Managing Inventory in Supply Chains with Nonstationary Demand

John J. Neale () and Sean P. Willems ()
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John J. Neale: School of Management, Boston University, Boston, Massachusetts 02215
Sean P. Willems: School of Management, Boston University, Boston, Massachusetts 02215

Interfaces, 2009, vol. 39, issue 5, 388-399

Abstract: Many companies experience nonstationary demand because of short product life cycles, seasonality, customer buying patterns, or other factors. We present a practical model for managing inventory in a supply chain facing stochastic, nonstationary demand. Our model is based on the guaranteed service modeling framework. We first describe how inventory levels should adapt to changes in demand at a single stage. We then show how nonstationary demand propagates in a supply chain, allowing us to link stages and apply a multiechelon optimization algorithm designed originally for stationary demand. We describe two successful applications of this model. The first is a tactical implementation to support monthly safety stock planning at Microsoft. The second is a strategic project to evaluate the benefits of using an inventory pool at Case New Holland.

Keywords: multiechelon inventory optimization; stochastic; nonstationary demand; base-stock policy; supply chain application (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:39:y:2009:i:5:p:388-399

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