Title
Correcting Heterogeneous and Biased Forecast Error at Intel for Supply Chain Optimization
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.
Year
DOI
Venue
2009
10.1287/inte.1090.0452
Interfaces
Keywords
Field
DocType
biased forecast error,on-hand inventory commitment,heterogeneous forecast error,multiechelon inventory optimization model,existing planning process,inventory target,nonnormal forecast error,forecast imperfection,forecast bias,correcting heterogeneous,intel business unit,supply chain optimization,structured decision-making process,applications,forecasting,supply chain
Safety stock,Supply chain optimization,Communication channel,Operations research,Supply chain,Engineering,Forecast error,Supply and demand,Inventory optimization,Operations management,Forecast bias
Journal
Volume
Issue
ISSN
39
5
0092-2102
Citations 
PageRank 
References 
3
0.52
1
Authors
3
Name
Order
Citations
PageRank
Matthew P. Manary191.75
Sean P. Willems225129.89
Alison F. Shihata330.52