Gene Pease, Boyce Byerly, Jac Fitz-Enz

Human Capital Analytics (eBook, ePUB)

How to Harness the Potential of Your Organization's Greatest Asset

• Format: ePub

Produktbeschreibung

An insightful look at the implementation of advanced analytics on human capital 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.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 256
• Erscheinungstermin: 10. Oktober 2012
• Englisch
• ISBN-13: 9781118506998
• Artikelnr.: 37345596

Autorenporträt

GENE PEASE is cofounder and CEO of Capital Analytics, a consultancy revolutionizing the way companies evaluate their investments in people. He has over 25 years' experience as a CEO managing mid-cap and early stage companies. Under his leadership, Capital Analytics has been recognized by Bersin and Associates, CLO Magazine, Gartner, and the ROI Institute. BOYCE BYERLY, PHD, is cofounder and chief scientist of Capital Analytics. He has more than fifteen years of experience designing and managing pure and applied research projects with high technology firms in the Research Triangle Area of North Carolina. He directed the Capital Analytics team that developed the methodology and the analytical tools that are the core intellectual assets of Capital Analytics. JAC FITZ-ENZ, PHD, is widely regarded as the father of human capital strategic analysis and measurement. He founded the famous Saratoga Institute and published the first HR metrics in 1978 and the first international HR benchmarks in 1985. HR World cited him as one of the top five "HR Management Gurus," IHRIM gave him its Chairman's Award for innovation, and SHRM chose him as one of the persons in the twentieth century who "significantly changed what HR does and how it does it." He has authored twelve books and trained 90,000 managers in forty-six countries on strategic management and measurement. His book, The New HR Analytics, introduced predictive analytics to HR.

Inhaltsangabe

Preface xi
Acknowledgments xiii
Introduction Realizing the Dream: From Nuisance to Necessity 1
Chapter 1 Human Capital Analytics 13
Human Capital Analytics Continuum 16
Summary 28
Notes 28
Chapter 2 Alignment 31
The Stakeholder Workshop: Creating the Right Climate for Alignment 33
Aligning Stakeholders 33
Who Are Your Stakeholders? 35
What Should You Accomplish in a Stakeholder Meeting? 37
Deciding What to Measure with Your Stakeholders 41
Leading Indicators 42
Business Impact 44
Assigning Financial Values to "Intangibles" 44
Defining Your Participants 45
Summary 59
Notes 60
Chapter 3 The Measurement Plan 61
Defining the Intervention(s) 62
Measurement Map 63
Hypotheses or Business Questions 66
Defining the Metrics 67
Demographics 68
Data Sources and Requirements 70
Summary 77
Note 77
Chapter 4 It's All about the Data 79
Types of Data 80
Tying Your Data Sets Together 86
Difficulties in Obtaining Data 89
Ethics of Measurement and Evaluation 90
Telling the Truth 92
Summary 97
Notes 98
Chapter 5 What Dashboards Are Telling You: Descriptive Statistics and
Correlations 101
Descriptive Statistics 102
Going Graphic with the Data 103
Data over Time 104
Descriptive Statistics on Steroids 106
Correlation Does Not Imply Causation 108
Summary 115
Notes 116
Chapter 6 Causation: What Really Drives Performance 117
Can You Create Separate Test and Control Groups? 120
Are There Observable Differences? 121
Did You Consider Prior Performance? 121
Did You Consider Time-Related Changes? 122
Did You Look at the Descriptive Statistics? 123
Have You Considered the Relationship between the Metrics? 123
A Gentle Introduction to Statistics 123
Basic Ideas behind Regression 125
Model Fit and Statistical Significance 126
Summary 130
Notes 131
Chapter 7 Beyond ROI to Optimization 133
Optimization 134
Summary 143
Notes 144
Chapter 8 Share the Story 145
Presenting the Financials 147
Telling the Story and Adding Up the Numbers 148
Preparing for the Meetings 152
Summary 152
Notes 153
Chapter 9 Conclusion 155
Human Capital Analytics 156
Alignment 156
The Measurement Plan 157
It's All about the Data 159
What Dashboards Are Telling You: Descriptive Statistics and Correlations
159
Causation: What Really Drives Performance 161
Beyond ROI to Optimization 162
The Ultimate Goal 164
What Others Think about the Future of Analytics 164
Final Thoughts 169
Notes 169
Appendix A: Different Levels to Describe Measurement 171
Appendix B: Getting Your Feet Wet in Data: Preparing and Cleaning the Data
Set 181
Appendix C: Details of Basic Descriptive Statistics 193
Appendix D: Regression Modeling 199
Appendix E: Generating Soft Data from Employees 205
Glossary 209
About the Authors 225
Index 227