Correcting Heterogeneous and Biased Forecast Error at Intel for Supply Chain Optimization

Matthew P. Manary (), Sean P. Willems () and Alison F. Shihata ()
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Matthew P. Manary: Server Platform Group, Intel Corporation, Hillsboro, Oregon 97124
Sean P. Willems: School of Management, Boston University, Boston, Massachusetts 02215
Alison F. Shihata: Planning and Logistics Group, Intel Corporation, Hillsboro, Oregon 97124

Interfaces, 2009, vol. 39, issue 5, 415-427

Abstract: In 2007, Intel's Channel Supply Demand Operations launched an initiative to improve its supply chain performance. To ensure success, the process had to fit within the existing planning processes. In practice, this meant that setting service-level and inventory targets, which had previously been external inputs to the process, had to become part of the structured decision-making process. Although other Intel business units had achieved success implementing a multiechelon inventory optimization model, the boxed processor environment posed some unique challenges. The primary technical challenge required correcting for the impact of forecast bias, nonnormal forecast errors, and heterogeneous forecast errors. This paper documents the procedure and algorithms that Intel developed and implemented in 2008 to counter the impact of forecast imperfections. The process resulted in safety stock reductions of approximately 15 percent. At any given time, Intel applies this process to its 20--30 highest-volume boxed processors, determining an on-hand inventory commitment between $50 million and $75 million.

Keywords: forecasting; applications; industries; computer/electronic; inventory/production; applications; multiechelon safety stock optimization (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (9)

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