Optimize Your Greatest Asset -- Your People E-Book

Gene Pease

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Veröffentlichungsjahr: 2015

Beschreibung

Drive better business strategy with practical analytics for people data

Optimize Your Greatest Asset — Your People brings advanced analytics into Human Resources, giving you a framework for optimizing human capital investments through predictive analysis. You'll learn how to transition from anecdotes and surveys to more advanced measurement techniques, and combine the data from multiple systems into a unified plan of action that improves business results. Practical examples and case studies show how these techniques are applied in real-world settings, and executives and thought leaders weigh in on how advanced analytics are informing better business decisions every day. Coverage includes the latest research on the state of current HR measurement techniques, as well as the important considerations surrounding data security and employee trust.

Executives and managers alike are swimming in pools of people data, spread across multiple systems that don't talk to each other. This book shows you how to bring that data together, organize it, and turn it into useful information, and how to build your data strategy to take advantage of the wealth of available tools.

• Produce actionable intelligence with data from multiple systems
• Move beyond activity metrics and into advanced measurements
• Create stronger policy covering security, privacy, and ethics
• Achieve sophisticated HR analytics without breaking employee trust

It's time for HR leaders to get over their fear of Big Data. Good data drives good business, and human capital is the biggest asset a company has. Start measuring the things that matter, and start turning those measurements into actual information that goes beyond the spreadsheet. Optimize Your Greatest Asset — Your People shows you how to get started, and where to go from there.

Leseprobe

Table of Contents

Title Page

Copyright

Dedication

Foreword

Preface

Acknowledgments

Chapter 1: The Need for Measurement in a Changing Environment

Analytics Give Companies a Competitive Edge

Everybody's Doing It

Transcending Borders

Slim Down, Do More

Everybody Wins

Changing Workforce

Who's Working Today?

How Are Employers Responding to Generation Z?

The Boomers Are Still Here

What about Generation X?

So Now What?

Notes

Chapter 2: What Exactly Is Predictive Analytics, and Why Is It Useful?

Workforce Planning

Workforce Optimization

What Can Analytics Do for You?

Using Macroeconomic Data at Wells Fargo

Reducing Turnover with Unstructured Data

Notes

Chapter 3: The State of Human Capital Analytics

Profiling the Early Adopters

Barriers and Key Enablers to Success

Notes

Chapter 4: From Data to Action

The Continuum of Analytics

Taking Action

Designing the Study

Conducting the Study

Other Differentiators

Notes

Chapter 5: The Big Data Conundrum

Death by Dashboard

What to Do

Descriptive Analysis

How Much Data Is Big?

Ethics and Other Considerations

The Career Perspective

The New Art of HR

Big Data: Passing Trend or Here to Stay?

Notes

Chapter 6: The Future of Talent Investments

Tools and Technology

Talent Acquisition and Management

Learning Customization

The Future Workforce

Notes

Appendix A: 2014 Human Capital Analytics Study (Making Human Capital Analytics Work): October 2014

Quick Facts

Purpose and Overview of the Study

The Organization, Structure, and Operation of Human Capital Analytics Practice

Project Selection Types and Use of Analytics

Maturity, Progress, and Success

Summary

Appendix B: Driving Talent Development with Data

Introduction

Understanding Human Capital Analytics

The Human Capital Analytics Continuum

How to Start a Measurement Strategy

When Human Capital Analytics Pay Off

Conclusion

Sources

Appendix C: Training Case Studies

ACS: Analysis of a Call Center Agent Turnover

Chrysler LLC: Sales Consultant Training

Chrysler Academy: Sales Manager Training

US Bank: Retail Branch Manager Training

Sun Microsystems: New Director Training

Appendix D: Leadership Development Case Studies

National Grid: Foundations of Leadership

ConAgra Foods: Foundations of Leadership

Appendix E: Mentoring Case Study

Sun Microsystems: University Mentoring Program

Appendix F: Social Learning Case Study

Sun Learning Services: SUN Learning eXchange (SLX)

Appendix G: Performance Management Case Study

VF Corporation: Measuring the Impact of Performance Management—Maximizing Performance

