JD.com Improves Fulfillment Efficiency with Data-Driven Integrated Assortment Planning and Inventory Allocation

Zuo-Jun Max Shen (), Shuo Sun (), Yongzhi Qi (), Hao Hu (), Ningxuan Kang (), Jianshen Zhang (), Xin Wang () and Xiaoming Lin ()
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Zuo-Jun Max Shen: Department of Industrial Engineering and Operations Research, University of California, Berkeley, California 94720; and Faculty of Engineering, The University of Hong Kong, Hong Kong; and Faculty of Business and Economics, The University of Hong Kong, Hong Kong
Shuo Sun: Department of Industrial Engineering and Operations Research, University of California, Berkeley, California 94720
Yongzhi Qi: Supply Chain Tech Team, JD.com, Beijing 101111, China
Hao Hu: Supply Chain Tech Team, JD.com, Beijing 101111, China
Ningxuan Kang: Supply Chain Tech Team, JD.com, Beijing 101111, China
Jianshen Zhang: Supply Chain Tech Team, JD.com, Beijing 101111, China
Xin Wang: Supply Chain Tech Team, JD.com, Beijing 101111, China
Xiaoming Lin: Supply Chain Tech Team, JD.com, Beijing 101111, China

Interfaces, 2025, vol. 55, issue 5, 386-398

Abstract: This paper presents data-driven approaches for integrated assortment planning and inventory allocation that significantly improve fulfillment efficiency at JD.com, a leading e-commerce company. JD.com uses a two-level distribution network that includes regional distribution centers (RDCs) and front distribution centers (FDCs). Selecting products to stock at FDCs and then, optimizing daily inventory allocation from RDCs to FDCs are critical to improving fulfillment efficiency, which is crucial for enhancing customer experiences. For assortment planning, we propose efficient algorithms to maximize the number of orders that can be fulfilled by FDCs (local fulfillment). For inventory allocation, we develop a novel end-to-end algorithm that integrates forecasting, optimization, and simulation to minimize lost sales and inventory-transfer costs. Numerical experiments demonstrate that our methods outperform existing approaches, increasing local order fulfillment rates by 0.54%, and our inventory allocation algorithm increases FDC demand satisfaction rates by 1.05%. Considering the high-volume operations of JD.com, with millions of weekly orders per region, these improvements yield substantial benefits beyond the company’s established supply chain system. Implementation across JD.com’s network has reduced costs, improved stock availability, and increased local order fulfillment rates for millions of orders annually.

Keywords: Wagner Prize; assortment planning; inventory allocation; fulfillment efficiency; supply chain system (search for similar items in EconPapers)
Date: 2025
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