 |
+
quality and fun through every aspect of the player experience, now and in the future. We look
|
| 668 |
+
|
| 669 |
+
forward to sharing more updates in the months to come.
|
| 670 |
+
|
| 671 |
+
Now Blake and I are here for your questions.
|
| 672 |
+
|
| 673 |
+
Forward-Looking Statements
|
| 674 |
+
|
| 675 |
+
Some statements set forth in this document, including the information relating to EA’s fiscal
|
| 676 |
+
|
| 677 |
+
2020 guidance information and title slate contain forward-looking statements that are subject to
|
| 678 |
+
|
| 679 |
+
change. Statements including words such as “anticipate,” “believe,” “expect,” “intend,”
|
| 680 |
+
|
| 681 |
+
“estimate”, “plan”, “predict”, “seek”, “goal”, “will”, “may”, “likely”, “should”, “could” (and the
|
| 682 |
+
|
| 683 |
+
negative of any of these terms), “future” and similar expressions also identify forward-looking
|
| 684 |
+
|
| 685 |
+
13
|
| 686 |
+
|
| 687 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 688 |
+
|
| 689 |
+
FY20Q1
|
| 690 |
+
|
| 691 |
+
statements. These forward-looking statements are not guarantees of future performance and
|
| 692 |
+
|
| 693 |
+
reflect management’s current expectations. Our actual results could differ materially from those
|
| 694 |
+
|
| 695 |
+
discussed in the forward-looking statements.
|
| 696 |
+
|
| 697 |
+
Some of the factors which could cause the Company’s results to differ materially from its
|
| 698 |
+
|
| 699 |
+
expectations include the following: sales of the Company’s products and services; the
|
| 700 |
+
|
| 701 |
+
Company’s ability to develop and support digital products and services, including managing
|
| 702 |
+
|
| 703 |
+
online security and privacy; outages of our products, services and technological infrastructure;
|
| 704 |
+
|
| 705 |
+
the Company’s ability to manage expenses; the competition in the interactive entertainment
|
| 706 |
+
|
| 707 |
+
industry; governmental regulations; the effectiveness of the Company’s sales and marketing
|
| 708 |
+
|
| 709 |
+
programs; timely development and release of the Company’s products and services; the
|
| 710 |
+
|
| 711 |
+
Company’s ability to realize the anticipated benefits of acquisitions; the consumer demand for,
|
| 712 |
+
|
| 713 |
+
and the availability of an adequate supply of console hardware units; the Company’s ability to
|
| 714 |
+
|
| 715 |
+
predict consumer preferences among competing platforms; the Company’s ability to develop
|
| 716 |
+
|
| 717 |
+
and implement new technology; foreign currency exchange rate fluctuations; general economic
|
| 718 |
+
|
| 719 |
+
conditions; changes in our tax rates or tax laws; and other factors described in Part I, Item 1A of
|
| 720 |
+
|
| 721 |
+
Electronic Arts’ latest Annual Report on Form 10-K under the heading “Risk Factors”, as well as
|
| 722 |
+
|
| 723 |
+
in other documents we have filed with the Securities and Exchange Commission.
|
| 724 |
+
|
| 725 |
+
These forward-looking statements are current as of July 30, 2019. Electronic Arts assumes no
|
| 726 |
+
|
| 727 |
+
obligation to revise or update any forward-looking statement for any reason, except as required
|
| 728 |
+
|
| 729 |
+
by law. In addition, the preliminary financial results set forth in this release are estimates based
|
| 730 |
+
|
| 731 |
+
on information currently available to Electronic Arts.
|
| 732 |
+
|
| 733 |
+
While Electronic Arts believes these estimates are meaningful, they could differ from the actual
|
| 734 |
+
|
| 735 |
+
amounts that Electronic Arts ultimately reports in its Quarterly Report on Form 10-Q for the
|
| 736 |
+
|
| 737 |
+
14
|
| 738 |
+
|
| 739 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 740 |
+
|
| 741 |
+
FY20Q1
|
| 742 |
+
|
| 743 |
+
fiscal quarter ended June 30, 2019. Electronic Arts assumes no obligation and does not intend
|
| 744 |
+
|
| 745 |
+
to update these estimates prior to filing its Form 10-Q for the fiscal quarter ended June 30,
|
| 746 |
+
|
| 747 |
+
2019.
|
| 748 |
+
|
| 749 |
+
15
|
| 750 |
+
|
q136/random_k2/random_2.md
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q136/random_k4/question.json
CHANGED
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| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
"f1f5242528411b262be447e61e2eb10f.pdf",
|
| 20 |
-
"
|
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"
|
| 22 |
-
"
|
| 23 |
-
"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
|
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|
| 17 |
],
|
| 18 |
"original_filenames": [
|
| 19 |
"f1f5242528411b262be447e61e2eb10f.pdf",
|
| 20 |
+
"web_cb05559b91321f82.pdf",
|
| 21 |
+
"web_f77c9a6a0c40e754.pdf",
|
| 22 |
+
"resize_fb_1.pdf",
|
| 23 |
+
"web_5050add9b28048e4.pdf"
|
| 24 |
],
|
| 25 |
"modality": "markdown"
|
| 26 |
}
|
q136/random_k4/random_1.md
CHANGED
|
@@ -1,224 +1,750 @@
|
|
| 1 |
-
|
| 2 |
-
INTERNATIONAL VISITORS
|
| 3 |
|
| 4 |
-
|
| 5 |
|
| 6 |
-
|
| 7 |
|
| 8 |
-
|
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-
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|
| 18 |
-
|
| 19 |
|
| 20 |
-
|
| 21 |
|
| 22 |
-
|
| 23 |
-
review the official payment guidelines from the People's Bank of China:
|
| 24 |
|
| 25 |
-
|
| 26 |
|
| 27 |
-
|
| 28 |
|
| 29 |
-
|
| 30 |
|
| 31 |
-
|
| 32 |
-
international visitors may use UnionPay chip-enabled cards,
|
| 33 |
-
internationally issued Visa, Mastercard, and American Express chip-enabled cards to
|
| 34 |
-
take Chengdu Metro.
|
| 35 |
|
| 36 |
-
|
| 37 |
|
| 38 |
-
|
| 39 |
|
| 40 |
-
|
| 41 |
-
|
|
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|
| 42 |
|
| 43 |
1
|
| 44 |
|
| 45 |
-
|
|
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|
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|
|
|
|
|
|
|
|
|
| 46 |
|
| 47 |
-
|
| 48 |
-
directly through the app.
|
| 49 |
|
| 50 |
-
|
| 51 |
-
outlets at the airport).
|
| 52 |
|
| 53 |
-
|
| 54 |
|
| 55 |
-
|
| 56 |
|
| 57 |
-
|
| 58 |
-
(passport/visa, etc.).
|
| 59 |
|
| 60 |
-
|
| 61 |
|
| 62 |
-
|
| 63 |
-
quickly.
|
| 64 |
|
| 65 |
-
|
| 66 |
-
functions properly.
|
| 67 |
|
| 68 |
-
|
| 69 |
|
| 70 |
-
|
| 71 |
|
| 72 |
-
|
| 73 |
-
International Airport.
|
| 74 |
|
| 75 |
-
|
| 76 |
-
that connects 80%+ high-speed routes), Chengdu South Railway Station (regional
|
| 77 |
-
services that link to Leshan City, Mianyang City, Yibin City...), and Chengdu West
|
| 78 |
-
Railway Station (serves western routes, e.g., Pujiang, Dujiangyan).
|
| 79 |
|
| 80 |
-
|
| 81 |
-
|
|
|
|
| 82 |
|
| 83 |
2
|
| 84 |
|
| 85 |
-
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transportation to other destinations, please check the official airport shuttle schedule upon
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complies with the rules below:
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scanning “Transport → Select Chengdu Bus”
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Chengdu:
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regulations.
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|
| 1 |
+
PREPARED REMARKS
|
|
|
|
| 2 |
|
| 3 |
+
Q1 FISCAL 2020
|
| 4 |
|
| 5 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 6 |
|
| 7 |
+
FY20Q1
|
| 8 |
|
| 9 |
+
CHRIS:
|
| 10 |
|
| 11 |
+
Thank you.
|
| 12 |
|
| 13 |
+
Welcome to EA’s first quarter fiscal 2020 earnings call. With me on the call today are Andrew
|
| 14 |
|
| 15 |
+
Wilson, our CEO, and Blake Jorgensen, our CFO and COO.
|
| 16 |
|
| 17 |
+
Please note that our SEC filings and our earnings release are available at ir.ea.com. In addition,
|
| 18 |
|
| 19 |
+
we have posted earnings slides to accompany our prepared remarks. Lastly, after the call, we
|
| 20 |
|
| 21 |
+
will post our prepared remarks, an audio replay of this call, our financial model, a transcript, and
|
|
|
|
| 22 |
|
| 23 |
+
an updated accounting FAQ.
|
| 24 |
|
| 25 |
+
With regards to our calendar: our annual shareholder meeting will take place on Thursday,
|
| 26 |
|
| 27 |
+
August 8, here in Redwood Shores; and our Q2 fiscal 2020 earnings call is scheduled for
|
| 28 |
|
| 29 |
+
Tuesday, October 29.
|
|
|
|
|
|
|
|
|
|
| 30 |
|
| 31 |
+
This presentation and our comments include forward-looking statements regarding future events
|
| 32 |
|
| 33 |
+
and the future financial performance of the Company. Actual events and results may differ
|
| 34 |
|
| 35 |
+
materially from our expectations. We refer you to our most recent Form 10-K for a discussion of
|
| 36 |
+
|
| 37 |
+
risks that could cause actual results to differ materially from those discussed today. Electronic
|
| 38 |
+
|
| 39 |
+
Arts makes these statements as of today, July 30, 2019, and disclaims any duty to update
|
| 40 |
+
|
| 41 |
+
them.
|
| 42 |
+
|
| 43 |
+
During this call, the financial metrics, with the exception of free cash flow, will be presented on a
|
| 44 |
+
|
| 45 |
+
GAAP basis. All comparisons made in the course of this call are against the same period in the
|
| 46 |
+
|
| 47 |
+
prior year unless otherwise stated.
|
| 48 |
+
|
| 49 |
+
Now, I’ll turn the call over to Andrew.
|
| 50 |
|
| 51 |
1
|
| 52 |
|
| 53 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 54 |
+
|
| 55 |
+
FY20Q1
|
| 56 |
+
|
| 57 |
+
ANDREW:
|
| 58 |
+
|
| 59 |
+
Thanks, Chris.
|
| 60 |
+
|
| 61 |
+
We delivered a strong start to FY20. Players were deeply engaged in our top franchises, with
|
| 62 |
+
|
| 63 |
+
growing communities reaching new peaks of engagement fueled by new content and in-game
|
| 64 |
+
|
| 65 |
+
events in our live services. As a result, our operating results significantly exceeded our
|
| 66 |
+
|
| 67 |
+
expectations for the first quarter. We’re thrilled by the great experiences that players are having
|
| 68 |
+
|
| 69 |
+
in our games, and we’re looking forward to delivering a lot more throughout the fiscal year.
|
| 70 |
+
|
| 71 |
+
Interactive entertainment continues to grow. An expanding global player base, new platforms,
|
| 72 |
+
|
| 73 |
+
new business models and more ways to play and watch are fueling tailwinds for the
|
| 74 |
+
|
| 75 |
+
industry. With this backdrop, the core drivers of growth for EA are: the depth and breadth of our
|
| 76 |
|
| 77 |
+
portfolio and IP; our expertise in live services; our leadership in subscriptions; and competitive
|
|
|
|
| 78 |
|
| 79 |
+
gaming that expands our reach and drives deeper engagement. We’re also continually
|
|
|
|
| 80 |
|
| 81 |
+
strengthening our foundation of great talent and technology. I’ll touch on some of these drivers
|
| 82 |
|
| 83 |
+
with a few highlights here.
|
| 84 |
|
| 85 |
+
Let’s start with Apex Legends. We have a massive global audience continuing to engage in this
|
|
|
|
| 86 |
|
| 87 |
+
high-quality, free-to-play experience. Apex has tremendous gameplay at its core, and we’ve
|
| 88 |
|
| 89 |
+
built it to have longevity as a live service that will continue to drive engagement over time. In
|
|
|
|
| 90 |
|
| 91 |
+
our live service, we’re delivering Seasons of new content – a collection of new content and
|
|
|
|
| 92 |
|
| 93 |
+
updates that begin to roll out at the start of each season, and continue throughout the course of
|
| 94 |
|
| 95 |
+
several weeks and months. We launched Season 2 in early July, including a robust Battle Pass
|
| 96 |
|
| 97 |
+
offering, a new character, and additions to the environment – and to date, it has outperformed
|
|
|
|
| 98 |
|
| 99 |
+
our expectations with significant growth in daily and weekly active players. In each season,
|
|
|
|
|
|
|
|
|
|
| 100 |
|
| 101 |
+
there are in-game events that are additional drivers of engagement – such as the event coming
|
| 102 |
+
|
| 103 |
+
in the next few weeks that will bring new content and deliver one of the most fan-requested
|
| 104 |
|
| 105 |
2
|
| 106 |
|
| 107 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 108 |
+
|
| 109 |
+
FY20Q1
|
| 110 |
+
|
| 111 |
+
features since the launch of Apex. There will be more updates and in-game experiences in the
|
| 112 |
+
|
| 113 |
+
weeks to come for Season 2, and Season 3 is shaping up to be even bigger. All of these
|
| 114 |
+
|
| 115 |
+
elements – the fantastic core gameplay, Seasons of new content, and additional in-game events
|
| 116 |
+
|
| 117 |
+
– are designed to continually excite and engage the Apex community over the long-term.
|
| 118 |
+
|
| 119 |
+
We’re also expanding into additional growth opportunities for Apex Legends. Esports will bring
|
| 120 |
+
|
| 121 |
+
new drivers of social interaction and competition to the Apex ecosystem. Interest from teams,
|
| 122 |
+
|
| 123 |
+
broadcast partners and sponsors is strong, and we’ve had great success with our first exhibition
|
| 124 |
+
|
| 125 |
+
events, including a competition at the ESPYS that was broadcast on ESPN and ABC. We’ll
|
| 126 |
+
|
| 127 |
+
have 80 teams from around the world participating in our first official competition in September.
|
| 128 |
+
|
| 129 |
+
Our plans to bring Apex Legends to China and a worldwide mobile launch are also on course,
|
| 130 |
+
|
| 131 |
+
and we will share more on our plans in the future.
|
| 132 |
+
|
| 133 |
+
In our EA SPORTS portfolio, our franchises like Madden NFL and FIFA are delivering for core
|
| 134 |
+
|
| 135 |
+
fans, innovating to reach new players, and leading our growth in esports. Looking first at
|
| 136 |
+
|
| 137 |
+
Madden NFL, we continue to see deep year-round engagement in the franchise. Live service
|
| 138 |
+
|
| 139 |
+
events and tie-in content with the NFL Draft drove growth in new players joining Madden NFL
|
| 140 |
|
| 141 |
+
19 in Q1, and also deepened engagement in Madden Ultimate Team. We’re now just days
|
|
|
|
| 142 |
|
| 143 |
+
away from launching Madden NFL 20. The innovations in this year’s game, like the new
|
| 144 |
|
| 145 |
+
superstar X-Factor abilities, new personalized Career Campaign, and the more fluid core
|
| 146 |
+
|
| 147 |
+
gameplay, are all designed to appeal to new and existing football fans. Madden NFL esports
|
| 148 |
+
|
| 149 |
+
also continues to drive growing viewership. Players in our Madden NFL competitive
|
| 150 |
+
|
| 151 |
+
ecosystem engaged four times more than non-competitors last season, and our events drove
|
| 152 |
+
|
| 153 |
+
record broadcast and digital viewership. We’re now looking to build on that success with the
|
| 154 |
+
|
| 155 |
+
Madden NFL 20 Championship Series. We’re partnered with all 32 NFL teams, our
|
| 156 |
+
|
| 157 |
+
competitions are aligned with key beats in the NFL season, and we’re welcoming major
|
| 158 |
|
| 159 |
3
|
| 160 |
|
| 161 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 162 |
+
|
| 163 |
+
FY20Q1
|
| 164 |
+
|
| 165 |
+
sponsors including Pizza Hut, Snickers and Starbucks. Finally, the latest season of our fan-
|
| 166 |
+
|
| 167 |
+
favorite Madden NFL Mobile game launches tomorrow, and this year the game is bringing back
|
| 168 |
+
|
| 169 |
+
some of the classic modes that fans love, as well as new innovation in social co-op play and
|
| 170 |
+
|
| 171 |
+
customization. Through great experiences on console and PC, the ever-popular Madden NFL
|
| 172 |
+
|
| 173 |
+
Mobile game, and our leading esports programming, Madden NFL continues to reach and
|
| 174 |
+
|
| 175 |
+
engage a wide audience of fans.
|
| 176 |
+
|
| 177 |
+
Our FIFA franchise had a very strong Q1, with players deeply engaged in our Ultimate Team
|
| 178 |
+
|
| 179 |
+
live service. Our biggest in-game event, Team of the Season, had more than 3 million players
|
| 180 |
+
|
| 181 |
+
logging into FUT daily to play – the highest daily levels we’ve ever seen for this event. Esports
|
| 182 |
+
|
| 183 |
+
for FIFA is exploding as well, with our competitive modes growing faster than any other mode in
|
| 184 |
+
|
| 185 |
+
FUT. Momentum is strong across our entire FIFA esports ecosystem, and next week’s FIFA
|
| 186 |
|
| 187 |
+
eWorld Cup Finals will be the culmination of a season that has engaged 17 official league
|
| 188 |
|
| 189 |
+
partners, players from 20 different nations, more than 30 live events, and more than 60 million
|
| 190 |
|
| 191 |
+
total views to date. Looking ahead to September, FIFA 20 is set to expand our FIFA platform
|
| 192 |
|
| 193 |
+
with a brand new dimension of the game for players who want more personalization,
|
| 194 |
|
| 195 |
+
customization and community. VOLTA Football brings a street soccer experience to the
|
| 196 |
|
| 197 |
+
franchise, where players can build their own characters, express themselves, and play different
|
| 198 |
|
| 199 |
+
forms of the sport in different environments around the world. That’s in addition to major
|
|
|
|
| 200 |
|
| 201 |
+
advancements in the core experience designed to deliver the most authentic football gameplay
|
| 202 |
|
| 203 |
+
we’ve ever produced. FIFA 20 will have an unmatched breadth of top leagues, teams and
|
| 204 |
|
| 205 |
+
players included in the game – a continuing differentiator of the authenticity in our FIFA
|
| 206 |
|
| 207 |
+
franchise. Our licensing program is built on the strength of multi-year relationships and careful
|
| 208 |
+
|
| 209 |
+
consideration of the most important players, teams and leagues that our fans love to see in the
|
| 210 |
+
|
| 211 |
+
game. From console to PC, to our FIFA Mobile games in the west and China, to our FIFA
|
| 212 |
+
|
| 213 |
+
Online offerings in Asia, FIFA continues to be the way that hundreds of millions of players
|
| 214 |
+
|
| 215 |
+
around the world come together in their shared passion for soccer.
|
| 216 |
|
| 217 |
4
|
| 218 |
|
| 219 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 220 |
+
|
| 221 |
+
FY20Q1
|
| 222 |
+
|
| 223 |
+
Our Sims 4 live service also continues to be a rich and rewarding experience for our players,
|
| 224 |
+
|
| 225 |
+
and a strong platform for growth. The Sims 4 continues to be one of the great owned IP
|
| 226 |
+
|
| 227 |
+
success stories of our portfolio, and we’re planning for FY20 to be our biggest year yet of new
|
| 228 |
+
|
| 229 |
+
content. Knowing that, we gave more fans a chance to get into the game through a one-week
|
| 230 |
+
|
| 231 |
+
promotion in May to download the base game for free. Almost 7 million players downloaded the
|
| 232 |
+
|
| 233 |
+
game during that time. In addition to the base game promotion, total expansion and game pack
|
| 234 |
+
|
| 235 |
+
downloads also increased 55% year-over-year in Q1. We launched our seventh expansion
|
| 236 |
+
|
| 237 |
+
pack – Island Living – in late June, and it has already become one of our best-selling packs for
|
| 238 |
+
|
| 239 |
+
The Sims 4. We are fortunate to have an incredibly vibrant and creative Sims community on
|
| 240 |
+
|
| 241 |
+
console, PC and mobile, and we are continuing to double down on this amazing franchise to
|
| 242 |
+
|
| 243 |
+
reach new players and open up exciting new dimensions of The Sims this year.
|
| 244 |
+
|
| 245 |
+
Subscription services are expanding across the industry, as well. We’re a pioneer and a leader
|
| 246 |
+
|
| 247 |
+
in this space, having just launched our subscription on a third major platform with EA Access on
|
| 248 |
+
|
| 249 |
+
the Sony PlayStation 4. We believe subscriptions can be transformative to the player
|
| 250 |
+
|
| 251 |
+
experience and the gaming industry over the long term, as they offer tremendous value and
|
| 252 |
+
|
| 253 |
+
choice to players, and greater flexibility in the games we bring to market. Our PC subscription
|
| 254 |
+
|
| 255 |
+
already includes more than 220 games, 140 of which are from third party developers. We’re
|
| 256 |
+
|
| 257 |
+
continually adding to this with new games from EA, from indie developers seeking to expand
|
| 258 |
+
|
| 259 |
+
their reach through our EA Originals program, and from other third-party partners ready to reach
|
| 260 |
+
|
| 261 |
+
more players through our services. We’re also working to expand our subscriptions to even
|
| 262 |
+
|
| 263 |
+
more platforms.
|
| 264 |
+
|
| 265 |
+
Mobile continues to be a growth opportunity for us. Live services are a key aspect of our mobile
|
| 266 |
+
|
| 267 |
+
business, with franchises like Madden Mobile, FIFA Mobile and The Sims continuing to drive
|
| 268 |
+
|
| 269 |
+
strong ongoing engagement. Star Wars Galaxy of Heroes has grown to nearly 80 million
|
| 270 |
+
|
| 271 |
+
players life-to-date. Galaxy of Heroes has the most deeply engaged community of all our
|
| 272 |
|
| 273 |
5
|
| 274 |
|
| 275 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 276 |
+
|
| 277 |
+
FY20Q1
|
| 278 |
+
|
| 279 |
+
mobile games, and we plan to continue delivering great new content and in-game events to
|
| 280 |
+
|
| 281 |
+
grow the audience this year. We’ve also just started pre-alpha testing for Plants vs. Zombies 3.
|
| 282 |
+
|
| 283 |
+
In a market where discovery and acquisition can be challenging, Plants vs. Zombies is one of
|
| 284 |
+
|
| 285 |
+
the most beloved brands in gaming. To date, we’ve had more than a billion downloads
|
| 286 |
|
| 287 |
+
worldwide of PvZ games on mobile, and we’re looking forward to bringing something new to
|
| 288 |
|
| 289 |
+
fans around the world. We’re continuing to prototype and develop more bespoke mobile
|
| 290 |
|
| 291 |
+
projects, as well as new concepts for cross-platform play. The mobile space is complex and
|
| 292 |
|
| 293 |
+
competitive, and our focus is on bringing more innovation and unique new experiences to
|
| 294 |
|
| 295 |
+
mobile players.
|
| 296 |
|
| 297 |
+
In addition to the franchises and live services that I’ve already mentioned, we’ll be delivering
|
| 298 |
|
| 299 |
+
many other new experiences to players throughout the remainder of this fiscal year. NHL 20 is
|
| 300 |
|
| 301 |
+
launching in Q2, with hundreds of gameplay advancements, as well as new competitive and
|
| 302 |
|
| 303 |
+
multiplayer modes. We’ll take the wraps off our new Need for Speed game heading into
|
|
|
|
|
|
|
| 304 |
|
| 305 |
+
Gamescom in a few weeks. We have a Plants vs. Zombies shooter title coming to console and
|
| 306 |
|
| 307 |
+
PC later this year. And the excitement and anticipation for Star Wars Jedi: Fallen Order has
|
| 308 |
|
| 309 |
+
been strong coming out of EA PLAY and E3, where the game received 45 award nominations
|
| 310 |
|
| 311 |
+
and great buzz from the player community. Respawn’s track record speaks for the high-quality
|
|
|
|
| 312 |
|
| 313 |
+
games they develop, and they have created a brand new Star Wars story that will be a lot of fun
|
| 314 |
|
| 315 |
+
to play when it launches this holiday.
|
| 316 |
+
|
| 317 |
+
From the core game to live services that extend and enhance the experience, to new ways to
|
| 318 |
+
|
| 319 |
+
engage through subscriptions and competitive gaming, our focus continues to be on strong
|
| 320 |
+
|
| 321 |
+
execution and delivering innovation, quality and fun for players at every turn. We’re fortunate to
|
| 322 |
+
|
| 323 |
+
have some of the greatest and most creative talent in the industry, driving our efforts to
|
| 324 |
+
|
| 325 |
+
continually learn and improve. With robust, best-in-class technology powering our efforts, we’re
|
| 326 |
+
|
| 327 |
+
also in position to scale and evolve with the changing needs of our players.
|
| 328 |
|
| 329 |
6
|
| 330 |
|
| 331 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 332 |
+
|
| 333 |
+
FY20Q1
|
| 334 |
+
|
| 335 |
+
Now I’ll hand the call over to Blake.
