Whether it's where to locate a factory for the best labor pool or how a VP of sales should structure incentives, workforce analytics software can help an enterprise sail beyond the flat earth of spreadsheets.
By Samuel Greengard Comments 0 | Recommend 0
eof Pejsa can see the future of human resources through the 18-inch
flat-panel monitor placed on his desktop. Seated in his office at a large
federal facility in the suburbs of Washington, D.C., the chief of the pay,
processing, and systems branch for the U.S. Census Bureau is closely studying a
map of the United States. He positions his hand on his computer mouse and moves
the cursor to Texas. Instantly, a bubble pops up on his monitor showing minimum,
maximum, and average salaries for the 272 bureau employees working in the Lone
Star State.
"This is data that used to take days or weeks to assemble," says the
affable 40-year-old public servant. Another click of the mouse and he’s
drilling down into the data by county and then by job position. Seconds later,
he’s able to slice through the data to view individual workers. "We’re
able to determine how pay scales vary in different states and uncover patterns
that influence them, such as education, training, gender, and race. This is like
lining up a Rubik’s Cube."
The high-tech operation could never be mistaken for grandpa’s federal
government. The Census Bureau--along with a growing number of companies such as
Interwoven, Royal Caribbean Cruises, Merck, and Northrop Grumman Information
Technology--is turning to sophisticated workforce analytics applications to
mine data and gain insight into business processes and labor conditions. These
applications can spot hidden patterns and problems and help an organization make
more effective business decisions surrounding programs, policies, and pay. Yet,
while workforce analytics uses data-mining and reporting tools that weren’t
available just a few years ago, the system isn’t problem free.
Unless an
organization taps into the right data and ensures that it is accurate--and then
puts the data into action--workforce analytics can become a trip down the
rabbit hole. Ron Hanscome, senior program director at META Group in Plymouth,
Minnesota, is one who can see the distinct advantages. "It turns the
intangible into tangible," he says. META reports that about 60 percent of
Global 2000 companies will use some form of workforce analytics by the end of
2003, mostly to improve decision-making on compensation, recruiting, retention,
and performance issues. David Ulrich, a business professor at the University of
Michigan, says that the technology is bringing healthy change. "Organizations
are beginning to recognize that the softer side of the business can be measured
and that it’s a key factor in achieving success," he says. Betty Silver,
human capital strategist at SAS Institute Inc. in Cary, North Carolina, adds,
"Workforce analytics allows organizations to examine a multitude of
interrelated factors. It can drill into places that previously couldn’t be
reached."
Although workforce analytics is rooted in human
resources, the ability to deliver detailed information
about workforce issues and trends--ranging from where to locate a factory for
the best labor pool to how a VP of sales should build incentives--has real applications throughout the organization. Done properly,
workforce analytics can help an enterprise sail beyond the flat earth of
spreadsheets and simple reporting and discover a brave new world.
Counting on analytics
Step inside Federal Office Building Number 3 in the Washington, D.C., suburb
of Suitland, Maryland, and you will find yourself wandering through a
mind-numbing labyrinth of corridors and hallways. Hundreds of offices,
stretching almost as far as the eye can see, provide an apt metaphor for the
level of complexity that confronts a person trying to navigate today’s data
infrastructure. Without a map and an address for finding a particular person or
office, all the brainpower ensconced in this massive building is out of reach
and virtually useless.
"By putting data into the hands of
managers, we’re allowing decision-making to take place on the front lines of
the organization rather than in the executive offices."
Seated at a simulated wood grain desk in room 3254, Pejsa is explaining the
how and why of workforce analytics. In sharp contrast to the world of technology
he lives and breathes, he surrounds himself with an array of personal items.
There are Beavis and Butthead figurines, framed cloth patches from various space
missions, and a Sopranos poster. At this moment, he is reflecting on how the
behemoth agency is migrating into the digital age. Having spent his entire
working life at the organization--he joined the Census Bureau in 1985 after
graduating from Virginia Tech with a degree in business management--he
certainly has a sense of perspective. "By putting data into the hands of
managers, we’re allowing decision-making to take place on the front lines of
the organization rather than in the executive offices."
