Integrated Digital Supply Chain at JD Logistics: Architecture, Practices, and Future Directions

JD Logistics, originally serving JD.com, spun off in 2017 to become an independent logistics provider, leveraging a decade of technology to serve external customers with a technology‑driven approach.

The company promotes an integrated supply‑chain model that combines physical networks (warehousing, last‑mile, cold‑chain, cross‑border, etc.) with advanced digital capabilities, aiming to transform logistics into a system‑wide, algorithmic, and data‑centric operation.

Digitalization is pursued through three stages—intelligent planning, intelligent scheduling, and intelligent execution—supported by a layered architecture that includes a data middle‑platform, an algorithm platform, and two engineering platforms (the YiBu engineering platform and the digital‑twin platform).

The algorithm platform abstracts business‑driven algorithms into reusable components, enabling rapid deployment of over 130 prediction models and 40+ algorithm strategies across 30+ scenarios, improving service efficiency for thousands of merchants.

The YiBu platform focuses on forecasting and scenario configuration, while the digital‑twin platform creates virtual representations of physical logistics to simulate and optimize decisions before applying them to the real world.

Three system applications—intelligent planning tower, intelligent scheduling tower, and the JD慧 supply‑chain system—leverage these platforms to optimize network design, routing, inventory allocation, and demand forecasting, delivering measurable cost reductions and performance gains.

Case studies illustrate the impact: a consumer‑goods client achieved lower logistics costs, higher inventory turnover, and improved fulfillment rates through end‑to‑end digital integration; a spare‑parts manufacturer reduced inventory by 20‑30% and enhanced supplier on‑time delivery via a comprehensive digital supply‑chain solution.

For smaller merchants, JD Logistics offers standardized, configurable supply‑chain services that have already benefited hundreds of businesses, reducing cross‑region shipments and overall logistics expenses.

The future outlook emphasizes talent development at the intersection of data science, AI, and engineering, the progression from digital infrastructure to digital‑twin platforms, and ultimately the creation of an industry‑wide digital ecosystem resembling a supply‑chain metaverse.

A Q&A section highlights the synergy between traditional operations research and deep learning, as well as innovative warehouse practices such as pick‑path optimization and computer‑vision‑based damage detection.