Using military operational planning system data to drive reserve stocking decisions

Forecast-based demand predictions have become a mainstay in the military inventory management process. However, their sole reliance on retrospective demand prediction may make them unsuitable to handle unforeseen lumpy demands. To address this gap, we present a methodology, which effectively incorporates Advance Demand Information (ADI) derived from a military operational planning system, to determine strategic reserve stocks required to satisfy unforeseen lumpy demands. We present two approaches - the Adjusted Reorder Point approach (AROP) and the Coordinated Management approach (CM) - to determine strategic reserve stocks and incorporate them in the military inventory management process. The two approaches have been tested against their ability to satisfy unforeseen variable lumpy demand for a single supply item. Our empirical evaluation indicates that the AROP approach is more suited to the planning of recurrent military operations, while the CM approach is well suited for one-off military operations.