Dynamic Forecasting in Emergency Communications A Modern Approach to Aligning Staffing with Real Demand

Abstract

Emergency communication centres face unique operational pressures when staffing models fail to reflect true call demand. Traditional static staffing assumes uniform workload across time, yet emergency call patterns fluctuate daily, weekly, monthly, and seasonally. At Calgary 911 (C911), these mismatches resulted in inefficiencies, heightened employee strain, and unpredictable service levels. In response, C911 implemented a dynamic forecasting system built on complementary long-term and short-term predictive models. These forecasts feed into Erlang C calculations and are refined further with operational constraints, producing accurate, actionable staffing requirements. This article explores the development and implementation of this system, highlighting insights gained, lessons learned, and the operational advantages of data-driven staffing. The approach demonstrates how modern forecasting strengthens emergency communication operations and improves the alignment between workload and workforce.