This volume is a step-by-step guide to implementing predictive data analytics in human resource management (HRM). It demonstrates how to apply and predict various HR outcomes which have an organisational impact, to aid in strategising and better decision-making.
- Presents key concepts and expands on the need and role of HR analytics in business management.
- Utilises popular analytical tools like artificial neural networks (ANNs) and K-nearest neighbour (KNN) to provide practical demonstrations through R scripts for predicting turnover and applicant screening.
- Discusses real-world corporate examples and employee data collected first-hand by the authors.
- Includes individual chapter exercises and case studies for students and teachers.
Comprehensive and accessible, this guide will be useful for students, teachers, and researchers of data analytics, Big Data, human resource management, statistics, and economics. It will also be of interest to readers interested in learning more about statistics or programming.
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|Publisher:||Taylor & Francis|
|Product dimensions:||6.12(w) x 9.19(h) x (d)|
About the Author
Shivinder Nijjer is a faculty member at Chitkara Business School, Chitkara University, Punjab, India. She has also previously worked as a software engineer with Infosys Technologies Limited. She has a PhD in predictive analytics and has contributed extensively to publications in the field of management information systems and business analytics. She has published various research articles in eminent ABDC-ranked and Scopus Indexed Journals. She is also a reviewer for Scopus indexed journals. She has also been actively involved in designing and delivery of analytics courses for students.
Sahil Raj is a faculty member at School of Management Studies, Punjabi University, Patiala, India. He has a PhD in information systems and has previously worked with Ranbaxy Laboratories. His recent publications include Management Information Systems (2017) and Business Analytics (2015). He has also published numerous research papers, and is a reviewer and on the editorial board of many national and international journals. He has been invited as an expert speaker and trainer in analytics by various national institutions.
Table of Contents
List of illustrations ix
Foreword DP Goyal xi
Foreword Vipul Gupta xii
Foreword Kulwant Kumar xiii
List of abbreviations xix
1 Analytics in HRM 1
2 Looking for data 33
3 Modelling the business problem 67
4 Predictive analytics tools and techniques 86
5 Evaluation of analytical outcomes 109
6 Predictive HR analytics in recruitment and selection 123
7 Predictive HR analytics in turnover and separation 151
8 Predictive HR analytics in other areas of HRM 176
9 Emerging trends in predictive HR analytics 197
Subject index 213
Company index 216