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Predictive Analytics for Human Resources (ePub eBook)


Predictive Analytics for Human Resources (ePub eBook)

eBook by Mattox, John/Fitz-enz, Jac

Predictive Analytics for Human Resources (ePub eBook)

£39.00

ISBN:
9781118940693
Publication Date:
09 Jul 2014
Publisher:
Wiley
Pages:
176 pages
Format:
eBook
For delivery:
Download available
Predictive Analytics for Human Resources (ePub eBook)

Description

Create and run a human resource analytics project with confidence 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 businessthe 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.

Contents

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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