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

Matthew P. Manary (), Brian Wieland (), Sean P. Willems () and Karl G. Kempf ()
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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

Interfaces, 2019, vol. 49, issue 1, 52-63

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.

Keywords: industries: high technology and semiconductors; inventory/production: applications; multi-item/echelon/stage; forecasting; bias removal; change management (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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