|
| 336 |
+
|
| 337 |
+
BLAKE:
|
| 338 |
|
| 339 |
+
Thanks, Andrew.
|
| 340 |
|
| 341 |
+
We delivered operating results significantly above our expectations this quarter. At a high level,
|
| 342 |
|
| 343 |
+
those results were driven by broad strength across our core franchises. Apex Legends
|
| 344 |
|
| 345 |
+
continues to delight players and we are pleased with the impact of Season 2 since its launch on
|
|
|
|
| 346 |
|
| 347 |
+
July 2. This quarter’s results demonstrate how the power of our portfolio strategy, combined
|
| 348 |
|
| 349 |
+
with extra content, delivers strong results - even in relatively quiet quarters.
|
| 350 |
|
| 351 |
+
I’ll report the specifics of our results on a GAAP basis, then use our operational measure of net
|
| 352 |
|
| 353 |
+
bookings to discuss the dynamics of our business. To compare this quarter’s results to
|
| 354 |
|
| 355 |
+
historically-reported non-GAAP measures, please refer to the relevant tabs in our downloadable
|
|
|
|
| 356 |
|
| 357 |
+
financial model.
|
| 358 |
|
| 359 |
+
EA’s net revenue was $1.21 billion, compared to $1.14 billion a year ago, and above our
|
| 360 |
|
| 361 |
+
guidance by $79 million. Operating expenses were $607 million, compared to $622 million a
|
| 362 |
|
| 363 |
+
year ago, primarily driven by lower sales and marketing partially offset by continued investment
|
| 364 |
+
|
| 365 |
+
in new IP. This was significantly below our forecast, driven by timing of advertising
|
| 366 |
+
|
| 367 |
+
spend. Operating income was $415 million, compared to $300 million a year ago and above
|
| 368 |
+
|
| 369 |
+
our expectations. Diluted earnings per share was $4.75, up over 400% year on
|
| 370 |
+
|
| 371 |
+
year. Underlying EPS was well above our expectations, driven by net bookings, gross profit and
|
| 372 |
+
|
| 373 |
+
operating expenses.
|
| 374 |
+
|
| 375 |
+
Operating cash flow for the quarter was $158 million, up $38 million from last year. Capital
|
| 376 |
+
|
| 377 |
+
expenditures for the quarter were $45 million, resulting in a free cash flow of
|
| 378 |
|
| 379 |
7
|
| 380 |
|
| 381 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 382 |
+
|
| 383 |
+
FY20Q1
|
| 384 |
|
| 385 |
+
$113 million. Operating cash flow for the last twelve months was $1.59 billion. See our
|
| 386 |
|
| 387 |
+
earnings slides for further cash flow information.
|
| 388 |
|
| 389 |
+
During the quarter, we also repurchased 3.2 million shares at a cost of $305 million, leaving
|
| 390 |
|
| 391 |
+
$979 million available in our buyback program.
|
| 392 |
|
| 393 |
+
Our cash and short-term investments at the end of the quarter were $5.19 billion, up 4% year
|
|
|
|
| 394 |
|
| 395 |
+
on year.
|
|
|
|
| 396 |
|
| 397 |
+
Now, I’d like to turn to the key drivers of our business this quarter.
|
| 398 |
|
| 399 |
+
Net bookings for the quarter were $743 million, approximately flat year on year. It was
|
| 400 |
|
| 401 |
+
$53 million above our guidance, driven by strength across the board, with strong performance
|
| 402 |
+
|
| 403 |
+
from our core franchises and live services.
|
| 404 |
+
|
| 405 |
+
Digital net bookings were $701 million, up $8 million on the year-ago period. On a trailing
|
| 406 |
+
|
| 407 |
+
twelve-month basis, digital net bookings now represent 76% of our business, compared to 69%
|
| 408 |
+
|
| 409 |
+
a year ago.
|
| 410 |
+
|
| 411 |
+
Looking at each of the components of this quarter’s digital bookings in turn:
|
| 412 |
+
|
| 413 |
+
• Live services net bookings were up 12% year on year, to $504 million, led by Apex
|
| 414 |
+
|
| 415 |
+
Legends and The Sims 4. FIFA Ultimate Team was up 11% year on year at constant
|
| 416 |
+
|
| 417 |
+
currency, 5% at actual exchange rates.
|
| 418 |
+
|
| 419 |
+
Diving into the details: Season 2 launched for Apex Legends at the beginning of Q2, and
|
| 420 |
+
|
| 421 |
+
we’re pleased with its performance, with regards to both sales and engagement. We will
|
| 422 |
+
|
| 423 |
+
continue to add content during the quarter, with a major event in mid-August, and Season 3
|
| 424 |
+
|
| 425 |
+
will begin next quarter. We are increasing investment in content development and
|
| 426 |
+
|
| 427 |
+
marketing to continue to drive growth in Apex Legends.
|
| 428 |
|
| 429 |
8
|
| 430 |
|
| 431 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 432 |
+
|
| 433 |
+
FY20Q1
|
| 434 |
+
|
| 435 |
+
FIFA Online outperformed our expectations. FIFA Online 4 performed well in Korea, where
|
| 436 |
+
|
| 437 |
+
we have fully transitioned from FIFA Online 3 to FIFA Online 4. Meanwhile, FIFA Online 3
|
| 438 |
+
|
| 439 |
+
outperformed our expectations in China, and we are positioned well for switching over to
|
| 440 |
+
|
| 441 |
+
FIFA Online 4.
|
| 442 |
+
|
| 443 |
+
Finally, as Andrew mentioned, The Sims 4 base game promotion delivered nearly 7 million
|
| 444 |
+
|
| 445 |
+
new installs and we remain on track to have the fifth consecutive year of growth in
|
| 446 |
+
|
| 447 |
+
The Sims 4, following its launch in 2014.
|
| 448 |
+
|
| 449 |
+
• Mobile delivered net bookings of $122 million, down 17% year on year, driven by aging
|
| 450 |
+
|
| 451 |
+
titles. Although down year on year, Star Wars Galaxy of Heroes outperformed our
|
| 452 |
+
|
| 453 |
+
expectations and maintains a highly engaged user base, leading us to be optimistic about
|
| 454 |
+
|
| 455 |
+
performance in a huge year for Star Wars, with new TV show, movie and theme park
|
| 456 |
+
|
| 457 |
+
launches.
|
| 458 |
+
|
| 459 |
+
• Full game PC and console downloads generated net bookings of $75 million, down 22%
|
| 460 |
+
|
| 461 |
+
year on year, due to last year’s launch of A Way Out and FIFA 18 World Cup
|
| 462 |
+
|
| 463 |
+
promotions. 47% of our unit sales are now digital rather than physical, measured on Xbox
|
| 464 |
+
|
| 465 |
+
One and PlayStation 4 over the last twelve months. Although this is up 7 percentage points
|
| 466 |
+
|
| 467 |
+
year on year, we continue to model an annual shift of 5 percentage points, given how
|
| 468 |
+
|
| 469 |
+
strongly digital Anthem was at its launch last quarter.
|
| 470 |
+
|
| 471 |
+
Before discussing guidance, I would like to highlight that there were three income tax events
|
| 472 |
+
|
| 473 |
+
in the quarter that impacted our GAAP Q1 results and our full year GAAP guidance. Please
|
| 474 |
+
|
| 475 |
+
refer to our press release for the details. As a result, we expect to recognize a $1.700 billion
|
| 476 |
+
|
| 477 |
+
benefit in the fiscal year, which is $200 million better than we had included in our guidance last
|
| 478 |
+
|
| 479 |
+
quarter, although the phasing of the benefit between Q1 and Q2 has changed since we gave
|
| 480 |
+
|
| 481 |
+
that guidance. $1.080 billion of this amount was recognized in the first quarter and the
|
| 482 |
+
|
| 483 |
+
9
|
| 484 |
+
|
| 485 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 486 |
+
|
| 487 |
+
FY20Q1
|
| 488 |
+
|
| 489 |
+
remaining $620 million will be recognized when the Swiss tax rates change, which we expect to
|
| 490 |
+
|
| 491 |
+
occur in the second quarter. We do not expect the above events to impact our FY20 operating
|
| 492 |
+
|
| 493 |
+
cash flow or our management tax rate for fiscal 2020.
|
| 494 |
+
|
| 495 |
+
Now, turning to guidance: Except for the increase in our tax benefit of $200 million or $0.66
|
| 496 |
+
|
| 497 |
+
on GAAP EPS, we are reiterating our guidance for the full year.
|
| 498 |
+
|
| 499 |
+
We continue to expect The Sims 4 and Apex Legends to each deliver net bookings in the
|
| 500 |
+
|
| 501 |
+
$300 million to $400 million range.
|
| 502 |
+
|
| 503 |
+
We are holding our operating cash flow guidance at approximately $1.575 billion, with capex
|
| 504 |
+
|
| 505 |
+
still expected to be $125 million and free cash flow of about $1.45 billion.
|
| 506 |
+
|
| 507 |
+
For the second quarter, we continue to expect net revenue of $1.315 billion, cost of revenue
|
| 508 |
+
|
| 509 |
+
to be $407 million, and operating expenses of $679 million. This results in earnings per
|
| 510 |
+
|
| 511 |
+
share of $2.60 for the second quarter.
|
| 512 |
+
|
| 513 |
+
We anticipate net bookings for the quarter to be $1.23 billion. We’re excited about the Madden
|
| 514 |
+
|
| 515 |
+
NFL launch and upcoming Apex Legends event, and the launch of FIFA 20 with VOLTA
|
| 516 |
+
|
| 517 |
+
Football at the end of the quarter.
|
| 518 |
+
|
| 519 |
+
We over delivered this quarter as a result of the performance of our core franchises. These
|
| 520 |
+
|
| 521 |
+
evergreen live services provide a tremendously solid base for our business and enable us to
|
| 522 |
+
|
| 523 |
+
invest in new opportunities, to innovate and to take risks. We are unique among our peers in
|
| 524 |
+
|
| 525 |
+
this, and it is no coincidence that we are a leader in cloud gaming, subscriptions and in the
|
| 526 |
+
|
| 527 |
+
strength of our player networks.
|
| 528 |
+
|
| 529 |
+
People will only engage with our games if they have fun playing them. And we continue to
|
| 530 |
+
|
| 531 |
+
invest in keeping them fun – whether it’s the major innovation of VOLTA Football in FIFA, or
|
| 532 |
+
|
| 533 |
+
new modes, events and legends in Apex Legends, or even adding laundry to The Sims 4, we
|
| 534 |
+
|
| 535 |
+
10
|
| 536 |
+
|
| 537 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 538 |
+
|
| 539 |
+
FY20Q1
|
| 540 |
+
|
| 541 |
+
aim to give players content they want to play. If we’re successful in that, we’re successful as a
|
| 542 |
+
|
| 543 |
+
business.
|
| 544 |
+
|
| 545 |
+
This combination of core plus innovation plus fun will drive our success through the
|
| 546 |
+
|
| 547 |
+
year. Coming up in August we have more live services for our newest franchise, Apex
|
| 548 |
+
|
| 549 |
+
Legends, and the latest installment in one of our most storied, Madden NFL. FIFA 20 launches
|
| 550 |
+
|
| 551 |
+
right at the end of the quarter. The following quarter we have a new IP, Star Wars Jedi: Fallen
|
| 552 |
+
|
| 553 |
+
Order. Simultaneously, we continue to invest in more new IP, new technologies and new
|
| 554 |
+
|
| 555 |
+
business models.
|
| 556 |
+
|
| 557 |
+
We believe we have the right ingredients in place to deliver fun for our players and success for
|
| 558 |
+
|
| 559 |
+
our business, and I look forward to reporting our progress to you next quarter.
|
| 560 |
+
|
| 561 |
+
Now, I’ll turn the call back to Andrew.
|
| 562 |
+
|
| 563 |
+
ANDREW CLOSING:
|
| 564 |
+
|
| 565 |
+
Thanks, Blake.
|
| 566 |
+
|
| 567 |
+
The world loves to play games. As the global gaming audience continues to grow and spend
|
| 568 |
+
|
| 569 |
+
more time with the games they love, interactive entertainment is an increasingly important part
|
| 570 |
+
|
| 571 |
+
of our daily lives. At the heart of this is social connection – the unique ability that games have to
|
| 572 |
+
|
| 573 |
+
connect and inspire players to be part of a shared experience. New platforms, new
|
| 574 |
+
|
| 575 |
+
technologies and new ways to engage will continue to fuel growth for the industry, and through
|
| 576 |
+
|
| 577 |
+
these opportunities we are positioning EA to lead.
|
| 578 |
+
|
| 579 |
+
It begins with great games that can fulfill the motivations of a diverse global player base. We
|
| 580 |
+
|
| 581 |
+
continue to invest across our portfolio to deliver the depth, breadth and quality of experiences
|
| 582 |
+
|
| 583 |
+
that players seek. Our top titles across sports, simulation, shooters, and racing connect
|
| 584 |
+
|
| 585 |
+
11
|
| 586 |
+
|
| 587 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 588 |
+
|
| 589 |
+
FY20Q1
|
| 590 |
+
|
| 591 |
+
hundreds of millions of players on console, PC and mobile. We create experiences in some of
|
| 592 |
+
|
| 593 |
+
the most popular owned IP in the industry, including The Sims, Battlefield, Need for Speed and
|
| 594 |
+
|
| 595 |
+
Plants vs. Zombies. We’ve introduced powerful new IP like Apex Legends, and we’re building
|
| 596 |
+
|
| 597 |
+
new licensed experiences like Star Wars Jedi: Fallen Order. Our pipeline is full of innovative
|
| 598 |
+
|
| 599 |
+
new projects for our current franchises, new IP, and plans to revisit some of our fan-favorite
|
| 600 |
+
|
| 601 |
+
brands, as we continually work to bring more high-quality games to players across a growing
|
| 602 |
+
|
| 603 |
+
number of platforms and devices.
|
| 604 |
+
|
| 605 |
+
Live services enable us to build powerful communities, where players come together and
|
| 606 |
+
|
| 607 |
+
continue to share in the experiences they love. We’ve had great success building deeply-
|
| 608 |
+
|
| 609 |
+
engaged, long-term communities in Ultimate Team, The Sims, Battlefield, Star Wars and more –
|
| 610 |
+
|
| 611 |
+
and now we’re adding to that with our massive player base in Apex Legends. Each live service
|
| 612 |
+
|
| 613 |
+
is different, designed uniquely for the community it serves. They also enable us to continually
|
| 614 |
+
|
| 615 |
+
learn from our players – their feedback and their motivations – so we can drive more innovation
|
| 616 |
+
|
| 617 |
+
and creative exploration for the future.
|
| 618 |
+
|
| 619 |
+
Interactive entertainment today transcends the act of playing a game. New ways to engage like
|
| 620 |
+
|
| 621 |
+
esports are becoming just as important. With FIFA and Madden, we have the largest esports
|
| 622 |
+
|
| 623 |
+
ecosystems in sports games, and Apex Legends is going to be a major new addition to the
|
| 624 |
+
|
| 625 |
+
global competitive gaming scene this year. We believe that our games can make competition
|
| 626 |
+
|
| 627 |
+
accessible to anyone. We see opportunities to bring competitive play to more of our franchises,
|
| 628 |
+
|
| 629 |
+
and we look forward to delivering for more players, viewers, sponsors and broadcasters around
|
| 630 |
+
|
| 631 |
+
the world.
|
| 632 |
+
|
| 633 |
+
With games becoming an increasingly important part of our lives, subscriptions offer a
|
| 634 |
+
|
| 635 |
+
compelling new value proposition for players. Other industries have demonstrated how
|
| 636 |
+
|
| 637 |
+
12
|
| 638 |
+
|
| 639 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 640 |
+
|
| 641 |
+
FY20Q1
|
| 642 |
+
|
| 643 |
+
subscriptions fundamentally shift consumer behavior. We consume more television content in
|
| 644 |
+
|
| 645 |
+
different ways because of video subscriptions. We consume more music in different ways
|
| 646 |
+
|
| 647 |
+
because of music subscription services. We believe the same is happening with games, where
|
| 648 |
+
|
| 649 |
+
subscriptions can offer access to great content, at great value, with tremendously low
|
| 650 |
+
|
| 651 |
+
friction. When combined with cloud streaming, the barriers are lowered even further, making it
|
| 652 |
+
|
| 653 |
+
even more compelling to jump into new games and connect with new communities. The
|
| 654 |
+
|
| 655 |
+
subscription opportunity is powerful for both players and game creators, and we’re continuing to
|
| 656 |
+
|
| 657 |
+
invest in our leading services on console and PC.
|
| 658 |
+
|
| 659 |
+
In addition to more great games, passionate global communities, and new ways to engage,
|
| 660 |
+
|
| 661 |
+
there will be more transformative shifts on the horizon. The constant push of progress and
|
| 662 |
+
|
| 663 |
+
innovation is what sets this industry apart from every other form of entertainment. With our
|
| 664 |
+
|
| 665 |
+
teams of incredibly talented developers, artists and engineers, we are working to drive creativity,
|
| 666 |
+
|
| 667 |
+
quality and fun through every aspect of the player experience, now and in the future. We look
|
| 668 |
+
|
| 669 |
+
forward to sharing more updates in the months to come.
|
| 670 |
+
|
| 671 |
+
Now Blake and I are here for your questions.
|
| 672 |
+
|
| 673 |
+
Forward-Looking Statements
|
| 674 |
+
|
| 675 |
+
Some statements set forth in this document, including the information relating to EA’s fiscal
|
| 676 |
+
|
| 677 |
+
2020 guidance information and title slate contain forward-looking statements that are subject to
|
| 678 |
+
|
| 679 |
+
change. Statements including words such as “anticipate,” “believe,” “expect,” “intend,”
|
| 680 |
+
|
| 681 |
+
“estimate”, “plan”, “predict”, “seek”, “goal”, “will”, “may”, “likely”, “should”, “could” (and the
|
| 682 |
+
|
| 683 |
+
negative of any of these terms), “future” and similar expressions also identify forward-looking
|
| 684 |
+
|
| 685 |
+
13
|
| 686 |
+
|
| 687 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 688 |
+
|
| 689 |
+
FY20Q1
|
| 690 |
+
|
| 691 |
+
statements. These forward-looking statements are not guarantees of future performance and
|
| 692 |
+
|
| 693 |
+
reflect management’s current expectations. Our actual results could differ materially from those
|
| 694 |
+
|
| 695 |
+
discussed in the forward-looking statements.
|
| 696 |
+
|
| 697 |
+
Some of the factors which could cause the Company’s results to differ materially from its
|
| 698 |
+
|
| 699 |
+
expectations include the following: sales of the Company’s products and services; the
|
| 700 |
+
|
| 701 |
+
Company’s ability to develop and support digital products and services, including managing
|
| 702 |
+
|
| 703 |
+
online security and privacy; outages of our products, services and technological infrastructure;
|
| 704 |
+
|
| 705 |
+
the Company’s ability to manage expenses; the competition in the interactive entertainment
|
| 706 |
+
|
| 707 |
+
industry; governmental regulations; the effectiveness of the Company’s sales and marketing
|
| 708 |
+
|
| 709 |
+
programs; timely development and release of the Company’s products and services; the
|
| 710 |
+
|
| 711 |
+
Company’s ability to realize the anticipated benefits of acquisitions; the consumer demand for,
|
| 712 |
+
|
| 713 |
+
and the availability of an adequate supply of console hardware units; the Company’s ability to
|
| 714 |
+
|
| 715 |
+
predict consumer preferences among competing platforms; the Company’s ability to develop
|
| 716 |
+
|
| 717 |
+
and implement new technology; foreign currency exchange rate fluctuations; general economic
|
| 718 |
+
|
| 719 |
+
conditions; changes in our tax rates or tax laws; and other factors described in Part I, Item 1A of
|
| 720 |
+
|
| 721 |
+
Electronic Arts’ latest Annual Report on Form 10-K under the heading “Risk Factors”, as well as
|
| 722 |
+
|
| 723 |
+
in other documents we have filed with the Securities and Exchange Commission.
|
| 724 |
+
|
| 725 |
+
These forward-looking statements are current as of July 30, 2019. Electronic Arts assumes no
|
| 726 |
+
|
| 727 |
+
obligation to revise or update any forward-looking statement for any reason, except as required
|
| 728 |
+
|
| 729 |
+
by law. In addition, the preliminary financial results set forth in this release are estimates based
|
| 730 |
+
|
| 731 |
+
on information currently available to Electronic Arts.
|
| 732 |
+
|
| 733 |
+
While Electronic Arts believes these estimates are meaningful, they could differ from the actual
|
| 734 |
+
|
| 735 |
+
amounts that Electronic Arts ultimately reports in its Quarterly Report on Form 10-Q for the
|
| 736 |
+
|
| 737 |
+
14
|
| 738 |
+
|
| 739 |
+
ELECTRONIC ARTS PREPARED REMARKS
|
| 740 |
+
|
| 741 |
+
FY20Q1
|
| 742 |
+
|
| 743 |
+
fiscal quarter ended June 30, 2019. Electronic Arts assumes no obligation and does not intend
|
| 744 |
+
|
| 745 |
+
to update these estimates prior to filing its Form 10-Q for the fiscal quarter ended June 30,
|
| 746 |
+
|
| 747 |
+
2019.
|
| 748 |
+
|
| 749 |
+
15
|
| 750 |
+
|
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|
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| 155 |
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| 156 |
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consumer demand. Smartphones and tablets, the cornerstone of this market, are no longer
|
| 157 |
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simply communication tools; they've evolved into productivity powerhouses. Cutting-edge
|
| 158 |
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smart wearables, hearables, and clothing are redefining how humans connect with
|
| 159 |
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technology, offering health monitoring, augmented experiences, and seamless
|
| 160 |
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communication. The rise of 5G networks, advancements in artificial intelligence (AI), and the
|
| 161 |
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expanding Internet of Things (IoT) are accelerating the development of increasingly
|
| 162 |
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sophisticated mobile devices. This transformation is fueled by the desire for global
|
| 163 |
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connectivity, enhanced productivity, personalized experiences, and the adoption of cutting-
|
| 164 |
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edge technology. As mobile devices become increasingly integrated into daily life, a
|
| 165 |
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comprehensive understanding of this market landscape is crucial to support informed
|
| 166 |
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business decisions.
|
| 167 |
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| 168 |
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| 169 |
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| 177 |
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| 179 |
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| 180 |
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|
| 181 |
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smartphone sales have shown signs of plateauing due to incremental upgrades and market
|
| 182 |
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saturation, other segments are emerging as growth drivers. Smart hearables and wearables
|
| 183 |
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are popular, offering enhanced connectivity and health-tracking features. Foldable devices
|
| 184 |
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are carving out a niche, albeit with high prices and durability concerns. Smart clothing is still
|
| 185 |
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in its nascent stage but shows promise in integrating technology seamlessly into everyday
|
| 186 |
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life. Tablets, meanwhile, are finding renewed relevance for productivity and entertainment
|
| 187 |
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purposes. Overall, the mobile device landscape is diversifying, with innovation focusing on
|
| 188 |
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integrating various devices and creating a more connected and personalized user experience.
|
| 189 |
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| 190 |
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|
| 191 |
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| 192 |
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|
| 193 |
|
| 194 |
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|
| 195 |
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market is expected to stabilize and see modest growth due to several factors. One key driver
|
| 196 |
-
is the replacement cycle for 5G-compatible devices, as companies like Apple and Samsung,
|
| 197 |
-
among others, continue to release advanced models. Additionally, the rise of foldable
|
| 198 |
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smartphones is creating a new niche market segment with premium pricing. According to an
|
| 199 |
-
article published by Arstechnica in February 2024, the top 7 selling smartphones in 2023 were
|
| 200 |
-
manufactured by Apple, whereas Samsung manufactured the next 3 in the list.
|
| 201 |
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| 202 |
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| 203 |
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| 204 |
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| 237 |
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| 238 |
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| 239 |
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| 240 |
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|
| 241 |
-
massive consumer base and robust local manufacturing capabilities. With leading companies
|
| 242 |
-
like Huawei, Xiaomi, and OPPO continuously innovating, China's market share is substantial.
|
| 243 |
-
However, geopolitical tensions and trade restrictions could impact growth. The aggressive
|
| 244 |
-
push for 5G adoption and beyond in China makes it likely that a significant portion of mobile
|
| 245 |
-
sales will be 5G-capable devices in the coming years.
|
| 246 |
|
| 247 |
-
|
| 248 |
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| 249 |
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|
| 250 |
|
| 251 |
-
|
| 252 |
|
| 253 |
-
|
| 254 |
-
consumer preference for high-end smartphones and the rapid rollout of 5G networks. Apple
|
| 255 |
-
and Samsung remain dominant players, with the former enjoying a loyal customer base.
|
| 256 |
-
Introducing innovative features and technologies, such as foldable screens and AI-enhanced
|
| 257 |
-
applications, could spur replacement cycles. However, the market is nearing saturation, with
|
| 258 |
-
smartphone penetration already high. Growth may increasingly come from wearable devices
|
| 259 |
-
and smart home technologies.
