WorkforceAI — Workforce & Capacity Planner
Mathematical headcount modeling factoring contact volume forecasts, AHT, shrinkage, occupancy thresholds, and scenario planning.
Data Source
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Workforce & Capacity Planning Intelligence Scenario
Simulates an enterprise omnichannel contact center across Billing & Payments, Customer Support, Technical Helpdesk over 90 days (2024-01-01 to 2024-03-30). Demonstrates intraday demand profiling, staffing gap analysis, and what-if capacity scenarios.
Dataset Name
Synthetic Omnichannel Operations Dataset
Time Period
2024-01-01 to 2024-03-30
Record Count
76,574 records
Granularity
Hourly Channel Aggregations
Available Dimensions
Date, Hour, Department (3)
Primary Objective
Eliminate arbitrary headcount guessing using transparent FTE formulas, demand forecasting, and shrinkage modeling.
70,622 Answered (92.23%)
Total Workload: 5,783.2 hrs
Talk 294.8s + Hold 25s + ACW 35s
Gap: +12.7 FTE vs 35 Avail
Intraday Hourly Call Distribution
Demand Forecast vs Actual Volume
Rule-Based Workforce Insights
Peak call arrival occurs between 13:00 and 14:00.
Available staffing (35 FTE) meets or exceeds required capacity (22.3 FTE).
Estimated Staffing Gap by Day & Hour
| Day | 00 | 03 | 06 | 09 | 12 | 15 | 18 | 21 | ||||||||||||||||
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| Sat |
Each cell shows the estimated required scheduled FTE for that day-of-week × hour interval, averaged over the observed days. Available FTE is a flat user assumption (no real roster exists). Gaps are planning estimates, not observed historical shortages.