People Analytics in the Age of Big Data: An Agenda for IS Research

Uri Gal, Tina Blegind Jensen, Mari-Klara Stein

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


Over the last decade, a growing number of organizations have started to apply various data-driven computational techniques and algorithmic technologies to manage their workforce. The fundamental objective of these technologies, known as People Analytics, is to enable more effective, objective, and rational decision-making about people. High expectations surround such technologies, as they can drive competitive advantage and innovation through better utilization of human talent. However, the application of algorithms to manage people (rather than supply chains or business processes) entails multiple ethical and practical complexities. In this short paper, we seek to unpack the main assumptions that underlie the use of People Analytics to portray a nuanced and critical picture of its possible ramifications. Based on this critical examination, we outline a research agenda that identifies multiple avenues for future IS research into People Analytics.
Original languageEnglish
Title of host publicationICIS 2017 Proceedings
Number of pages11
Place of PublicationAtlanta, GA
PublisherAssociation for Information Systems. AIS Electronic Library (AISeL)
Publication date2017
Publication statusPublished - 2017
Event38th International Conference on Information Systems: Transforming Society with Digital Innovation, ICIS 2017: Transforming Society with Digital Innovation - Coex Convention Center , Seoul, Korea, Republic of
Duration: 10 Dec 201713 Dec 2017
Conference number: 38


Conference38th International Conference on Information Systems: Transforming Society with Digital Innovation, ICIS 2017
LocationCoex Convention Center
Country/TerritoryKorea, Republic of
Internet address
SeriesProceedings of the International Conference on Information Systems


  • People analytics
  • Big data
  • IS research agenda
  • Workforce management

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