At the Census Bureau, workforce analytics has unleashed a new level of
knowledge. From their desktop PCs, line managers have access to information that
would have been unimaginable only a few years ago. It’s possible to examine
data on employee education and training patterns; salary breakdowns by geography
or employee segments; the effectiveness of diversity programs; termination
histories; who uses employee benefits; alternative work schedules; and
retirement and early retirement planning.
When Pejsa decides to create a report, he selects the desired elements from
drop-down boxes and slots them into the appropriate rows and columns. Once a
report appears on his monitor, he can apply filters--such as employees at
headquarters within a specific pay grade--and instantly view a more detailed,
customized report. Using SAS Institute’s Human Capital Management application
(formerly HR Vision), Pejsa and others can view charts, graphs, and raw data and
begin to map out a business strategy for people and resources more effectively.
One advantage of using analytics is the organization’s ability to better
understand the demand for temporary positions and how much they cost. Because
many job assignments are cyclical in nature--and the Census Bureau sometimes
promotes current employees for weeks or months at a time--planning for changes
and budgeting can become a complex task. By using the application, "managers
are able to take changes into account and structure the workforce dynamically,"
Pejsa says.
Recently, the Census Bureau also turned to the application to better
understand employee work schedules before negotiating with its labor union. By
modeling various scenarios--such as four 10-hour days and the traditional 5x8
week--Pejsa can view how changes in staffing levels will affect pay and
performance. "We were able to run the report and discuss the issue
immediately," he says.
In the past, such reporting capabilities required the MIS department to spend
days, even weeks, digesting data on a mainframe. And in many instances, the data
sets were so complex that it was simply impossible to generate a report. Just as
room numbers help locate the right office within the vast expanse of Census
Bureau headquarters, workforce analytics attempts to bring order to a chaotic
data universe.
Putting data to work
One thing that makes workforce analytics so powerful is that organizations
can tap into data from operations, finance, marketing, human resources, and
more. In addition, it’s often possible to use 10, 20, even 30 years of data
that has grown cobwebs sitting in long-neglected databases. By overlaying and
combining data--like a giant Rubik’s Cube--it’s possible to understand how
a particular incentive or compensation plan actually plays out or what
constitutes an optimal level of turnover. "An organization can make some
scientific adjustments based on past successes and failures," Ulrich says.
Simply put, workforce analytics puts line managers on the front lines of
decision-making. A VP of operations can tweak compensation, rewards, and
responsibilities
to keep top performers engaged. If he or she adds a bonus, it’s possible to
measure the corresponding results before and after. A finance executive can
slice and dice data about labor trends and costs to create a favorable pay
structure at a new factory. At the same time, a director of human resources can
identify which benefits employees use, which are frivolous, and how to maximize
corporate resources.
META Group estimates that the initial cost of workforce analytics starts in
the low six figures and averages about $250,000 per 10,000 employees, plus
ongoing annual licensing and maintenance fees. In some cases, that can translate
into an ROI ranging from a few months to a year or more. And a well-designed
system can integrate with a human resources scorecard and incorporate industry
metrics to provide a more complete picture of cause-and-effect relationships.
That could mean taking industry averages for the cost of a particular benefit
and overlaying them with internal costs, or examining how incentives at
best-practice companies affect productivity and comparing it to internal
practices.
At the Census Bureau, the genesis of workforce analytics is rooted in such
knowledge. One day, while Pejsa was sitting with his boss discussing human
resources systems, the two realized how inefficient a homegrown application was
for managing the 10,000 employees spread across 12 regional offices. "The
system was inflexible, and we had questions about the data quality," he says.
What’s more, the system had a tendency to crash and couldn’t accommodate all
of the data residing in various databases and datamarts. So, they began to look
at the various analytics and reporting tools on the market.
Eventually, the Census Bureau chose a workforce analytics application from
SAS. The selling points, Pejsa says, were the simplicity of the Web interface,
built-in templates, and the flexibility to add and create reports as needed.
Moreover, Human Capital Management allowed the Census Bureau to plug in a
diverse array of formats, including Microsoft Access and Excel.
After a six-month implementation, the Census Bureau went live with the system
in the spring of 2002. In September, it moved to a Web-based version of Human
Capital Management, and put the application on the desktops of 25 analysts
within human resources (Pejsa hopes to expand the use of the system to 200 to
300 managers within the next year or so). Finally, the government agency was
ready to put its human resources data to work in a big way. "We had access to
data and information that would significantly change the way we make decisions,"
Pejsa says.
