Turn operational uncertainty
into better decisions.
Simulate demand, test staffing strategies and understand the trade-offs between service quality, customer abandonment and cost.
Performance snapshot
Staffing frontier
Each point uses the same simulated arrival cohorts for fair comparison.
Expected shift cost ⓘ
Service-level performance ⓘ
Recommended strategy
Use Run simulation to find the cheapest staffing level that achieves your SLA target.
Variability across simulations
Replicated simulation output will appear here.
Staffing comparison
| AGENTS | SLA | AVG WAIT | LOST / SHIFT | UTILIZATION | TOTAL COST | FLAG |
|---|---|---|---|---|---|---|
| Run the simulation to generate comparison data. | ||||||
Transparent by design.
This model assumes hourly Poisson arrivals, triangular service duration, first-come-first-served queues, fixed customer patience and fixed staffing. It simulates an 8-hour shift with optional overtime, compares identical sampled cohorts across staffing levels and reports cost in illustrative USD.
Important: This is a planning sandbox with synthetic demand, not an AI predictor or a validated production forecast. Check assumptions against actual operations before making decisions. For zero-arrival shifts the modeled SLA is defined as 100%.