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Blending OR/MS, Judgment, and GIS: Restructuring P&G's Supply Chain

Author

Listed:
  • Jeffrey D. Camm

    (Department of Quantitative Analysis and Operations Management, University of Cincinnati, Cincinnati, Ohio 45221-0130)

  • Thomas E. Chorman

    (The Procter & Gamble Company, Cincinnati, Ohio 45224)

  • Franz A. Dill

    (The Procter & Gamble Company, Cincinnati, Ohio 45224)

  • James R. Evans

    (Department of Quantitative Analysis and Operations Management, University of Cincinnati, Cincinnati, Ohio 45221-0130)

  • Dennis J. Sweeney

    (Department of Quantitative Analysis and Operations Management, University of Cincinnati, Cincinnati, Ohio 45221-0130)

  • Glenn W. Wegryn

    (The Procter & Gamble Company, 2 Procter & Gamble Plaza, PNC-12, Cincinnati, Ohio 45201-5559)

Abstract

In 1993, Procter & Gamble (P&G) began an effort entitled strengthening global effectiveness (SGE) to streamline work processes, drive out nonvalue-added costs, and eliminate duplication. A principal component of SGE was the North American product supply study, designed to reexamine and reengineer P&G's product-sourcing and distribution system for its North American operations. The methodology developed to solve this problem drew on OR/MS and information technology, merging integer programming, network optimization models, and a geographical information system (GIS). As a result of this study, P&G is reducing the number of North American plants by almost 20 percent, saving over $200 million in pretax costs per year and renewing its focus on OR/MS approaches.

Suggested Citation

  • Jeffrey D. Camm & Thomas E. Chorman & Franz A. Dill & James R. Evans & Dennis J. Sweeney & Glenn W. Wegryn, 1997. "Blending OR/MS, Judgment, and GIS: Restructuring P&G's Supply Chain," Interfaces, INFORMS, vol. 27(1), pages 128-142, February.
    • Handle: RePEc:inm:orinte:v:27:y:1997:i:1:p:128-142
    DOI: 10.1287/inte.27.1.128
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    Cited by:

    1. De Boeck, Kim & Decouttere, Catherine & Jónasson, Jónas Oddur & Vandaele, Nico, 2022. "Vaccine supply chains in resource-limited settings: Mitigating the impact of rainy season disruptions," European Journal of Operational Research, Elsevier, vol. 301(1), pages 300-317.
    2. Murray, Alan T., 2021. "Contemporary optimization application through geographic information systems," Omega, Elsevier, vol. 99(C).
    3. Valerie Tardif & Sridhar Tayur & James Reardon & Reid Stines & Pete Zimmerman, 2010. "OR Practice---Implementing Seasonal Logistics Tactics for Finished Goods Distribution at Deere & Company's C&CE Division," Operations Research, INFORMS, vol. 58(1), pages 1-15, February.
    4. Holzapfel, Andreas & Potoczki, Tobias & Kuhn, Heinrich, 2023. "Designing the breadth and depth of distribution networks in the retail trade," International Journal of Production Economics, Elsevier, vol. 257(C).
    5. Mustapha Ouhimmou & Sophie D'Amours & Robert Beauregard & Daoud Ait-Kadi & Satyaveer Singh Chauhan, 2009. "Optimization Helps Shermag Gain Competitive Edge," Interfaces, INFORMS, vol. 39(4), pages 329-345, August.
    6. Feng Yang & Dexiang Wu & Liang Liang & Gongbing Bi & Desheng Wu, 2011. "Supply chain DEA: production possibility set and performance evaluation model," Annals of Operations Research, Springer, vol. 185(1), pages 195-211, May.

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