Human capital analytics, also known as human resources analytics or talent analytics, is the application of sophisticated data mining and business analytics techniques to human resources data. Human Capital Analytics provides an in-depth look at the science of human capital analytics, giving practical examples from case studies of companies applying analytics to their people decisions and providing a framework for using predictive analytics to optimize human capital investments.

Written by Gene Pease, Boyce Byerly, and Jac Fitz-enz, widely regarded as the father of human capital
Offers practical examples from case studies of companies applying analytics to their people decisions
An in-depth discussion of tools needed to do the work, particularly focusing on multivariate analysis

The challenge of human resources analytics is to identify what data should be captured and how to use the data to model and predict capabilities so the organization gets an optimal return on investment on its human capital. The goal of human capital analytics is to provide an organization with insights for effectively managing employees so that business goals can be reached quickly and efficiently. Written by human capital analytics specialists Gene Pease, Boyce Byerly, and Jac Fitz-enz, Human Capital Analytics provides essential action steps for implementation of advanced analytics on human capital.

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Yes, you can access Human Capital Analytics by Gene Pease, Boyce Byerly, Jac Fitz-enz in PDF and/or ePUB format, as well as other popular books in Business & Decision Making. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Wiley

Year

2012

ISBN

9781118506998

Edition

Topic

Business

Subtopic

Decision Making

Index

Business

Cover
Contents
Title
Copyright
Dedication
Preface
Acknowledgments
Introduction
Chapter 1: Human Capital Analytics
Chapter 2: Alignment
Chapter 3: The Measurement Plan
Chapter 4: It’s all about the Data
Chapter 5: What Dashboards are Telling You: Descriptive Statistics and Correlations
Chapter 6: Causation: What Really Drives Performance
Chapter 7: Beyond ROI to Optimization
Chapter 8: Share the Story
Chapter 9: Conclusion
Appendix A: Different Levels to Describe Measurement
Appendix B: Getting Your Feet Wet in Data: Preparing and Cleaning the Data Set
Appendix C: Details of Basic Descriptive Statistics
Appendix D: Regression Modeling
Appendix E: Generating Soft Data from Employees
Glossary
About the Authors
Index