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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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