Predictive analytics for human resources / Jac Fitz-enz, John Mattox, II.

Includes index.

"Create and run a human resource analytics project with confidenceFor 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"-- Provided by publisher.

"Predictive Analytics for Human Resources is a comprehensive guide to developing and implementing a human resource analytics project. The book starts with the basic idea of engaging in predictive analytics and walks through case simulations showing statistical examples. In addition, it addresses the topics of internal coaching, mentoring, and sponsoring and includes information on how to recruit a sponsor"-- Provided by publisher.

Machine generated contents note: Foreword Preface Chapter 1: Where's The Value? Some Basics What Is Analytics? Two Values Analytic Capabilities Analytic Value Chain The Analytic Model A Typical Application Training Value Measurement Model Inside The Data Notes Chapter 2: Getting Started Go-to-Market Models Assessment Developmental Experiences Financial Connections A Sample Case Focusing on the Purpose Present Day Needs How Human Capital Analytics Is Being Used Turning Data into Information Three Value Paths Solving a Problem An Essential Step The Prime Question A Case in Point Preparing For an Analytics Unit Ten Steps for an Analytics Unit Structure and Team Building Developing an Analytics Culture Notes Chapter 3: What You Will Need Dealing with the C-Level Breaking Through Research Recruiting a Sponsor or Champion Making the Sale A Selling Example Working with Consultants and Coaches Designing and Delivering Reports Making an Impact Process Management Preparation Notes Chapter 4: Data Issues Efficiency Measures Effectiveness Measures Business Outcome Measures Note Chapter 5: Predictive Statistics Examples Begin with the End in Mind Go Back to the Beginning Who Owns It and Will They Share It? What Will You Do with It? What Form Is It In? Is There Sufficient Quality? Note Chapter 6: Predictive Analytics in Action First Step: Determine the Key Performance Indicators Second Step: Analyze and Report the Data Relationships, Optimization, and Predictive Analytics Predictive Analytics Interpreting the Results Predicting the Future Structural Equation Modeling Notes Chapter 7: Predicting the Future of Human Capital Analytics What Does the Future Look Like? Bringing It All Together What Does the Future Look Like? Notes Epilogue Appendix: Example Measures of Efficiency Effectiveness and Outcomes About the Authors Index.

Print version record and CIP data provided by publisher.

Includes bibliographical references and index.

Title; Copyright; Dedication; Foreword; Preface; Chapter 1: Where's the Value?; Some Basics; What Is Analytics?; Two Values; Analytic Capabilities; Analytic Value Chain; Analytic Model; Typical Application; Training Value Measurement Model; Inside the Data; Notes; Chapter 2: Getting Started; Go-to-Market Models; Assessment; Developmental Experiences; Financial Connections; Sample Case; Focusing on the Purpose; Present-Day Needs; How Human Capital Analytics Is Being Used; Turning Data into Information; Three Value Paths; Solving a Problem; Essential Step; Prime Question

Case in PointPreparing for an Analytics Unit; Ten Steps for an Analytics Unit; Structure and Team Building; Developing an Analytics Culture; Notes; Chapter 3: What You Will Need; Dealing with the C Level; Breaking Through; Research; Recruiting a Sponsor or Champion; Making the Sale; Selling Example; Working with Consultants and Coaches; Designing and Delivering Reports; Making an Impact; Process Management; Preparation; Notes; Chapter 4: Data Issues; Efficiency Measures; Effectiveness Measures; Business Outcome Measures; Note; Chapter 5: Predictive Statistics Examples

Begin with the End in MindGo Back to the Beginning; Who Owns Data, and Will They Share It?; What Will You Do with the Data?; What Form Is the Data In?; Is the Data Quality Sufficient?; Note; Chapter 6: Predictive Analytics in Action; First Step: Determine the Key Performance Indicators; Second Step: Analyze and Report the Data; Relationships, Optimization, and Predictive Analytics; Predictive Analytics; Interpreting the Results; Predicting the Future; Structural Equation Modeling; Notes; Chapter 7: Predicting the Future of Human Capital Analytics; What Does the Future Look Like?

Bringing It All TogetherPredictive Analytics for HR in Action; Notes; Epilogue; Appendix: Example Measures of Efficiency, Effectiveness, and Outcomes; About the Authors; Index; End User License Agreement