The New HR Analytics: Predicting the Economic Value of Your Company's Human Capital Investments
368The New HR Analytics: Predicting the Economic Value of Your Company's Human Capital Investments
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Overview
Using Fitz-enz's proprietary analytic model, you will be equipped to measure and evaluate past and current returns and apply the information to make predictions about the future value of human capital investments.
In his landmark book, The ROI of Human Capital, Jac Fitz-enz presented a system of powerful metrics for quantifying the contributions of individual employees to a company's bottom line. Now, in The New HR Analytics, he reveals how human resources professionals can apply this expense-based knowledge to make the most strategic staffing decisions for their companies.
You'll learn how to:
- evaluate and prioritize the skills needed to sustain performance;
- build an agile workforce through flexible Capability Planning;
- determine how the organization can stimulate and reward behaviors that matter;
- apply a proven succession planning strategy that leverages employee engagement and drives top-line revenue growth;
- and recognize risks and formulate responses that avoid surprises.
Brimming with real-world examples and input from thirty top HR practitioners and thought leaders as well as exclusive analytical tools, The New HR Analytics ushers in a new era in human resources and human capital management.
Product Details
ISBN-13: | 9780814438848 |
---|---|
Publisher: | AMACOM |
Publication date: | 05/26/2010 |
Edition description: | Special |
Pages: | 368 |
Product dimensions: | 6.00(w) x 8.90(h) x 1.00(d) |
Age Range: | 18 Years |
About the Author
Read an Excerpt
PREFACE
This book was twenty-five years in the writing. It started in 1984, with the
publication of my How to Measure Human Resources Management; it was
augmented with Human Value Management six years later; and then the
concept was updated ten years ago in The ROI of Human Capital. Those
books chronicle the development of metrics in human resources from its
inception in the 1970s to today. They have passed the test of time with
second and third editions, and two were honored with Book of the Year
Awards from the Society for Human Resource Management.
Now, The New HR Analytics is both the product of these endeavors
and the look into the future. Although this book talks to human resources
managers, it deals with the broader issue of human capital management
processes. Hence, it is as applicable to the work of line managers as to
that of the human resources department. Anyone who manages people
can find value in the model we present here and the case studies that are
offered in support of that model.
HR as an Expense
Having come into HR in 1969 from ten years in line jobs, I could not
understand why any company would create a function that was only an
expense. But then, too, at that time line management itself was not so
sophisticated. Management models of the day were a patchwork quilt of
fads that came and went, sometimes to reappear later. Others flashed
across the sky like a meteor and burned out when they hit the atmosphere
of managerial impatience. During that period, HR was simply a place
where you put people ‘‘who couldn’t do any harm,’’ as a manager in my
company said at the time.
I quickly discovered the problem behind the perception. It had two
parts. One part was that HR people actually believed and accepted the
idea that they were an expense center and nothing more. To be sure, there
were a few who fought that perception, but they were overwhelmed by
the accounting-driven belief system of the time. The second part of the
problem was that HR didn’t know, and never talked about, the value they
were generating because they couldn’t—they had no language for it. All
their terms were qualitative, subjective, and equivocal. Anecdotes were
their only way of responding when management asked for evidence of
the value added by HR’s services.
‘‘How is employee morale?’’
‘‘It’s good!’’
‘‘How good?’’
‘‘Very good.’’
Could you run any other function with such performance indicators?
It is enough to make one despair.
The Introduction of Metrics
The solution was obvious. We in HR needed to learn to speak in quantitative,
objective terms, using numbers to express our activity and value
added. Business uses numbers to explain itself. Sales, operating expenses,
time cycles, and production volumes are principal indices that express
business activity. In the 1970s, productivity was the key issue. In the
1980s, the quality movement emphasized process quality as a competitive
advantage. Both relied on numbers to express degrees of change.
At the time, I asked the HR director of a major corporation if he
was involved in these initiatives. He answered that they were not human
resources management issues. Here were the major initiatives of the day,
and he could not see what they had to do with people. Is it any wonder
that people write about nuking the HR function?
During the 1970s, we in HR began to experiment with simple cost,
time, and quantity metrics to show that HR was at least managing
expense and generating something of value. In the beginning it was
largely a defensive maneuver. But by the 1980s, we were able to show
that we were indeed adding measureable value. In 1984, I wrote the first
book mentioned earlier. In 1985, at my consulting company, the Saratoga
Institute, we published the first national benchmarks, and this led to publi-
cation of Human Value Management, which was a marketing model
applied to the HR function. By 2000, we had advanced the methodology
to a point where we were talking about return on investment. Basically,
we shifted the paradigm from that of running the HR department to that
of managing human capital in the organization. At that point we were
still using primarily standard arithmetic functions. Later in the decade
we began to apply simple statistical tools, and this opened up the era of
human capital analytics—which brings us to today.
