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Data-Driven Human Capital Decisions
Today's human resource information systems make it easier to manage by the numbers.
Sun Microsystems Inc., a Santa Clara, Calif.-based computer maker, wanted to know the results of a mentoring program it conducted for thousands of employees. A standard HR practice would have been to distribute a questionnaire to participants and draw conclusions from their subjective responses.
Instead, Sun conducted a statistical analysis of employee data—68 variables—looking for correlations between the program and promotion rates, salary increases, performance ratings and other factors. It studied data from a statistically significant sample of participants—mentors and mentees—and from a control group of employees who did not participate.
By drilling into data, Sun gleaned insights it never could have gotten with any certainty from a survey. Among the findings were three conclusions that ran counter to hunches: Mentors benefited as much as or more than the mentees did; administrative employees benefited more than engineers; and low performers benefited much more than high performers. Sun used these and other findings to optimize its mentoring program for the future.
A small but vocal group of HR professionals, consultants and thought leaders believe it is time for the profession to adopt such analytical methods, which are widely used in other areas of business. Called workforce analytics, they drive data-based decision-making, which is more systematic than the gut feelings HR professionals have too often relied on.
“The next battleground for organizations is to address productivity, retention and employee acquisition by doing this kind of analysis,” says Jim Bowles, vice president of workforce development at Cingular Wireless, an Atlanta-based subsidiary of AT&T Inc., in San Antonio. “We’re moving toward fact-based decisions. The business demands it. Most organizations are numbers-driven, and HR must be able to produce reliable numbers and explain interrelations and how they drive decisions.” ›
Bowles uses workforce analytics to study call-center retention, but the variety of uses is constrained only by the imagination. This month’s cover story (see page 44) tells how data can be used in workforce planning. In this article, you will learn how analytics can be used to study retention, training—and even office space.
Intuition vs. Information
In the realm of human capital decisions, hunches and intuition are becoming passé. Replacing them are regression curves and causality modeling. HR professionals who don’t understand this will find themselves replaced by analytical-minded managers from finance or a business division.
“The business demands on HR are increasingly going to be on analysis—just because people are so expensive,” says David Foster, director of human capital management at Aberdeen Group Inc. in Boston. “But a large percentage of HR professionals are not trained or prepared for this.”
In August 2006, Foster conducted a benchmark study of the use of workforce analytics, canvassing 147 companies of all sizes. The “best-practice” companies (about 20 percent) found workforce analytics most useful in three areas: assessing skill requirements, workforce availability and deployment; measuring performance; and making employee transition decisions such as terminations, promotions and transfers.
“All those decisions can be made intuitively or informatively,” Foster notes. “The analytic engines exist to crunch the data so you can make better-informed decisions. The best-practice companies in our survey said making smart decisions about human capital makes them more competitive.”
The good news is, analytical tools have never been better. The array of tools can be bewildering, however.
The first-generation tools offered a library of key performance indicators that can be rolled up and provided to HR staff and line managers in web-based reports, allowing them to slice and dice data in different ways. Sometimes called “dashboards,” they’re useful as far as they go, says James Holincheck, human capital analyst for Gartner Group, in Stamford, Conn.
The City of Albuquerque, N.M., for example, uses software from Cognos Inc., in Ottawa, Ontario, for all kinds of business analysis. The city produces several HR metrics reports, which managers and HR can study, according to Chris Framel, applications group manager in the information services division. More than half of managers and HR staff are using these reports.
In a recent research brief, Holincheck concludes: “It is, in fact, very useful for HR organizations to have access to the data necessary to help them understand how well they are doing in providing their services to their stakeholders. However, it is not enough.”
The next-generation tools, from vendors like People Business Network, Capital Analytics, DoubleStar, Infohrm, Cognos and others, give HR and business managers an ability to make predictive correlations between HR metrics and the business outcomes they are expected to achieve—such as the impact of a mentoring program on performance, for example.
Holincheck, who wrote a case study on what Sun Microsystems learned by using analytics to measure the impact of its mentoring program, says the company is a good example of the more advanced use of analytics. Sun used software and consulting from Capital Analytics Inc., in Durham, N.C., which is getting ready to make its ProCourse software available commercially later this year. “Capital Analytics offers more of a decision support tool,” he says. “It is more predictive and allows for more precision than some of the other tools.”
Other tools, including the human resource management system (HRMS) packages from SAP, Oracle, Lawson and others, are evolving in this direction.
A Scientific Approach To Turnover
Few work areas have turnover rates as high as those in call centers—the industry average is above 50 percent. Not long ago, Cingular only had 300 call-center workers and a turnover rate of less than 35 percent. As a result of acquisitions, it now has 30,000 workers in 100 call centers—and a churn rate Bowles declines to disclose.
To study turnover and learn how Cingular might stem it, Bowles and his staff used software and consultants from People Business Network Inc. (PBN), a Liberty Corner, N.J., human capital analytics and decision support vendor recently acquired by Vurv Technology in Jacksonville, Fla. PBN software pulled data from the HRMS (PeopleSoft at Cingular) and other systems, then analyzed the data in various ways.