|
| 260 |
|
| 261 |
-
|
| 262 |
|
| 263 |
-
|
| 264 |
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| 265 |
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| 266 |
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| 283 |
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| 284 |
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| 285 |
-
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| 286 |
|
| 287 |
-
|
| 288 |
-
devices capable of handling data-intensive applications, augmented reality experiences, and
|
| 289 |
-
cloud-based services. Furthermore, the growth of high-quality video streaming on mobile
|
| 290 |
-
devices drives increased subscriptions to content providers, which fuels demand for devices
|
| 291 |
-
capable of delivering an exceptional viewing experience. This surge in demand is driving
|
| 292 |
-
innovation across smartphones, wearables, and hearables.
|
| 293 |
|
| 294 |
-
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| 295 |
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| 296 |
-
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| 297 |
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| 298 |
-
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| 299 |
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| 313 |
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| 314 |
-
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| 315 |
|
| 316 |
-
|
| 317 |
|
| 318 |
-
|
| 319 |
-
eroding consumer trust and hindering industry growth. Frequent and increasingly
|
| 320 |
-
sophisticated cyberattacks and invasive tracking and data collection practices by apps and
|
| 321 |
-
services have fueled these concerns. Vulnerabilities in operating systems and applications
|
| 322 |
-
further exacerbate the risks, leaving users' personal information exposed to potential
|
| 323 |
-
breaches and misuse.
|
| 324 |
|
| 325 |
-
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| 326 |
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| 327 |
-
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| 328 |
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| 329 |
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| 330 |
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| 332 |
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| 333 |
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| 334 |
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| 335 |
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| 336 |
|
| 337 |
-
|
| 338 |
|
| 339 |
-
|
| 340 |
-
geopolitical tensions, particularly between major technology-producing nations. These
|
| 341 |
-
tensions have led to stricter trade policies, tariffs, and restrictions on technology transfers,
|
| 342 |
-
significantly impacting global supply chain dynamics. In response, companies are urgently
|
| 343 |
-
reassessing and realigning their supply chains to reduce dependency on regions with high
|
| 344 |
-
geopolitical risks. This includes diversifying sourcing and manufacturing locations to more
|
| 345 |
-
geopolitically stable or neutral countries. Moreover, there is an accelerated trend towards the
|
| 346 |
-
friend-shoring/nearshoring of critical components where companies prefer to trade with
|
| 347 |
-
allies or within blocks that share similar regulatory and political frameworks. This strategic
|
| 348 |
-
shift aims to safeguard access to essential materials and components, such as rare earth
|
| 349 |
-
metals and advanced semiconductors, which are pivotal for mobile device manufacturing.
|
| 350 |
-
Additionally, companies are increasingly investing in technology and infrastructure to
|
| 351 |
-
enhance supply chain visibility and resilience, enabling more agile responses to future
|
| 352 |
-
geopolitical shifts.
|
| 353 |
|
| 354 |
-
|
| 355 |
|
| 356 |
-
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| 357 |
|
| 358 |
-
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| 359 |
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| 360 |
-
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| 361 |
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| 362 |
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| 364 |
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| 367 |
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| 373 |
|
| 374 |
-
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|
| 375 |
|
| 376 |
-
|
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| 377 |
|
| 378 |
-
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|
| 379 |
|
| 380 |
-
|
| 381 |
|
| 382 |
-
|
| 383 |
|
| 384 |
-
|
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|
| 385 |
|
| 386 |
-
|
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|
| 387 |
|
| 388 |
-
|
| 389 |
|
| 390 |
-
|
| 391 |
|
| 392 |
-
|
| 393 |
|
| 394 |
-
|
| 395 |
-
generation of mobile devices and experiences. Faster speeds, reduced latency, and massive
|
| 396 |
-
device connectivity will supercharge applications like real-time AR/VR experiences, remote
|
| 397 |
-
collaboration, high-fidelity cloud gaming, and a flourishing Internet of Things (IoT) landscape.
|
| 398 |
-
These developments drive innovation across smartphones, wearables, and hearables,
|
| 399 |
-
enabling unprecedented connectivity and interaction.
|
| 400 |
|
| 401 |
-
|
| 402 |
|
| 403 |
-
|
| 404 |
|
| 405 |
-
|
| 406 |
|
| 407 |
-
|
| 408 |
|
| 409 |
-
|
| 410 |
|
| 411 |
-
|
| 412 |
|
| 413 |
-
|
| 414 |
|
| 415 |
-
|
| 416 |
|
| 417 |
-
|
| 418 |
|
| 419 |
-
|
| 420 |
|
| 421 |
-
|
| 422 |
|
| 423 |
-
|
| 424 |
|
| 425 |
-
|
| 426 |
|
| 427 |
-
|
| 428 |
|
| 429 |
-
|
| 430 |
|
| 431 |
-
|
| 432 |
|
| 433 |
-
|
| 434 |
|
| 435 |
-
|
| 436 |
|
| 437 |
-
|
| 438 |
|
| 439 |
-
|
| 440 |
|
| 441 |
-
|
| 442 |
-
the next 3-4 years. The widespread adoption of 5G networks is expected to unlock the full
|
| 443 |
-
potential of mobile devices, enabling faster speeds, lower latency, and new applications like
|
| 444 |
-
augmented reality and virtual reality. AI and machine learning advancements will further
|
| 445 |
-
enhance device capabilities, offering more personalized experiences and improved
|
| 446 |
-
functionality. The convergence of mobile devices with other emerging technologies like
|
| 447 |
-
blockchain and IoT will also create new opportunities for innovation and growth.
|
| 448 |
|
| 449 |
-
|
| 450 |
-
growth trajectories. In developed regions like North America and Europe, growth is expected
|
| 451 |
-
to be steady but slower due to market saturation. However, emerging markets like India,
|
| 452 |
-
Southeast Asia, and Africa will rapidly grow as smartphone penetration increases and
|
| 453 |
-
consumers upgrade to newer models with advanced features. These regions will become
|
| 454 |
-
critical drivers of the global mobile device market, with local brands playing a significant role
|
| 455 |
-
in catering to these diverse consumer bases' unique needs and preferences. Additionally,
|
| 456 |
-
government initiatives to improve digital infrastructure and promote affordable access to
|
| 457 |
-
mobile devices will further fuel growth in these regions.
|
| 458 |
|
| 459 |
-
|
| 460 |
|
| 461 |
-
|
| 462 |
|
| 463 |
-
|
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|
| 464 |
|
| 465 |
-
|
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| 466 |
|
| 467 |
-
|
| 468 |
|
| 469 |
-
|
| 470 |
|
| 471 |
-
|
| 472 |
|
| 473 |
-
|
| 474 |
|
| 475 |
-
|
| 476 |
|
| 477 |
-
|
| 478 |
|
| 479 |
-
|
| 480 |
|
| 481 |
-
|
| 482 |
|
| 483 |
-
|
| 484 |
|
| 485 |
-
|
| 486 |
|
| 487 |
-
|
| 488 |
|
| 489 |
-
|
| 490 |
|
| 491 |
-
|
| 492 |
|
| 493 |
-
|
| 494 |
|
| 495 |
-
|
| 496 |
|
| 497 |
-
|
| 498 |
-
construed as investment advice. The information contained in this document is not an offer to
|
| 499 |
-
buy or sell any securities or other financial instruments. Any investment decisions made
|
| 500 |
-
based on the information contained in this document are made at the sole discretion of the
|
| 501 |
-
reader. The author(s) of this document are not investment advisors and are not registered
|
| 502 |
-
with any regulatory authority. The author(s) of this document disclaim any liability for any
|
| 503 |
-
direct or consequential loss arising from any use of this document or its contents.
|
| 504 |
|
| 505 |
-
|
| 506 |
-
identification purposes only and are the property of their respective owners.
|
| 507 |
|
| 508 |
-
|
| 509 |
|
| 510 |
-
|
| 511 |
|
|
|
|
| 1 |
+
BY08 Capital Asset Plan and Business Case Summary
|
| 2 |
+
Exhibit 300
|
| 3 |
|
| 4 |
+
PART I: SUMMARY INFORMATION AND JUSTIFICATION
|
| 5 |
|
| 6 |
+
In Part I, complete Sections A. B, C, and D for all capital assets (IT and non-IT). Complete Sections E and
|
| 7 |
+
F for IT capital assets.
|
| 8 |
|
| 9 |
+
Section A: Overview (All Capital Assets)
|
| 10 |
|
| 11 |
+
The following series of questions are to be completed for all investments to help OMB to identify which
|
| 12 |
+
agency and bureau is responsible for managing each capital asset, which OMB MAX budget account funds
|
| 13 |
+
the project, the kind of the project, who to contact with questions about the information provided in the
|
| 14 |
+
exhibit 300, and whether or not it is an IT or a non-IT capital asset.
|
| 15 |
|
| 16 |
+
(1) Date of Submission:
|
| 17 |
+
(2) Agency:
|
| 18 |
+
(3) Bureau:
|
| 19 |
+
(4) Name of this Capital Asset:
|
| 20 |
|
| 21 |
+
09/11/2006
|
| 22 |
+
422
|
| 23 |
|
| 24 |
+
00
|
| 25 |
|
| 26 |
+
Financial Accounting System (FAS)
|
| 27 |
|
| 28 |
+
(250 Character Max)
|
| 29 |
+
(5) Unique ID (Unique Project
|
| 30 |
+
Identifier ) :
|
| 31 |
+
Format xxx-xx-xx-xx-xx-xxxx-xx
|
| 32 |
+
(For IT investments only, see section 53. For all other, use agency ID system.)
|
| 33 |
|
| 34 |
+
422-00-01-01-01-0001-00
|
| 35 |
|
| 36 |
+
(6) What kind of investment
|
| 37 |
+
Will in be this FY2008?
|
| 38 |
+
(7) What was the first budget
|
| 39 |
+
year this investment was
|
| 40 |
+
submitted to OMB?
|
| 41 |
|
| 42 |
+
Operations and Maintenance
|
| 43 |
|
| 44 |
+
FY2001 or earlier
|
| 45 |
|
| 46 |
+
(8) Provide a brief summary and justification for this investment, including a brief description of how this
|
| 47 |
+
closes a gap in part or in whole an identified agency performance gap: (2500 Char Max)
|
| 48 |
|
| 49 |
+
The Financial Accounting System (FAS) is the main tool NSF staff utilizes to monitor, control, and execute the
|
| 50 |
+
management and financial accountability of approximately 20,000 active awards with 2000+ external
|
| 51 |
+
grantees. The FAS is an on-line real time system is the primary vehicle for managing all funding allocated to the
|
| 52 |
+
NSF. A central transaction management procedure called the "post-routine" represents the core of the system,
|
| 53 |
+
handling the full spectrum of financial transaction processing, accounts maintenance, transaction history, and
|
| 54 |
+
rules processing. This procedure processes any financial request, whether generated from within the Financial
|
| 55 |
+
System itself or by an external system. The FAS is extensively integrated with all of NSF's core business
|
| 56 |
+
systems including the e-Jacket, Proposal and Reviewer System, the Awards System, Guest Travel System, and
|
| 57 |
+
the FastLane System in support of Grants management. NSF's accounting and financial systems staff
|
| 58 |
+
created a data warehousing environment with the ability to produce our financial statements including the
|
| 59 |
+
Closing Package statements, generate automated closing entries and in produce the SGL Tie points reports. In
|
| 60 |
+
FY06, NSF implemented a near real-time interface between FAS and FedTraveler that
|
| 61 |
|
| 62 |
+
NSF FAS 1-3-07
|
| 63 |
|
| 64 |
+
1 of 18
|
| 65 |
|
| 66 |
+
FY08 Exhibit 300
|
| 67 |
|
| 68 |
+
includes evaluation of funds availability and funds obligation. NSF expects the same type of data exchanges with
|
| 69 |
+
other externally provided cross-services. The e-Learning and e-Procurement /FAS interfaces are
|
| 70 |
+
scheduled to be implemented in FY 2007. The FAS will remain in a steady-state phase in the FY05-FY10
|
| 71 |
+
timeframe. NSF will be approaching its future financial system requirements as an integral part of its grant
|
| 72 |
+
process. NSF will conduct an integrated review of the GMLOB/FMLOB solution in 2007. If that solution is
|
| 73 |
+
determined to not be feasible, NSF will analyze the FMLOB Shared Service Provider (SSP) options in 2008. If
|
| 74 |
+
necessary, NSF will conduct a Business Case Feasibility Study for the FMLOB solution in 2009. This plan allows
|
| 75 |
+
the NSF to take advantage of the results/findings of the GMLOB process in becoming a SSP to more fully
|
| 76 |
+
define our financial requirements. NSF anticipates that if a conversion is necessary it will substantially impact
|
| 77 |
+
NSF Grantees and will begin in 2010. The current FAS will remain in steady-state maintenance until the
|
| 78 |
+
conversion is complete. Any decisions NSF makes regarding the future financial system modernization will
|
| 79 |
+
support the President's Management Agenda.
|
| 80 |
|
| 81 |
+
(9) Did the Agency's Executive/Investment Committee approve this request?
|
| 82 |
|
| 83 |
+
a. If "yes," what was the date of this approval?
|
| 84 |
|
| 85 |
+
(10) Did the Project Manager review this Exhibit?
|
| 86 |
|
| 87 |
+
11) Contact Information of Project Manager?
|
| 88 |
|
| 89 |
+
N a me :
|
| 90 |
+
Phone Number:
|
| 91 |
+
E-Mail:
|
| 92 |
|
| 93 |
+
Carolyn Miller
|
| 94 |
|
| 95 |
+
703-292-4272
|
| 96 |
|
| 97 |
+
cmiller@nsf.gov
|
| 98 |
|
| 99 |
+
yes
|
| 100 |
|
| 101 |
+
.
|
| 102 |
+
|
| 103 |
+
08/30/2006
|
| 104 |
+
|
| 105 |
+
yes
|
| 106 |
+
|
| 107 |
+
(12) Has the agency developed and/or promoted cost effective, energy-efficient and environmentally
|
| 108 |
+
sustainable techniques or practices for this project.
|
| 109 |
+
|
| 110 |
+
no
|
| 111 |
+
|
| 112 |
+
(a) Will this investment include electronic assets (including computers)?
|
| 113 |
+
|
| 114 |
+
yes
|
| 115 |
+
|
| 116 |
+
(b) Is this investment for new construction or major retrofit of a Federal building or
|
| 117 |
+
facility? (answer applicable to non-IT assets only)
|
| 118 |
+
[1] If "yes," is an ESPC or UESC being used to help fund this investment?
|
| 119 |
+
[2] If "yes," will this investment meet sustainable design principles?
|
| 120 |
+
[3] If "yes," is it designed to be 30% more energy efficient than relevant code?
|
| 121 |
+
|
| 122 |
+
(13) Does this investment support one of the PMA initiatives? yes
|
| 123 |
+
|
| 124 |
+
If "yes," select all that apply:
|
| 125 |
+
President's Management Agenda (PMA) Initiatives
|
| 126 |
+
E x p a n d e d E - G o v e r n m e n t
|
| 127 |
+
|
| 128 |
+
Budget Performance Integration
|
| 129 |
+
|
| 130 |
+
a. Briefly describe how this asset directly supports the identified initiative(s)?
|
| 131 |
+
|
| 132 |
+
NSF's Enterprise Information System, the FAS and the Report web reporting system provide
|
| 133 |
+
financial, budgetary, awards and performance information (including PART) that is accessible in
|
| 134 |
+
|
| 135 |
+
NSF FAS 1-3-07
|
| 136 |
+
|
| 137 |
+
2 of 18
|
| 138 |
+
|
| 139 |
+
FY08 Exhibit 300
|
| 140 |
+
|
| 141 |
+
multiple formats at every workstation on a 24/7, real-time basis. Managers use this information to
|
| 142 |
+
make decisions regarding NSF budget priorities and business processes. NSF's Statement of Net
|
| 143 |
+
Cost uses the FAS to report the full cost of each strategic goal - Ideas, Tools, People and
|
| 144 |
+
Stewardship.
|
| 145 |
+
|
| 146 |
+
(14) Does this investment support a program assessed using OMB's
|
| 147 |
+
Program Assessment Rating Tool (PART)?
|
| 148 |
+
(a) If "yes," does this investment address a
|
| 149 |
+
weakness found during a PART review?
|
| 150 |
+
(b) If "yes," what is the name of the PARTed
|
| 151 |
+
program ?
|
| 152 |
+
(c) If "yes," what rating did the PART receive?
|
| 153 |
+
|
| 154 |
+
no
|
| 155 |
+
|
| 156 |
+
(15) Is this investment for information technology? (see section 53 for definition)) yes
|
| 157 |
+
|
| 158 |
+
If the answer to Question 15 was "Yes," complete questions 16-23 below. If
|
| 159 |
+
the answer is "No," do not answer questions 16-23.
|
| 160 |
+
|
| 161 |
+
Level 1
|
| 162 |
+
|
| 163 |
+
(1) Project manager has been validated as qualified for this
|
| 164 |
+
investment
|
| 165 |
+
|
| 166 |
+
no
|
| 167 |
+
|
| 168 |
+
No
|
| 169 |
+
|
| 170 |
+
(16) What is the level of the IT Project (per CIO
|
| 171 |
+
Council PM Guidance)?
|
| 172 |
+
(17) What project management qualifications does
|
| 173 |
+
the Project Manager have? (per CIO Council PM
|
| 174 |
+
|
| 175 |
+
(18) Is this investment identified as "high risk" on
|
| 176 |
+
the Q4 - FY 2006 agency high risk report
|
| 177 |
+
(per OMB's 'high risk" memo)?
|
| 178 |
+
|
| 179 |
+
(19) Is this a financial management system?
|
| 180 |
+
(a) If "yes," does this investment address a FFMIA
|
| 181 |
+
compliance area?
|
| 182 |
+
|
| 183 |
+
[1] If "yes," which compliance area:
|
| 184 |
+
[2] If "no," what does it address?
|
| 185 |
+
|
| 186 |
+
(b) If "yes," please identify the system name(s) and
|
| 187 |
+
system acronym(s) as reported in the most recent
|
| 188 |
+
financial systems inventory update required by
|
| 189 |
+
Circular A-11 section 52:
|
| 190 |
+
|
| 191 |
+
(20) What is the percentage breakout for the total FY2008 funding request for the following?
|
| 192 |
+
(This should total 100%)
|
| 193 |
+
|
| 194 |
+
Hardware %:
|
| 195 |
+
0
|
| 196 |
+
|
| 197 |
+
Software %:
|
| 198 |
+
0
|
| 199 |
+
|
| 200 |
+
Services %:
|
| 201 |
+
100
|
| 202 |
+
|
| 203 |
+
Other %:
|
| 204 |
+
|
| 205 |
+
0
|
| 206 |
+
|
| 207 |
+
Total %
|
| 208 |
+
100
|
| 209 |
+
|
| 210 |
+
(21) If this project produces information dissemination products for the public, are these products
|
| 211 |
+
published to the Internet in conformance with OMB Memorandum 05-04 and included in your
|
| 212 |
+
agency inventory, schedules and priorities?
|
| 213 |
+
n/a
|
| 214 |
+
|
| 215 |
+
NSF FAS 1-3-07
|
| 216 |
+
|
| 217 |
+
3 of 18
|
| 218 |
+
|
| 219 |
+
FY08 Exhibit 300
|
| 220 |
+
|
| 221 |
+
(22) Contact information of individual responsible for privacy related questions:
|
| 222 |
+
|
| 223 |
+
Name:
|
| 224 |
+
Phone
|
| 225 |
+
Number:
|
| 226 |
+
Title:
|
| 227 |
+
E-Mail:
|
| 228 |
+
|
| 229 |
+
Leslie A. Jensen
|
| 230 |
+
|
| 231 |
+
703-292-8060
|
| 232 |
+
|
| 233 |
+
NSF FOIA/Privacy Act Officer
|
| 234 |
+
|
| 235 |
+
Ijensen@nsf.gov
|
| 236 |
+
|
| 237 |
+
(23) Are the records produced by this investment appropriately scheduled with the National
|
| 238 |
+
Archives and Records Administration's approval? no
|
| 239 |
+
|
| 240 |
+
Section B: Summary of Funding (All Capital Assets)
|
| 241 |
+
(1) Provide the total estimated life-cycle cost for this investment by completing the following table.
|
| 242 |
+
All amounts represent budget authority in millions, and are rounded to three decimal places.
|
| 243 |
+
Federal personnel costs should be included only in the row designated "Government FTE Cost,"
|
| 244 |
+
and should be excluded from the amounts shown for "Planning," "Full Acquisition," and
|
| 245 |
+
"Operation/Maintenance." The total estimated annual cost of the investment is the sum of costs for
|
| 246 |
+
"Planning," "Full Acquisition," and "Operation/Maintenance." For Federal buildings and facilities,
|
| 247 |
+
life-cycle costs should include long term energy, environmental, decommissioning, and/or
|
| 248 |
+
restoration costs. The costs associated with the entire life-cycle of the investment should be
|
| 249 |
+
included in this report.
|
| 250 |
+
|
| 251 |
+
Table 1: SUMMARY OF SPENDING FOR PROJECT PHASES (REPORTED IN MILLIONS)
|
| 252 |
+
All amounts represent Budget Authority (Estimates for BY+1 and beyond are for planning purposes only and do not
|
| 253 |
+
represent budget decisions)
|
| 254 |
+
|
| 255 |
+
PY-1
|
| 256 |
+
Spending
|
| 257 |
+
Prior to 2006
|
| 258 |
+
|
| 259 |
+
BY +1 BY+2 2010
|
| 260 |
+
2009
|
| 261 |
+
|
| 262 |
+
2011
|
| 263 |
+
|
| 264 |
+
Total
|
| 265 |
+
|
| 266 |
+
BY+4
|
| 267 |
+
2012 and
|
| 268 |
+
beyond
|
| 269 |
+
|
| 270 |
+
Planning
|
| 271 |
+
|
| 272 |
+
Acquisition
|
| 273 |
+
Subtotal
|
| 274 |
+
Planning &
|
| 275 |
+
Acquisition
|
| 276 |
+
Operations
|
| 277 |
+
|
| 278 |
+
$0.000
|
| 279 |
+
|
| 280 |
+
$0.000
|
| 281 |
+
$0.000
|
| 282 |
+
|
| 283 |
+
$0.000
|
| 284 |
+
|
| 285 |
+
$0.000
|
| 286 |
+
$0.000
|
| 287 |
+
|
| 288 |
+
$0.000
|
| 289 |
+
|
| 290 |
+
$0.000
|
| 291 |
+
$0.000
|
| 292 |
+
|
| 293 |
+
$0.000
|
| 294 |
+
|
| 295 |
+
$0.000
|
| 296 |
+
$0.000
|
| 297 |
+
|
| 298 |
+
$7.570
|
| 299 |
+
|
| 300 |
+
$1.500
|
| 301 |
+
|
| 302 |
+
$1.500
|
| 303 |
+
|
| 304 |
+
$1.120
|
| 305 |
+
|
| 306 |
+
TOTAL
|
| 307 |
+
|
| 308 |
+
$7.570
|
| 309 |
+
|
| 310 |
+
$1.500
|
| 311 |
+
|
| 312 |
+
$1.500
|
| 313 |
+
|
| 314 |
+
$1.120
|
| 315 |
+
|
| 316 |
+
Government FTE Costs
|
| 317 |
+
should not be included
|
| 318 |
+
th
|
| 319 |
+
|
| 320 |
+
i
|
| 321 |
+
|
| 322 |
+
t
|
| 323 |
+
|
| 324 |
+
provided
|
| 325 |
+
above.
|
| 326 |
+
|
| 327 |
+
$0.360
|
| 328 |
+
|
| 329 |
+
$0.360
|
| 330 |
+
|
| 331 |
+
$0.360
|
| 332 |
+
|
| 333 |
+
$1.800
|
| 334 |
+
|
| 335 |
+
Government
|
| 336 |
+
FTE Costs
|
| 337 |
+
Number of
|
| 338 |
+
FTE
|
| 339 |
+
represented
|
| 340 |
+
by cost
|
| 341 |
+
Note: For the cross-agency investments, this table should include all funding (both managing partner
|
| 342 |
+
and partner agencies). Government FTE Costs should not be included as part of the TOTAL
|
| 343 |
+
represented.
|
| 344 |
+
|
| 345 |
+
NSF FAS 1-3-07
|
| 346 |
+
|
| 347 |
+
4 of 18
|
| 348 |
+
|
| 349 |
+
FY08 Exhibit 300
|
| 350 |
+
|
| 351 |
+
(2) Will this project require the agency to hire additional FTE's? no
|
| 352 |
+
|
| 353 |
+
(a) If "yes," How many and in what year?
|
| 354 |
+
|
| 355 |
+
(3) If the summary of spending has changed from the FY2007 President's budget request, briefly
|
| 356 |
+
explain those changes.