Appendix H: Words of Wisdom from Human Capital Analytics Practitioners

About the Author

Index

End User License Agreement

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Guide

Cover

Table of Contents

Foreword

Preface

Begin Reading

List of Illustrations

Chapter 3: The State of Human Capital Analytics

Figure 3.1 Survey Demographics

Figure 3.2 Human Capital Analytics Budget

Figure 3.3 Measurement Versus Cost/Benefit Gain

Chapter 4: From Data to Action

Figure 4.1 Human Capital Analytics Continuum

Figure 4.2 Correlation of Drowning and Ice Cream Consumption

Figure 4.3 Sample Measurement Map

Appendix A: 2014 Human Capital Analytics Study (Making Human Capital Analytics Work)

Figure A.1 Purpose of the HCA Function

Figure A.2 Expertise of Existing/Planned Team Members

Figure A.3 Tools or Platforms Currently Using/Planning to Use

Figure A.4 Projects Currently Identified or Planned for the Near Future

Figure A.5 Functional Areas Currently Addressed or Planned to Address in the Near Future

Figure A.6 Predictive Relationships Explored or Planned to Explore

Figure A.7 How Findings from HCA Projects are Being Used

Figure A.8 Follow-Up on HCA Action Items

Figure A.9 Who Uses the Results from HCA Projects

Figure A.10 Methods Used to Communicate Results

Figure A.11 The Maturity of Your HCA Practice

Figure A.12 Enablers to Success

Figure A.13 Barriers to Success

Figure A.14 Factors that Make Your HCA Practice Most Successful

Figure A.15 Benefits of HCA Projects

Appendix C: Training Case Studies

Figure C.1 Retention Model with Five Key Learning Interventions

Figure C.2 Breakdown of Tenure for Agents

Figure C.3 Breakdown of Tenure for Supervisors

Appendix D: Leadership Development Case Studies

Figure D.1 Plant Size and Training Penetration

Appendix F: Social Learning Case Study

Figure F.1 Interest in SLX Content

Figure F.2 Total SLX Hours Viewed

Appendix G: Performance Management Case Study

Figure G.1 Three Phases of Maximizing Performance

Figure G.2 Engagement with Manager

Optimize Your Greatest Asset—Your People

How to Apply Analytics to Big Data to Improve Your Human Capital Investments

Gene Pease

Copyright © 2015 by Gene Pease. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data:

Pease, Gene, 1950-

Optimize your greatest asset— your people : how to apply analytics to big data to improve your human capital investments / Gene Pease.

pages cm

Includes bibliographical references and index.

ISBN 978-1-119-00438-7 (cloth)—ISBN 978-1-119-03997-6 (ePDF)— ISBN 978-1-119-03982-2 (ePub)

1. Manpower planning. 2. Human capital— Management. 3. Personnel management. 4. Big data. I. Title.

HF5549.5.M3P433 2015

658.3′01— dc23

2015016150

Cover Design: Wendy Lai

Cover Image: Business Silhouettes © iStock.com/Robert Churchill

My father, Gene A. Pease Sr., was the most influential person in my life, both professionally and personally. He was a World War II veteran, and upon returning from the war started a company in his partner's mother's garage while pursuing a college degree at night. He successfully ran his company for over 30 years while juggling being a terrific husband and helping to raise four children. He taught me the virtue of hard work and the value of ethics, and he showed me how entrepreneurs persevere in spite of the odds. Although he passed away too young, I use the lessons I learned from him every day. I love and miss you, Dad.

When you are an entrepreneur, you will experience many, and I mean many, ups and downs in attempting to take a dream and turn it into a reality. You will also understand how important support from your family assists you getting through those many down days. The commitment to be an entrepreneur is stressful for all involved. My partner, Pamela Pease, has supported my career for many years. She is my lifelong confidant, psychiatrist, and mentor. My two daughters, Tiffany and Heather, have wisdom beyond their years and consistently give me advice and perspective that surprises me. Thank you for your love and support. You make me strive to be the man our dog Bailey thinks I am.

I have been very fortunate to have grown up in a close-knit family that practices unconditional love. My mother, Deanne, the matriarch of the family, has taught us too many lessons for one book. My sister, Dr. Susan Instone, provides her younger siblings wisdom. My brothers, Jeff and Scott, are a joy to be around, especially where there's beer and a band. Thank you for your continued support and encouragement.

—Gene A. Pease Jr.

