Strategic Safety Stocks in Supply Chains with Evolving Forecasts
Abstract
We examine the placement of safety stocks in a supply chain for which we have an evolving demand forecast. Under assumptions about the forecasts, the demand process, and the supply chain structure, we show that safety-stock placement for such systems is effectively equivalent to the corresponding well-studied problem for systems with stationary demand bounds and base-stock policies. Hence, we can use existing algorithms to find the optimal safety stocks. We use a case study with real data to demonstrate that there are significant benefits from the inclusion of the forecast process when determining the optimal safety stocks. We also conduct a computational experiment to explore how the placement and size of the safety stocks depend on the nature of the forecast evolution process.