|
| 357 |
+
|
| 358 |
+
Section C: Acquisition/Contract Strategy (All Capital Assets)
|
| 359 |
+
|
| 360 |
+
(1) Complete the table for all contracts and/or task orders in place or planned for this investment:
|
| 361 |
+
|
| 362 |
+
Contract or Task Order Number: BZ-11/0533982 Type of Contract/TO Used: Cost Plus Fixed Fee
|
| 363 |
+
Has the Contract Being Awarded: yes
|
| 364 |
+
Contract Actual/Planned Award Date:
|
| 365 |
+
05/01/2005
|
| 366 |
+
Contract/TO Start Date:
|
| 367 |
+
05/01/2005
|
| 368 |
+
Contract/TO End Date:
|
| 369 |
+
04/30/2007
|
| 370 |
+
Contract/TO Total Value ($M): $32.200 Inter Agency Acquisition: no
|
| 371 |
+
Performance Based Contract: yes
|
| 372 |
+
Competitively Awarded Contract: yes
|
| 373 |
+
Alternative Financing: NA EVM Required: yes
|
| 374 |
+
Security Privacy Clause: yes
|
| 375 |
+
|
| 376 |
+
Contracting Officer (CO) Contact Information:
|
| 377 |
+
|
| 378 |
+
CO Name: Patricia S. Williams
|
| 379 |
+
CO Contact Information (Phone/Email): (703) 292-8240 pswillia@nsf.gov
|
| 380 |
+
CO Certification Level (Level 1, 2, 3, N/A): 3
|
| 381 |
+
If N/A has the agency determined the CO assigned has the competencies and skills necessary to
|
| 382 |
+
support this acquisition? (Y/N)
|
| 383 |
+
|
| 384 |
+
(2) If earned value is not required or will not be a contract requirement for any of the contracts or
|
| 385 |
+
|
| 386 |
+
task orders above, explain why:
|
| 387 |
+
|
| 388 |
+
The contract has a requirement to utilize earned value management (EVM) for tasks/projects designated as
|
| 389 |
+
new development or "Development/Modernization/Enhancements (DME)." FAS is in Steady State and its
|
| 390 |
+
maintenance activities are exempt from EVM at this time per OMB Guidance.
|
| 391 |
+
|
| 392 |
+
(3) Do the contracts ensure Section 508 compliance? yes
|
| 393 |
+
Section 508 Compliance Explanation:
|
| 394 |
+
The system was reviewed and modified, as needed, in 2001 for Section 508 compliance. The FAS consists of an
|
| 395 |
+
end-user GUI and back-end software programs. Only the end-user GUI is used by users; therefore only changes
|
| 396 |
+
to it would affect Section 508 compliance. While the majority of maintenance changes are to the back-end
|
| 397 |
+
software, when the GUI is affected, NSF staff review each maintenance change for Section 508 compliance
|
| 398 |
+
before the change is implemented.
|
| 399 |
+
|
| 400 |
+
NSF FAS 1-3-07
|
| 401 |
+
|
| 402 |
+
5 of 18
|
| 403 |
+
|
| 404 |
+
FY08 Exhibit 300
|
| 405 |
+
|
| 406 |
+
(4) Is there an acquisition plan which has been approved in accordance with agency requirements?
|
| 407 |
+
|
| 408 |
+
yes
|
| 409 |
+
|
| 410 |
+
(a) If "yes", what is the date?
|
| 411 |
+
12/01/2001
|
| 412 |
+
(b) If "no," will an acquisition plan be developed?
|
| 413 |
+
|
| 414 |
+
[1] If "no," briefly explain why:
|
| 415 |
+
|
| 416 |
+
Section D: Performance Information (All Capital Assets)
|
| 417 |
+
|
| 418 |
+
In order to successfully address this area of the exhibit 300, performance goals must be provided for the
|
| 419 |
+
agency and be linked to the annual performance plan. The investment must discuss the agency's mission and
|
| 420 |
+
strategic goals, and performance measures must be provided. These goals need to map to the gap in the
|
| 421 |
+
agency's strategic goals and objectives this investment is designed to fill. They are the internal and external
|
| 422 |
+
performance benefits this investment is expected to deliver to the agency (e.g., improve efficiency by 60
|
| 423 |
+
percent, increase citizen participation by 300 percent a year to achieve an overall citizen participation rate of
|
| 424 |
+
75 percent by FY 2xxx, etc.). The goals must be clearly measurable investment outcomes, and if applicable,
|
| 425 |
+
investment outputs. They do not include the completion date of the module, milestones, or investment, or
|
| 426 |
+
general goals, such as, significant, better, improved that do not have a quantitative or qualitative measure.
|
| 427 |
+
|
| 428 |
+
Agencies must use Table 1 below for reporting performance goals and measures for all non-IT investments
|
| 429 |
+
and for existing IT investments that were initiated prior to FY 2005. The table can be extended to include
|
| 430 |
+
measures for years beyond FY 2006.
|
| 431 |
+
|
| 432 |
+
Table 1
|
| 433 |
+
|
| 434 |
+
Fiscal Year
|
| 435 |
+
|
| 436 |
+
Strategic
|
| 437 |
+
|
| 438 |
+
Goal(s)
|
| 439 |
+
Supported
|
| 440 |
+
|
| 441 |
+
2003
|
| 442 |
+
|
| 443 |
+
2003
|
| 444 |
+
|
| 445 |
+
2003
|
| 446 |
+
|
| 447 |
+
2003
|
| 448 |
+
|
| 449 |
+
2004
|
| 450 |
+
|
| 451 |
+
2004
|
| 452 |
+
|
| 453 |
+
2004
|
| 454 |
+
|
| 455 |
+
2004
|
| 456 |
+
|
| 457 |
+
Financial
|
| 458 |
+
Management
|
| 459 |
+
Financial
|
| 460 |
+
Management
|
| 461 |
+
|
| 462 |
+
Financial
|
| 463 |
+
Management
|
| 464 |
+
|
| 465 |
+
Financial
|
| 466 |
+
Management
|
| 467 |
+
|
| 468 |
+
Financial
|
| 469 |
+
Management
|
| 470 |
+
|
| 471 |
+
Financial
|
| 472 |
+
Management
|
| 473 |
+
|
| 474 |
+
Financial
|
| 475 |
+
Management
|
| 476 |
+
|
| 477 |
+
Financial
|
| 478 |
+
Management
|
| 479 |
+
|
| 480 |
+
Performance Measure
|
| 481 |
+
|
| 482 |
+
Actual/
|
| 483 |
+
|
| 484 |
+
Migrate from current payroll system to
|
| 485 |
+
Government wide Payroll provider
|
| 486 |
+
|
| 487 |
+
Meet Accelerated Financial Management
|
| 488 |
+
Reporting Requirements (45 days after
|
| 489 |
+
fiscal year-end)
|
| 490 |
+
Meet Quarterly reporting requirement
|
| 491 |
+
|
| 492 |
+
Unqualified Audit Opinion for Financial
|
| 493 |
+
Statements
|
| 494 |
+
|
| 495 |
+
Implement Government wide ePayroll
|
| 496 |
+
service provider
|
| 497 |
+
|
| 498 |
+
Baseline (from
|
| 499 |
+
previous year)
|
| 500 |
+
|
| 501 |
+
Legacy System-IPAY
|
| 502 |
+
|
| 503 |
+
Met Current Financial
|
| 504 |
+
Management Reporting
|
| 505 |
+
Requirements
|
| 506 |
+
Met Current Financial
|
| 507 |
+
Management Reporting
|
| 508 |
+
Requirements
|
| 509 |
+
Unqualified Audit
|
| 510 |
+
Opinion
|
| 511 |
+
|
| 512 |
+
Legacy System-IPAY
|
| 513 |
+
|
| 514 |
+
Planned
|
| 515 |
+
Performance
|
| 516 |
+
Metric (Target)
|
| 517 |
+
|
| 518 |
+
Select ePayroll provider in
|
| 519 |
+
FY03
|
| 520 |
+
Submit NSF Performance
|
| 521 |
+
and Accountability Report
|
| 522 |
+
to OMB on November 17
|
| 523 |
+
Submit Quarterly financial
|
| 524 |
+
statements to OMB within
|
| 525 |
+
45 days of end of quarter
|
| 526 |
+
|
| 527 |
+
Unqualified Audit Opinion
|
| 528 |
+
for FY 2003 Financial
|
| 529 |
+
Statements
|
| 530 |
+
Successful transition to
|
| 531 |
+
Government wide ePayroll
|
| 532 |
+
service provide and
|
| 533 |
+
retirement of IPAY system
|
| 534 |
+
|
| 535 |
+
Meet Accelerated Financial Management
|
| 536 |
+
Reporting Requirements 45 days after fiscal
|
| 537 |
+
year end
|
| 538 |
+
Unqualified Audit Opinion for Financial
|
| 539 |
+
Statements
|
| 540 |
+
|
| 541 |
+
Met Current Financial
|
| 542 |
+
Management Reporting
|
| 543 |
+
Requirements
|
| 544 |
+
Unqualified Audit
|
| 545 |
+
Opinion
|
| 546 |
+
|
| 547 |
+
Submit NSF Performance
|
| 548 |
+
and Accountability Report
|
| 549 |
+
by November 15
|
| 550 |
+
Unqualified Audit Opinion
|
| 551 |
+
for FY 2004 Financial
|
| 552 |
+
Statements
|
| 553 |
+
|
| 554 |
+
Produce Quarterly Financial Statements
|
| 555 |
+
within 21 days of end of quarter
|
| 556 |
+
|
| 557 |
+
Produced Quarterly
|
| 558 |
+
Financial Statements
|
| 559 |
+
within 21 days of end of
|
| 560 |
+
quarter
|
| 561 |
+
|
| 562 |
+
Produce Quarterly
|
| 563 |
+
Financial Statements
|
| 564 |
+
within 21 days of end of
|
| 565 |
+
quarter
|
| 566 |
+
|
| 567 |
+
Performance Metric
|
| 568 |
+
Results (Actual)
|
| 569 |
+
|
| 570 |
+
ePayroll Service Provider
|
| 571 |
+
selected in January 2003
|
| 572 |
+
November 15th date was
|
| 573 |
+
achieved one year ahead of
|
| 574 |
+
OMB requirements
|
| 575 |
+
NSF's Quarterly reports
|
| 576 |
+
were consistently one of the
|
| 577 |
+
first submitted to OMB
|
| 578 |
+
NSF received an Unqualified
|
| 579 |
+
Audit Opinion for FY 2003
|
| 580 |
+
on 11/05/04
|
| 581 |
+
New ePayroll service
|
| 582 |
+
provider began processing
|
| 583 |
+
NSF's payroll in May 2004.
|
| 584 |
+
Because NSF's payroll
|
| 585 |
+
system ran for part of the
|
| 586 |
+
calendar year, NSF cannot
|
| 587 |
+
retire its IPAY system until
|
| 588 |
+
all reconciliation for the
|
| 589 |
+
calendar year is done and W-
|
| 590 |
+
2s are generated
|
| 591 |
+
PAR Report submitted on
|
| 592 |
+
11/15/2004
|
| 593 |
+
|
| 594 |
+
NSF received an Unqualified
|
| 595 |
+
Audit Opinion for FY 2004
|
| 596 |
+
on 11/04/2005
|
| 597 |
+
Quarterly reports produced
|
| 598 |
+
within 21 days beginning
|
| 599 |
+
March 2004
|
| 600 |
+
|
| 601 |
+
NSF FAS 1-3-07
|
| 602 |
+
|
| 603 |
+
6 of 18
|
| 604 |
+
|
| 605 |
+
FY08 Exhibit 300
|
| 606 |
+
|
| 607 |
+
Fiscal Year
|
| 608 |
+
|
| 609 |
+
Strategic
|
| 610 |
+
Goal(s)
|
| 611 |
+
Supported
|
| 612 |
+
|
| 613 |
+
Performance Measure
|
| 614 |
+
|
| 615 |
+
Actual/
|
| 616 |
+
Baseline (from
|
| 617 |
+
previous year)
|
| 618 |
+
|
| 619 |
+
2004
|
| 620 |
+
|
| 621 |
+
2005
|
| 622 |
+
|
| 623 |
+
Financial
|
| 624 |
+
Management
|
| 625 |
+
|
| 626 |
+
Automate closing package financial
|
| 627 |
+
statements
|
| 628 |
+
|
| 629 |
+
Met new Closing
|
| 630 |
+
package requirements
|
| 631 |
+
|
| 632 |
+
Financial
|
| 633 |
+
Management
|
| 634 |
+
|
| 635 |
+
Unqualified Audit Opinion for Financial
|
| 636 |
+
Statements
|
| 637 |
+
|
| 638 |
+
Unqualified Audit
|
| 639 |
+
Opinion
|
| 640 |
+
|
| 641 |
+
2005
|
| 642 |
+
|
| 643 |
+
FFMIA Compliance
|
| 644 |
+
|
| 645 |
+
Receive Assertion of FFMIA Compliance -
|
| 646 |
+
Implement FAS Requirements necessary to
|
| 647 |
+
maintain compliance
|
| 648 |
+
|
| 649 |
+
Financial
|
| 650 |
+
Management
|
| 651 |
+
|
| 652 |
+
Produce Quarterly Financial Statements
|
| 653 |
+
within 21 days of end of quarter
|
| 654 |
+
|
| 655 |
+
Financial
|
| 656 |
+
Management
|
| 657 |
+
|
| 658 |
+
Unqualified Audit Opinion for Financial
|
| 659 |
+
Statements
|
| 660 |
+
|
| 661 |
+
Unqualified Audit
|
| 662 |
+
Opinion
|
| 663 |
+
|
| 664 |
+
Financial
|
| 665 |
+
Management
|
| 666 |
+
|
| 667 |
+
Produce Quarterly and year end Financial
|
| 668 |
+
statement
|
| 669 |
+
|
| 670 |
+
2006
|
| 671 |
+
|
| 672 |
+
FFMIA Compliance
|
| 673 |
+
|
| 674 |
+
Receive Assertion of FFMIA Compliance -
|
| 675 |
+
Implement FAS Requirements necessary to
|
| 676 |
+
maintain compliance
|
| 677 |
+
|
| 678 |
+
Financial
|
| 679 |
+
Management
|
| 680 |
+
|
| 681 |
+
Unqualified Audit Opinion for Financial
|
| 682 |
+
Statements
|
| 683 |
+
|
| 684 |
+
Unqualified Audit
|
| 685 |
+
Opinion
|
| 686 |
+
|
| 687 |
+
2005
|
| 688 |
+
|
| 689 |
+
2006
|
| 690 |
+
|
| 691 |
+
20116
|
| 692 |
+
|
| 693 |
+
2007
|
| 694 |
+
|
| 695 |
+
2007
|
| 696 |
+
|
| 697 |
+
Financial
|
| 698 |
+
Management
|
| 699 |
+
|
| 700 |
+
Produce Quarterly and year end Financial
|
| 701 |
+
statement
|
| 702 |
+
|
| 703 |
+
2007
|
| 704 |
+
|
| 705 |
+
FFMIA Compliance
|
| 706 |
+
|
| 707 |
+
Receive Assertion of FFMIA Compliance -
|
| 708 |
+
Implement FAS Requirements necessary to
|
| 709 |
+
maintain compliance
|
| 710 |
+
|
| 711 |
+
2007
|
| 712 |
+
|
| 713 |
+
2007
|
| 714 |
+
|
| 715 |
+
2008
|
| 716 |
+
|
| 717 |
+
2008
|
| 718 |
+
|
| 719 |
+
2008
|
| 720 |
+
|
| 721 |
+
2008
|
| 722 |
+
|
| 723 |
+
2008
|
| 724 |
+
|
| 725 |
+
Financial
|
| 726 |
+
Management
|
| 727 |
+
|
| 728 |
+
Federal Cash Transactions Report
|
| 729 |
+
Monitoring
|
| 730 |
+
|
| 731 |
+
Financial
|
| 732 |
+
Management
|
| 733 |
+
|
| 734 |
+
Grant Closeout - Review the Award
|
| 735 |
+
Closeout Report on a quarterly basis
|
| 736 |
+
|
| 737 |
+
Financial
|
| 738 |
+
Management
|
| 739 |
+
|
| 740 |
+
Federal Cash Transactions Report
|
| 741 |
+
Monitoring
|
| 742 |
+
|
| 743 |
+
Financial
|
| 744 |
+
Management
|
| 745 |
+
|
| 746 |
+
Grant Closeout - Review the Award
|
| 747 |
+
Closeout Report on a quarterly basis
|
| 748 |
+
|
| 749 |
+
Financial
|
| 750 |
+
Management
|
| 751 |
+
|
| 752 |
+
Unqualified Audit Opinion for Financial
|
| 753 |
+
Statements
|
| 754 |
+
|
| 755 |
+
Financial
|
| 756 |
+
Management
|
| 757 |
+
|
| 758 |
+
Produce Quarterly and year end Financial
|
| 759 |
+
statement
|
| 760 |
+
|
| 761 |
+
FFMIA Compliance
|
| 762 |
+
|
| 763 |
+
Receive Assertion of FFMIA Compliance -
|
| 764 |
+
Implement FAS Requirements necessary to
|
| 765 |
+
maintain compliance
|
| 766 |
+
|
| 767 |
+
Planned
|
| 768 |
+
Performance
|
| 769 |
+
Metric (Target)
|
| 770 |
+
Automate closing package
|
| 771 |
+
financial statements
|
| 772 |
+
|
| 773 |
+
Performance Metric
|
| 774 |
+
Results (Actual)
|
| 775 |
+
|
| 776 |
+
Closing package statement
|
| 777 |
+
became automated in June
|
| 778 |
+
2004 NSF produces its
|
| 779 |
+
automated financial
|
| 780 |
+
statements and closing
|
| 781 |
+
package statements
|
| 782 |
+
simultaneously
|
| 783 |
+
|
| 784 |
+
Unqualified Audit Opinion
|
| 785 |
+
for FY 2005 Financial
|
| 786 |
+
Statements
|
| 787 |
+
Maintain Assertion of
|
| 788 |
+
FFMIA Compliance
|
| 789 |
+
through FAS compliance
|
| 790 |
+
with requirements
|
| 791 |
+
|
| 792 |
+
FFMIA compliance asserted
|
| 793 |
+
on 11/08/2005
|
| 794 |
+
|
| 795 |
+
Produce Quarterly
|
| 796 |
+
Financial Statements
|
| 797 |
+
within 21 days of end of
|
| 798 |
+
quarter
|
| 799 |
+
|
| 800 |
+
NSF submitted timely and
|
| 801 |
+
accurate quarterly statements
|
| 802 |
+
within 21 days of the end of
|
| 803 |
+
quarter
|
| 804 |
+
|
| 805 |
+
Unqualified Audit Opinion
|
| 806 |
+
for FY 2006 Financial
|
| 807 |
+
Statements
|
| 808 |
+
Quarterly reports
|
| 809 |
+
produced
|
| 810 |
+
within 21 days and year
|
| 811 |
+
|
| 812 |
+
ithi 45 d
|
| 813 |
+
|
| 814 |
+
Maintain Assertion of
|
| 815 |
+
FFMIA Compliance
|
| 816 |
+
through FAS compliance
|
| 817 |
+
with requirements
|
| 818 |
+
|
| 819 |
+
Unqualified Audit Opinion
|
| 820 |
+
for FY 2007 Financial
|
| 821 |
+
Statements
|
| 822 |
+
Quarterly reports
|
| 823 |
+
produced
|
| 824 |
+
within 21 days and year
|
| 825 |
+
Maintain Assertion of
|
| 826 |
+
FFMIA Compliance
|
| 827 |
+
through FAS compliance
|
| 828 |
+
with requirements
|
| 829 |
+
|
| 830 |
+
ithi 45 d
|
| 831 |
+
|
| 832 |
+
Resolve 100% of
|
| 833 |
+
excessive cash on hand
|
| 834 |
+
findings
|
| 835 |
+
|
| 836 |
+
Close 100% of awards
|
| 837 |
+
within two full reporting
|
| 838 |
+
quarters after the
|
| 839 |
+
expiration date
|
| 840 |
+
|
| 841 |
+
Resolve 100% of
|
| 842 |
+
excessive cash on hand
|
| 843 |
+
findings
|
| 844 |
+
|
| 845 |
+
Close 100% of awards
|
| 846 |
+
within two full reporting
|
| 847 |
+
quarters after the
|
| 848 |
+
expiration date
|
| 849 |
+
|
| 850 |
+
Unqualified Audit Opinion
|
| 851 |
+
for FY 2008 Financial
|
| 852 |
+
Statements
|
| 853 |
+
Quarterly reports
|
| 854 |
+
produced
|
| 855 |
+
within 21 days and year
|
| 856 |
+
|
| 857 |
+
ithi 45 d
|
| 858 |
+
|
| 859 |
+
Maintain Assertion of
|
| 860 |
+
FFMIA Compliance
|
| 861 |
+
through FAS compliance
|
| 862 |
+
with requirements
|
| 863 |
+
|
| 864 |
+
Received Assertion of
|
| 865 |
+
FFMIA Compliance -
|
| 866 |
+
Implemented required
|
| 867 |
+
changes to SGL and
|
| 868 |
+
transactions
|
| 869 |
+
|
| 870 |
+
Produced Quarterly
|
| 871 |
+
Financial Statements
|
| 872 |
+
within 21 days of end
|
| 873 |
+
of
|
| 874 |
+
|
| 875 |
+
Produced Quarterly and
|
| 876 |
+
year-end Financial
|
| 877 |
+
Statements by deadlines
|
| 878 |
+
|
| 879 |
+
Received Assertion of
|
| 880 |
+
FFMIA Compliance -
|
| 881 |
+
Implemented required
|
| 882 |
+
changes to SGL and
|
| 883 |
+
transactions
|
| 884 |
+
|
| 885 |
+
Produce Quarterly and
|
| 886 |
+
year-end Financial
|
| 887 |
+
Statements by deadlines
|
| 888 |
+
|
| 889 |
+
Received Assertion of
|
| 890 |
+
FFMIA Compliance -
|
| 891 |
+
Implemented required
|
| 892 |
+
changes to SGL and
|
| 893 |
+
transactions
|
| 894 |
+
|
| 895 |
+
Reviewed 100% of
|
| 896 |
+
Federal Cash
|
| 897 |
+
Transactions Reports
|
| 898 |
+
with positive cash on
|
| 899 |
+
hand
|
| 900 |
+
|
| 901 |
+
Closed 100% of awards
|
| 902 |
+
within two full
|
| 903 |
+
reporting
|
| 904 |
+
quarters after the
|
| 905 |
+
expiration date
|
| 906 |
+
Reviewed 100% of
|
| 907 |
+
Federal Cash
|
| 908 |
+
Transactions Reports
|
| 909 |
+
with positive cash on
|
| 910 |
+
hand
|
| 911 |
+
|
| 912 |
+
Closed 100% of awards
|
| 913 |
+
within two full
|
| 914 |
+
reporting
|
| 915 |
+
quarters after the
|
| 916 |
+
expiration date
|
| 917 |
+
Unqualified Audit
|
| 918 |
+
Opinion
|
| 919 |
+
|
| 920 |
+
Produced Quarterly and
|
| 921 |
+
year-end Financial
|
| 922 |
+
Statements by deadlines
|
| 923 |
+
|
| 924 |
+
Received Assertion of
|
| 925 |
+
FFMIA Compliance -
|
| 926 |
+
Implemented required
|
| 927 |
+
changes to SGL and
|
| 928 |
+
transactions
|
| 929 |
+
|
| 930 |
+
NSF FAS 1-3-07
|
| 931 |
+
|
| 932 |
+
7 of 18
|
| 933 |
+
|
| 934 |
+
FY08 Exhibit 300
|
| 935 |
+
|
| 936 |
+
Fiscal Year
|
| 937 |
+
|
| 938 |
+
Strategic
|
| 939 |
+
Goal(s)
|
| 940 |
+
Supported
|
| 941 |
+
|
| 942 |
+
Performance Measure
|
| 943 |
+
|
| 944 |
+
Actual/
|
| 945 |
+
Baseline (from
|
| 946 |
+
previous year)
|
| 947 |
+
|
| 948 |
+
Planned
|
| 949 |
+
Performance
|
| 950 |
+
Metric (Target)
|
| 951 |
+
|
| 952 |
+
Performance Metric
|
| 953 |
+
Results (Actual)
|
| 954 |
+
|
| 955 |
+
2009
|
| 956 |
+
|
| 957 |
+
2009
|
| 958 |
+
|
| 959 |
+
2009
|
| 960 |
+
|
| 961 |
+
2009
|
| 962 |
+
|
| 963 |
+
2009
|
| 964 |
+
|
| 965 |
+
2010
|
| 966 |
+
|
| 967 |
+
2011
|
| 968 |
+
|
| 969 |
+
2010
|
| 970 |
+
|
| 971 |
+
2010
|
| 972 |
+
|
| 973 |
+
2010
|
| 974 |
+
|
| 975 |
+
2011-
|
| 976 |
+
|
| 977 |
+
2011
|
| 978 |
+
|
| 979 |
+
2011
|
| 980 |
+
|
| 981 |
+
2011
|
| 982 |
+
|
| 983 |
+
2011
|
| 984 |
+
|
| 985 |
+
All new IT investments initiated for FY 2005 and beyond must use Table 2 and are required to use the
|
| 986 |
+
Federal Enterprise Architecture (FEA) Performance Reference Model (PRM). Please use Table 2 and the
|
| 987 |
+
PRM to identify the performance information pertaining to this major IT investment. Map all Measurement
|
| 988 |
+
Indicators to the corresponding "Measurement Area" and "Measurement Grouping" identified in the PRM.
|
| 989 |
+
There should be at least one Measurement Indicator for at least four different Measurement Areas (for each
|
| 990 |
+
fiscal year). The PRM is available at www.egov.gov.
