Strategic Safety Stocks in Supply Chains with Evolving Forecasts

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.