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Data Analytics in Operations Management: A Review

Author

Listed:
  • Velibor V. Mišić

    (Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095;)

  • Georgia Perakis

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

Research in operations management has traditionally focused on models for understanding, mostly at a strategic level, how firms should operate. Spurred by the growing availability of data and recent advances in machine learning and optimization methodologies, there has been an increasing application of data analytics to problems in operations management. In this paper, we review recent applications of data analytics to operations management in three major areas—supply chain management, revenue management, and healthcare operations—and highlight some exciting directions for the future.

Suggested Citation

  • Velibor V. Mišić & Georgia Perakis, 2020. "Data Analytics in Operations Management: A Review," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 158-169, January.
    • Handle: RePEc:inm:ormsom:v:22:y:2020:i:1:p:158-169
    DOI: 10.1287/msom.2019.0805
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    References listed on IDEAS

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    1. Ravindra K. Ahuja & James B. Orlin, 2001. "Inverse Optimization," Operations Research, INFORMS, vol. 49(5), pages 771-783, October.
    2. Pavithra Harsha & Shivaram Subramanian & Joline Uichanco, 2019. "Dynamic Pricing of Omnichannel Inventories," Service Science, INFORMS, vol. 21(1), pages 47-65, January.
    3. Vivek F. Farias & Andrew A. L, 2019. "Learning Preferences with Side Information," Management Science, INFORMS, vol. 65(7), pages 3131-3149, July.
    4. Fernando Bernstein & Sajad Modaresi & Denis Sauré, 2019. "A Dynamic Clustering Approach to Data-Driven Assortment Personalization," Management Science, INFORMS, vol. 67(5), pages 2095-2115, May.
    5. Assaf Avrahami & Yale T. Herer & Retsef Levi, 2014. "Matching Supply and Demand: Delayed Two-Phase Distribution at Yedioth Group—Models, Algorithms, and Information Technology," Interfaces, INFORMS, vol. 44(5), pages 445-460, October.
    6. Jose Blanchet & Guillermo Gallego & Vineet Goyal, 2016. "A Markov Chain Approximation to Choice Modeling," Operations Research, INFORMS, vol. 64(4), pages 886-905, August.
    7. Teck-Hua Ho & Noah Lim & Sadat Reza & Xiaoyu Xia, 2017. "OM Forum—Causal Inference Models in Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 509-525, October.
    8. Gah-Yi Ban & Cynthia Rudin, 2019. "The Big Data Newsvendor: Practical Insights from Machine Learning," Operations Research, INFORMS, vol. 67(1), pages 90-108, January.
    9. Jacob Feldman & Alice Paul & Huseyin Topaloglu, 2019. "Technical Note—Assortment Optimization with Small Consideration Sets," Operations Research, INFORMS, vol. 67(5), pages 1283-1299, September.
    10. Negin Golrezaei & Hamid Nazerzadeh & Paat Rusmevichientong, 2014. "Real-Time Optimization of Personalized Assortments," Management Science, INFORMS, vol. 60(6), pages 1532-1551, June.
    11. Anil Aswani & Zuo-Jun Max Shen & Auyon Siddiq, 2019. "Data-Driven Incentive Design in the Medicare Shared Savings Program," Operations Research, INFORMS, vol. 67(4), pages 1002-1026, July.
    12. Long He & Ho-Yin Mak & Ying Rong & Zuo-Jun Max Shen, 2017. "Service Region Design for Urban Electric Vehicle Sharing Systems," Manufacturing & Service Operations Management, INFORMS, vol. 19(2), pages 309-327, May.
    13. Vivek F. Farias & Srikanth Jagabathula & Devavrat Shah, 2013. "A Nonparametric Approach to Modeling Choice with Limited Data," Management Science, INFORMS, vol. 59(2), pages 305-322, December.
    14. Dimitris Bertsimas & Vivek F. Farias & Nikolaos Trichakis, 2013. "Fairness, Efficiency, and Flexibility in Organ Allocation for Kidney Transplantation," Operations Research, INFORMS, vol. 61(1), pages 73-87, February.
    15. Sandeep Rath & Kumar Rajaram & Aman Mahajan, 2017. "Integrated Anesthesiologist and Room Scheduling for Surgeries: Methodology and Application," Operations Research, INFORMS, vol. 65(6), pages 1460-1478, December.
    16. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
    17. Dimitris Bertsimas & Allison O’Hair & Stephen Relyea & John Silberholz, 2016. "An Analytics Approach to Designing Combination Chemotherapy Regimens for Cancer," Management Science, INFORMS, vol. 62(5), pages 1511-1531, May.
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