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Kroger Uses Simulation-Optimization to Improve Pharmacy Inventory Management

Author

Listed:
  • Xinhui Zhang

    (Kroger Operations Research Group, Cincinnati, Ohio 45242; and Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, Ohio 45435)

  • Doug Meiser

    (Kroger Operations Research Group, Cincinnati, Ohio 45242)

  • Yan Liu

    (Kroger Operations Research Group, Cincinnati, Ohio 45242; and Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, Ohio 45435)

  • Brett Bonner

    (Kroger Operations Research Group, Cincinnati, Ohio 45242)

  • Lebin Lin

    (Kroger Operations Research Group, Cincinnati, Ohio 45242; and Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, Ohio 45435)

Abstract

The Kroger Co. is the largest grocery retailer in the United States. It operates 2,422 supermarkets and 1,950 in-store pharmacies. Improving customer service is at the heart of Kroger’s business strategy. Toward this end, Kroger’s operations research team, in collaboration with faculty from Wright State University, developed an innovative simulation-optimization system for pharmacy inventory management. In pharmacy applications, traditional standard statistical distributions fall short of providing accurate pharmacy demand distributions. To overcome business resistance to complex formulas, this simulation-optimization approach uses empirical distributions to model demand, provides end users with a visual intuitive experience, and delivers optimal or near-optimal results in milliseconds through local search heuristics. The system was implemented in October 2011 in all Kroger pharmacies in the United States, and has reduced out-of-stocks by 1.6 million per year, ensuring greater patient access to medications. It has resulted in an increase in revenue of $80 million per year, a reduction in inventory of more than $120 million, and a reduction in labor cost equivalent to $10 million per year.

Suggested Citation

  • Xinhui Zhang & Doug Meiser & Yan Liu & Brett Bonner & Lebin Lin, 2014. "Kroger Uses Simulation-Optimization to Improve Pharmacy Inventory Management," Interfaces, INFORMS, vol. 44(1), pages 70-84, February.
  • Handle: RePEc:inm:orinte:v:44:y:2014:i:1:p:70-84
    DOI: 10.1287/inte.2013.0724
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    References listed on IDEAS

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    Cited by:

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    2. Yuming Deng & Xinhui Zhang & Tong Wang & Lin Wang & Yidong Zhang & Xiaoqing Wang & Su Zhao & Yunwei Qi & Guangyao Yang & Xuezheng Peng, 2023. "Alibaba Realizes Millions in Cost Savings Through Integrated Demand Forecasting, Inventory Management, Price Optimization, and Product Recommendations," Interfaces, INFORMS, vol. 53(1), pages 32-46, January.
    3. Nguyen, Duy Tan & Adulyasak, Yossiri & Landry, Sylvain, 2021. "Research manuscript: The Bullwhip Effect in rule-based supply chain planning systems–A case-based simulation at a hard goods retailer," Omega, Elsevier, vol. 98(C).
    4. Qiang Liu & Xinhui Zhang & Yan Liu & Lebin Lin, 2013. "Spreadsheet Inventory Simulation and Optimization Models and Their Application in a National Pharmacy Chain," INFORMS Transactions on Education, INFORMS, vol. 14(1), pages 13-25, September.
    5. Yucheng Chen & Stephanie A. Gernant & Charlie M. Upton & Manuel A. Nunez, 2022. "Incorporating medication therapy management into community pharmacy workflows," Health Care Management Science, Springer, vol. 25(4), pages 710-724, December.
    6. John P. Saldanha & Bradley S. Price & Douglas J. Thomas, 2023. "A nonparametric approach for setting safety stock levels," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1150-1168, April.

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