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Regionalize and Scale: Amazon’s Fulfillment Network Design for Faster and Cheaper Delivery

Author

Listed:
  • Amitabh Sinha

    (Amazon.com, Bellevue, Washington 98004)

  • Jeremy Agte

    (Amazon.com, Bellevue, Washington 98004)

  • Russell Allgor

    (Auger.com, Bellevue, Washington 98004)

  • Cristiana L. Lara

    (Amazon.com, Bellevue, Washington 98004)

  • Ashish Agiwal

    (Amazon.com, Bellevue, Washington 98004)

  • Semih Atakan

    (Amazon.com, Bellevue, Washington 98004)

  • Lourdes Campo

    (Amazon.com, Arlington, Virginia 22202)

  • Tolga Cezik

    (Amazon.com, Bellevue, Washington 98004)

  • Daniel Chen

    (Amazon.com, Singapore 018916)

  • Qi Chen

    (Amazon.com, Bellevue, Washington 98004)

  • Jesse Fischer

    (Amazon.com, Bellevue, Washington 98004)

  • Eitan Gor

    (Amazon.com, Bellevue, Washington 98004)

  • Nader Kabbani

    (Hims & Hers, Bellevue, Washington 98004)

  • Ryan Kennedy

    (Amazon.com, Bellevue, Washington 98004)

  • Kaushik Krishnan

    (Amazon.com, Bellevue, Washington 98004)

  • Yuan Li

    (Amazon.com, Bellevue, Washington 98004)

  • Shahbaaz Mubeen Mamadapur

    (Amazon.com, Bellevue, Washington 98004)

  • Tanmay Mathur

    (Blue Origin, Kent, Washington 98032)

  • Nick McCabe

    (Amazon.com, Tempe, Arizona 85281)

  • David Mildebrath

    (Amazon.com, Bellevue, Washington 98004)

  • Eric Powell

    (Cape, Washington, District of Columbia 20003)

  • Andrea Qualizza

    (Amazon.com, Washington, District of Columbia 20001)

  • Denton Schroeder

    (Amazon.com, New York, New York 10001)

  • Nityansh Seth

    (Blue Origin, Kent, Washington 98032)

  • Xiaoyan Si

    (Amazon.com, Bellevue, Washington 98004)

  • Kaushik Sinha

    (Amazon.com, Boston, Massachusetts 02210)

  • Darren Stegner

    (Amazon.com, Bellevue, Washington 98004)

  • Jun Xiao

    (Amazon.com, Bellevue, Washington 98004)

  • Ling Zhang

    (Amazon.com, Bellevue, Washington 98004)

  • Shanshan Zhang

    (Amazon.com, Bellevue, Washington 98004)

  • Jikai Zou

    (Coupang, Inc., Seattle, Washington 98101)

Abstract

This paper presents Amazon’s implementation of regionalization, a strategic transformation of its fulfillment network in the United States that partitioned the country into eight interconnected but largely self-sufficient regions to address growing complexity and inefficiencies in order fulfillment. By 2021, Amazon’s unprecedented network growth had led to nonlinear increases in transportation system complexity and suboptimal equilibria that increased costs while reducing delivery speeds. The core principle behind regionalization involves matching demand with capacity through geographical partitioning, moving away from a flexible national network toward a more structured regional approach. The development leveraged extensive operations research methodologies over 1.5 years, encompassing region design, network optimization modeling, inventory-speed trade-off analysis, and significant software and operational changes. Following successful pilot and full network deployment by March 2023, regionalization helped deliver substantial improvements: a 15% reduction in distance between sites and customers, 12% fewer middle-mile touchpoints, increased in-region fulfillment from 62% to 76%, and the first reduction in cost-to-serve per unit since 2018, with over $0.45 per-unit savings in the United States alone while simultaneously improving delivery speeds with over nine billion items delivered the same or next day globally in 2024.

Suggested Citation

  • Amitabh Sinha & Jeremy Agte & Russell Allgor & Cristiana L. Lara & Ashish Agiwal & Semih Atakan & Lourdes Campo & Tolga Cezik & Daniel Chen & Qi Chen & Jesse Fischer & Eitan Gor & Nader Kabbani & Ryan, 2026. "Regionalize and Scale: Amazon’s Fulfillment Network Design for Faster and Cheaper Delivery," Interfaces, INFORMS, vol. 56(1), pages 23-41, January.
  • Handle: RePEc:inm:orinte:v:56:y:2026:i:1:p:23-41
    DOI: 10.1287/inte.2025.0295
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    References listed on IDEAS

    as
    1. Philipp Afèche & René Caldentey & Varun Gupta, 2022. "On the Optimal Design of a Bipartite Matching Queueing System," Operations Research, INFORMS, vol. 70(1), pages 363-401, January.
    2. Levi DeValve & Yehua Wei & Di Wu & Rong Yuan, 2023. "Understanding the Value of Fulfillment Flexibility in an Online Retailing Environment," Manufacturing & Service Operations Management, INFORMS, vol. 25(2), pages 391-408, March.
    3. William C. Jordan & Stephen C. Graves, 1995. "Principles on the Benefits of Manufacturing Process Flexibility," Management Science, INFORMS, vol. 41(4), pages 577-594, April.
    4. Omar Besbes & Francisco Castro & Ilan Lobel, 2022. "Spatial Capacity Planning," Operations Research, INFORMS, vol. 70(2), pages 1271-1291, March.
    5. Russell Allgor & Tolga Cezik & Daniel Chen, 2023. "Algorithm for Robotic Picking in Amazon Fulfillment Centers Enables Humans and Robots to Work Together Effectively," Interfaces, INFORMS, vol. 53(4), pages 266-282, July.
    6. John Gunnar Carlsson & Xiaoshan Peng & Ilya O. Ryzhov, 2024. "Demand Equilibria in Spatial Service Systems," Manufacturing & Service Operations Management, INFORMS, vol. 26(6), pages 2305-2321, November.
    7. Lara, Cristiana L. & Koenemann, Jochen & Nie, Yisu & de Souza, Cid C., 2023. "Scalable timing-aware network design via lagrangian decomposition," European Journal of Operational Research, Elsevier, vol. 309(1), pages 152-169.
    8. Mulvey, John M. & Beck, Michael P., 1984. "Solving capacitated clustering problems," European Journal of Operational Research, Elsevier, vol. 18(3), pages 339-348, December.
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