"We have gained a level of sophistication that didn’t exist
only a few years ago."
Analyze that
Not only has workforce analytics reduced the risk of delays, errors, and
inconsistencies, but it also has saved the Census Bureau tens of thousands of
dollars in staff time. The MIS department no longer spends hours generating
reports. Managers can steer clear of reams of paper or mind-numbing
spreadsheets. "We have gained a level of sophistication that didn’t exist
only a few years ago," Pejsa boasts.
That may be so. But like any other emerging technology, workforce analytics
can present a hornet’s nest of challenges, frustrations, and problems. "Workforce
analytics is only as good as the underlying data and how it’s used," META
Group’s Hanscome cautions. One of the biggest problems is identifying business
objectives and mapping data so that it can flow seamlessly across departments,
divisions, and business units. Adds Marcia Barkley, president of MBarkley
Consulting, a Sacramento, California, firm: "Building the infrastructure for
workforce analytics can prove intimidating. Many organizations have purchased
applications and wound up with them sitting on the shelf or sitting idle."
There’s also the task of changing a culture that once allowed only the top
executives to view data but now pushes decision-making further down into the
organization. "If line managers and others don’t understand the value of a
workforce analytics application and how to collaborate and share data, then the
system isn’t going to produce anything close to the desired results,"
Barkley explains.
At the Census Bureau, the learning curve has been steeper than expected,
Pejsa admits. When the agency first turned to workforce analytics a couple of
years ago, it had plans to use an assortment of features and tools that have
since been placed on the back burner. What’s more, it wanted to introduce the
application to dozens of senior-level managers, but most were woefully
unprepared for the hands-on approach. "Our goals were too ambitious," he
says.
Another giant headache was revamping the agency’s organizational structure
to fit the application. Over the years, the Census Bureau had assumed a
decidedly horizontal structure, and the SAS software required a distinctly
hierarchical model to function effectively. Pejsa spent more than a month
working with his boss and staff analysts to map all the desired tools,
capabilities, and permission rights to the appropriate users.
Finally, the process of connecting all the various systems proved more than a
bit troublesome. At first, other applications and systems produced hiccups when
the Census Bureau attempted to switch on the workforce analytics tools. And in
some cases, servers crashed and nerves frayed when the agency attempted to plug
in back-end applications and stream data across the organization.
The Census Bureau’s encounter with workforce analytics has been more
successful than most. Only about 10 percent of
organizations are now using it in any significant way, and another 10 to 15
percent are dabbling in it, says META Group’s Hanscome. Part of the problem,
he says, is that some vendors’ applications aren’t ready for prime time.
They simply cannot cull and organize data in ways that provide maximum insight.
Another factor is that tight IT budgets and a heavy emphasis on other projects,
including customer-relationship management and supply-chain management, have
diverted funding and attention away from the somewhat nebulous world of
workforce analytics.
Yet, for the Census Bureau, which spent less than $100,000 to get the project
off the ground, the payoff has been substantial. Despite occasional glitches and
breakdowns, the agency is evolving into a smarter, more flexible organization
that’s finally able to measure the cost and value of its workforce. And as the
agency has plowed through various problems and challenges, it has found a clear
path to success, Pejsa says. "We now have the tools to make strategic
decisions faster and better.
Samuel Greengard is a contributing editor for Workforce. E-mail sam@greengard.com to comment. Next Article: 1. Putting Analytics to Work
What companies should be looking at and how they can navigate this new frontier.
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eof Pejsa can see the future of human resources through the 18-inch
flat-panel monitor placed on his desktop. Seated in his office at a large
federal facility in the suburbs of Washington, D.C., the chief of the pay,
processing, and systems branch for the U.S. Census Bureau is closely studying a
map of the United States. He positions his hand on his computer mouse and moves
the cursor to Texas. Instantly, a bubble pops up on his monitor showing minimum,
maximum, and average salaries for the 272 bureau employees working in the Lone
Star State.
"This is data that used to take days or weeks to assemble," says the
affable 40-year-old public servant. Another click of the mouse and he’s
drilling down into the data by county and then by job position. Seconds later,
he’s able to slice through the data to view individual workers. "We’re
able to determine how pay scales vary in different states and uncover patterns
that influence them, such as education, training, gender, and race. This is like
lining up a Rubik’s Cube."
