Predictive Analytics in Human Resource Management

A Hands-on Approach

Written By

Ap Eigenhuis • Rob van Dijk

INTRODUCTION

As of my last knowledge update in January 2022, I don’t have specific information about a book titled “Predictive Analytics in Human Resource Management: A Hands-on Approach.” However, based on the title, I can offer a general overview of what you might expect from a book with such a focus:

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

Potential Overview:
This book is likely to explore the application of predictive analytics in the field of Human Resource Management (HRM). Predictive analytics involves using data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data.

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BOOKS

Key Topics:

Introduction to Predictive Analytics: The book might provide an introduction to the concepts and techniques of predictive analytics, explaining how it differs from traditional HRM practices.

Data Collection and Analysis: Expect discussions on the types of data relevant to HRM, methods for collecting and analyzing data, and the importance of data quality in predictive analytics.

Predictive Modeling: The book may delve into building predictive models for HR-related outcomes such as employee turnover, performance, and engagement.

Case Studies and Examples: Real-world case studies and examples could be included to illustrate how predictive analytics has been successfully applied in HRM scenarios.

Practical Applications: A hands-on approach implies practical guidance. The book might offer step-by-step instructions, tools, and techniques for HR professionals to implement predictive analytics in their organizations.

Target Audience:
The intended audience for this book is likely HR professionals, managers, data analysts, and anyone involved in making strategic decisions related to human capital within an organization.

Authorship:
Check the authors or editors of the book, as their expertise and background can provide insights into the credibility and focus of the content.

Technological Tools: Given the hands-on approach, the book might introduce readers to specific tools or software commonly used in predictive analytics within the HR context.

Ethical Considerations: An ethical dimension might be addressed, discussing the responsible use of data and potential ethical concerns associated with predictive analytics in HRM.

To get the most accurate and detailed information about the book, including its content, target audience, and practical applications, I recommend checking reputable bookstores, the publisher’s website, or other online platforms for the latest details on “Predictive Analytics in Human Resource Management: A Hands-on Approach.”