Forecasting Navy issue and receipt workload at Defense Logistics Agency depots

Abstract

Each year the Defense Logistics Agency (DLA) asks the military services to estimate their future issue and receipt workload demands at DLA distribution depots. DLA uses these estimates to determine expected costs and revenues at the distribution depots. Accurate workload forecasting allows DLA planners to establish appropriate surcharges for their services. Inaccurate estimates can lead to higher costs to DLA and, ultimately, to the Navy. We evaluate current Navy forecasting methods and develop several causative factors that influence issue and receipt workload. We present single and multiple regression models to predict future issue and receipt demands and compare these models with those currently used by Naval Supply Systems Command. Our results suggest that causal based modeling is a feasible alternative to current models and may more accurately estimate future issue and receipt workload for the Navy