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Optimizing Capital Investment Decisions at Intel Corporation

Author

Listed:
  • Karl G. Kempf

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

  • Feryal Erhun

    (Management Science and Engineering, Stanford University, Stanford, California 94305)

  • Erik F. Hertzler

    (Technology Manufacturing Engineering, Intel Corporation, Chandler, Arizona 85226)

  • Timothy R. Rosenberg

    (Financial Enterprise Services, Intel Corporation, Chandler, Arizona 85226)

  • Chen Peng

    (Management Science and Engineering, Stanford University, Stanford, California 94305, chenpeng@alumni.stanford.edu; currently at Google Inc., Mountain View, California)

Abstract

Intel Corporation spends over $5 billion annually on manufacturing equipment. With increasing lead times from equipment suppliers and increasing complexity in forecasting market demand, optimizing capital investment decisions is a significant managerial challenge. In response to this challenge, we developed a capital supply chain velocity program for ordering, shipping, and installing production equipment. At the core of this velocity program is a new and additional procurement framework that enables Intel to purchase options from its equipment suppliers for a faster delivery of some equipment. The framework seamlessly combines statistical forecasting with Monte Carlo simulation and stochastic programming to determine the number of options Intel should procure and exercise, and it includes built-in scenario and sensitivity analysis capabilities to support Intel’s contract selection, options reservation, and equipment procurement decisions. The velocity program and the framework provided Intel with hundreds of millions of dollars in cost savings and at least $2 billion in revenue upside during a recent period of global economic crisis.

Suggested Citation

  • Karl G. Kempf & Feryal Erhun & Erik F. Hertzler & Timothy R. Rosenberg & Chen Peng, 2013. "Optimizing Capital Investment Decisions at Intel Corporation," Interfaces, INFORMS, vol. 43(1), pages 62-78, February.
    • Handle: RePEc:inm:orinte:v:43:y:2013:i:1:p:62-78
    DOI: 10.1287/inte.1120.0659
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    References listed on IDEAS

    as
    1. Özgür Yazlali & Feryal Erhun, 2009. "Dual-supply inventory problem with capacity limits on order sizes and unrestricted ordering costs," IISE Transactions, Taylor & Francis Journals, vol. 41(8), pages 716-729.
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    Cited by:

    1. Dimitrios Folinas & Naoum Tsolakis & Dimitrios Aidonis, 2018. "Logistics Services Sector and Economic Recession in Greece: Challenges and Opportunities," Logistics, MDPI, vol. 2(3), pages 1-16, August.
    2. Hongmin Li & Dieter Armbruster & Karl G. Kempf, 2013. "A Population-Growth Model for Multiple Generations of Technology Products," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 343-360, July.
    3. Smirnov, Dina & van Jaarsveld, Willem & Atan, Zümbül & de Kok, Ton, 2021. "Long-term resource planning in the high-tech industry: Capacity or inventory?," European Journal of Operational Research, Elsevier, vol. 293(3), pages 926-940.
    4. Wagner, Stephan M. & Grosse-Ruyken, Pan Theo & Erhun, Feryal, 2018. "Determinants of sourcing flexibility and its impact on performance," International Journal of Production Economics, Elsevier, vol. 205(C), pages 329-341.

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