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Developing human capital : using anaytics to plan and optimize your learning and development investments

Author
  • Pease, Gene
Additional Author(s)
-
Publisher
Hoboken, New Jersey: John Wiley & Sons, 2014
Language
English
ISBN
9781118753507
Series
Subject(s)
  • EMPLOYEES-TRAINING OF
  • HUMAN CAPITAL--MANAGEMENT
  • PERSONNEL MANAGEMENT
  • MANPOWER PLANNING
Notes
  • Appendix: p. 191-257
  • Glossary: p. 259-272
. . Index: p. 275-290
Abstract

Don't squander your most valuable resource! Collectively, your workers are your company's most important and most valuable asset. To make the most of this asset, nothing beats quantitative performance and investment measurement. Learning and Development is an 80 billion-dollar industry, and every valuable employee represents a sizable investment on the part of your company. To keep your business moving forward, effective management of human capital is crucial. It generates plenty of data, and deep analysis of this data helps you provide feedback and make adjustments to capitalize on the combin.
Physical Dimension
Number of Page(s)
xxvi, 290 p.
Dimension
24 cm.
Other Desc.
ill.
Summary / Review / Table of Content
Foreword xiii Preface xvii Acknowledgments xix Introduction xxi Chapter 1 The New Workforce 1 Defining the Generations 2 Projected Gaps as the Generations Shift 4 Chasing Down Retirement 4 Changing the Way We Work 5 Technology 6 Economy 7 Globalization 8 Demographics 9 Are Virtual Workplaces Here to Stay? 9 What Can Learning Leaders Do? 9 Summary 10 Notes 11 Chapter 2 The Need for a Strategy 13 Measurement as an Intentional Process 15 Continuum of Analytics 17 Continuum of Learning and Development Analytics 20 Summary 22 Notes 22 Case Study: A Measurement Strategy in Action: Pfizer 24 Chapter 3 Establishing a Measurement Framework 31 Measurement Frameworks 32 A Practical Measurement Framework for Learning 35 Summary 39 Notes 40 Case Study: Improving Collectors Skills: AT&T 41 Chapter 4 Planning for Success 61 Purpose and Political Will 62 Skills and Capabilities 65 Tools and Technology 66 Data 67 Taking Inventory: What It Takes 69 Developing the Plan: Measurement Blueprints 69 Summary 73 Note 73 Case Study: A Culture of Measurement: Chrysler Academy 74 Chapter 5 Curriculum Alignment 79 Goal: To Close the Skill Gaps 80 The Performance Map 80 How We Learn from High Performers 82 Quantifying the Gap 84 Aligning and Prioritizing the Curriculum 85 Beyond Curricula 86 Summary 87 Case Study: Performance Analytics for an Aligned Curriculum: VW Credit, Inc. 88 Chapter 6 Measurement Alignment 97 Alignment Wanted 98 Maps An Old Idea, a New Application 98 What Is a Measurement Map? 99 What Does a Measurement Map Look Like? 100 Building a Measurement Map 104 Defining the Data 106 Summary 107 Case Study: Showing Learning s Alignment with the Business: VW Credit, Inc. 109 Chapter 7 Improving on the Basics 115 The Basics 116 Improving Level 1 118 Improving Level 2 124 Improving the Analysis 130 Summary 137 Notes 137 Case Study: Leadership Program at a Fortune 500 Financial Company 139 Chapter 8 Hard Evidence Using Advanced Analytics 145 The Quest for Isolated Impact 146 Causation: What Really Drives Performance? 149 Isolating the Impact: Improving Levels 4 and 5 150 A Gentle Guide to the Statistics of Causation 152 Statistical Modeling and Significance 154 Isolation and the Analytics Continuum 155 Summary 156 Note 157 Case Study: Achieving Business Impact at a Major Utility Company 158 Case Study: Hard Evidence Using Advanced Analytics: Valuing Training at Defense Acquisition University 164 Chapter 9 Optimization through Predictive Analytics 169 Predictive Analytics 170 How to Optimize Investments 171 Getting the Data for Optimization 174 Predictive Analytics A Learning Game Changer 175 Pioneers of Predictive Analytics in Human Resources 176 Conclusion 177 Notes 179 Case Study: Optimizing Performance Management: VF Corporation 180 Chapter 10 In Conclusion Get Started 187 Note 189 Appendix A Talent Development Reporting Principles (TDRp): Managing Learning like a Business to Deliver Greater Impact, Effectiveness, and Efficiency 191 Appendix B What It Takes 219 Appendix C Measurement Plan: Blueprints for Measurement 225 Appendix D Using Bloom s Taxonomy 233 Appendix E Guidelines for Creating Multiple Choice Questions 237 Appendix F Getting Your Feet Wet in Data: Preparing and Cleaning the Data Set 241 Appendix G How Many Participants Do You Need in a Study? 255 Glossary 259 About the Authors 273 Index 275
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