Assessment of Forecasting Methods: Cooperative Logistics Supply SupportArrangement (CLSSA) Investment Items

摘要

The United States (US) promotes collective security in the Free World via theForeign Military Sales (FMS) program. FMS customers prefer to acquire weapon system logistic support through FMS rather than by direct commercial vendor support. Ninety-seven percent of the follow-on logistics requirements are submitted via a special program called Cooperative Logistics Supply Support Arrangement (CLSSA). CLSSA, while sound in theory, has been a poor performer. The USAF must modify the CLSSA program or risk losing future FMS to competing nations. Modifying CLSSA to utilize an automated forecasting process will greatly improve customer service. Efficient and timely logistic support is a key decision factor as friendly nations evaluate the source of their next major weapon system acquisition. The US as a whole will gain from the USAFs new approach to CLSSA through the political, military and economic benefits that remit from increase FMS demand for US weapon systems. This study measured the relative accuracy of four time series forecasting methods in predicting future demands for CLSSA Investment Items. The double exponential smoothing, adaptive response, and classical decomposition were compared to the AFSAC retention model to determine the impact of changing to an automated method. The results favored the implementation of the AFSAC retention method with some minor modifications in the weighting scheme, rounding rules, and demand smoothing. Forecasting, Reparable items, Inventory management, Retention, Cooperative Logistics Supply Support Arrangement (CLSSA), Foreign Military Sales (FMS).