|
| 991 |
+
|
| 992 |
+
NSF FAS 1-3-07
|
| 993 |
+
|
| 994 |
+
8 of 18
|
| 995 |
+
|
| 996 |
+
FY08 Exhibit 300
|
| 997 |
+
|
| 998 |
+
Table 2
|
| 999 |
+
Fiscal
|
| 1000 |
+
Year
|
| 1001 |
+
|
| 1002 |
+
Measurement Area IT
|
| 1003 |
+
|
| 1004 |
+
Measurement Grouping IT
|
| 1005 |
+
|
| 1006 |
+
Measurement
|
| 1007 |
+
I di
|
| 1008 |
+
|
| 1009 |
+
t
|
| 1010 |
+
|
| 1011 |
+
Baseline Planned
|
| 1012 |
+
|
| 1013 |
+
Actual Results
|
| 1014 |
+
|
| 1015 |
+
Improvement to
|
| 1016 |
+
the Baseline
|
| 1017 |
+
|
| 1018 |
+
Section E: Security and Privacy (IT Capital Assets Only)
|
| 1019 |
+
|
| 1020 |
+
In order to successfully address this area of the business case, each question below must be answered at the
|
| 1021 |
+
system/application level, not at a program or agency level. Systems supporting this investment on the planning and
|
| 1022 |
+
operational systems security tables should match the systems on the privacy table below. Systems on the Operational
|
| 1023 |
+
Security Table must be included on your agency FISMA system inventory and should be easily referenced in the
|
| 1024 |
+
inventory (i.e., should use the same name or identifier).
|
| 1025 |
+
|
| 1026 |
+
All systems supporting and/or part of this investment should be included in the tables below, inclusive of both agency
|
| 1027 |
+
owned systems and contractor systems. For IT investments under development, security and privacy planning must
|
| 1028 |
+
proceed in parallel with the development of the system/s to ensure IT security and privacy requirements and costs are
|
| 1029 |
+
identified and incorporated into the overall lifecycle of the system/s.
|
| 1030 |
+
|
| 1031 |
+
Please respond to the questions below and verify the system owner took the following actions:
|
| 1032 |
+
|
| 1033 |
+
(1) Have the IT security costs for the system(s) been identified and integrated into the overall costs of the
|
| 1034 |
+
|
| 1035 |
+
investment: yes
|
| 1036 |
+
|
| 1037 |
+
(a) If "yes," provide the "Percentage IT Security" for the budget year: 14
|
| 1038 |
+
|
| 1039 |
+
(2) Is identifying and assessing security and privacy risks a part of the overall risk management effort for
|
| 1040 |
+
each system supporting or part of this investment. yes
|
| 1041 |
+
|
| 1042 |
+
(3) Systems in Planning - Security:
|
| 1043 |
+
|
| 1044 |
+
Name Of System
|
| 1045 |
+
|
| 1046 |
+
Agency Or Contractor Operated
|
| 1047 |
+
|
| 1048 |
+
System?
|
| 1049 |
+
|
| 1050 |
+
Planned Operational Date
|
| 1051 |
+
|
| 1052 |
+
Planned or Actual
|
| 1053 |
+
C&A Completion Date
|
| 1054 |
+
|
| 1055 |
+
(4) Operational Systems - Security:
|
| 1056 |
+
|
| 1057 |
+
Name Of System
|
| 1058 |
+
|
| 1059 |
+
Agency Or Contractor
|
| 1060 |
+
Operated system
|
| 1061 |
+
|
| 1062 |
+
NIST FIPS
|
| 1063 |
+
199
|
| 1064 |
+
|
| 1065 |
+
Risk Impact
|
| 1066 |
+
Level (High,
|
| 1067 |
+
Moderate,
|
| 1068 |
+
Low)
|
| 1069 |
+
|
| 1070 |
+
Has the
|
| 1071 |
+
C&A been
|
| 1072 |
+
completed
|
| 1073 |
+
using
|
| 1074 |
+
NIST 800-
|
| 1075 |
+
37?
|
| 1076 |
+
|
| 1077 |
+
Date C&A
|
| 1078 |
+
Complete
|
| 1079 |
+
|
| 1080 |
+
What standards we
|
| 1081 |
+
used for the
|
| 1082 |
+
Security Controls
|
| 1083 |
+
tests?
|
| 1084 |
+
|
| 1085 |
+
Date Completed
|
| 1086 |
+
|
| 1087 |
+
Security
|
| 1088 |
+
Control Testing
|
| 1089 |
+
|
| 1090 |
+
Date
|
| 1091 |
+
Contingency
|
| 1092 |
+
Plan Tested
|
| 1093 |
+
|
| 1094 |
+
FAS
|
| 1095 |
+
|
| 1096 |
+
Contractor and
|
| 1097 |
+
Government
|
| 1098 |
+
|
| 1099 |
+
High
|
| 1100 |
+
|
| 1101 |
+
yes
|
| 1102 |
+
|
| 1103 |
+
04/05/06
|
| 1104 |
+
|
| 1105 |
+
FIPS 200 / NIST
|
| 1106 |
+
800-53
|
| 1107 |
+
|
| 1108 |
+
01/18/06
|
| 1109 |
+
|
| 1110 |
+
02/15/06
|
| 1111 |
+
|
| 1112 |
+
(5) Have any weaknesses, not yet remediated, related to any of the systems part of or supporting this
|
| 1113 |
+
investment been identified by the agency or IG? no
|
| 1114 |
+
|
| 1115 |
+
(a) If "yes," have those weaknesses been incorporated into the agency's plan of action and milestone
|
| 1116 |
+
|
| 1117 |
+
process?
|
| 1118 |
+
|
| 1119 |
+
(6) Indicate whether an increase in IT security funding is requested to remediate IT security
|
| 1120 |
+
weaknesses? no
|
| 1121 |
+
|
| 1122 |
+
NSF FAS 1-3-07
|
| 1123 |
+
|
| 1124 |
+
9 of 18
|
| 1125 |
+
|
| 1126 |
+
FY08 Exhibit 300
|
| 1127 |
+
|
| 1128 |
+
(a) If "yes," specify the amount, a general description of the weakness, and how the funding request
|
| 1129 |
+
will remediate the weakness.
|
| 1130 |
+
|
| 1131 |
+
(7) How are contractor security procedures monitored, verified, and validated by the agency for
|
| 1132 |
+
|
| 1133 |
+
the contractor systems above?
|
| 1134 |
+
|
| 1135 |
+
NSF uses a range of methods to review the security of operations through contract requirements, project
|
| 1136 |
+
management oversight and review, certification and accreditation processes, IG independent reviews,
|
| 1137 |
+
proactive testing of controls through penetration testing and vulnerability scans to ensure services are
|
| 1138 |
+
adequately secure and meet the requirements of FISMA, OMB policy, NIST guidelines and NSF policy. The
|
| 1139 |
+
system is operated on-site by a team of contractors and NSF personnel with system administrators tightly
|
| 1140 |
+
controlling access to the systems. Only administrators with current need have access to the system,
|
| 1141 |
+
and strict code migration, quality control, and configuration management procedures prevent deployment of
|
| 1142 |
+
hostile or vulnerable software on the systems. Contractors are trained in the same security measures as
|
| 1143 |
+
NSF employees. All NSF employees and contract staff are required to complete an on-line security training
|
| 1144 |
+
class each year, including the rules of behavior. Background checks are done routinely as a part of the
|
| 1145 |
+
NSF contracting process, and IT security requirements are stated in the contracts statement of work.
|
| 1146 |
+
Contractor security procedures are monitored, verified, and validated by the agency in the same way as for
|
| 1147 |
+
government employees. Once on board, contractors are allowed access to the NSF systems based on their
|
| 1148 |
+
specific job requirements. Audit logs are also implemented to monitor operating system changes - these
|
| 1149 |
+
audit logs are reviewed by the system administrators. Additionally, roles and responsibilities are separated
|
| 1150 |
+
to the extent possible to allow for checks and balances in system management and multiple levels of
|
| 1151 |
+
oversight.
|
| 1152 |
+
|
| 1153 |
+
(8) Planning and Operational Systems - Privacy:
|
| 1154 |
+
|
| 1155 |
+
(a) Name Of System
|
| 1156 |
+
|
| 1157 |
+
(b) Is this a
|
| 1158 |
+
new system?
|
| 1159 |
+
|
| 1160 |
+
(c) Is there a PIA that
|
| 1161 |
+
covers this system? •
|
| 1162 |
+
|
| 1163 |
+
(d) Is the PIA available to the public?
|
| 1164 |
+
|
| 1165 |
+
F A S
|
| 1166 |
+
|
| 1167 |
+
no
|
| 1168 |
+
|
| 1169 |
+
1. Y e s .
|
| 1170 |
+
|
| 1171 |
+
2 . No, because a PIA is not yet
|
| 1172 |
+
|
| 1173 |
+
required to be completed at this time.
|
| 1174 |
+
|
| 1175 |
+
(e) Is a
|
| 1176 |
+
System
|
| 1177 |
+
Records
|
| 1178 |
+
Notice
|
| 1179 |
+
(SORN)
|
| 1180 |
+
required for
|
| 1181 |
+
this system?
|
| 1182 |
+
|
| 1183 |
+
no
|
| 1184 |
+
|
| 1185 |
+
(I) Was a new or amended SORN
|
| 1186 |
+
published in FY06?
|
| 1187 |
+
|
| 1188 |
+
5. No, because the system is
|
| 1189 |
+
|
| 1190 |
+
not a Privacy Act system of
|
| 1191 |
+
|
| 1192 |
+
records.
|
| 1193 |
+
|
| 1194 |
+
(c) Is there a Privacy Impact Assessment (PIA) that covers this system?
|
| 1195 |
+
|
| 1196 |
+
1. Yes.
|
| 1197 |
+
2. No.
|
| 1198 |
+
3. No, because the system does not contain, process, or transmit personal identifying information.
|
| 1199 |
+
4. No, because even though it has personal identifying information, the system contains information solely about
|
| 1200 |
+
|
| 1201 |
+
federal employees and agency contractors.
|
| 1202 |
+
|
| 1203 |
+
(d) Is the PIA available to the public?
|
| 1204 |
+
|
| 1205 |
+
1. Yes.
|
| 1206 |
+
2. No, because a PIA is not yet required to be completed at this time.
|
| 1207 |
+
3. No, because the PIA has not been prepared.
|
| 1208 |
+
|
| 1209 |
+
(f) Was a new or amended SORN published in FY2006?
|
| 1210 |
+
|
| 1211 |
+
NSF FAS 1-3-07
|
| 1212 |
+
|
| 1213 |
+
10 of 18
|
| 1214 |
+
|
| 1215 |
+
FY08 Exhibit 300
|
| 1216 |
+
|
| 1217 |
+
1. Yes, because this is a newly established Privacy Act system of records.
|
| 1218 |
+
2. Yes, because the existing Privacy Act system of records was substantially revised in FY 06.
|
| 1219 |
+
3. No, because the existing Privacy Act system of records was not substantially revised in FY 06.
|
| 1220 |
+
4. No; the system is operational, but the SORN has not yet been published.
|
| 1221 |
+
5. No, because the system is not a Privacy Act system of records.
|
| 1222 |
+
|
| 1223 |
+
Section F: Enterprise Architecture (EA) (IT Capital Assets Only)
|
| 1224 |
+
|
| 1225 |
+
In order to successfully address this area of the business case and capital asset plan you must ensure
|
| 1226 |
+
the investment is included in the agency's EA and Capital Planning and Investment Control (CPIC)
|
| 1227 |
+
process, and is mapped to and supports the FEA. You must also ensure the business case demonstrates
|
| 1228 |
+
the relationship between the investment and the business, performance, data, services, application, and
|
| 1229 |
+
technology layers of the agency's EA.
|
| 1230 |
+
|
| 1231 |
+
(1) Is this investment included in your agency's target enterprise architecture? yes (a)
|
| 1232 |
+
|
| 1233 |
+
If "no," please explain why?
|
| 1234 |
+
|
| 1235 |
+
(2) Is this investment included in the agency's EA Transition Strategy? yes
|
| 1236 |
+
|
| 1237 |
+
a. If "yes," provide the
|
| 1238 |
+
investment name as identified
|
| 1239 |
+
in the Transition Strategy
|
| 1240 |
+
provided in the agency's most
|
| 1241 |
+
recent annual EA
|
| 1242 |
+
Assessment.
|
| 1243 |
+
b. If "no," please explain
|
| 1244 |
+
why?
|
| 1245 |
+
|
| 1246 |
+
The Financial Accounting System (FAS) is included as part of the Next
|
| 1247 |
+
Generation Grants Management workstream in the EA Transition Strategy
|
| 1248 |
+
submitted to OMB on February 28, 2006.
|
| 1249 |
+
|
| 1250 |
+
(3) Identify the service components funded by this major IT investment (e.g., knowledge
|
| 1251 |
+
management, content management, customer relationship management, etc.). Provide this
|
| 1252 |
+
information in the format of the following table. For detailed guidance regarding components,
|
| 1253 |
+
please refer to http://www.whitehouse.gov/omb/egov/.
|
| 1254 |
+
|
| 1255 |
+
Agency
|
| 1256 |
+
Component
|
| 1257 |
+
Name
|
| 1258 |
+
|
| 1259 |
+
Agency
|
| 1260 |
+
Comonent
|
| 1261 |
+
p
|
| 1262 |
+
|
| 1263 |
+
Description
|
| 1264 |
+
|
| 1265 |
+
Advice of BEP Maintenance of
|
| 1266 |
+
|
| 1267 |
+
FEASRM
|
| 1268 |
+
Service Type
|
| 1269 |
+
|
| 1270 |
+
FEA SRM
|
| 1271 |
+
Component
|
| 1272 |
+
(a)
|
| 1273 |
+
|
| 1274 |
+
Billing and
|
| 1275 |
+
|
| 1276 |
+
FEA Service Component Reused (b)
|
| 1277 |
+
|
| 1278 |
+
Reused Service
|
| 1279 |
+
Component Name
|
| 1280 |
+
|
| 1281 |
+
Reused Service Component
|
| 1282 |
+
UPI
|
| 1283 |
+
|
| 1284 |
+
Internal External
|
| 1285 |
+
Reuse (c)
|
| 1286 |
+
|
| 1287 |
+
Funding
|
| 1288 |
+
Percentage
|
| 1289 |
+
(d)
|
| 1290 |
+
|
| 1291 |
+
No Reuse
|
| 1292 |
+
|
| 1293 |
+
10
|
| 1294 |
+
|
| 1295 |
+
Charge Card
|
| 1296 |
+
Module
|
| 1297 |
+
|
| 1298 |
+
FASTRAN
|
| 1299 |
+
|
| 1300 |
+
AP Log
|
| 1301 |
+
|
| 1302 |
+
Funding
|
| 1303 |
+
Allocations
|
| 1304 |
+
Charge Card
|
| 1305 |
+
Bill Processing
|
| 1306 |
+
|
| 1307 |
+
Transaction
|
| 1308 |
+
Processing
|
| 1309 |
+
Module
|
| 1310 |
+
|
| 1311 |
+
Accounts
|
| 1312 |
+
Payable/Prompt
|
| 1313 |
+
Pay and Invoice
|
| 1314 |
+
tracking
|
| 1315 |
+
|
| 1316 |
+
Management
|
| 1317 |
+
|
| 1318 |
+
Credit /
|
| 1319 |
+
Charge
|
| 1320 |
+
|
| 1321 |
+
Management
|
| 1322 |
+
|
| 1323 |
+
Financials
|
| 1324 |
+
|
| 1325 |
+
Management
|
| 1326 |
+
|
| 1327 |
+
Expense
|
| 1328 |
+
Management
|
| 1329 |
+
|
| 1330 |
+
Financial
|
| 1331 |
+
|
| 1332 |
+
Management
|
| 1333 |
+
|
| 1334 |
+
Payment /
|
| 1335 |
+
Settlement
|
| 1336 |
+
|
| 1337 |
+
No Reuse
|
| 1338 |
+
|
| 1339 |
+
No Reuse
|
| 1340 |
+
|
| 1341 |
+
No Reuse
|
| 1342 |
+
|
| 1343 |
+
3
|
| 1344 |
+
|
| 1345 |
+
10
|
| 1346 |
+
|
| 1347 |
+
7
|
| 1348 |
+
|
| 1349 |
+
NSF FAS 1-3-07
|
| 1350 |
+
|
| 1351 |
+
11 of 18
|
| 1352 |
+
|
| 1353 |
+
FY08 Exhibit 300
|
| 1354 |
+
|
| 1355 |
+
Agency
|
| 1356 |
+
Componen
|
| 1357 |
+
Name
|
| 1358 |
+
|
| 1359 |
+
FASTRAN
|
| 1360 |
+
|
| 1361 |
+
FAS Core
|
| 1362 |
+
|
| 1363 |
+
Agency
|
| 1364 |
+
Component
|
| 1365 |
+
Description
|
| 1366 |
+
|
| 1367 |
+
FEASRM
|
| 1368 |
+
Service Type
|
| 1369 |
+
|
| 1370 |
+
FEA SRM
|
| 1371 |
+
Component
|
| 1372 |
+
(a)
|
| 1373 |
+
|
| 1374 |
+
FEA Service Component Reused (b)
|
| 1375 |
+
|
| 1376 |
+
Reused Service
|
| 1377 |
+
Component Name
|
| 1378 |
+
|
| 1379 |
+
Reused Service Component
|
| 1380 |
+
UPI
|
| 1381 |
+
|
| 1382 |
+
Internal External
|
| 1383 |
+
Reuse(c)
|
| 1384 |
+
|
| 1385 |
+
Funding
|
| 1386 |
+
Percentage
|
| 1387 |
+
(d)
|
| 1388 |
+
|
| 1389 |
+
Transaction
|
| 1390 |
+
Processing
|
| 1391 |
+
Module
|
| 1392 |
+
|
| 1393 |
+
Financial
|
| 1394 |
+
Management
|
| 1395 |
+
|
| 1396 |
+
Debt
|
| 1397 |
+
Collection
|
| 1398 |
+
|
| 1399 |
+
Core
|
| 1400 |
+
Functionally of
|
| 1401 |
+
Accounting
|
| 1402 |
+
System
|
| 1403 |
+
|
| 1404 |
+
Internal
|
| 1405 |
+
Controls
|
| 1406 |
+
|
| 1407 |
+
Financial
|
| 1408 |
+
|
| 1409 |
+
Management
|
| 1410 |
+
|
| 1411 |
+
No Reuse
|
| 1412 |
+
|
| 1413 |
+
10
|
| 1414 |
+
|
| 1415 |
+
No Reuse
|
| 1416 |
+
|
| 1417 |
+
60
|
| 1418 |
+
|
| 1419 |
+
a. Use existing SRM Components or identify as "NEW". A "NEW" component is one not already
|
| 1420 |
+
identified as a service component in the FEA SRM.
|
| 1421 |
+
|
| 1422 |
+
b. A reused component is one being funded by another investment, but being used by this
|
| 1423 |
+
investment. Rather than answer yes or no, identify the reused service component funded by the other
|
| 1424 |
+
investment and identify the other investment using the Unique Project Identifier (UPI) code from the
|
| 1425 |
+
OMB Ex 300 or Ex 53 submission.
|
| 1426 |
+
|
| 1427 |
+
c. 'Internal' reuse is within an agency. For example, one agency within a department is reusing a
|
| 1428 |
+
service component provided by another agency within the same department. 'External' reuse is one
|
| 1429 |
+
agency within a department reusing a service component provided by another agency in another
|
| 1430 |
+
department. A good example of this is an E-Gov initiatiye service being reused by multiple
|
| 1431 |
+
organizations across the federal government.
|
| 1432 |
+
|
| 1433 |
+
d. Please provide the percentage of the BY requested funding amount used for each service
|
| 1434 |
+
component listed in the table. If external, provide the funding level transferred to another agency to
|
| 1435 |
+
pay for the service.
|
| 1436 |
+
|
| 1437 |
+
4. To demonstrate how this major IT investment aligns with the FEA Technical Reference Model
|
| 1438 |
+
(TRM), please list the Service Areas, Categories, Standards, and Service Specifications supporting
|
| 1439 |
+
this IT investment.
|
| 1440 |
+
|
| 1441 |
+
FEA SRM Component (a) FEA TRM Service Area
|
| 1442 |
+
Billing and Accounting
|
| 1443 |
+
|
| 1444 |
+
Service Access and
|
| 1445 |
+
|
| 1446 |
+
FEA TRM Service Category
|
| 1447 |
+
Access Channels
|
| 1448 |
+
|
| 1449 |
+
FEA TRM Service Standard
|
| 1450 |
+
Other Electronic Channels
|
| 1451 |
+
|
| 1452 |
+
FEAService Specification (b)
|
| 1453 |
+
|
| 1454 |
+
Billing and Accounting
|
| 1455 |
+
|
| 1456 |
+
Delivery
|
| 1457 |
+
|
| 1458 |
+
Delivery Channels
|
| 1459 |
+
|
| 1460 |
+
Intranet
|
| 1461 |
+
|
| 1462 |
+
Billing and Accounting
|
| 1463 |
+
|
| 1464 |
+
Billing and Accounting
|
| 1465 |
+
|
| 1466 |
+
Service Access and
|
| 1467 |
+
|
| 1468 |
+
Delivery
|
| 1469 |
+
|
| 1470 |
+
Service Access and
|
| 1471 |
+
Delivery
|
| 1472 |
+
|
| 1473 |
+
Service Access and
|
| 1474 |
+
Delivery
|
| 1475 |
+
|
| 1476 |
+
Service Requirements
|
| 1477 |
+
|
| 1478 |
+
Legislative / Compliance
|
| 1479 |
+
|
| 1480 |
+
Service Transport
|
| 1481 |
+
|
| 1482 |
+
Service Transport
|
| 1483 |
+
|
| 1484 |
+
Billing and Accounting.
|
| 1485 |
+
|
| 1486 |
+
Service Platform and
|
| 1487 |
+
|
| 1488 |
+
Support Platforms
|
| 1489 |
+
|
| 1490 |
+
Platform Dependent
|
| 1491 |
+
|
| 1492 |
+
Windows XP
|
| 1493 |
+
|
| 1494 |
+
Billing and Accounting
|
| 1495 |
+
|
| 1496 |
+
Billing and Accounting
|
| 1497 |
+
|
| 1498 |
+
Billing and Accounting
|
| 1499 |
+
|
| 1500 |
+
Infrastructure
|
| 1501 |
+
|
| 1502 |
+
Service Platform and
|
| 1503 |
+
|
| 1504 |
+
Infrastructure
|
| 1505 |
+
|
| 1506 |
+
Service Platform and
|
| 1507 |
+
|
| 1508 |
+
Infrastructure
|
| 1509 |
+
|
| 1510 |
+
Service Platform and
|
| 1511 |
+
|
| 1512 |
+
Infrastructure
|
| 1513 |
+
|
| 1514 |
+
Delivery Servers
|
| 1515 |
+
|
| 1516 |
+
Application Servers
|
| 1517 |
+
|
| 1518 |
+
Windows NT
|
| 1519 |
+
|
| 1520 |
+
Database / Storage
|
| 1521 |
+
|
| 1522 |
+
Database
|
| 1523 |
+
|
| 1524 |
+
Sybase 12,x
|
| 1525 |
+
|
| 1526 |
+
Hardware / Infrastructure
|
| 1527 |
+
|
| 1528 |
+
Servers / Computers
|
| 1529 |
+
|
| 1530 |
+
Windows NT
|
| 1531 |
+
|
| 1532 |
+
NSF FAS 1-3-07
|
| 1533 |
+
|
| 1534 |
+
12 of 18
|
| 1535 |
+
|
| 1536 |
+
FY08 Exhibit 300
|
| 1537 |
+
|
| 1538 |
+
Billing and Accounting
|
| 1539 |
+
|
| 1540 |
+
Billing and Accounting
|
| 1541 |
+
|
| 1542 |
+
Billing and Accounting
|
| 1543 |
+
Billing and Accounting
|
| 1544 |
+
|
| 1545 |
+
Component Framework Presentation / Interface
|
| 1546 |
+
|
| 1547 |
+
Static Display
|
| 1548 |
+
|
| 1549 |
+
Component Framework Data Management
|
| 1550 |
+
|
| 1551 |
+
Database Connectivity.
