app.py

import streamlit as st
import pandas as pd

# Define survey questions and options
survey_data = {
    "What % of recurring issues have well-defined SOPs or repeatable resolution steps?": {
        "< 20%": 1,
        "20–50%": 2,
        "51–70%": 3,
        "71–90%": 4,
        "> 90%": 5
    },
    "Are SOPs documented in a standardized and machine-readable format (e.g., YAML, BPMN)?": {
        "Not documented": 1,
        "Free-text or wiki-based": 2,
        "Semi-structured documents (PDFs, flows)": 3,
        "Structured formats (JSON, forms)": 4,
        "Fully machine-readable & API-integrated": 5
    },
    "What % of tickets & service requests (SRs) are low complexity and potentially automatable?": {
        "< 10%": 1,
        "10–30%": 2,
        "31–50%": 3,
        "51–70%": 4,
        "> 70%": 5
    },
    "How well are alerts integrated with your ticketing system?": {
        "No integration": 1,
        "Manual linking": 2,
        "Basic rule-based mapping": 3,
        "Event-driven ticket creation": 4,
        "Full integration with correlation logic": 5
    },
    "How mature is your knowledge management system?": {
        "Tribal knowledge / ad-hoc": 1,
        "Partially documented but not maintained": 2,
        "Basic documentation maintained": 3,
        "Regularly updated and searchable KB": 4,
        "Integrated with AI/chatbot search": 5
    },
    "What % of your team’s decisions are made using documented knowledge assets?": {
        "< 10%": 1,
        "10–30%": 2,
        "31–50%": 3,
        "51–70%": 4,
        "> 70%": 5
    },
    "How well is your monitoring and alerting infrastructure set up?": {
        "Minimal / reactive alerts only": 1,
        "Basic metrics dashboards": 2,
        "Alerts with some thresholds set": 3,
        "Advanced monitoring with alerts & log correlation": 4,
        "AI-powered observability with predictive insights": 5
    },
    "How frequently do you do health checks or preemptive diagnostics?": {
        "Only when issues arise": 1,
        "Ad-hoc manual checks": 2,
        "Weekly manual checks": 3,
        "Automated scheduled checks": 4,
        "Continuous monitoring with anomaly detection": 5
    },
    "What % of operational workload is non-ticket-based (e.g., maintenance, health checks)?": {
        "< 10%": 1,
        "10–30%": 2,
        "31–50%": 3,
        "51–70%": 4,
        "> 70%": 5
    },
    "What % of incidents are resolved without human intervention today?": {
        "< 5%": 1,
        "5–10%": 2,
        "11–25%": 3,
        "26–50%": 4,
        "> 50%": 5
    },
    "What is your team's comfort with adopting automation tools (bots, RPA, AI agents)?": {
        "Resistant / low exposure": 1,
        "Curious but skeptical": 2,
        "Open but not trained": 3,
        "Familiar & trained on automation tools": 4,
        "Already using automation in daily work": 5
    },
    "Are there governance frameworks to support automation (approvals, security, versioning)?": {
        "None": 1,
        "Informal guidelines": 2,
        "Partial policy in place": 3,
        "Documented governance policies": 4,
        "Mature, enforced automation governance": 5
    }
}

# Benefit calculation logic
def calculate_benefit(score):
    if 1 <= score <= 20:
        return "Low", "20 to 30%"
    elif 21 <= score <= 40:
        return "Medium", "30 to 40%"
    elif 41 <= score <= 60:
        return "High", "40 to 50%"
    else:
        return "Unknown", "Unknown"

# Streamlit UI
st.title("Automation Potential Survey")
st.write("Answer the following questions to estimate the potential benefits of implementing our automation solution.")

# Initialize session state for responses
if 'responses' not in st.session_state:
    st.session_state.responses = {}

# Display survey questions
for question, options in survey_data.items():
    st.subheader(question)
    response = st.radio(
        question,
        list(options.keys()),
        key=question,
        index=0
    )
    st.session_state.responses[question] = response

# Calculate and display results
if st.button("Submit Survey"):
    total_score = 0
    for question, response in st.session_state.responses.items():
        score = survey_data[question][response]
        total_score += score
    
    benefit, effort_reduction = calculate_benefit(total_score)
    
    st.write("### Survey Results")
    st.write(f"**Total Score**: {total_score}")
    st.write(f"**Benefit Level**: {benefit}")
    st.write(f"**Potential Effort Reduction**: {effort_reduction}")
    st.write("Thank you for completing the survey! This assessment indicates the potential efficiency gains from our automation solution.")