Optimal Demand Execution Strategy for the Defense Logistics Agency

Abstract

The Defense Logistics Agency (DLA) updates its demand forecasts and creates orders to replenish aviation hardware inventory levels once each month. The current system creates cyclical shortages in demand planning staff due to monthly spikes in forecasting and purchase order activities. These staffing shortfalls could be reduced or eliminated if the workload were more evenly distributed over time. The project goal is to determine the optimal forecast interval (time between forecast updates) and duration (length of forecast) such that monthly workload variation among the DLA's purchasing staff is minimized, subject to the constraint of satisfying customer order requirements. The measure of effectiveness is the extent to which workload variations are reduced over time compared to the status quo.