Foreword

I am always excited for the start of a new year—it is a time of reflection for the year just past and an opportunity to look forward to the year ahead. I am an optimistic person by nature, so this reflective process is always filled with promise, hoping to learn from my experiences over the previous 12 months. I felt especially optimistic approaching 2015; my personal life is great (wife, Molly; daughters, Regan and Maggie; and son, Aidan, are all healthy, happy, and doing well) and the horizon for my profession has perhaps never been brighter. After almost 20 years in the workforce analytics and planning industry, the marketplace was FINALLY accelerating; the discussions have moved from whether organizations should invest in analytics to how to optimize investments.

The industry has been on quite a journey the past few decades. Many point to Dr. Jac Fitz-enz starting the industry with human capital benchmarking programs and the launch of the Saratoga Institute. This work was enhanced through innovative consulting, benchmarking, and technology firms across the globe. The contributors were many, including InfoHRM (Peter Howes and Anastasia Ellerby from Australia) and the larger professional services firms (Mercer, Deloitte, AonHewitt, etc.) all the way to combinations of the two (PwC/Saratoga). I believe the growth of the industry started an initial period of acceleration, and acceptance, as the software firms started to get into the game. Large, global enterprise resource planning (ERP) software firms such as PeopleSoft, SAP, and Oracle included benchmarking, metrics, and dashboarding capabilities into their software platforms. These innovations, and the capable software sales teams, made HR dashboards a must-have tool for every human resources department.

The growth capabilities in the large ERP software platforms also contributed to the growth of the performance/talent management software vendor community and the rise of cloud computing. These new cloud-based firms such as SuccessFactors, Taleo, Kenexa, and Cornerstone OnDemand brought new capabilities to the marketplace. The industry started to move from HR Metrics and benchmarks to more advanced analytics and concepts around workforce planning. The ability to aggregate data in the cloud across organizations brought a whole new dimension to the analysis that could be conducted, produced, and delivered to C-suite executives. These were exciting times as the promise of finally linking human capital to business results appeared to be achievable. And it was! The industry saw leading companies such as Capital One, The Home Depot, Starbucks, Target, Ameriprise Financial, Avaya, and others influencing capital decisions within their respective organizations. It was not unusual to see many companies presenting findings, results, and program strategies at conferences across the globe and many companies establishing dedicated workforce analytics and planning centers-of-expertise (COEs).

The growth of COEs represents a significant achievement for our industry. Organizations were recognizing the importance of human capital analytics and workforce planning and were willing to invest capital (human and financial) in this capability. Many of the COEs reported directly to chief human resources officers (CHROs) and had direct access to the C-suite at large. HR was starting to become more quantitative in its capabilities, with statisticians, industrial-organizational psychologists, and business operations executives migrating into COEs and HR executive suites. COEs were starting to drive the innovation expected from the technology vendor community, pushing the boundaries of existing vendor capabilities. And then the HR technology community had another merger-and-acquisitions wave as the talent management vendors were swallowed up by the ERP vendors (SAP/SuccessFactors, Oracle/Taleo, IBM/Kenexa) and pure-play cloud ERP firms emerged with vendors like Workday. This consolidation of the HR technology industry did not drive the innovation in the analytics industry—the growth of COEs was the largest contributing factor to the growth we are seeing in the industry today.

This brings us to today, and I am so excited and optimistic for our industry. The growth and innovation of our industry is now driven by practitioners—the same practitioners that have launched and run COEs for the better part of a decade. These practitioners have taken the next step in the evolution of workforce analytics and planning and have moved to predictive analytics capabilities. COEs are harnessing the power of big data, leveraging machine learning functionality and providing insights to business leaders that were never before possible. In many ways, COEs serve as the R&D function for today's HR technology community and for their own organizations!

I was excited to be approached by Gene Pease regarding participating in the writing of his latest book. Gene and I are working together at Vestrics, provider of the industry's leading predictive analytics platform. Vestrics joins the companies I mentioned above in industry innovation and specifically in placing predictive analytics technology in the hands of talent professionals. Vestrics has been a thought leader in this work, and I was excited that, with his third book, Gene was going to formally document, and share, the innovation taking place in today's predictive analytics marketplace.

This book is not theory; the examples cited are real-world experiences and examples of some of the globe's leading companies tackling their thorniest business issues. The examples should serve as a template for organizations looking to analytics, a call to action for organizations struggling with their own efforts, and a confirmation of success for those already leading the charge.

I remain optimistic on the future of our industry—and hope you are as excited as I am for the next chapters of learning and growth that remain ahead.

