Predictive Analytics in Human Resource Management: A Hands-on Approach

Where HR Meets Predictive Analytics

Human resource decisions often involve uncertainty: who will stay, who will leave, which applicant is likely to succeed, and where intervention will matter most. Predictive Analytics in Human Resource Management: A Hands-on Approach addresses those questions by connecting HR practice with data-driven modelling. Written by Shivinder Nijjer and Sahil Raj, the book is designed for readers who want both conceptual grounding and practical, code-supported methods.

From Business Problem to Analytical Model

The book follows a structured path through the analytics workflow. Early chapters introduce the role of analytics in HRM and the LAMP framework, then move into data collection, sampling, and the translation of organisational needs into analytical problems. Later sections cover predictive tools and techniques, including artificial neural networks (ANNs) and K-nearest neighbour (KNN), with R scripts that demonstrate how these methods can be applied to turnover prediction and applicant screening.

Applied Chapters for Real HR Challenges

Dedicated chapters focus on recruitment and selection, turnover and separation, and other areas of HRM. Corporate examples and employee data collected by the authors help bridge the gap between classroom concepts and workplace implementation. Each chapter includes exercises and case studies, making the material suitable for students, teachers, and researchers who want to work through the methods rather than simply read about them.

Who This Book Is For

This guide is aimed at readers studying or working in data analytics, Big Data, human resource management, statistics, and economics. It can also support those with an interest in statistics or programming who want to see how predictive methods are used in an organisational context. The combination of R-based demonstrations, practical HR scenarios, and academic framing makes it a useful resource for courses, self-study, and professional exploration.

Inside the Approach

• Clear explanations of HR analytics concepts and their business relevance
• Step-by-step predictive modelling techniques using R
• Applications of ANN and KNN to HR outcomes
• Real-world corporate examples and first-hand employee data
• Chapter exercises and case studies for teaching or independent practice

Why It Matters

As organisations accumulate more workforce data, the ability to ask precise questions and interpret analytical results becomes a practical HR skill. This book does not treat analytics as an abstract specialty; it shows how predictive methods can support strategising, screening, retention, and better decision-making. For readers who want a hands-on introduction to predictive HR analytics, this volume offers a focused and applied starting point.