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Analytics Makes Inventory Planning a Lights-Out Activity at Intel Corporation

Author

Listed:
  • Matthew P. Manary

    (Data Center Group, Intel Corporation, Hillsboro, Oregon 97124)

  • Brian Wieland

    (Supply Chain Design and Analytics Group, Intel Corporation, Folsom, California 95464)

  • Sean P. Willems

    (Haslam College of Business, University of Tennessee, Knoxville, Tennessee 37934)

  • Karl G. Kempf

    (Decision Engineering Group, Intel Corporation, Chandler, Arizona 85226)

Abstract

This paper documents more than a decade of work to produce an automated inventory target-setting process to enable Intel to manage more than $1 billion of finished-goods inventory. What began as a manual pilot project in 2005 has grown into an automated inventory planning process encompassing all forward-staged inventory points in Intel’s global distribution network. Key elements in the change transformation include the automatic removal of forecast bias and forecasting based on similar past products. Pivotal to the transformation was first piloting the multiechelon inventory optimization (MEIO) within the existing business process, enabling supply planners to be able to see how MEIO would have been an improvement over their ad hoc approach and tracking the reasons for their system overrides. The resulting inventory models are run weekly, and over 99.5% of each week’s inventory targets are accepted automatically by the supply planning community. For the four-year period spanning 2014–2017, Intel’s finance organization credits the deployment of MEIO with increasing Intel’s gross profits by over $1.3 billion. As of this writing in 2018, this lights-out process manages approximately 85% of all finished-goods inventory. The breadth of the implementation at Intel is evidence that other companies can implement this process and achieve similar results.

Suggested Citation

  • Matthew P. Manary & Brian Wieland & Sean P. Willems & Karl G. Kempf, 2019. "Analytics Makes Inventory Planning a Lights-Out Activity at Intel Corporation," Interfaces, INFORMS, vol. 49(1), pages 52-63, January.
  • Handle: RePEc:inm:orinte:v:49:y:2019:i:1:p:52-63
    DOI: 10.1287/inte.2018.0976
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    References listed on IDEAS

    as
    1. Matthew P. Manary & Sean P. Willems & Alison F. Shihata, 2009. "Correcting Heterogeneous and Biased Forecast Error at Intel for Supply Chain Optimization," Interfaces, INFORMS, vol. 39(5), pages 415-427, October.
    2. Brian Wieland & Pat Mastrantonio & Sean P. Willems & Karl G. Kempf, 2012. "Optimizing Inventory Levels Within Intel's Channel Supply Demand Operations," Interfaces, INFORMS, vol. 42(6), pages 517-527, December.
    3. John J. Neale & Sean P. Willems, 2015. "The Failure of Practical Intuition: How Forward-Coverage Inventory Targets Cause the Landslide Effect," Production and Operations Management, Production and Operations Management Society, vol. 24(4), pages 535-546, April.
    4. Matthew P. Manary & Sean P. Willems, 2008. "Setting Safety-Stock Targets at Intel in the Presence of Forecast Bias," Interfaces, INFORMS, vol. 38(2), pages 112-122, April.
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    Cited by:

    1. Michael F. Gorman, 2021. "Contextual Complications in Analytical Modeling: When the Problem is Not the Problem," Interfaces, INFORMS, vol. 51(4), pages 245-261, July.
    2. Klosterhalfen, Steffen T. & Willems, Sean P. & Dittmar, Daniel, 2023. "Safety stock placement in supply chains with expediting," European Journal of Operational Research, Elsevier, vol. 307(2), pages 745-757.

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