Predictive Analytics for Human Resources

For any human resource professional that wants to harness the power of analytics, this essential resource answers the questions: "Where do I start?" and "What tools are available?" Predictive Analytics for Human Resources is designed to answer these and other vital questions. The book explains the basics of every business—the vision, the brand, and the culture, and shows how predictive analytics supports them. The authors put the focus on the fundamentals of predictability and include a framework of logical questions to help set up an analytic program or project, then follow up by offering a clear explanation of statistical applications.

Predictive Analytics for Human Resources is a how-to guide filled with practical and targeted advice. The book starts with the basic idea of engaging in predictive analytics and walks through case simulations showing statistical examples. In addition, this important resource addresses the topics of internal coaching, mentoring, and sponsoring and includes information on how to recruit a sponsor. In the book, you'll find:

• A comprehensive guide to developing and implementing a human resource analytics project
• Illustrative examples that show how to go to market, develop a leadership model, and link it to financial targets through causal modeling
• Explanations of the ten steps required in building an analytics function
• How to add value through analysis of systems such as staffing, training, and retention

For anyone who wants to launch an analytics project or program for HR, this complete guide provides the information and instruction to get started the right way.

JAC FITZ-ENZ, PHD, is founder and Chief Executive Officer of Human Capital Source, Inc. He founded the Saratoga Institute in Santa Clara, California after holding human resource positions at several major technology and financial services companies. He is widely regarded as the father of human capital strategic analysis, having published the first HR metrics in 1978 and the first international HR benchmarks in 1985.

JOHN R. MATTOX II, PHD, is Director of Research at KnowledgeAdvisors. He is a former Associate Director of Performance Management at KPMG, Manager of Learning Effectiveness at PricewaterhouseCoopers, and a Manager at Arthur Andersen.

Foreword xiii

Preface xv

Chapter 1 Where’s the Value? 1

Some Basics 1

What Is Analytics? 2

Two Values 4

Analytic Capabilities 4

Analytic Value Chain 6

Analytic Model 8

Typical Application 14

Training Value Measurement Model 15

Inside the Data 16

Notes 19

Chapter 2 Getting Started 21

Go-to-Market Models 22

Assessment 23

Developmental Experiences 23

Financial Connections 24

Sample Case 26

Focusing on the Purpose 26

Present-Day Needs 28

How Human Capital Analytics Is Being Used 29

Turning Data into Information 30

Three Value Paths 30

Solving a Problem 31

Essential Step 31

Prime Question 32

Case in Point 32

Preparing for an Analytics Unit 33

Ten Steps for an Analytics Unit 35

Structure and Team Building 36

Developing an Analytics Culture 37

Notes 37

Chapter 3 What You Will Need 39

Dealing with the C Level 40

Breaking Through 41

Research 41

Recruiting a Sponsor or Champion 42

Making the Sale 43

Selling Example 44

Working with Consultants and Coaches 46

Designing and Delivering Reports 48

Making an Impact 50

Process Management 50

Preparation 52

Notes 54

Chapter 4 Data Issues 55

Efficiency Measures 56

Effectiveness Measures 61

Business Outcome Measures 67

Note 69

Chapter 5 Predictive Statistics Examples 71

Begin with the End in Mind 71

Go Back to the Beginning 74

Who Owns Data, and Will They Share It? 75

What Will You Do with the Data? 77

What Form Is the Data In? 79

Is the Data Quality Sufficient? 80

Note 82

Chapter 6 Predictive Analytics in Action 83

First Step: Determine the Key Performance Indicators 83

Second Step: Analyze and Report the Data 89

Relationships, Optimization, and Predictive Analytics 96

Predictive Analytics 97

Interpreting the Results 102

Predicting the Future 111

Structural Equation Modeling 113

Notes 114

Chapter 7 Predicting the Future of Human Capital Analytics 115

What Does the Future Look Like? 116

Bringing It All Together 126

Predictive Analytics for HR in Action 126

Notes 128

Epilogue 129

Appendix: Example Measures of Efficiency, Effectiveness, and Outcomes 133

About the Authors 135

Index 137

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