Brian KellyPresident, Vestrics

Preface

In 2005, I went to the Masie Conference in Florida. It was the first industry conference I had attended since we started Capital Analytics (now Vestrics) the year before. The conference was very interesting with presentations on a wide variety of topics related to learning. However, there were very few presentations at the conference related to measuring and evaluating learning. Those that discussed measurement focused on how to create and deploy better surveys. Among over 100+ scheduled presentations, there was one breakout session on the topic of the return on investment (ROI) of training investments. Approximately 50 people showed up for the discussion, so we put our chairs in a large oval in a banquet room. I was very excited to participate in what I considered the most important topic of the conference. A professor from one of the East Coast business schools kicked off the discussion. The attendees represented middle to senior management learning executives from some of the world's largest and best-known corporations, as well as representatives from many prestigious universities. I was eager to hear from the industry as my team had just started to apply advanced analytics to measure training programs.

For the first 30 minutes or so, one executive after another stated that you can't measure learning investments because people are too complicated and organizations are too complex. Generally, the group believed that measuring ROI was a waste of time and had no value. We had formed Capital Analytics knowing that statistics were being used in many disciplines—drug trials, actuarial work, supply chain optimization, and many others. Even marketing (which had long been thought of as an art form) was beginning to apply statistics to better understand the effectiveness of their investments. What's the old saying? I knew that 50 percent of my marketing budget was wasted; I just didn't know which 50 percent.

The discussion was hard for me to believe. And it went on and on. I couldn't stand it any longer and meekly raised my hand. When called upon, I stated that I strongly disagreed with their opinions. Our scientists (from Duke University, by the way!) were applying statistical work to learning investments. This work was enabling us to see insights into the investments that qualitative methods could not uncover.

You would have thought I was from Mars with the violent reaction to my comments. The next half-hour turned into a free-for-all of 50 against 1 (me). The argument both discouraged and energized me. I was discouraged to learn that the learning profession was so far behind in thinking about how to link investments to business outcomes. It discouraged me enough that I didn't attend another industry conference for the next three years.

However, in spite of this beat down, I knew this work could be done, and it energized me to show the industry that it could be done. So we quietly stuck to the work over the next 10 years and, along with others, helped shepherd advanced analytics into the human capital profession. Look at where we are a decade later. There is significant proof that applying analytics and understanding how investments are working significantly improves business outcomes. We now use predictive analytics to help navigate rapidly changing work environments. Big data allows us to capture both structured and unstructured data and turn it into information that enables us to make better-informed decisions.

I have co-authored two books on how to design and deploy advanced analytics for human capital investments. I was fortunate to have co-authored those books with a very talented group of experts in the field of measurement. The books were based primarily on the work and numerous mistakes we made, as we built on decades of previous work in the industry and added predictive analytics into the mix. These books focused on HOW to get started and do the work. This new book focuses more on WHY we should be doing the work every day.

As significant research shows, Human Resources (HR) is playing catch-up with adopting analytics. Some of us estimate the HR profession is about where marketing was a decade ago regarding the use of analytics. According to Bersin by Deloitte, only 14 percent of human resource departments have an analytics function. This compares to 77 percent of operations departments having an analytics function, 58 percent in sales, and 56 percent in marketing. With all the evidence we have on the value of analytics, HR has to do better.

There is some extraordinary work going on in organizations where HR analytics is being practiced. In addition to including case studies in the appendices of this book, I have invited some practitioners to give you their thoughts and lessons learned in their measurement journey. I am hopeful their stories and advice will help you overcome any obstacles you or your organization may have and inspire you to join the HR analytics movement. If you do, I promise you won't regret it.

Gene Pease

Acknowledgments

This is the third book I have authored, and Sara Jensen has collaborated with me on every one. She is a first-rate researcher and editor and all around a good person. Sara in many cases turns my gibberish into English. You are a pleasure to work with, Sara—thank you. Mia Heckendorf also has been part of our team for each book. Mia deserves a special thank you for keeping me organized and on schedule. Without these two incredible, talented women, I would not be able to run a company full time and share our research with the industry. Sincere thanks, ladies, for your assistance and putting up with my crazy ideas and unpredictable schedule.

For the past decade, I have been blessed to have the good fortune of working with a tremendous amount of talented colleagues at Vestrics (formerly Capital Analytics). Thank you for your inspiration, mentoring, and collaboration. Dr. Phil Buchanan, Barrie Trinkle, and Dr. Andy Collins have been my investment partners this entire journey and deserve a special thank you. Thank you, also, to Dr. Joan Troy-Ontjes, who has also been my business partner since the beginning.

