Predictive Hr Analytics : Mastering the Hr Metric

Edwards, Martin; Edwards, Kirsten; Jang, Daisung

ISBN 10: 139861565X / ISBN 13: 9781398615656

Published by Kogan Page, 2024

About this Item

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Bibliographic Details

• Title: Predictive Hr Analytics : Mastering the Hr Metric
• Publisher: Kogan Page
• Publication Date: 2024
• Language: English
• ISBN 10: 139861565X
• ISBN 13: 9781398615656
• Binding: Soft cover
• Edition: 3rd Edition
• Condition: good

About this title

Synopsis

This is the essential guide for HR practitioners who want to gain the statistical and analytical knowledge to fully harness the potential of HR metrics and organizational people-related data.

The ability to use and analyse data has become an invaluable skill for HR professionals to not only identify trends and patterns, but also make well-informed business decisions. The third edition of Predictive HR Analytics provides a clear, accessible framework for understanding people data, working with people analytics and advanced statistical techniques.

Readers will be taken step-by-step through worked examples, showing them how to carry out analyses and interpret HR data in areas such as employee engagement, performance and turnover. Learn how to make effective business decision with this updated edition that includes the latest materials on biased algorithms and data protection, supported by online resources consisting of R and Excel data sets.

About the Authors

Martin R Edwards is Reader in HRM and Organizational Psychology at King's Business School, King's College London. He has taught statistics to undergraduate, postgraduate and PhD students for over 15 years and also teaches HR analytics to MSc students. As a consultant, he has delivered HR analytics workshops to FTSE-100 companies.

Kirsten Edwards is Global Head of People Data and Insights at Rio Tinto. She has over 20 years' broad international experience in analytics, HR and management consulting. She is based in Queensland.

Daisung Jang is an Assistant Professor at Melbourne Business School. He has over a decade of experience in data visualization and analysis using R. He has conducted workshops for PhD students and academic staff on statistical analyses using R.