|
| 1552 |
+
|
| 1553 |
+
Sybase 12.x
|
| 1554 |
+
|
| 1555 |
+
Component Framework Data Management
|
| 1556 |
+
|
| 1557 |
+
Service Interface and
|
| 1558 |
+
|
| 1559 |
+
Integration
|
| 1560 |
+
|
| 1561 |
+
Integration
|
| 1562 |
+
|
| 1563 |
+
Reporting and Analysis
|
| 1564 |
+
Enterprise Application
|
| 1565 |
+
|
| 1566 |
+
Integration
|
| 1567 |
+
|
| 1568 |
+
Billing and Accounting
|
| 1569 |
+
|
| 1570 |
+
Service Interface and
|
| 1571 |
+
|
| 1572 |
+
lnteroperability
|
| 1573 |
+
|
| 1574 |
+
Data Transformation
|
| 1575 |
+
|
| 1576 |
+
Integration
|
| 1577 |
+
|
| 1578 |
+
Billing and Accounting
|
| 1579 |
+
|
| 1580 |
+
Service Interface and
|
| 1581 |
+
|
| 1582 |
+
Interface
|
| 1583 |
+
|
| 1584 |
+
Service Description
|
| 1585 |
+
|
| 1586 |
+
API
|
| 1587 |
+
|
| 1588 |
+
Credit / Charge
|
| 1589 |
+
|
| 1590 |
+
Service Access and
|
| 1591 |
+
|
| 1592 |
+
Access Channels
|
| 1593 |
+
|
| 1594 |
+
Other Electronic Channels
|
| 1595 |
+
|
| 1596 |
+
Integration
|
| 1597 |
+
|
| 1598 |
+
Interface
|
| 1599 |
+
|
| 1600 |
+
Delivery
|
| 1601 |
+
|
| 1602 |
+
Credit / Charge
|
| 1603 |
+
|
| 1604 |
+
Service Access and
|
| 1605 |
+
|
| 1606 |
+
Delivery Channels
|
| 1607 |
+
|
| 1608 |
+
Intranet
|
| 1609 |
+
|
| 1610 |
+
Delivery
|
| 1611 |
+
|
| 1612 |
+
Credit / Charge
|
| 1613 |
+
|
| 1614 |
+
Service Access and
|
| 1615 |
+
|
| 1616 |
+
Service Requirements
|
| 1617 |
|
| 1618 |
+
Legislative / Compliance
|
| 1619 |
|
| 1620 |
+
Credit / Charge
|
| 1621 |
|
| 1622 |
+
Service Access and
|
| 1623 |
|
| 1624 |
+
Service Transport
|
| 1625 |
|
| 1626 |
+
Service Transport
|
| 1627 |
|
| 1628 |
+
Delivery
|
| 1629 |
|
| 1630 |
+
Credit / Charge
|
| 1631 |
|
| 1632 |
+
Credit / Charge
|
| 1633 |
|
| 1634 |
+
Credit / Charge
|
| 1635 |
|
| 1636 |
+
Credit / Charge
|
| 1637 |
|
| 1638 |
+
Delivery.
|
| 1639 |
|
| 1640 |
+
Service Platform and
|
| 1641 |
|
| 1642 |
+
Infrastructure
|
| 1643 |
|
| 1644 |
+
Service Platform and
|
| 1645 |
|
| 1646 |
+
Infrastructure
|
| 1647 |
|
| 1648 |
+
Service Platform and
|
| 1649 |
|
| 1650 |
+
Infrastructure
|
| 1651 |
|
| 1652 |
+
Service Platform and
|
| 1653 |
|
| 1654 |
+
Infrastructure
|
| 1655 |
|
| 1656 |
+
Support Platforms
|
| 1657 |
|
| 1658 |
+
Platform Dependent
|
| 1659 |
|
| 1660 |
+
Windows XP
|
| 1661 |
|
| 1662 |
+
Delivery Servers
|
| 1663 |
|
| 1664 |
+
Application Servers
|
| 1665 |
|
| 1666 |
+
Windows NT
|
| 1667 |
|
| 1668 |
+
Database / Storage
|
| 1669 |
|
| 1670 |
+
Database:
|
| 1671 |
|
| 1672 |
+
Sybase 12,x
|
| 1673 |
|
| 1674 |
+
Hardware / Infrastructure Servers / Computers
|
| 1675 |
|
| 1676 |
+
Windows NT
|
| 1677 |
|
| 1678 |
+
Credit / Charge
|
| 1679 |
|
| 1680 |
+
Component Framework
|
| 1681 |
|
| 1682 |
+
Presentation / Interface
|
| 1683 |
|
| 1684 |
+
Static Display
|
| 1685 |
|
| 1686 |
+
Credit / Charge
|
| 1687 |
|
| 1688 |
+
Component Framework Data Management
|
| 1689 |
|
| 1690 |
+
Database Connectivity
|
| 1691 |
|
| 1692 |
+
Sybase 12.x
|
| 1693 |
|
| 1694 |
+
Credit / Charge
|
| 1695 |
|
| 1696 |
+
Component Framework Data Management
|
| 1697 |
|
| 1698 |
+
Credit / Charge
|
| 1699 |
|
| 1700 |
+
Service Interface and
|
| 1701 |
|
| 1702 |
+
Integration;
|
| 1703 |
|
| 1704 |
+
Reporting and Analysis
|
| 1705 |
|
| 1706 |
+
.
|
| 1707 |
|
| 1708 |
+
Enterprise Application
|
| 1709 |
+
Integration
|
| 1710 |
|
| 1711 |
+
Credit / Charge
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1712 |
|
| 1713 |
+
Credit / Charge
|
| 1714 |
|
| 1715 |
+
Integration
|
| 1716 |
|
| 1717 |
+
Service Interface and
|
| 1718 |
|
| 1719 |
+
Integration
|
| 1720 |
|
| 1721 |
+
Service Interface and
|
| 1722 |
+
Integration
|
| 1723 |
|
| 1724 |
+
lnteroperability
|
| 1725 |
|
| 1726 |
+
Data Transformation
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1727 |
|
| 1728 |
+
Interface
|
| 1729 |
|
| 1730 |
+
Service Description /
|
| 1731 |
|
| 1732 |
+
API
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1733 |
|
| 1734 |
+
Interface
|
| 1735 |
|
| 1736 |
+
Expense Management
|
| 1737 |
|
| 1738 |
+
Service Access and
|
| 1739 |
|
| 1740 |
+
Access Channels
|
| 1741 |
|
| 1742 |
+
Other Electronic Channels
|
| 1743 |
|
| 1744 |
+
Delivery
|
| 1745 |
|
| 1746 |
+
Expense Management
|
| 1747 |
|
| 1748 |
+
Service Access and
|
| 1749 |
|
| 1750 |
+
Delivery Channels
|
| 1751 |
|
| 1752 |
+
Intranet
|
| 1753 |
|
| 1754 |
+
Delivery
|
| 1755 |
|
| 1756 |
+
Expense Management
|
| 1757 |
|
| 1758 |
+
Service Access and
|
| 1759 |
|
| 1760 |
+
Service Requirements
|
| 1761 |
|
| 1762 |
+
Legislative / Compliance
|
| 1763 |
|
| 1764 |
+
Expense Management
|
| 1765 |
|
| 1766 |
+
Service Access and
|
| 1767 |
|
| 1768 |
+
Service Transport
|
| 1769 |
|
| 1770 |
+
Service Transport
|
| 1771 |
|
| 1772 |
+
Delivery
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1773 |
|
| 1774 |
+
Delivery
|
| 1775 |
|
| 1776 |
+
Expense Management
|
| 1777 |
|
| 1778 |
+
Service Platform and
|
| 1779 |
|
| 1780 |
+
Support Platforms
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1781 |
|
| 1782 |
+
Platform Dependent
|
| 1783 |
|
| 1784 |
+
Windows XP
|
| 1785 |
|
| 1786 |
+
Infrastructure
|
| 1787 |
|
| 1788 |
+
Expense Management
|
| 1789 |
|
| 1790 |
+
Service Platform and
|
| 1791 |
|
| 1792 |
+
Delivery Servers
|
| 1793 |
|
| 1794 |
+
Application Servers
|
| 1795 |
|
| 1796 |
+
Windows NT
|
| 1797 |
|
| 1798 |
+
Expense Management
|
| 1799 |
|
| 1800 |
+
Service Platform and
|
| 1801 |
|
| 1802 |
+
Database / Storage
|
| 1803 |
|
| 1804 |
+
Database,
|
| 1805 |
|
| 1806 |
+
Sybase 12,x
|
| 1807 |
|
| 1808 |
+
Infrastructure
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1809 |
|
| 1810 |
+
Infrastructure
|
| 1811 |
|
| 1812 |
+
NSF FAS 1-3-07
|
| 1813 |
|
| 1814 |
+
13 of 18
|
| 1815 |
|
| 1816 |
+
FY08 Exhibit 300
|
| 1817 |
|
| 1818 |
+
Expense Management
|
| 1819 |
|
| 1820 |
+
Service Platform and
|
| 1821 |
|
| 1822 |
+
Hardware / Infrastructure
|
| 1823 |
|
| 1824 |
+
Servers / Computers,
|
| 1825 |
|
| 1826 |
+
Windows NT
|
| 1827 |
|
| 1828 |
+
Infrastructure
|
| 1829 |
|
| 1830 |
+
Expense Management
|
| 1831 |
|
| 1832 |
+
Component Framework
|
| 1833 |
|
| 1834 |
+
Presentation / Interface
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1835 |
|
| 1836 |
+
Static Display
|
| 1837 |
|
| 1838 |
+
Expense Management
|
| 1839 |
|
| 1840 |
+
Component Framework Data Management
|
| 1841 |
|
| 1842 |
+
Database Connectivity
|
| 1843 |
|
| 1844 |
+
Sybase 12.x
|
| 1845 |
|
| 1846 |
+
Expense Management
|
| 1847 |
+
Expense Management
|
| 1848 |
|
| 1849 |
+
Component Framework Data Management
|
| 1850 |
|
| 1851 |
+
Reporting and Analysis
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1852 |
|
| 1853 |
+
Service Interface and
|
| 1854 |
|
| 1855 |
+
Integration
|
| 1856 |
|
| 1857 |
+
Integration
|
| 1858 |
|
| 1859 |
+
Enterprise Application
|
| 1860 |
|
| 1861 |
+
Integration
|
| 1862 |
|
| 1863 |
+
Expense Management.
|
| 1864 |
|
| 1865 |
+
Service Interface and
|
| 1866 |
|
| 1867 |
+
lnteroperability
|
| 1868 |
|
| 1869 |
+
Data Transformation
|
| 1870 |
|
| 1871 |
+
Integration:
|
| 1872 |
+
|
| 1873 |
+
Expense Management
|
| 1874 |
+
|
| 1875 |
+
Service Interface and
|
| 1876 |
+
|
| 1877 |
+
Interface
|
| 1878 |
+
|
| 1879 |
+
Service Description /
|
| 1880 |
+
|
| 1881 |
+
API
|
| 1882 |
+
|
| 1883 |
+
Payment / Settlement
|
| 1884 |
+
|
| 1885 |
+
Service Access and
|
| 1886 |
+
|
| 1887 |
+
Access Channels
|
| 1888 |
+
|
| 1889 |
+
Other Electronic Channels
|
| 1890 |
+
|
| 1891 |
+
Integration
|
| 1892 |
+
|
| 1893 |
+
Interface
|
| 1894 |
+
|
| 1895 |
+
Delivery
|
| 1896 |
+
|
| 1897 |
+
Payment / Settlement
|
| 1898 |
+
|
| 1899 |
+
Service Access and
|
| 1900 |
+
|
| 1901 |
+
Delivery Channels
|
| 1902 |
+
|
| 1903 |
+
Intranet
|
| 1904 |
+
|
| 1905 |
+
Delivery
|
| 1906 |
+
|
| 1907 |
+
Payment / Settlement
|
| 1908 |
+
|
| 1909 |
+
Service Access and
|
| 1910 |
+
|
| 1911 |
+
Service Requirements
|
| 1912 |
+
|
| 1913 |
+
Legislative / Compliance
|
| 1914 |
+
|
| 1915 |
+
Payment / Settlement
|
| 1916 |
+
|
| 1917 |
+
Payment / Settlement
|
| 1918 |
+
|
| 1919 |
+
Payment / Settlement
|
| 1920 |
+
|
| 1921 |
+
Delivery
|
| 1922 |
+
|
| 1923 |
+
Service Access and
|
| 1924 |
+
Delivery
|
| 1925 |
+
|
| 1926 |
+
Service Platform and
|
| 1927 |
+
|
| 1928 |
+
Infrastructure
|
| 1929 |
+
|
| 1930 |
+
Service Platform and
|
| 1931 |
+
|
| 1932 |
+
Infrastructure
|
| 1933 |
+
|
| 1934 |
+
Service Transport
|
| 1935 |
+
|
| 1936 |
+
Service Transport
|
| 1937 |
+
|
| 1938 |
+
Support Platforms
|
| 1939 |
+
|
| 1940 |
+
Platform Dependent
|
| 1941 |
+
|
| 1942 |
+
Windows XP
|
| 1943 |
+
|
| 1944 |
+
Delivery Servers
|
| 1945 |
+
|
| 1946 |
+
Application Servers
|
| 1947 |
+
|
| 1948 |
+
Windows NT
|
| 1949 |
+
|
| 1950 |
+
Payment / Settlement
|
| 1951 |
+
|
| 1952 |
+
Service Platform and
|
| 1953 |
+
|
| 1954 |
+
Database / Storage
|
| 1955 |
+
|
| 1956 |
+
Database
|
| 1957 |
+
|
| 1958 |
+
Sybase 12,x
|
| 1959 |
+
|
| 1960 |
+
Infrastructure
|
| 1961 |
+
|
| 1962 |
+
Payment / Settlement
|
| 1963 |
+
|
| 1964 |
+
Service Platform and
|
| 1965 |
+
|
| 1966 |
+
Hardware / Infrastructure
|
| 1967 |
+
|
| 1968 |
+
Servers / Computers
|
| 1969 |
+
|
| 1970 |
+
Windows NT
|
| 1971 |
+
|
| 1972 |
+
Payment / Settlement
|
| 1973 |
+
|
| 1974 |
+
Infrastructure
|
| 1975 |
+
Component Framework Presentation / Interface
|
| 1976 |
+
|
| 1977 |
+
Static Display
|
| 1978 |
+
|
| 1979 |
+
Payment / Settlement
|
| 1980 |
+
|
| 1981 |
+
Component Framework Data Management
|
| 1982 |
+
|
| 1983 |
+
Database Connectivity
|
| 1984 |
+
|
| 1985 |
+
Sybase 12.x
|
| 1986 |
+
|
| 1987 |
+
Payment / Settlement
|
| 1988 |
+
|
| 1989 |
+
Component Framework: Data Management
|
| 1990 |
+
|
| 1991 |
+
Reporting and Analysis,
|
| 1992 |
+
|
| 1993 |
+
Payment / Settlement
|
| 1994 |
+
|
| 1995 |
+
Service Interface and
|
| 1996 |
+
|
| 1997 |
+
Integration
|
| 1998 |
+
|
| 1999 |
+
Integration
|
| 2000 |
+
|
| 2001 |
+
Payment / Settlement
|
| 2002 |
+
|
| 2003 |
+
Service Interface and
|
| 2004 |
+
|
| 2005 |
+
Interoperability
|
| 2006 |
+
|
| 2007 |
+
Payment / Settlement
|
| 2008 |
+
|
| 2009 |
+
Debt Collection
|
| 2010 |
+
|
| 2011 |
+
Integration
|
| 2012 |
+
|
| 2013 |
+
Service Interface and
|
| 2014 |
+
Integration
|
| 2015 |
+
|
| 2016 |
+
Interface
|
| 2017 |
+
|
| 2018 |
+
Enterprise Application
|
| 2019 |
+
|
| 2020 |
+
Integration
|
| 2021 |
+
„..,,
|
| 2022 |
+
Data Transformation
|
| 2023 |
+
|
| 2024 |
+
Service Description /
|
| 2025 |
+
|
| 2026 |
+
Interface'
|
| 2027 |
+
|
| 2028 |
+
Service Access and
|
| 2029 |
+
|
| 2030 |
+
Delivery
|
| 2031 |
+
|
| 2032 |
+
Access Channels
|
| 2033 |
+
|
| 2034 |
+
Other Electronic Channels
|
| 2035 |
+
|
| 2036 |
+
Debt Collection
|
| 2037 |
+
|
| 2038 |
+
Service Access and
|
| 2039 |
+
|
| 2040 |
+
Delivery Channels
|
| 2041 |
+
|
| 2042 |
+
Intranet
|
| 2043 |
+
|
| 2044 |
+
Debt Collection
|
| 2045 |
+
|
| 2046 |
+
Debt Collection
|
| 2047 |
+
|
| 2048 |
+
Debt Collection
|
| 2049 |
+
|
| 2050 |
+
Debt Collection
|
| 2051 |
+
|
| 2052 |
+
Delivery
|
| 2053 |
+
|
| 2054 |
+
Service Access and
|
| 2055 |
+
|
| 2056 |
+
Delivery
|
| 2057 |
+
|
| 2058 |
+
Service Access and
|
| 2059 |
+
|
| 2060 |
+
Delivery
|
| 2061 |
+
|
| 2062 |
+
Service Platform and,
|
| 2063 |
+
|
| 2064 |
+
Infrastructure
|
| 2065 |
+
|
| 2066 |
+
Service Platform and
|
| 2067 |
+
|
| 2068 |
+
Infrastructure
|
| 2069 |
+
|
| 2070 |
+
Service Requirements
|
| 2071 |
+
|
| 2072 |
+
Legislative / Compliance
|
| 2073 |
+
|
| 2074 |
+
Service Transport
|
| 2075 |
+
|
| 2076 |
+
Service Transport
|
| 2077 |
+
|
| 2078 |
+
Support Platforms
|
| 2079 |
+
|
| 2080 |
+
Platform Dependent
|
| 2081 |
+
|
| 2082 |
+
Windows XP
|
| 2083 |
+
|
| 2084 |
+
Delivery Servers
|
| 2085 |
+
|
| 2086 |
+
!Application Servers
|
| 2087 |
+
|
| 2088 |
+
Windows NT
|
| 2089 |
+
|
| 2090 |
+
NSF FAS 1-3-07
|
| 2091 |
+
|
| 2092 |
+
14 of 18
|
| 2093 |
+
|
| 2094 |
+
FY08 Exhibit 300
|
| 2095 |
+
|
| 2096 |
+
Debt Collection
|
| 2097 |
+
|
| 2098 |
+
Debt Collection
|
| 2099 |
+
|
| 2100 |
+
Service Platform and
|
| 2101 |
+
|
| 2102 |
+
Infrastructure
|
| 2103 |
+
|
| 2104 |
+
Service Platform and
|
| 2105 |
+
|
| 2106 |
+
Infrastructure
|
| 2107 |
+
|
| 2108 |
+
Database / Storage
|
| 2109 |
+
|
| 2110 |
+
Database
|
| 2111 |
+
|
| 2112 |
+
Sybase 12,x
|
| 2113 |
+
|
| 2114 |
+
Hardware / Infrastructure
|
| 2115 |
+
|
| 2116 |
+
Servers / Computers
|
| 2117 |
+
|
| 2118 |
+
Windows NT
|
| 2119 |
+
|
| 2120 |
+
Debt Collection
|
| 2121 |
+
|
| 2122 |
+
Component Framework
|
| 2123 |
+
|
| 2124 |
+
Presentation / Interface
|
| 2125 |
+
|
| 2126 |
+
Static Display
|
| 2127 |
+
|
| 2128 |
+
Debt Collection
|
| 2129 |
+
|
| 2130 |
+
Component Framework Data Management
|
| 2131 |
+
|
| 2132 |
+
Database Connectivity
|
| 2133 |
+
|
| 2134 |
+
Sybase 12.x.
|
| 2135 |
+
|
| 2136 |
+
Debt Collection
|
| 2137 |
+
Debt Collection
|
| 2138 |
+
|
| 2139 |
+
Debt Collection
|
| 2140 |
+
|
| 2141 |
+
Debt Collection
|
| 2142 |
+
|
| 2143 |
+
Internal Controls
|
| 2144 |
+
|
| 2145 |
+
Internal Controls
|
| 2146 |
+
|
| 2147 |
+
Internal Controls
|
| 2148 |
+
|
| 2149 |
+
Internal Controls
|
| 2150 |
+
|
| 2151 |
+
Internal Controls
|
| 2152 |
+
|
| 2153 |
+
Internal Controls
|
| 2154 |
+
|
| 2155 |
+
Internal Controls
|
| 2156 |
+
|
| 2157 |
+
Internal Controls
|
| 2158 |
+
|
| 2159 |
+
Component Framework Data Management
|
| 2160 |
+
|
| 2161 |
+
Reporting and Analysis
|
| 2162 |
+
|
| 2163 |
+
Service Interface and
|
| 2164 |
+
Integration
|
| 2165 |
+
|
| 2166 |
+
Service Interface and
|
| 2167 |
+
Integration
|
| 2168 |
+
|
| 2169 |
+
Service Interface and
|
| 2170 |
+
Integration
|
| 2171 |
+
|
| 2172 |
+
Service Access and
|
| 2173 |
+
Delivery
|
| 2174 |
+
|
| 2175 |
+
Service Access and
|
| 2176 |
+
|
| 2177 |
+
Delivery
|
| 2178 |
+
|
| 2179 |
+
Service Access and
|
| 2180 |
+
|
| 2181 |
+
Delivery
|
| 2182 |
+
|
| 2183 |
+
Service Access and
|
| 2184 |
+
Delivery
|
| 2185 |
+
|
| 2186 |
+
Service Platform and
|
| 2187 |
+
|
| 2188 |
+
Infrastructure
|
| 2189 |
+
|
| 2190 |
+
Service Platform and
|
| 2191 |
+
|
| 2192 |
+
Infrastructure
|
| 2193 |
+
|
| 2194 |
+
Service Platform and
|
| 2195 |
+
|
| 2196 |
+
Infrastructure
|
| 2197 |
+
|
| 2198 |
+
Service Platform and
|
| 2199 |
+
|
| 2200 |
+
Infrastructure
|
| 2201 |
+
|
| 2202 |
+
Integration
|
| 2203 |
+
|
| 2204 |
+
Enterprise Application:
|
| 2205 |
+
|
| 2206 |
+
Integration
|
| 2207 |
+
|
| 2208 |
+
Interoperability
|
| 2209 |
+
|
| 2210 |
+
Data Transformation
|
| 2211 |
+
|
| 2212 |
+
Interface
|
| 2213 |
+
|
| 2214 |
+
Service Description /
|
| 2215 |
+
|
| 2216 |
+
Interface
|
| 2217 |
+
|
| 2218 |
+
API
|
| 2219 |
+
|
| 2220 |
+
Access Channels
|
| 2221 |
+
|
| 2222 |
+
:Other Electronic Channels.
|
| 2223 |
+
|
| 2224 |
+
Delivery Channels
|
| 2225 |
+
|
| 2226 |
+
Intranet
|
| 2227 |
+
|
| 2228 |
+
Service Requirements
|
| 2229 |
+
|
| 2230 |
+
Legislative / Compliance
|
| 2231 |
+
|
| 2232 |
+
Service Transport
|
| 2233 |
+
|
| 2234 |
+
Service Transport
|
| 2235 |
+
|
| 2236 |
+
Support Platforms
|
| 2237 |
+
|
| 2238 |
+
Platform Dependent
|
| 2239 |
+
|
| 2240 |
+
Windows XP
|
| 2241 |
+
|
| 2242 |
+
Delivery Servers
|
| 2243 |
+
|
| 2244 |
+
Application Servers
|
| 2245 |
+
|
| 2246 |
+
Windows NT
|
| 2247 |
+
|
| 2248 |
+
Database / Storage
|
| 2249 |
+
|
| 2250 |
+
Database
|
| 2251 |
+
|
| 2252 |
+
Sybase 12,x
|
| 2253 |
+
|
| 2254 |
+
Hardware / Infrastructure
|
| 2255 |
+
|
| 2256 |
+
Servers / Computers
|
| 2257 |
+
|
| 2258 |
+
Windows NT
|
| 2259 |
+
|
| 2260 |
+
Internal Controls
|
| 2261 |
+
|
| 2262 |
+
Component Framework Presentation / Interface
|
| 2263 |
+
|
| 2264 |
+
Internal Controls
|
| 2265 |
+
|
| 2266 |
+
Component Framework Data Management
|
| 2267 |
+
|
| 2268 |
+
Static Display
|
| 2269 |
+
Database Connectivity
|
| 2270 |
+
|
| 2271 |
+
Sybase 12.x
|
| 2272 |
+
|
| 2273 |
+
Internal Controls
|
| 2274 |
+
Internal Controls
|
| 2275 |
+
|
| 2276 |
+
Internal Controls
|
| 2277 |
+
|
| 2278 |
+
Component Framework Data Management
|
| 2279 |
+
|
| 2280 |
+
Reporting and Analysis,
|
| 2281 |
+
|
| 2282 |
+
Service Interface and
|
| 2283 |
+
Integration
|
| 2284 |
+
|
| 2285 |
+
Service Interface and
|
| 2286 |
+
Integration
|
| 2287 |
+
|
| 2288 |
+
Integration
|
| 2289 |
+
|
| 2290 |
+
Enterprise Application
|
| 2291 |
+
|
| 2292 |
+
Integration
|
| 2293 |
+
|
| 2294 |
+
Interoperability.
|
| 2295 |
+
|
| 2296 |
+
Data Transformation
|
| 2297 |
+
|
| 2298 |
+
Internal Controls:
|
| 2299 |
+
|
| 2300 |
+
Service Interface and!
|
| 2301 |
+
|
| 2302 |
+
Interface
|
| 2303 |
+
|
| 2304 |
+
Service Description /
|
| 2305 |
+
|
| 2306 |
+
API
|
| 2307 |
+
|
| 2308 |
+
Integration
|
| 2309 |
+
|
| 2310 |
+
Interface
|
| 2311 |
+
|
| 2312 |
+
a. Service Components identified in the previous question should be entered in this column. Please
|
| 2313 |
+
enter multiple rows for FEA SRM Components supported by multiple TRM Service Specifications.
