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To wait or not to wait: Optimal ordering under lead time uncertainty and forecast updating

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  • Yimin Wang
  • Brian Tomlin

Abstract

There has been a dramatic increase over the past decade in the number of firms that source finished product from overseas. Although this has reduced procurement costs, it has increased supply risk; procurement lead times are longer and are often unreliable. In deciding when and how much to order, firms must consider the lead time risk and the demand risk, i.e., the accuracy of their demand forecast. To improve the accuracy of its demand forecast, a firm may update its forecast as the selling season approaches. In this article we consider both forecast updating and lead time uncertainty. We characterize the firm's optimal procurement policy, and we prove that, with multiplicative forecast revisions, the firm's optimal procurement time is independent of the demand forecast evolution but that the optimal procurement quantity is not. This leads to a number of important managerial insights into the firm's planning process. We show that the firm becomes less sensitive to lead time variability as the forecast updating process becomes more efficient. Interestingly, a forecast‐updating firm might procure earlier than a firm with no forecast updating. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009

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  • Yimin Wang & Brian Tomlin, 2009. "To wait or not to wait: Optimal ordering under lead time uncertainty and forecast updating," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(8), pages 766-779, December.
    • Handle: RePEc:wly:navres:v:56:y:2009:i:8:p:766-779
    DOI: 10.1002/nav.20381
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    3. Liu, Weifeng & Zhu, Feilin & Zhao, Tongtiegang & Wang, Hao & Lei, Xiaohui & Zhong, Ping-an & Fthenakis, Vasilis, 2020. "Optimal stochastic scheduling of hydropower-based compensation for combined wind and photovoltaic power outputs," Applied Energy, Elsevier, vol. 276(C).
    4. Alexandre Forel & Martin Grunow, 2023. "Dynamic stochastic lot sizing with forecast evolution in rolling‐horizon planning," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 449-468, February.
    5. Riezebos, Jan & Zhu, Stuart X., 2020. "Inventory control with seasonality of lead times," Omega, Elsevier, vol. 92(C).
    6. Liu, Zhongyi & Li, Mengyu & Lei, Ying & Zhai, Xin, 2022. "A joint strategy based on ordering and insurance for mitigating the effects of supply chain disruption on risk-averse firms," International Journal of Production Economics, Elsevier, vol. 244(C).
    7. Taher Ahmadi & Zümbül Atan & Ton de Kok & Ivo Adan, 2019. "Optimal control policies for an inventory system with commitment lead time," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(3), pages 193-212, April.
    8. Luo, Sha & Ahiska, S. Sebnem & Fang, Shu-Cherng & King, Russell E. & Warsing, Donald P. & Wu, Shuohao, 2021. "An analysis of optimal ordering policies for a two-supplier system with disruption risk," Omega, Elsevier, vol. 105(C).
    9. Brian M. Lewis & Alan L. Erera & Maciek A. Nowak & White Chelsea C., 2013. "Managing Inventory in Global Supply Chains Facing Port-of-Entry Disruption Risks," Transportation Science, INFORMS, vol. 47(2), pages 162-180, May.
    10. Dina Smirnov & Yale T. Herer & Assaf Avrahami, 2021. "Two‐Phase Newsvendor with Optimally Timed Additional Replenishment: Model, Algorithm, Case Study," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 2871-2889, September.
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