The Era of Analytics
We are on the threshold of the most exciting and promising phase of the
evolution of human resources and human capital management. We’ve
gone from the horse and buggy to the automobile to the airplane. Now
it’s time to mount the rocket and head for the stratosphere.
Like arithmetic, statistics are bias free and are applicable over a vast
range of opportunities. They can be used in studies of single, localized
problems or for supporting organization-wide makeovers. The secret
sauce of statistics is just like the source code of computer programs—a
buried logic that can go step-by-step or leap ahead, using macros to speed
to the solution.
Today, we shift our attention to predictability. This book is about
predictive management. We think of it as ‘‘managing today, tomorrow.’’
Predictive management, or HCM:21, is the outcome of our eighteen-
month study called the Predictive Initiative. It is the first holistic, predictive
management model and operating system for the human resources
function. We launched it in the last quarter of 2008 and it has been suc-
cessfully applied in industry and government, in the United States and
overseas.
HCM:21 is a four-phase process that starts with scanning the marketplace
and ends with an integrated measurement system. In the middle, it
addresses workforce and succession planning in a new way and shows
how to optimize and synchronize the delivery of HR services. It is
detailed in the chapters that follow.
Table of Contents
PART ONE: INTRODUCTION TO PREDICTIVE ANALYTICS 1CHAPTER ONE Disruptive Technology: The Power to Predict 3
CHAPTER TWO Toward Analytics and Prediction 8
Why Analytics Is Important 17
Measuring What Is Important, by Luis Maria Cravino
Strategic Human Capital Measures: Using Leading HCM to Implement Strategy, by Stephen Gates and Pascal Langevin
From Business Analytics to Rational Action, by Kirk Smith
PART TWO: THE HCM:21(r) MODEL 45
CHAPTER THREE Scan the Market, Manage the Risk 47
How to Improve HR Processes 56
The Intersection of People and Profits: The Employee Value Proposition, by Joni Thomas Doolin, Michael Harms, and Shyam Patel
More Than Compensation: Attracting, Motivating, and Retaining Employees, Now and in the Future, by Ryan M. Johnson
''Best in Brazil'': Human Capital and Business Management for Sustainability, by Rugenia Pomi
CHAPTER FOUR
The New Face of Workforce Planning 85
How to Put Capability Planning into Practice 94
Scenario Planning: Preparing for Uncertainty, by James P. Ware
Quality Employee Engagement Measurement: The CEO's Essential Hucametric to Manage the Future, by Kenneth Scarlett
Truly Paying for Performance, by Erik Berggren
The Slippery Staircase: Recognizing the Telltale Signs of Employee Disengagement and Turnover, by F. Leigh Branham
CHAPTER FIVE Collapsing the Silos 141
How They Are Applying It 153
Roberta Versus the Inventory Control System: A Case Study in Human Capital Return on Investment, by Kirk Hallowell
The Treasure Trove You Already Own, by Robert Coon
Waking the Sleeping Giant in Workforce Intelligence, by Lisa Disselkamp
CHAPTER SIX
Turning Data into Business Intelligence 182
How to Interpret the Data 192
Predictive Analytics for Human Capital Management, by Nico Peruzzi
Using Human Capital Data for Performance Management During Economic Uncertainty, by Kent Barnett and Jeffrey Berk
Using HR Metrics to Make a Difference, by Lee Elliott, Daniel Elliott, and Louis R. Forbringer
PART THREE: THE MODEL IN PRACTICE 215
CHAPTER SEVEN Impacting Productivity and the Bottom Line: Ingram Content Group, by Wayne M. Keegan 217
CHAPTER EIGHT Leveraging Human Capital Analytics for Site Selection: Monster and Enterprise Rent-A-Car, by Jesse Harriott, Jeffrey Quinn, and Marie Artim 224
CHAPTER NINE Predictive Management at Descon Engineering, by Umair Majid and Ahmed Tahir 240
CHAPTER TEN Working a Mission-Critical Problem in a Federal Agency, by Jac Fitz-enz 259
CHAPTER ELEVEN UnitedHealth Group Leverages Predictive Analytics for Enhanced Staffing and Retention, by Judy Sweeney 265
PART FOUR: LOOKING FORWARD 271
CHAPTER TWELVE Look What's Coming Tomorrow 273
Views of the Future: Human Capital Analytics 276
APPENDIX: THE HCM:21(r) MODEL: SUMMARY AND SAMPLES 301