Strategic Safety Stocks in Supply Chains with Evolving Forecasts
Manufacturing & Service Operations Management
Manufacturing & Service Operations Management
Model composability and execution across simulation, optimization, and forecast models
Proceedings of the Symposium on Theory of Modeling & Simulation - DEVS Integrative M&S Symposium
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The life cycle of new products is becoming shorter and shorter in all markets. For electronic products, life cycles are measured in units of months, with 6-to 12-month life cycles being common. Given these short product life cycles, product demand is increasingly difficult to forecast. Furthermore, demand is never really stationary because the demand rate evolves over the life of the product. In this paper, we consider the problem of where in a supply chain to place strategic safety stocks to provide a high level of service to the final customer with minimum cost. We extend our model for stationary demand to the case of nonstationary demand, as might occur for products with short life cycles. We assume that we can model the supply chain as a network, that each stage in the supply chain operates with a periodic review base-stock policy, that demand is bounded, and that there is a guaranteed service time between every stage and its customers. We consider a constant service time (CST) policy for which the safety stock locations are stationary; the actual safety stock levels change as the demand process changes. We show that the optimization algorithm for the case of stationary demand extends directly to determining the safety stocks when demand is nonstationary for a CST policy. We then examine with an illustrative example how well the CST policy performs relative to a dynamic policy that dynamically modifies the service times. In addition, we report on numerical tests that demonstrate the efficacy of the proposed solution and how it would be deployed.