I have known Brian Kelly for over five years, and recently he joined Vestrics as our first president. It was time for me to hand some of the day-to-day responsibilities over to someone, and I couldn't be more pleased that he shared our vision and decided to join. Thank you, Brian, for writing the Foreword.

Stacey Boyle, PhD, deserves credit for coordinating the Vestrics/ROI Institute research project and for her contributions to Chapter 3. It was also a pleasure to collaborate with Jack and Patti Phillips, specifically on that project and other initiatives our two organizations are working on. John Zonneveld, thank you for your continued collaboration and contributions to our work.

I also want to acknowledge a few pioneers who have inspired me in this journey of optimizing human capital investments: Donald Kirkpatrick, Jack Phillips, Jac Fitz-enz, Tom Davenport, Ed Lawler, John Boudreau, Mike Echols, Jeffrey Pfeffer, and Marshall Goldsmith.

I offer hearty thanks to the executives who contributed their thoughts, sprinkled throughout this book. I hope they offer some context and inspiration that with conviction, advanced analytics can be applied to human capital investments, and significant insights can be found. Thank you, in no specific order:

AD Detrick—Learning measurement consultant, Xerox

Amit Mohindra—Vice president, talent management and diversity, McKesson

Brad Pearce—Vice president, analytics manager, Wells Fargo

Buddy Benge—HR analytics leader, Monsanto

Ian O'Keefe—Formerly senior direct, head of talent analytics and reporting, Sears Holdings Corporation

Lisa Van Cappelle—Vice president, global human resources, Quintiles

Mark Berry—Formerly vice president, human resources, ConAgra Foods

Ron Lawrence—Vice president, global talent management, VF Corporation

Tracey Smith—President, Numerical Insights

Melissa Arronte—Senior vice president, HR analytics, Citizens Bank

Candis Fields-Johnson—Manager, organizational effectiveness and talent development, Saint-Gobain

David Kuhl—Executive vice president, chief human resource officer

RJ Milnor—Manager, planning and analytics, Chevron

I would also like to acknowledge and thank our strategic partnership with Bellevue University, Bellevue University's Human Capital Lab, and its PhD program: specifically, President Mary Hawkins, PhD; and Executive Vice President Michael Echols, PhD.

I want to thank our editor at John Wiley & Sons, Sheck Cho, for being such a pleasure to work with. We want to thank the Wiley editorial team, particularly Stacey Rivera, who reviewed every chapter and offered substantial feedback.

Chapter 1The Need for Measurement in a Changing Environment

Have you ever heard of a company requiring a business case for investing in marketing? Or having a sales force? For that matter, what about training? Although specific budgets require justification, you'd be hard pressed to find a business leader who doesn't believe in developing the company's human capital. We dream of a day that the same will be said of measuring investments in human capital. From our perspective, as well as that of a growing cohort of HR and business leaders, evaluating these investments and using that intelligence to improve them is simply common sense. This day is coming, but for now such measurement is still seen as a competitive advantage—or worse, something nice to have but just not worth the trouble.

As this is my third book, written after practicing human capital analytics for over 10 years, I've written extensively on the justifications for measurement. For those of you who haven't yet seen the light, I present the arguments here again.

Analytics Give Companies a Competitive Edge

Recent studies by Deloitte and Bain have proven that the more advanced an organization's analytics capabilities, the greater the margins by which they outperformed their competitors. We'll go into more detail on these studies in Chapter 2, but for now suffice it to say that HR analytics can directly impact a company's bottom line. The Bain study in particular looks more broadly at the impact of analytics applied to nearly every aspect of business performance, which brings us to the next point.

Everybody's Doing It

The old adage from your mother about everybody else jumping off a bridge simply doesn't apply here. The other departments in your organization leverage their data and advances in analytics to make more intelligent, strategic decisions. Every time you scan your customer loyalty card at the supermarket, you're exchanging valuable information about your shopping habits in exchange for that buy-one-get-one deal on Cheez-Its. Marketers analyze patterns in the immense amount of data they collect to figure out how to get you to spend a little more on your next trip. This is predictive analytics.

Think about supply chain management. An automotive manufacturer bleeds cash for every minute its assembly line has to shut down because it has run out of a car part. Using analytics, it manages inventory to assure this doesn't happen, while simultaneously avoiding an overstock on a costly component. This, too, is predictive analytics.