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Predictive Analytics for Human Resources.

By: Fitz-enz, Jac.
Contributor(s): Mattox, John.
Material type: TextTextSeries: eBooks on Demand.Wiley and SAS Business Series: Publisher: Hoboken : Wiley, 2014Description: 1 online resource (172 p.).ISBN: 9781118940709.Subject(s): Decision making | Human capital -- Management | Personnel managementGenre/Form: Electronic books.Additional physical formats: Print version:: Predictive Analytics for Human ResourcesDDC classification: 658.3 | 658.301 LOC classification: HF5549 .F559 2014Online resources: Click here to view this ebook.
Contents:
Predictive Analytics for Human Resources; Wiley & SAS Business Series; Copyright; Contents; Foreword; Preface; Measurement and Analytics; Analytics and the New Work Model; Valuation; Book Structure: How to Do It; Chapter 1: Where's the Value?; Some Basics; What Is Analytics?; Two Values; Analytic Capabilities; Analytic Value Chain; Analytic Model; Organizing; Displaying; Relating; Modeling; Evaluating; Typical Application; Training Value Measurement Model; Inside the Data; Standards; Intangibles; Notes; Chapter 2: Getting Started; Go-to-Market Models; Assessment; Developmental Experiences
Financial ConnectionsSample 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 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; Selling Example; Working with Consultants and Coaches; Coaches
Designing and Delivering ReportsReports; Analysis; Making an Impact; Process Management; Preparation; Notes; Chapter 4: Data Issues; Efficiency Measures; Effectiveness Measures; Results and Interpretation; Business Outcome Measures; Business Outcomes; Notes; Chapter 5: Predictive Statistics Examples; Begin with the End in Mind; Go 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?; Notes; Chapter 6: Predictive Analytics in Action; First Step: Determine the Key Performance Indicators
CommunicationsFormatting the Data for Analysis; Second Step: Analyze and Report the Data; Relationships, Optimization, and Predictive Analytics; Predictive Analytics; Interpreting the Results; Correlation; Multiple Linear Regression; Interpretation/Action; Predicting the Future; Structural Equation Modeling; Notes; Chapter 7: Predicting the Future of Human Capital Analytics; What Does the Future Look Like?; Finance: Business Standards and Valuation of Organizations; Mathematics: Chaos Theory; Information Technology: Big Data; Automated Processes: Decision Support; Bringing It All Together
Predictive Analytics for HR in ActionNotes; Epilogue; Appendix: Example Measures of Efficiency, Effectiveness, and Outcomes; About the Authors; Index; End User License Agreement
Summary: 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 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
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Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
HF5549 .F559 2014 (Browse shelf) http://uttyler.eblib.com/patron/FullRecord.aspx?p=1734303 Available EBL1734303

Predictive Analytics for Human Resources; Wiley & SAS Business Series; Copyright; Contents; Foreword; Preface; Measurement and Analytics; Analytics and the New Work Model; Valuation; Book Structure: How to Do It; Chapter 1: Where's the Value?; Some Basics; What Is Analytics?; Two Values; Analytic Capabilities; Analytic Value Chain; Analytic Model; Organizing; Displaying; Relating; Modeling; Evaluating; Typical Application; Training Value Measurement Model; Inside the Data; Standards; Intangibles; Notes; Chapter 2: Getting Started; Go-to-Market Models; Assessment; Developmental Experiences

Financial ConnectionsSample 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 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; Selling Example; Working with Consultants and Coaches; Coaches

Designing and Delivering ReportsReports; Analysis; Making an Impact; Process Management; Preparation; Notes; Chapter 4: Data Issues; Efficiency Measures; Effectiveness Measures; Results and Interpretation; Business Outcome Measures; Business Outcomes; Notes; Chapter 5: Predictive Statistics Examples; Begin with the End in Mind; Go 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?; Notes; Chapter 6: Predictive Analytics in Action; First Step: Determine the Key Performance Indicators

CommunicationsFormatting the Data for Analysis; Second Step: Analyze and Report the Data; Relationships, Optimization, and Predictive Analytics; Predictive Analytics; Interpreting the Results; Correlation; Multiple Linear Regression; Interpretation/Action; Predicting the Future; Structural Equation Modeling; Notes; Chapter 7: Predicting the Future of Human Capital Analytics; What Does the Future Look Like?; Finance: Business Standards and Valuation of Organizations; Mathematics: Chaos Theory; Information Technology: Big Data; Automated Processes: Decision Support; Bringing It All Together

Predictive Analytics for HR in ActionNotes; Epilogue; Appendix: Example Measures of Efficiency, Effectiveness, and Outcomes; About the Authors; Index; End User License Agreement

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 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

Description based upon print version of record.

Author notes provided by Syndetics

<p> JAC FITZ-ENZ, P H D, 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.</p> <p> JOHN R. MATTOX II, P H D, 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.</p>

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