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TITLE: Strategic safety stocks in supply chains: update on recent research
SPEAKER: Stephen C. Graves
ABSTRACT:
A central question in supply chain management is how to coordinate activities and inventories over a large number of stages and locations, while providing a high level of service to end customers. One methodology for addressing this problem is the guaranteed service (GS) framework, in which each supply-chain stage operates with a base stock policy and provides guaranteed service to its immediate customers, either internal or external. Demand is assumed to be bounded. Previous work on GS models has established algorithms for finding the optimal safety stock placement. In this talk we will present two important extensions that broaden the applicability of the GS models (time permitting). First, we apply the GS framework to a setting with an evolving forecast, i.e., where we have a rolling multi-period forecast that changes over time. We now assume a bound on the forecast errors rather than on the demand process, and can show how to adapt the GS model and algorithms to account for the evolving forecast. For a case study we find that inclusion of the forecast has the potential to reduce safety stocks by 25%, relative to the base-stock model. Second, we generalize the GS model to account for capacity constraints. We develop a single-stage base-stock model with a capacity constraint; we can then incorporate this single-stage model into a network model. We also find that the inclusion of a capacity constraint can sometimes result in less inventory than in the corresponding GS model without a capacity constraint.
