ABSTRACT. I draw on a substantial body of theoretical and empirical research on workforce analytics and human resource metrics, and to explore this, I inspected, used, and replicated survey data from Bright & Company, Corporate Research Forum, Deloitte, McKinsey, and Top Employers Institute, performing analyses and making estimates regarding how organizations use workforce analytics to improve both business and people outcomes (%). Structural equation modeling was used to analyze the data and test the proposed conceptual model.
JEL codes: E24; J21; J54; J64

Keywords: workforce analytics; human resource metrics; tracking; surveillance

How to cite: Kassick, Diana (2019). “Workforce Analytics and Human Resource Metrics: Algorithmically Managed Workers, Tracking and Surveillance Technologies, and Wearable Biological Measuring Devices,” Psychosociological Issues in Human Resource Management 7(2): 55–60. doi:10.22381/PIHRM7220199

Received 15 July 2019 • Received in revised form 19 September 2019
Accepted 20 September 2019 • Available online 11 October 2019

Diana Kassick
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The Cognitive Labor Institute,
New York City, NY, USA

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