Cingular looked at more than 25,000 employee records from multiple systems and analyzed hundreds of thousands of data points for about two dozen variables, including about 300,000 data points just on performance. Variables included tenure, wage rates, age, time-to-proficiency and other data that could be pulled from PeopleSoft. “We could drill into specific drivers of turnover and try to eliminate them based on the analysis of information presented,” Bowles says. “It helped us get clarity.”
Even though the analysis hasn’t yet yielded anything the company has acted on, “we are going to continue to dig,” says Bowles. “It is a matter of hypothesis testing. Our turnover rates continue to be an irritant.”
This underscores a key point about workforce analytics: Like a scientist, the HR professional must test hypotheses, rule out possibilities and continue to examine data. Cingular’s next research will focus on organizational and cultural variables and their correlations to employee churn.
Dissecting Training ROI
Many companies would like to know the return on investment (ROI) for training. Workforce analytics can help. Stacey Boyle, a longtime consultant in the training business, is currently senior director of blended learning services for SkillSoft PLC in Nashua, N.H. In a previous job at a company she declines to name, she used Capital Analytics to analyze a training program at a large insurance company. The insurance firm wanted to know the ROI for a two-week training program for agents, both new and seasoned. Pre-training and post-training premium sales figures were the key data analyzed. Boyle also collected demographic data about each of the 200 agents in the group she studied.
“We calculated an ROI for each demographic group,” she says. “Then we looked at which group produced the greatest ROI, and the insurance company decided to keep sending those agents to the same training and modified training for other groups.” Many companies are not comfortable undertaking rigorous workforce analyses without consulting help. Boyle says one of the challenges is making mathematical models understandable to HR professionals who may not have a grasp of research methods.
“The insurance company was quantitatively driven. We didn’t have to explain regression curves to them,” Boyle says. “There was a little skepticism, but not around the mathematical approach—rather, around whether they were going to be able to use the data.
“Some HR executives’ eyes glaze over when we talk about this stuff,” she says. “When I see that, I bring it back to outcomes—here are the kinds of decisions you can make with this.”
Analyzing Facilities Needs
At Capital One Financial Corp., in McLean, Va., HR eyes do not glaze over at the mention of analytics. Capital One revolutionized the credit card business by using analytics to determine what interest rate to offer each individual based on their risk level, replacing the old standard of one rate for everyone. ›
The company began to apply analytics in HR more than three years ago when it launched a dashboard. “All these metrics are ubiquitously available, in real time, and eliminate the need for HR to be dragged into tactical work,” says Matt Schuyler, Capital One’s chief human resources officer.
He declines to disclose which software tools the company uses, but acknowledges using several commercially available systems plus some that have been developed in-house. HR now has 15 analysts who collect and analyze metrics, then push results to the dashboard.
The facilities function is also under HR, and Schuyler applies analytics to facilities decisions, too. “Using analytics we asked, ‘How many people do we have, how much time do they spend in the office, what do they do there, why do we have assigned cubicles?’ ”
Facilities staff spent a few months walking around with clipboards every day to study seating occupancy. They also looked at what people did at their desks. “We determined that more than 40 percent of seats were vacant every day,” says Schuyler. “An additional 30 percent were vacant at some point during the day.”
Schuyler ended up with data to support the supposition that desks had become moot for many workers. “We discovered that people weren’t at their desks, but more often in meeting rooms or outside the building.” Because most of the workers in question were allowed flex schedules, few were actually at a desk from 8 to 5.
Schuyler computed a likely ROI for the changes he envisioned, then made his case to the executive staff: a smaller workplace for the same number of employees, with fewer desks and many more open areas where people could work comfortably alone or collaborate with others.
Only top managers and administrative assistants have assigned seating. Everyone else was given a small cart, like an artist’s carrel, to tote belongings. Each worker was given a laptop with robust wireless connectivity, a BlackBerry and other technological accoutrements.
The system has been rolled out at seven sites with more than 4,000 workers, and the reaction is positive. Schuyler says providing leading-edge technology took the sting out of not having a desk. HR continues to study the workplace and adjust. For example, the company downsized the carrels at one point and eventually got rid of them for many workers.
The HR department alone has been able to combine what were three floors into one for a $3 million annual savings, with similar results in other departments, he says.
“HR is no different than anyone else at Capital One,” says Schuyler. “We need to provide the data to prove the case. This is exacerbated by the fact that our company is made up mainly of business analysts. So everyone is held to a very high analytical standard here.”
Is HR Ready for This?
To apply statistical methods to business problems requires a different skill set than many HR professionals have. Cingular’s Bowles, who holds a doctorate in education, studied statistics and research methods. It was so long ago, he’s not sure how much it helps him today. “But my comfort level, in helping to frame the problem and understand the results, is there from past experience,” he says.
Schuyler has hired analysts from other Capital One divisions and from consulting firms, and discovered that recent college graduates seem to have a greater aptitude for analytics—and are comfortable with technology. He has also trained some HR professionals as analysts.
Still, in his experience, “We found it is easier to hire a businessperson and teach them HR domain expertise than to teach an HR person business.”
But as HR professionals who want to become business leaders know, it’s never too late to learn.
Bill Roberts, HR Magazine contributing technology editor, is a freelance writer based in Prunedale, Calif., who covers business, technology and management issues.
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