|
| 2314 |
+
|
| 2315 |
+
b. In the Service Specification field, Agencies should provide information on the specified technical
|
| 2316 |
+
standard or vendor product mapped to the FEA TRM Service Standard, including model or version
|
| 2317 |
+
numbers, as appropriate.
|
| 2318 |
+
|
| 2319 |
+
5. Will the application leverage existing components and/or applications across the Government
|
| 2320 |
+
(i.e., FirstGov, Pay.Gov, etc)? no
|
| 2321 |
+
|
| 2322 |
+
NSF FAS 1-3-07
|
| 2323 |
+
|
| 2324 |
+
15 of 18
|
| 2325 |
+
|
| 2326 |
+
FY08 Exhibit 300
|
| 2327 |
+
|
| 2328 |
+
a. If "yes," please describe.
|
| 2329 |
+
|
| 2330 |
+
6. Does this investment provide the public with access to a government automated information
|
| 2331 |
+
system? no
|
| 2332 |
+
|
| 2333 |
+
(a) If "yes," does customer access require specific software (e.g., a
|
| 2334 |
+
specific web browser version)?
|
| 2335 |
+
[1] If "yes," provide the specific product name(s) and version number(s) of the required software and
|
| 2336 |
+
the date when the public will be able to access this investment by any software (i.e. to ensure
|
| 2337 |
+
equitable and timely access of government information and services).
|
| 2338 |
+
|
| 2339 |
+
NSF FAS 1-3-07
|
| 2340 |
+
|
| 2341 |
+
16 of 18
|
| 2342 |
+
|
| 2343 |
+
FY08 Exhibit 300
|
| 2344 |
+
|
| 2345 |
+
PART III: For "Operation and Maintenance" Investments ONLY (Steady State)
|
| 2346 |
+
|
| 2347 |
+
Part III should be completed only for investments which will be in "Operation and Maintenance"
|
| 2348 |
+
(Steady State) in response to Question 6 in Part I, Section A above.
|
| 2349 |
+
|
| 2350 |
+
Section A: Risk Management (All Capital Assets)
|
| 2351 |
+
|
| 2352 |
+
You should have performed a risk assessment during the early planning and initial concept phase of
|
| 2353 |
+
this investment's life-cycle, developed a risk-adjusted life-cycle cost estimate and a plan to
|
| 2354 |
+
eliminate, mitigate or manage risk, and be actively managing risk throughout the investment's life-
|
| 2355 |
+
cycle.
|
| 2356 |
+
|
| 2357 |
+
Answer the following questions to describe how you are managing investment risks.
|
| 2358 |
+
|
| 2359 |
+
1. Does the investment have a Risk Management Plan? yes
|
| 2360 |
+
|
| 2361 |
+
a. If "yes," what is the date of the plan?
|
| 2362 |
+
|
| 2363 |
+
06/01/2005
|
| 2364 |
+
|
| 2365 |
+
b. Has the Risk Management Plan been significantly changed since last year's submission to
|
| 2366 |
+
|
| 2367 |
+
OMB? no
|
| 2368 |
+
|
| 2369 |
+
c. If "yes," describe any significant changes:
|
| 2370 |
+
|
| 2371 |
+
2. If there currently is no plan, will a plan be developed?
|
| 2372 |
+
|
| 2373 |
+
a. If "yes," what is the planned completion date?
|
| 2374 |
+
b. If "no," what is the strategy for managing the risks?
|
| 2375 |
+
|
| 2376 |
+
Section B: Cost and Schedule Performance (All Capital Assets)
|
| 2377 |
+
|
| 2378 |
+
Answer the following questions about how you are currently managing this investment.
|
| 2379 |
+
|
| 2380 |
+
1. Was an operational analysis conducted? yes
|
| 2381 |
+
|
| 2382 |
+
a. If "yes," provide the date the analysis was completed.
|
| 2383 |
+
|
| 2384 |
+
06/01/2005
|
| 2385 |
+
|
| 2386 |
+
b. If "yes," what were the results? (Max 2500 Characters)
|
| 2387 |
+
|
| 2388 |
+
The results of the OA recommend that the FAS continue to be used as the NSF's financial accounting
|
| 2389 |
+
|
| 2390 |
+
system for the next several years. The NSF is in the process of conducting a pilot project as a Grants
|
| 2391 |
+
|
| 2392 |
+
Management Line of Business provider. We plan to take advantage of the results/findings of the GMLOB
|
| 2393 |
+
|
| 2394 |
+
process in becoming an SSP to more fully define our financial requirements. This will allow the NSF to take
|
| 2395 |
+
|
| 2396 |
+
an integrated approach to both GMLOB & FMLOB in regards to the future of FAS and NSF's
|
| 2397 |
+
|
| 2398 |
+
financial system.
|
| 2399 |
+
|
| 2400 |
+
NSF FAS 1-3-07
|
| 2401 |
+
|
| 2402 |
+
17 of 18
|
| 2403 |
+
|
| 2404 |
+
FY08 Exhibit 300
|
| 2405 |
+
|
| 2406 |
+
c. If "no," please explain why it was not conducted and if there are any plans to conduct an
|
| 2407 |
+
|
| 2408 |
+
operational analysis in the future? (Max 2500 Characters)
|
| 2409 |
|
| 2410 |
+
2. Complete the following table to compare actual cost performance against the planned cost
|
| 2411 |
+
performance baseline. Milestones reported may include specific individual scheduled preventative
|
| 2412 |
+
and predictable corrective maintenance activities, or may be the total of planned annual operation
|
| 2413 |
+
and maintenance efforts). Indicate if the information provided includes government and contractor
|
| 2414 |
+
costs:
|
| 2415 |
|
| 2416 |
+
a. What costs are included in the reported Cost/Schedule Performance information (Government
|
| 2417 |
+
Only/Contractor Only/Both)? Contractor Only
|
| 2418 |
|
| 2419 |
+
Description of Milestone (Max 50
|
| 2420 |
+
Characters)
|
| 2421 |
|
| 2422 |
+
Planned
|
| 2423 |
|
| 2424 |
+
Completion Date
|
| 2425 |
|
| 2426 |
+
Total Cost
|
| 2427 |
+
($M)
|
| 2428 |
|
| 2429 |
+
Actual
|
| 2430 |
+
Completion Date Total Costs
|
| 2431 |
|
| 2432 |
+
($M)
|
| 2433 |
|
| 2434 |
+
$1.800
|
| 2435 |
|
| 2436 |
+
$1.500
|
| 2437 |
|
| 2438 |
+
09/30/2001
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2439 |
|
| 2440 |
+
09/30/2002
|
| 2441 |
|
| 2442 |
+
$1.800
|
| 2443 |
|
| 2444 |
+
$1.500
|
| 2445 |
|
| 2446 |
+
09/30/2001
|
| 2447 |
|
| 2448 |
+
09/30/2002
|
| 2449 |
|
| 2450 |
+
09/30/2003
|
| 2451 |
|
| 2452 |
+
$1.670
|
| 2453 |
|
| 2454 |
+
09/30/2003
|
| 2455 |
|
| 2456 |
+
$1.670
|
| 2457 |
|
| 2458 |
+
09/30/2004
|
| 2459 |
|
| 2460 |
+
09/30/2005
|
| 2461 |
|
| 2462 |
+
09/30/200
|
| 2463 |
|
| 2464 |
+
09/30/2007
|
| 2465 |
|
| 2466 |
+
$1.300
|
| 2467 |
|
| 2468 |
+
$1.300
|
| 2469 |
|
| 2470 |
+
$1.500
|
| 2471 |
|
| 2472 |
+
$1.500.
|
| 2473 |
|
| 2474 |
+
09/30/2004
|
| 2475 |
|
| 2476 |
+
09/30/2005
|
| 2477 |
|
| 2478 |
+
09/30/2006
|
| 2479 |
|
| 2480 |
+
$1.300:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2481 |
|
| 2482 |
+
$1.300
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2483 |
|
| 2484 |
+
$1.500
|
| 2485 |
|
| 2486 |
+
$0.000
|
| 2487 |
|
| 2488 |
+
Baseline
|
| 2489 |
+
Schedule
|
| 2490 |
+
Variance
|
| 2491 |
+
(#Days)
|
| 2492 |
|
| 2493 |
+
Baseline
|
| 2494 |
+
Cost
|
| 2495 |
+
Variance
|
| 2496 |
+
($M)
|
| 2497 |
|
| 2498 |
+
$0.000
|
| 2499 |
|
| 2500 |
+
$0.000
|
| 2501 |
|
| 2502 |
+
$0.000
|
| 2503 |
|
| 2504 |
+
$0.000
|
| 2505 |
|
| 2506 |
+
$0.000
|
| 2507 |
|
| 2508 |
+
$0.000
|
| 2509 |
|
| 2510 |
+
$0.000
|
| 2511 |
|
| 2512 |
+
FY01 Steady State Operations
|
| 2513 |
|
| 2514 |
+
FY02 Steady State Operations
|
| 2515 |
|
| 2516 |
+
FY03 Steady State Operations
|
| 2517 |
|
| 2518 |
+
FY04 Steady State Operations
|
| 2519 |
|
| 2520 |
+
FY05 Steady State Operations
|
| 2521 |
|
| 2522 |
+
FY06 Steady State Operations
|
| 2523 |
|
| 2524 |
+
FY07 Steady State Operations
|
| 2525 |
|
| 2526 |
+
Total Planned Costs:
|
| 2527 |
|
| 2528 |
+
Total Actual Costs: $9.070
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2529 |
|
| 2530 |
+
NSF FAS 1-3-07
|
|
|
|
| 2531 |
|
| 2532 |
+
18 of 18
|
| 2533 |
|
| 2534 |
+
FY08 Exhibit 300
|
| 2535 |
|
q136/random_k4/random_4.md
CHANGED
|
@@ -1,477 +1,655 @@
|
|
| 1 |
-
|
| 2 |
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|
| 3 |
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The
|
| 4 |
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| 5 |
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| 9 |
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| 33 |
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| 34 |
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|
| 35 |
-
and
|
| 36 |
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| 37 |
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| 38 |
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| 39 |
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| 40 |
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| 41 |
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| 47 |
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| 49 |
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| 50 |
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| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
-
|
| 55 |
-
|
| 56 |
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|
| 57 |
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| 58 |
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| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
-
|
| 69 |
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|
| 70 |
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| 71 |
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| 72 |
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| 73 |
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| 74 |
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| 75 |
-
|
| 76 |
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|
| 77 |
-
|
| 78 |
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|
| 79 |
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|
| 80 |
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| 81 |
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|
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|
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-
|
| 85 |
-
|
| 86 |
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|
| 87 |
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|
| 88 |
-
|
| 89 |
-
|
| 90 |
-
|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
-
|
| 95 |
-
|
| 96 |
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|
| 97 |
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|
| 98 |
-
|
| 99 |
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|
| 100 |
-
|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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|
| 105 |
-
|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
-
|
| 110 |
-
|
| 111 |
-
|
| 112 |
-
|
| 113 |
-
|
| 114 |
-
|
| 115 |
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|
| 116 |
-
|
| 117 |
-
|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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| 123 |
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|
| 124 |
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|
| 125 |
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|
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|
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|
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|
| 132 |
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|
| 133 |
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| 134 |
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|
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|
| 136 |
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|
| 137 |
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|
| 138 |
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| 139 |
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|
| 140 |
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|
| 141 |
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| 142 |
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| 145 |
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|
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|
| 147 |
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|
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|
| 149 |
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|
| 150 |
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|
| 151 |
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|
| 152 |
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|
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-
|
| 154 |
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|
| 155 |
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|
| 156 |
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|
| 157 |
-
|
| 158 |
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|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
-
|
| 163 |
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|
| 164 |
-
|
| 165 |
-
|
| 166 |
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|
| 167 |
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|
| 168 |
-
|
| 169 |
-
|
| 170 |
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|
| 171 |
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|
| 172 |
-
|
| 173 |
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|
| 174 |
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|
| 175 |
-
|
| 176 |
-
|
| 177 |
-
|
| 178 |
-
|
| 179 |
-
|
| 180 |
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|
| 1 |
+
1
|
| 2 |
+
|
| 3 |
+
The Nursing Home
|
| 4 |
+
Inspection Process
|
| 5 |
+
|
| 6 |
+
SUMMARY
|
| 7 |
+
|
| 8 |
+
Both the Minnesota Department of Health (MDH) and the U.S.
|
| 9 |
+
Department of Health and Human Services share responsibility for
|
| 10 |
+
ensuring that Minnesota’s nursing homes provide an acceptable level
|
| 11 |
+
of care for their residents. Because the federal government dictates
|
| 12 |
+
the overall structure and content of the inspection program, the State
|
| 13 |
+
of Minnesota has few opportunities to make significant changes in
|
| 14 |
+
how it conducts nursing home inspections. The federal government
|
| 15 |
+
mandates how often the state must inspect nursing homes, the steps
|
| 16 |
+
the state must follow when conducting inspections, and the standards
|
| 17 |
+
the state must apply. Although MDH and other states have asked the
|
| 18 |
+
federal government for more flexibility in conducting inspections, the
|
| 19 |
+
federal government has not issued any waivers that allow states to
|
| 20 |
+
significantly change or implement an alternative inspection program.
|
| 21 |
+
|
| 22 |
+
The current nursing home inspection process emerged in the mid-1980s, as
|
| 23 |
+
|
| 24 |
+
Congress responded to reports of resident abuse and inadequate enforcement
|
| 25 |
+
|
| 26 |
+
of nursing home regulations. In a 1986 report on nursing home quality, the
|
| 27 |
+
Institute of Medicine found “serious, even shocking inadequacies” in the
|
| 28 |
+
enforcement of regulations.1 As a result of this report and the efforts of advocacy
|
| 29 |
+
groups and professional organizations, Congress passed a major reform of nursing
|
| 30 |
+
home regulation as part of the Omnibus Budget Reconciliation Act of 1987.2
|
| 31 |
+
|
| 32 |
+
Since that time, Congress and the U.S. Department of Health and Human Services
|
| 33 |
+
have periodically modified inspection requirements in response to studies that
|
| 34 |
+
have shown continued weak and inconsistent enforcement of nursing home
|
| 35 |
+
regulations and quality of care problems. Most significantly, the Nursing Home
|
| 36 |
+
Oversight Improvement Program was implemented in 1998, which, among other
|
| 37 |
+
things, enhanced federal review of state inspections and required the federal
|
| 38 |
+
government to terminate funding for states that fail to conduct adequate
|
| 39 |
+
inspections.
|
| 40 |
+
|
| 41 |
+
This chapter addresses the following question about how the Minnesota
|
| 42 |
+
Department of Health (MDH) inspects nursing homes:
|
| 43 |
+
|
| 44 |
+
• What are the respective roles of the Minnesota Department of Health
|
| 45 |
+
and U.S. Department of Health and Human Services in conducting
|
| 46 |
+
nursing home inspections?
|
| 47 |
+
|
| 48 |
+
Institute of Medicine, Committee on Nursing Home Regulation, Improving the Quality of Care
|
| 49 |
+
|
| 50 |
+
1
|
| 51 |
+
in Nursing Homes (Washington DC: National Academy Press, 1986), 146.
|
| 52 |
+
2 Pub. L. 100-203, Dec. 22, 1987.
|
| 53 |
+
|
| 54 |
+
4
|
| 55 |
+
|
| 56 |
+
NURSING HOME INSPECTIONS
|
| 57 |
+
|
| 58 |
+
The federal
|
| 59 |
+
government and
|
| 60 |
+
states share
|
| 61 |
+
responsibility
|
| 62 |
+
for ensuring that
|
| 63 |
+
nursing homes
|
| 64 |
+
provide an
|
| 65 |
+
acceptable level
|
| 66 |
+
of care to
|
| 67 |
+
residents.
|
| 68 |
+
|
| 69 |
+
To answer this question, we examined state and federal laws, rules, regulations,
|
| 70 |
+
and guidelines related to nursing homes inspections, as well as a wide variety of
|
| 71 |
+
research reports by state and federal agencies. We also interviewed state
|
| 72 |
+
policymakers, nursing home inspectors and their supervisors, and a sample of
|
| 73 |
+
nursing home administrators from throughout the state.
|
| 74 |
+
|
| 75 |
+
FEDERAL REGULATION OF INSPECTIONS
|
| 76 |
+
|
| 77 |
+
State and federal laws define a nursing home as a facility (or that part of a facility)
|
| 78 |
+
that provides health evaluation and treatment services to five or more residents
|
| 79 |
+
who do not need an acute care facility (such as a hospital) but who require nursing
|
| 80 |
+
supervision or rehabilitation services on an inpatient basis.3 In lay terms, this
|
| 81 |
+
means a facility that provides a room, meals, recreational opportunities, and help
|
| 82 |
+
with daily living activities such as dressing, eating, bathing, walking, and using
|
| 83 |
+
the bathroom. Residents generally have health problems that keep them from
|
| 84 |
+
living on their own and may require daily medical attention.
|
| 85 |
+
|
| 86 |
+
The federal
|
| 87 |
+
government and
|
| 88 |
+
states share
|
| 89 |
+
responsibility for
|
| 90 |
+
ensuring that
|
| 91 |
+
nursing homes
|
| 92 |
+
provide an
|
| 93 |
+
acceptable level of
|
| 94 |
+
care to residents.
|
| 95 |
+
The Centers for
|
| 96 |
+
Medicare and
|
| 97 |
+
Medicaid Services
|
| 98 |
+
(CMS) in the U. S.
|
| 99 |
+
Department of
|
| 100 |
+
Health and Human
|
| 101 |
+
Services oversees
|
| 102 |
+
the inspection
|
| 103 |
+
program for
|
| 104 |
+
nursing homes that
|
| 105 |
+
participate in the
|
| 106 |
+
federal Medicare and Medicaid programs.4 The agency sets nursing home
|
| 107 |
+
standards; interprets federal regulations, guidelines, and polices; and establishes
|
| 108 |
+
and monitors inspection procedures. It contracts with MDH to conduct nursing
|
| 109 |
+
home inspections in Minnesota.5 In addition to conducting inspections, MDH
|
| 110 |
+
licenses nursing homes for state purposes and certifies their eligibility for
|
| 111 |
+
participation in the Medicare and Medicaid programs. Finally, the department is
|
| 112 |
+
|
| 113 |
+
Nursing home residents generally need help with many activities of
|
| 114 |
+
daily living.
|
| 115 |
+
|
| 116 |
+
3 Minn. Stat. (2004), §144A.01, subd. 5-6; and 42 U.S. Code, §1396r, (a) (2000).
|
| 117 |
+
4 CMS was formerly called the Health Care Financing Administration.
|
| 118 |
+
5 The Minnesota Department of Health contracts with the State Fire Marshall’s Office in the
|
| 119 |
+
Minnesota Department of Public Safety to determine facility compliance with the federal Life
|
| 120 |
+
Safety Code, which is necessary for participation in the Medicare and Medicaid programs. State
|
| 121 |
+
Fire Marshall findings are included in the inspection reports issued by MDH.
|
| 122 |
+
|
| 123 |
+
THE NURSING HOME INSPECTION PROCESS
|
| 124 |
+
|
| 125 |
+
5
|
| 126 |
+
|
| 127 |
+
responsible for explaining program participation requirements to providers to help
|
| 128 |
+
them comply with federal requirements.6
|
| 129 |
+
|
| 130 |
+
Overall, we found that:
|
| 131 |
+
|
| 132 |
+
• The federal government sets forth the overall structure and content of
|
| 133 |
+
the nursing home inspection program, and Minnesota has very few
|
| 134 |
+
opportunities to make significant changes in the program.
|
| 135 |
+
|
| 136 |
+
Federal regulations outline both the general parameters of the inspection process
|
| 137 |
+
as well as the specifics of how each inspection must be done. They dictate:
|
| 138 |
+
(1) how frequently the state must inspect nursing homes, (2) the steps the state
|
| 139 |
+
must follow when conducting inspections, and (3) the standards that the state
|
| 140 |
+
must apply. We discuss each of these areas in greater detail below.
|
| 141 |
+
|
| 142 |
+
Inspection Frequency
|
| 143 |
+
|
| 144 |
+
The federal government sets forth how often nursing homes must be inspected:
|
| 145 |
+
|
| 146 |
+
Federal law and regulations require that the Minnesota Department of
|
| 147 |
+
Health inspect nursing homes every 12 months, on average.
|
| 148 |
+
|
| 149 |
+
All nursing facilities must be inspected no later than once every 15 months, with
|
| 150 |
+
an average time statewide between inspections of 12 months. Federal regulations
|
| 151 |
+
do not allow states to inspect nursing homes with “good” inspection records less
|
| 152 |
+
frequently than homes with “bad” records. In addition, CMS requires that at least
|
| 153 |
+
10 percent of inspections be “staggered” (started outside of normal business
|
| 154 |
+
hours). To meet this requirement, the state must begin some inspections on
|
| 155 |
+
weekends or holidays, some in the early morning (before 8:00 AM), and some in
|
| 156 |
+
the evening (after 6:00 PM). Furthermore, the federal government requires that
|
| 157 |
+
all nursing home inspections be unannounced.
|
| 158 |
+
|
| 159 |
+
About 420 Minnesota nursing homes participated in the Medicare and Medicaid
|
| 160 |
+
programs during federal fiscal year 2003.7 The department inspected all of these
|
| 161 |
+
nursing homes within 14.7 months of their prior inspection, with an average time
|
| 162 |
+
between inspections of 12 months.8 In addition, 12 percent of the 403 inspections
|
| 163 |
+
conducted were staggered, with 21 inspections beginning before 8:00 AM, 16
|
| 164 |
+
inspections after 6:00 PM, and 10 beginning on a weekend or holiday.9
|
| 165 |
+
|
| 166 |
+
For the most part, nursing home providers, state policymakers, and nursing home
|
| 167 |
+
inspectors generally agree that requiring annual inspections of all nursing homes
|
| 168 |
+
|
| 169 |
+
6 The department has additional responsibilities related to nursing homes, such as investigating
|
| 170 |
+
complaints, which were outside the scope of our evaluation. Nursing home inspectors also inspect
|
| 171 |
+
other types of health care facilities, such as hospitals and intermediate care facilities for the mentally
|
| 172 |
+
retarded. These activities were likewise outside the scope of our evaluation.
|
| 173 |
+
7 The federal fiscal year runs from October 1 through September 30.
|
| 174 |
+
8 Centers for Medicare and Medicaid Services, Federal Fiscal Year 2003 State Performance
|
| 175 |
+
Standard Review Report (Washington, DC, March 15, 2004), 1.
|
| 176 |
+
9
|
| 177 |
+
Ibid., 2. Because nursing homes may go up to 15 months between inspections, the number of
|
| 178 |
+
nursing homes that MDH inspected during federal fiscal year 2003 was less than the total number of
|
| 179 |
+
nursing homes in the state.
|
| 180 |
+
|
| 181 |
+
Nursing homes
|
| 182 |
+
must have a
|
| 183 |
+
“surprise”
|
| 184 |
+
inspection no
|
| 185 |
+
later than once
|
| 186 |
+
every 15 months.
|
| 187 |
+
|
| 188 |
+
(cid:127)
|
| 189 |
+
6
|
| 190 |
+
|
| 191 |
+
NURSING HOME INSPECTIONS
|
| 192 |
+
|
| 193 |
+
Because of
|
| 194 |
+
federal
|
| 195 |
+
requirements,
|
| 196 |
+
MDH cannot
|
| 197 |
+
inspect nursing
|
| 198 |
+
homes with
|
| 199 |
+
“good”
|
| 200 |
+
inspection
|
| 201 |
+
records less
|
| 202 |
+
frequently than
|
| 203 |
+
those with "bad"
|
| 204 |
+
records.
|
| 205 |
+
|
| 206 |
+
is, at times, an inefficient use of staff resources. The requirement does not permit
|
| 207 |
+
the state to focus efforts on the nursing homes that need oversight the most. To
|
| 208 |
+
help increase the efficiency and effectiveness of the inspection process, the
|
| 209 |
+
Legislature has repeatedly required the Commissioner of Health to seek federal
|
| 210 |
+
permission to implement an alternative inspection process that would change how
|
| 211 |
+
often nursing homes must be inspected.10 In response, the department submitted a
|
| 212 |
+
proposal to CMS that would have increased the time between “full” inspections
|
| 213 |
+
up to 30 months for some homes with “good” compliance records. Other states
|
| 214 |
+
have proposed similar approaches, including ones to conduct abbreviated annual
|
| 215 |
+
inspections for homes with “good” compliance records.
|
| 216 |
+
|
| 217 |
+
To date, CMS has not approved an alternative inspection program put forth by any
|
| 218 |
+
state, including Minnesota. According to CMS, the social security law does not
|
| 219 |
+
allow states to obtain waivers to implement an alternative inspection program for
|
| 220 |
+
nursing homes participating in the Medicare program, although states could
|
| 221 |
+
implement an alternative inspection program for homes that only participate in the
|
| 222 |
+
Medicaid program. However, because this would involve only a few nursing
|
| 223 |
+
homes, it is generally not feasible for states to do so.
