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JAC FITZ-ENZ (San Jose, CA) is widely acknowledged as the father of human capital strategic analysis and measurement. As founder of Saratoga Institute, he developed the first international HR benchmarks. He was named by HR World as one of the Top 5 HR Management Gurus and cited by HR Magazine as one of 50 people in the last 50 years who have significantly changed the field of HR. He has authored a dozen books including the award-winning The ROI of Human Capital (978-0-8144-1332-6). His column, "Leading Edge", appears monthly in Talent Management magazine.
Preface | p. xi |
Contributors | p. xvii |
Introduction to Predictive Analytics | p. 1 |
Disruptive Technology: The Power to Predict | p. 3 |
Toward Analytics and Prediction | p. 8 |
Why Analytics is Important | p. 17 |
Measuring what is Important | |
Strategic Human Capital Measures: Using Leading HCM to Implement Strategy | |
From Business Analytics to Rational Action | |
The HCM:21“ Model | p. 45 |
Scan the Market, Manage the Risk | p. 47 |
How to Improve HR Processes | p. 56 |
The Intersection of People and Profits: The Employee Value Proposition | |
More than Compensation: Attracting, Motivating, and Retaining Employees, Now and in the Future | |
"Best in Brazil": Human Capital and Business Management for Sustainability | |
The New Face of Workforce Planning | p. 85 |
How to Put Capability Planning into Practice | |
Scenario Planning: Preparing for Uncertainty | |
Quality Employee Engagement Measurement: The CEO's Essential Hucametric to Manage the Future | |
Truly Paying for Performance | |
The Slippery Staircase: Recognizing the Telltale Signs of Employee Disengagement and Turnover | |
Collapsing the Silos | p. 141 |
How they are Applying it | p. 153 |
Roberta Versus the Inventory Control System: A Case Study in Human Capital Return on Investment | |
The Treasure Trove you already Own | |
Waking the Sleeping Giant in Workforce Intelligence | |
Turning Data into Business Intelligence | p. 182 |
How to Interpret the Data | p. 192 |
Predictive Analytics for Human Capital Management | |
Using Human Capital Data for Performance Management During Economic Uncertainty | |
Using HR Metrics to Make a Difference | |
The Model in Practice | p. 215 |
Impacting Productivity and the Bottom Line: Ingram Content Group | |
Leveraging Human Capital Analytics for Site Selection: Monster and Enterprise Rent-A-Car | p. 224 |
Predictive Management at Descon Engineering | p. 240 |
Working a Mission-Critical Problem in a Federal Agency | p. 259 |
UnitedHealth Group Leverages Predictive Analytics for Enhanced Staffing and Retention | p. 265 |
Looking Forward | p. 271 |
Look What's Coming Tomorrow | p. 273 |
Views of the Future: Human Capital Analytics | p. 276 |
Appendix: The HCM:21“ Model: Summary and Samples | p. 301 |
Index | p. 332 |
About the Author | p. 342 |
Table of Contents provided by Ingram. All Rights Reserved. |
The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.
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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.