Start Date
10-12-2017 12:00 AM
Description
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.
Recommended Citation
Gal, Uri; Jensen, Tina Blegind; and Stein, Mari-Klara, "People Analytics in the Age of Big Data: An Agenda for IS Research" (2017). ICIS 2017 Proceedings. 1.
https://aisel.aisnet.org/icis2017/TransformingSociety/Presentations/1
People Analytics in the Age of Big Data: An Agenda for IS Research
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.