Martin R. Edwards is a Professor of Management at the UQ Business School, University of Queensland, Australia. Martin has published widely in the area of Human Resource Management. He is active in the field of HR consultancy, having delivered projects to numerous multinationals; he has also provided bespoke HR Analytics training to global firms.

Dana Minbaeva is a Professor of Strategic Human Capital at King's Business School, King's College London, UK. She also holds a part-time position at Copenhagen Business School, Denmark, and is an affiliate faculty member at London Business School, UK. Professor Minbaeva is a Fellow of the Academy of International Business. She has received several national and international awards for her research achievements, including the prestigious JIBS Decade Award in 2013. Dana is also the founder and director of the Nordic Human Capital Advisory Aps.

Alec Levenson is Senior Research Scientist and Director at the Center for Effective Organizations, Marshall School of Business, University of Southern California. His research has been published in books, academic and business publications, and global media outlets, including the New York Times, Wall Street Journal, The Economist, CNN, Associated Press, US News and World Report, National Public Radio, Los Angeles Times, USA Today, Marketplace, and Fox News.

Mark A. Huselid is the Distinguished Professor of Workforce Analytics and director of the Center for Workforce Analytics at the D'Amore-McKim School of Business, Northeastern University. He was the editor of the Human Resource Management Journal, and is a current or former member of numerous professional and academic boards. He is a fellow of the National Academy of Human Resources (NAHR), the Society for Industrial and Organizational Psychology (SIOP), and the Association for Psychological Science (APS).

PART 1: WORK FORCE ANALYTICS (WFA)

1 Introduction and book overview

2 Theoretical frameworks for workforce analytics

3 Data collection and analysis

PART 2: ANALYTIC TECHNIQUES

4.0 Considering techniques in workforce analytics

4.1 Causal inference in HR analytics with Directed Acyclic Graphs

4.2 Latent Class and Latent Profile Analysis

4.3 Efficient ways to leverage untapped data sources: Using natural language processing to assess work attitudes and perceptions

4.4 Decision trees and HR analytics: An example

4.5 Organizational network analysis (ONA) at the Broad Institute

4.6 Machine learning tools to support strategic HR decision-making

4.7 Connecting employee survey data to organizational performance indicators using micro-macro multilevel regression

4.8 Key takeaways

PART 3: WFA APPLICATIONS AND FUTURE

5 Implementation and change management

6 Ethics and workforce analytics

7 Building the workforce analytics function

8 The future of workforce analytics