OPERATIONS, TECHNOLOGY, AND INFORMATION MANAGEMENT


A Practical End-to-End Inventory Management Model


MENG QI ASSISTANT PROFESSOR


Cornell Peter and Stephanie Nolan School of Hotel Administration


Cornell SC Johnson College of Business Cornell University


with Deep Learning Management Science, 69, 2, February 2023 LINK TO PAPER LINK TO VIDEO


Co-authors • Meng Qi, Assistant Professor, Cornell Peter and Stephanie Nolan School of Hotel


Administration, Cornell SC Johnson College of Business, Cornell University


• Chenxin Ma, Lehigh University • Yongzhi Qi, Design Veronique • Zuo-Jun (Max) Shen, University of California, Berkeley • Yuanyuan Shi, University of California, San Diego • Rong Yuan, Data Scientist, Stitch Fix • Di Wu, NVIDIA


Summary


Inventory management has been an active research topic in management science for more than a century. In today’s fiercely-competitive digital world, e-commerce companies are facing new inventory management challenges, due to increasing customer diversity, product variety, and service require- ments. Large e-commerce platforms like Amazon and JD.com sell hundreds of millions of products simultaneously, with various demand patterns requiring different replenishment strategies. Current practices can’t manage this many products efficiently, so it is critical to develop a framework that can identify optimal or close-to-optimal strategies.


Te authors propose a one-step end-to-end (E2E) framework that uses deep learning models to output the suggested replenishment amount directly from input features without any intermediate step. By conducting a series of thor- ough numerical experiments using real data and field experiments with lead- ing e-commerce companies, they demonstrate the advantages of the proposed E2E model over conventional predict-then-optimize (PTO) frameworks, and show that their algorithm substantially reduces holding cost, stockout cost, total inventory cost, and turnover rate compared with current practices. Tis E2E concept can also be useful for other supply chain management settings.


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RESEARCH WITH IMPACT: CORNELL SC JOHNSON COLLEGE OF BUSINESS • 2023 EDITION


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