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End-to-End Predictive Analytics and Optimization in Ingram Micro’s Two-Tier Distribution Business

Author

Listed:
  • Reetabrata (Reeto) Mookherjee

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

  • Jeet Mukherjee

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

  • Jim Martineau

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

  • Liang Xu

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612,)

  • Meggen Gullo

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

  • Kailai Zhou

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

  • Andrew Hazlewood

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

  • Xiaochuan (Tracy) Zhang

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

  • Ferrari Griarte

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

  • Ni Li

    (Global Business Intelligence and Analytics Center, Ingram Micro Inc., Irvine, California 92612)

Abstract

Ingram Micro, the world’s largest distributor of technology products, operates in a high-volume low-margin environment. The company started its Business Intelligence and Analytics practice in North America in 2009. This group has since built and deployed a scalable, innovative price-optimization engine, a set of analytics applications to identify sales opportunities for Ingram Micro’s sales force and an integrated digital marketing platform to run data-driven marketing campaigns for its customers and end-user businesses. Since 2011, these products and analytics programs have generated $1.3 billion of incremental product revenue and $42 million of incremental gross profit. Our next steps are to continue to implement these best practices in regions outside of North America and continue our activities that enable our sales force to generate revenue.

Suggested Citation

  • Reetabrata (Reeto) Mookherjee & Jeet Mukherjee & Jim Martineau & Liang Xu & Meggen Gullo & Kailai Zhou & Andrew Hazlewood & Xiaochuan (Tracy) Zhang & Ferrari Griarte & Ni Li, 2016. "End-to-End Predictive Analytics and Optimization in Ingram Micro’s Two-Tier Distribution Business," Interfaces, INFORMS, vol. 46(1), pages 49-73, February.
    • Handle: RePEc:inm:orinte:v:46:y:2016:i:1:p:49-73
    DOI: 10.1287/inte.2015.0834
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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. Hongmin Li & Scott Webster & Nicholas Mason & Karl Kempf, 2019. "Product-Line Pricing Under Discrete Mixed Multinomial Logit Demand," Service Science, INFORMS, vol. 21(1), pages 14-28, January.

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