Predictive HR Analytics: Mastering the HR Metric - Hardcover

Edwards, Dr Martin; Edwards, Kirsten

Hardcover

ISBN 10: 0749498021 ISBN 13: 9780749498023

Verlag: Kogan Page, 2019

Inhaltsangabe

HR metrics and organizational people-related data are an invaluable source of information from which to identify trends and patterns in order to make effective business decisions. But HR practitioners often lack the statistical and analytical know-how to fully harness the potential of this data.

Predictive HR Analytics provides a clear, accessible framework for understanding and working with people analytics and advanced statistical techniques. Using the statistical package SPSS (with R syntax included), it takes readers step by step through worked examples, showing them how to carry out and interpret analyses of HR data in areas such as employee engagement, performance and turnover. Readers are shown how to use the results to enable them to develop effective evidence-based HR strategies.

This second edition has been updated to include the latest material on machine learning, biased algorithms, data protection and GDPR considerations, a new example using survival analyses, and up-to-the-minute screenshots and examples with SPSS version 25. It is supported by a new appendix showing main R coding, and online resources consisting of SPSS and Excel data sets and R syntax with worked case study examples.

Über diesen Titel

Über die Autorinnen und Autoren

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 HR Lead for Advanced Analytics and Data Science at Rio Tinto and has over 20 years' broad international experience in analytics, HR and management consulting. She is a visiting lecturer at Kent Business School and at King's Business School.

Details zur Ausgabe

• Verlag: Kogan Page
• Erscheinungsdatum: 2019
• ISBN 10: 0749498021
• ISBN 13: 9780749498023
• Einband: Tapa dura
• Sprache: Englisch
• Auflage: 2
• Anzahl der Seiten: 504
• Kontakt zum Hersteller: Nicht verfügbar