|
| 224 |
+
|
| 225 |
+
For the last several years, CMS has been studying the feasibility of an alternative
|
| 226 |
+
inspection process. Recently, the agency announced that it would be establishing
|
| 227 |
+
a few pilot sites around the country to implement a “revamped” inspection
|
| 228 |
+
process. Designed to address concerns about inspection consistency and
|
| 229 |
+
efficiency, pilot sites will make greater use of computers to make initial
|
| 230 |
+
determinations of deficiencies rather than relying on the judgment of inspection
|
| 231 |
+
teams. The alternative process will not result in less frequent inspections for
|
| 232 |
+
facilities, but may allow inspectors to spend somewhat less time in “good”
|
| 233 |
+
facilities and more time in “bad” ones.
|
| 234 |
+
|
| 235 |
+
Inspection Steps
|
| 236 |
+
|
| 237 |
+
In addition to requiring an inspection no later than once every 15 months:
|
| 238 |
+
|
| 239 |
+
•
|
| 240 |
+
|
| 241 |
+
Federal regulations require that each nursing home’s annual
|
| 242 |
+
inspection be a “standard” or full inspection consisting of seven
|
| 243 |
+
federally mandated steps.
|
| 244 |
+
|
| 245 |
+
Federal regulations do not allow states to do shorter or abbreviated inspections of
|
| 246 |
+
nursing homes with “good” records of compliance or to cut short an inspection
|
| 247 |
+
when inspectors do not detect any problems in a facility. On the other hand, state
|
| 248 |
+
inspectors must extend the inspection if they suspect that a facility is providing
|
| 249 |
+
substandard care to its residents.
|
| 250 |
+
|
| 251 |
+
As shown in Table 1.1, the standard inspection consists of seven federally
|
| 252 |
+
mandated steps. First, inspectors prepare off-site by reviewing information about
|
| 253 |
+
the nursing home and its residents to help identify areas of concern. Immediately
|
| 254 |
+
upon arriving at the facility, the inspection team meets with the nursing home
|
| 255 |
+
administrator to explain the inspection process and request specific information;
|
| 256 |
+
|
| 257 |
+
10 Laws of Minnesota (2000), ch. 312, sec. 2, 5; Laws of Minnesota (1Sp2001), ch. 9, art. 5, sec. 38;
|
| 258 |
+
Laws of Minnesota (2002), ch. 379, art. 1, sec. 113; and Laws of Minnesota (2004), ch. 247,
|
| 259 |
+
sec. 6.
|
| 260 |
+
|
| 261 |
+
THE NURSING HOME INSPECTION PROCESS
|
| 262 |
+
|
| 263 |
+
7
|
| 264 |
+
|
| 265 |
+
Table 1.1: The Federal Nursing Home Inspection
|
| 266 |
+
Process
|
| 267 |
+
|
| 268 |
+
Step 1: Off-site preparation
|
| 269 |
+
|
| 270 |
+
Step 2: Entry conference and on-site preparation
|
| 271 |
+
|
| 272 |
+
Step 3:
|
| 273 |
+
|
| 274 |
+
Initial nursing home tour
|
| 275 |
+
|
| 276 |
+
Step 4: Resident sample selection
|
| 277 |
+
|
| 278 |
+
Step 5:
|
| 279 |
+
|
| 280 |
+
Information gathering
|
| 281 |
+
|
| 282 |
+
A. General observation of the facility
|
| 283 |
+
B. Kitchen/food service observation
|
| 284 |
+
C. Resident review
|
| 285 |
+
D. Quality of life assessment
|
| 286 |
+
E. Medication pass
|
| 287 |
+
F. Quality assessment and assurance review
|
| 288 |
+
G. Abuse prevention review
|
| 289 |
+
|
| 290 |
+
Step 6: Deficiency determination
|
| 291 |
+
|
| 292 |
+
A. Determination of substandard quality of care
|
| 293 |
+
|
| 294 |
+
Step 7: Exit conference
|
| 295 |
+
|
| 296 |
+
Likewise,
|
| 297 |
+
MDH cannot
|
| 298 |
+
do abbreviated
|
| 299 |
+
inspections in
|
| 300 |
+
nursing homes
|
| 301 |
+
with "good"
|
| 302 |
+
records.
|
| 303 |
+
|
| 304 |
+
SOURCE: Centers for Medicare and Medicaid Services, State Operations Manual (Washington, DC,
|
| 305 |
+
May 21, 2004), ch. 7, sec 7200.
|
| 306 |
+
|
| 307 |
+
this is followed by a facility tour. Using the information provided by the facility
|
| 308 |
+
and what inspectors learned during the tour, the team then selects a sample of
|
| 309 |
+
residents to focus on during the information-gathering portion of the inspection.
|
| 310 |
+
During this phase, the team meets on a daily basis to compare notes, discuss new
|
| 311 |
+
areas of concern, and make adjustments to the inspection as deemed necessary.
|
| 312 |
+
Inspectors observe the care and services that facility staff provide to residents,
|
| 313 |
+
such as preparing and serving meals, administering medications, and helping, as
|
| 314 |
+
necessary, with activities such as bathing, toileting, walking, and grooming.
|
| 315 |
+
Inspection team members also interview residents and staff and review resident
|
| 316 |
+
records. Once the team is satisfied that they have gathered enough information, it
|
| 317 |
+
meets to determine whether the facility has failed to meet any regulatory
|
| 318 |
+
requirements. The team prepares a draft inspection report that discusses each
|
| 319 |
+
violation of federal regulations (commonly referred to as a deficiency) that the
|
| 320 |
+
team has identified, and then meets with nursing home personnel and interested
|
| 321 |
+
residents and family members to present its preliminary list of deficiencies.
|
| 322 |
+
|
| 323 |
+
After the inspection team leaves the facility, it finalizes the “Statement of
|
| 324 |
+
Deficiencies” and submits it to the team’s district supervisor who is responsible
|
| 325 |
+
for reviewing the document and submitting a final copy to the facility and CMS.
|
| 326 |
+
The facility must submit a “Plan of Correction” within ten days that indicates how
|
| 327 |
+
and when it will correct each of the deficiencies that it has received.11 Inspectors
|
| 328 |
+
normally conduct an unannounced revisit to verify that the plan of correction has
|
| 329 |
+
been implemented and that the deficiencies no longer exist. For the most part,
|
| 330 |
+
MDH generally gives a facility 40 days from the end of the inspection to correct
|
| 331 |
+
deficiencies before MDH imposes any sanctions on the facility.
|
| 332 |
+
|
| 333 |
+
11 Facilities may also dispute a deficiency and request a hearing before MDH or an administrative
|
| 334 |
+
law judge within this ten-day period. Chapter 2 discusses how often this happens and the outcome
|
| 335 |
+
of such hearings.
|
| 336 |
+
|
| 337 |
+
Inspectors spend
|
| 338 |
+
much of their
|
| 339 |
+
time observing
|
| 340 |
+
and talking with
|
| 341 |
+
residents and
|
| 342 |
+
staff.
|
| 343 |
+
|
| 344 |
+
8
|
| 345 |
+
|
| 346 |
+
NURSING HOME INSPECTIONS
|
| 347 |
+
|
| 348 |
+
State law
|
| 349 |
+
requires
|
| 350 |
+
inspectors to
|
| 351 |
+
leave a draft
|
| 352 |
+
inspection report
|
| 353 |
+
with facilities
|
| 354 |
+
when they leave.
|
| 355 |
+
|
| 356 |
+
While the state is unable to make significant changes in how inspections are done:
|
| 357 |
+
|
| 358 |
+
• Minnesota has expanded the federal nursing home inspection process
|
| 359 |
+
|
| 360 |
+
in several ways.
|
| 361 |
+
|
| 362 |
+
The state goes beyond federal inspection requirements by adding other tasks,
|
| 363 |
+
including requirements to: (1) interview family council members; (2) expand the
|
| 364 |
+
number of evening observations nursing home inspectors must make each month;
|
| 365 |
+
(3) conduct a “verify and clarify” session with the provider to discuss possible
|
| 366 |
+
areas of concern prior to the exit conference; and (4) leave a draft inspection
|
| 367 |
+
report with nursing homes after the inspection, with the final report due within
|
| 368 |
+
15 days. Some of these activities were added to make the inspection process more
|
| 369 |
+
“user friendly” for providers. Others, such as expanding the inspection to include
|
| 370 |
+
final interviews with family council members, were at the urging of advocacy
|
| 371 |
+
groups.
|
| 372 |
+
|
| 373 |
+
For the year ending
|
| 374 |
+
September 30, 2004,
|
| 375 |
+
MDH inspectors,
|
| 376 |
+
working in teams of
|
| 377 |
+
three to five
|
| 378 |
+
registered nurses,
|
| 379 |
+
spent an average of
|
| 380 |
+
about 150 hours per
|
| 381 |
+
facility to complete
|
| 382 |
+
the state and
|
| 383 |
+
federally mandated
|
| 384 |
+
inspection tasks.12
|
| 385 |
+
As would be
|
| 386 |
+
expected, it took
|
| 387 |
+
longer to inspect
|
| 388 |
+
larger nursing homes
|
| 389 |
+
than smaller ones.
|
| 390 |
+
For example, a
|
| 391 |
+
facility with 40 or
|
| 392 |
+
fewer beds averaged about 72 hours per inspection while a facility with 116 to
|
| 393 |
+
160 beds averaged 176 hours.13
|
| 394 |
+
|
| 395 |
+
Nursing home inspectors must meet with each facility's resident
|
| 396 |
+
council.
|
| 397 |
+
|
| 398 |
+
Inspection Standards
|
| 399 |
+
|
| 400 |
+
The federal State Operations Manual (SOM) sets forth the federal standards that
|
| 401 |
+
inspectors must apply during an inspection as well as guidelines to help them
|
| 402 |
+
apply those standards.14 As currently written:
|
| 403 |
+
|
| 404 |
+
12 Minnesota Department of Health analysis of data from the Online Survey and Certification
|
| 405 |
+
Reporting System, December 2, 2004. State inspectors spent an additional 54 hours per facility, on
|
| 406 |
+
average, conducting follow-up inspections to ensure that facilities corrected deficiencies.
|
| 407 |
+
13 Minnesota Department of Health, Federal Fiscal Year 2005 Initial Budget Request (St. Paul,
|
| 408 |
+
July 15, 2004), unnumbered.
|
| 409 |
+
14 Centers for Medicare and Medicaid Services, State Operations Manual (Washington, DC,
|
| 410 |
+
May 21, 2004).
|
| 411 |
+
|
| 412 |
+
THE NURSING HOME INSPECTION PROCESS
|
| 413 |
+
|
| 414 |
+
9
|
| 415 |
+
|
| 416 |
+
Inspectors grade
|
| 417 |
+
the seriousness of
|
| 418 |
+
each deficiency
|
| 419 |
+
by assigning it a
|
| 420 |
+
letter code.
|
| 421 |
+
|
| 422 |
+
• The federal standards and guidelines that state inspection teams must
|
| 423 |
+
|
| 424 |
+
use to inspect nursing homes are prescriptive and complex.
|
| 425 |
+
|
| 426 |
+
The SOM covers hundreds of pages and contains 274 regulatory standards that
|
| 427 |
+
nursing homes must meet at all times. The standards cover 16 different categories
|
| 428 |
+
of operation, including administration, dietary services, infection control, life
|
| 429 |
+
safety, physical environment, quality of care, quality of life, resident assessment,
|
| 430 |
+
and resident rights. Some requirements must be met for each resident and any
|
| 431 |
+
violation of these requirements, even for one resident, is a deficiency. For
|
| 432 |
+
example, each resident must have a comprehensive care plan. Other requirements
|
| 433 |
+
focus on facility systems and are evaluated comprehensively rather than in terms
|
| 434 |
+
of a single incident. For example, a facility must have a medication error rate
|
| 435 |
+
below 5 percent.15
|
| 436 |
+
|
| 437 |
+
For each deficiency, inspectors must use professional judgment to assess how
|
| 438 |
+
many residents or staff are affected by or involved in the deficient practice (scope)
|
| 439 |
+
and the amount of actual or potential discomfort or harm involved for residents
|
| 440 |
+
(severity). As shown in Table 1.2, these two determinations result in the
|
| 441 |
+
inspection team assigning a letter code (A through L) to each deficiency, with
|
| 442 |
+
level “A” deficiencies being the least serious.
|
| 443 |
+
|
| 444 |
+
Table 1.2: Deficiency Scope and Severity Grid
|
| 445 |
+
|
| 446 |
+
Severity
|
| 447 |
+
|
| 448 |
+
Scope
|
| 449 |
+
Isolated Pattern Widespread
|
| 450 |
+
|
| 451 |
+
Level 4: A situation that has caused or is likely to cause
|
| 452 |
+
serious resident injury, harm, impairment, or death.
|
| 453 |
+
|
| 454 |
+
Level 3: A situation that has caused resident harm.
|
| 455 |
+
|
| 456 |
+
Level 2: A situation that has caused minimal discomfort to
|
| 457 |
+
a resident OR has the potential to cause resident harm.
|
| 458 |
+
|
| 459 |
+
Level 1: A situation that has the potential of causing no
|
| 460 |
+
|
| 461 |
+
more than minimal discomfort to a resident.
|
| 462 |
+
|
| 463 |
+
J
|
| 464 |
+
|
| 465 |
+
G
|
| 466 |
+
|
| 467 |
+
D
|
| 468 |
+
|
| 469 |
+
A
|
| 470 |
+
|
| 471 |
+
K
|
| 472 |
+
|
| 473 |
+
H
|
| 474 |
+
|
| 475 |
+
E
|
| 476 |
+
|
| 477 |
+
B
|
| 478 |
+
|
| 479 |
+
L
|
| 480 |
+
|
| 481 |
+
I
|
| 482 |
+
|
| 483 |
+
F
|
| 484 |
+
|
| 485 |
+
C
|
| 486 |
+
|
| 487 |
+
NOTE: Harm is defined as a situation that compromises a resident’s ability to maintain or reach his or
|
| 488 |
+
her highest practicable physical, mental, or psychosocial well being, as defined by an accurate and
|
| 489 |
+
comprehensive assessment, care plan, and provision of services. A nursing home with one or more
|
| 490 |
+
quality of life, quality of care, or resident behavior and facility practices deficiencies issued at level “F”
|
| 491 |
+
or “H” or above (the shaded area of the grid) is considered to be providing “substandard” care to its
|
| 492 |
+
residents.
|
| 493 |
+
|
| 494 |
+
SOURCE: Centers for Medicare and Medicaid Services, State Operations Manual (Washington, DC,
|
| 495 |
+
May 21, 2004), Appendix P, V, B-C.
|
| 496 |
+
|
| 497 |
+
To determine a deficiency’s scope, inspectors must classify each deficiency in one
|
| 498 |
+
of three ways: isolated, pattern, or widespread. Federal guidelines say that a
|
| 499 |
+
deficiency is isolated when one or a very limited number of residents or staff are
|
| 500 |
+
affected or the situation has occurred only occasionally or in a very limited
|
| 501 |
+
number of locations in the facility. For example, if 60 of 70 residents in a facility
|
| 502 |
+
are incontinent and the facility failed to provide adequate care or services to
|
| 503 |
+
restore or improve bladder function for 2 of these residents, the deficiency should
|
| 504 |
+
be classified as isolated. A deficiency represents a pattern when it affects more
|
| 505 |
+
|
| 506 |
+
15 However, a single medication error that is considered severe enough may result in a deficiency.
|
| 507 |
+
|
| 508 |
+
10
|
| 509 |
+
|
| 510 |
+
NURSING HOME INSPECTIONS
|
| 511 |
+
|
| 512 |
+
than a very limited number of residents or staff, occurs in several locations, or the
|
| 513 |
+
same resident has been affected by repeated occurrences of the same deficient
|
| 514 |
+
practice. If the above facility did not provide adequate care or services to 10 of its
|
| 515 |
+
60 incontinent residents, the resulting deficiency should be issued as a pattern. A
|
| 516 |
+
deficiency is identified as widespread when it refers to the entire facility or when
|
| 517 |
+
a system failure has affected or has the potential to affect a large number of
|
| 518 |
+
residents. For example, a facility failing to provide adequate care or services to
|
| 519 |
+
improve or restore bladder function to 30 of its 60 incontinent residents should be
|
| 520 |
+
issued a deficiency classified as widespread.
|
| 521 |
+
|
| 522 |
+
Inspectors must also determine the severity of a deficiency on a scale from one to
|
| 523 |
+
four. Level one refers to deficiencies that have the potential for causing no more
|
| 524 |
+
than a minor negative impact on, or minimal physical, mental, or psychosocial
|
| 525 |
+
discomfort to, a resident. For example, a facility should receive a level one
|
| 526 |
+
deficiency if it failed to post its inspection results or only made them available
|
| 527 |
+
upon request. Level two deficiencies are those that have resulted in resident
|
| 528 |
+
discomfort or have the potential to harm residents. Federal regulations define
|
| 529 |
+
harmful situations as those that compromise residents’ ability to maintain or reach
|
| 530 |
+
their highest practicable physical, mental, and psychosocial well being, excluding
|
| 531 |
+
situations that are of a “limited consequence” to residents. For example, a nursing
|
| 532 |
+
home should receive a level two deficiency if inspectors observed staff failing to
|
| 533 |
+
wash their hands properly between caring for residents but no one became
|
| 534 |
+
seriously ill as a result. Level three deficiencies are those that have actually
|
| 535 |
+
resulted in resident harm. The hand-washing example should be a level three
|
| 536 |
+
deficiency if there was evidence that a resident caught a contagious disease as a
|
| 537 |
+
result of staff failing to wash their hands properly after providing resident care.
|
| 538 |
+
Level four represents immediate jeopardy situations whereby the facility must
|
| 539 |
+
undertake immediate corrective action to address problems that have resulted in or
|
| 540 |
+
are likely to cause serious injury, harm, impairment, or death to a resident. For
|
| 541 |
+
example, if a resident with dementia was found outside during an inspection
|
| 542 |
+
heading toward a busy highway and the nursing home did not have a working
|
| 543 |
+
system in place to monitor residents with dementia, the facility should be issued a
|
| 544 |
+
level four deficiency.
|
| 545 |
+
|
| 546 |
+
The “seriousness” of a facility’s deficiencies (their scope and severity) helps
|
| 547 |
+
determine the sanctions for nursing homes that fail to correct deficiencies within
|
| 548 |
+
an allowable time frame. As shown in Table 1.3, there are three categories of
|
| 549 |
+
required sanctions. Generally, nursing homes do not face sanctions for
|
| 550 |
+
deficiencies issued at levels “A” through “C.”16 Category 1 sanctions are reserved
|
| 551 |
+
for deficiencies issued at levels “D” and “E” and require that facilities implement
|
| 552 |
+
a plan of correction developed by the state, have their staff attend a specific
|
| 553 |
+
training program, or be subject to state monitoring. Conversely, category 3
|
| 554 |
+
sanctions are reserved for the most serious deficiencies and include the state
|
| 555 |
+
assuming management of the facility, terminating the facility’s participation in the
|
| 556 |
+
Medicare and Medicaid programs, or closing the facility. Except in instances of
|
| 557 |
+
immediate jeopardy to residents (a deficiency issued at level “J” or above) or
|
| 558 |
+
when facilities receive level “G” or higher deficiencies in two consecutive
|
| 559 |
+
inspections, facilities are generally given an opportunity to correct deficiencies
|
| 560 |
+
before any sanctions are imposed—usually 40 days. MDH must deny Medicare
|
| 561 |
+
|
| 562 |
+
16 Although the federal government does not require that sanctions be imposed on facilities
|
| 563 |
+
for low-level deficiencies (levels “B” and “C”), the state may choose to impose sanctions from
|
| 564 |
+
category 1 when facilities fail to correct their deficiencies.
|
| 565 |
+
|
| 566 |
+
A deficiency's
|
| 567 |
+
letter code helps
|
| 568 |
+
determine what
|
| 569 |
+
sanctions MDH
|
| 570 |
+
could impose on
|
| 571 |
+
the facility.
|
| 572 |
+
|
| 573 |
+
THE NURSING HOME INSPECTION PROCESS
|
| 574 |
+
|
| 575 |
+
11
|
| 576 |
+
|
| 577 |
+
Table 1.3: Required Sanctions for Noncompliance
|
| 578 |
+
|
| 579 |
+
Category 1: Deficiencies issued at levels “D” and “E”
|
| 580 |
+
|
| 581 |
+
Directed plan of correction;
|
| 582 |
+
State monitoring; and/or
|
| 583 |
+
Directed in-service training.
|
| 584 |
+
|
| 585 |
+
Category 2: Deficiencies issued at levels “F” through “I”
|
| 586 |
+
|
| 587 |
+
Denial of payment for new Medicare and Medicaid admissionsa;
|
| 588 |
+
Denial of payment for all Medicare and Medicaid residents;
|
| 589 |
+
Civil money penalties of $50-$3,000 per day of noncompliance; and/or
|
| 590 |
+
Civil money penalties of $1,000-$10,000 per incident of noncompliance.
|
| 591 |
+
|
| 592 |
+
Category 3: Deficiencies issued at levels “J” and above
|
| 593 |
+
|
| 594 |
+
Temporary management;
|
| 595 |
+
Termination from the Medicare/Medicaid programs; and/orb
|
| 596 |
+
Facility closure.
|
| 597 |
+
|
| 598 |
+
NOTE: The Minnesota Department of Health may impose a category 2 sanction to supplement a
|
| 599 |
+
category 1 sanction for deficiencies issued at levels “D” and “E.” In general, a category 1 or 2 sanction
|
| 600 |
+
can also be imposed whenever a category 3 sanction is required, and a category 1 sanction may also
|
| 601 |
+
be imposed when a category 2 sanction is required. Civil penalties increase to $3,050-$10,000 per
|
| 602 |
+
day when they are imposed in addition to a category 3 sanction. The state may also assume
|
| 603 |
+
temporary management (a category 3 sanction) when a facility has been issued a level “I” deficiency.
|
| 604 |
+
Also, a facility cited for providing substandard care cannot operate a nurse aide training and
|
| 605 |
+
competency evaluation program for two years.
|
| 606 |
+
|
| 607 |
+
aThe state must deny Medicare and Medicaid payments for new admissions when a facility is not in
|
| 608 |
+
substantial compliance within three months of the inspection and when a facility has been cited for
|
| 609 |
+
substandard care on three consecutive annual inspections. In the latter situation, state monitoring
|
| 610 |
+
must also be imposed.
|
| 611 |
+
|
| 612 |
+
bThe state must recommend termination from the Medicare and Medicaid programs when a facility is
|
| 613 |
+
not in substantial compliance within six months of the inspection.
|
| 614 |
+
|
| 615 |
+
SOURCE: Centers for Medicare and Medicaid Services, State Operations Manual (Washington, DC,
|
| 616 |
+
May 21, 2004), ch. 7, sec. 7210G and 7400.
|
| 617 |
+
|
| 618 |
+
and Medicaid reimbursements for new admissions when facilities have not
|
| 619 |
+
corrected their deficiencies within three months of the department’s inspection.
|
| 620 |
+
Facilities must be terminated from the program if deficiencies are not corrected
|
| 621 |
+
within 6 months.
|
| 622 |
+
|
| 623 |
+
FUNDING
|
| 624 |
+
|
| 625 |
+
In keeping with the high degree of federal involvement in the nursing home
|
| 626 |
+
inspection program:
|
| 627 |
+
|
| 628 |
+
•
|
| 629 |
+
|
| 630 |
+
State funds cover less than 10 percent of the total cost of nursing home
|
| 631 |
+
inspections and complaint investigations.
|
| 632 |
+
|
| 633 |
+
The federal government is the major source of funding for the inspection
|
| 634 |
+
program, with the state contributing less than 10 percent of the total cost for
|
| 635 |
+
nursing homes. In fiscal year 2004, MDH spent about $12 million from state and
|
| 636 |
+
|
| 637 |
+
12
|
| 638 |
+
|
| 639 |
+
NURSING HOME INSPECTIONS
|
| 640 |
+
|
| 641 |
+
federal sources on activities related to nursing home inspections, including costs
|
| 642 |
+
related to investigating complaints against nursing homes.17 The state’s share
|
| 643 |
+
(about $1.1 million) is the result of state negotiations with CMS and has
|
| 644 |
+
historically been low when compared with that of other states. According to a
|
| 645 |
+
2000 analysis of costs by the Health Care Financing Administration, Minnesota
|
| 646 |
+
was the only state in the Chicago region that paid less than 10 percent of total
|
| 647 |
+
inspection costs.18 Other states paid at least 16 percent, with one state paying
|
| 648 |
+
almost 25 percent of total costs.
|
| 649 |
+
|
| 650 |
+
17 Cecelia Jackson, “Re: FFY 2004 Nursing Home Expenditures” (December 23, 2004), electronic
|
| 651 |
+
mail to jo.vos@state.mn.us.
|
| 652 |
+
18 Health Care Financing Administration, “Nursing Home Survey, State Licensure Cost Shares”
|
| 653 |
+
(Chicago, May 2000). Minnesota is part of the Chicago region, which also includes Illinois,
|
| 654 |
+
Indiana, Michigan, Ohio, and Wisconsin.
|
| 655 |
+
|
q137/random_k2/question.json
CHANGED
|
@@ -15,8 +15,8 @@
|
|
| 15 |
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|
| 16 |
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|
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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| 22 |
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q137/random_k2/random_1.md
CHANGED
|
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|
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