Data Analytics in Operations Management: A Review | Zendy

Velibor V. Mišić | Zendy; Georgia Perakis | Zendy

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Data Analytics in Operations Management: A Review

Author(s) -

Velibor V. Mišić,

Georgia Perakis

Publication year - 2019

Publication title -

manufacturing and service operations management

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.372

H-Index - 83

eISSN - 1526-5498

pISSN - 1523-4614

DOI - 10.1287/msom.2019.0805

Subject(s) - revenue management , analytics , computer science , data science , data management , revenue , supply chain management , big data , data analysis , supply chain , process management , operations research , business , marketing , engineering , data mining , accounting

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.

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