Boston Red Sox: Finding Business All-StarsBy Mel Duvall | Posted 2004-05-14 Email Print
Re-Thinking HR: What Every CIO Needs to Know About Tomorrow's Workforce
Keeping track of stats in the numbers-obsessed world of baseball is nothing new. But Boston Red Sox General Manager Theo Epstein has amassed a collection of personnel data utilizing the right blend of enterprise software and business intelligence applications other teams and corporate business managers can only dream about. This is the story of how success is created by blending intelligent analytical technology against employee performance management.
Boston Red Sox: Finding Business All-Stars
Unicru provides its clients, such as Albertson's, Target and The Sports Authority, with a kiosk-based system to accept job applications and screen candidates. In addition to general information and employment history, the kiosks ask applicants a variety of questions to determine if they have the right personality to sell on commission, or whether they'd be a courteous and attentive waiter. These include true-or-false questions such as, "I would rather sit around and read a book than go to a party with lots of people," and, "You don't act polite when you don't want to."
Within minutes after a candidate fills out an application, the system generates an assessment and also provides a hiring manager with a set of questions designed to probe a little further into areas of concern. If there's a worry that the candidate might not stay long with the company, the system prompts the interviewer to ask if the candidate remembers the name of his or her boss from two jobs ago, or three or four years ago. If the candidate does remember, the odds of retention are greater; if not, it's another strike against.
Unicru chief scientist David Scarborough says the Internet, human-resources applications and services such as online job boards now make it possible to do the same kind of analysis that baseball uses. "It's not that there was a lack of data in the past," says Scarborough. "There was a lack of data in a format that could be accessed and analyzed."
Now, however, it's not that hard to see how a Fortune 500 company could use its own sales or human capital management software to find the best heavy-hitting salesperson to fill a new opening. Criteria such as length of time to close a sale, size of average deal and number of deals closed per month are common metrics used in evaluations. Siebel Systems, which sells such metrics-based sales software, is known to be relentless in using such metrics, firing the bottom 5% of its salespeople each quarter.
Indeed, corporations are increasingly collecting vast amounts of data about their employees through sophisticated software offerings from vendors such as PeopleSoft, SAP and Siebel. Now these companies have to start using it to identify top performers, and tie it back to the training they've had, where they went to school, employment history and personal characteristics. Then, says Jason Averbook, director of marketing for PeopleSoft's human capital management division, corporations can start making smarter and more cost-effective decisions about hiring and managing people.
Some organizations are already making major league discoveries.
Charles Brooks, a senior human-resources officer with the Georgia Merit System, an agency that provides HR services to the State of Georgia, wondered, for example, why it was that some agents in the state's Child Support Enforcement (CSE) program were much more successful at collecting money from deadbeat dads than others.
When he began his research in 1998, Brooks noted that CSE agents collected child support payments ranging from $172,107 to $1.68 million per year. The average amount was $802,237 per agent. Upon further study, he found that performers in the top 13.5% collected at least $1.14 million, or 42% more than the average, while low performers, those in the bottom 13.5%, collected at least 42%, or $341,436, less than the average.
Brooks began looking into why there was such a disparity. He was initially told not to go there, that it wasn't a factor that could be fairly measured—some dads, after all, were just harder to collect from than others.
But he pushed ahead and began studying the top performers in the agency, poring over computerized records and looking for common characteristics. By 2001 Brooks had developed a survey that could predict with 95% accuracy whether an agent was a top performer. In other words, he could ask the agent a series of questions, and based on the answers he could tell if that person had the right stuff. A top performer, for example, provided this answer to the question: How do you cope with failure? "I talk to my colleagues and try to determine what I'm doing wrong, so I can fix it." A low performer, on the other hand, provided this answer: "It's a numbers game; I just tell myself I'll get the next one."
The results were impressive. The average collected per agent jumped 42%, from $802,237 in 1998 to $1.15 million by 2003. Not only could higher-performing agents be recruited, but the analysis could be used to identify underperforming agents and coach them in skills that could improve their success. The process resulted in an additional $24 million per year in increased collections for the agency. The state paid out $10 million less in welfare payments because it got more from the delinquent dads, and agent turnover has been decreased by 50%, resulting in further savings of $30 million over the four years the program has been in effect.
Other companies are asking the same types of questions of their human-resources data to find, hire and keep talent.
For years Dow Chemical Co., based in Midland, Mich., sent recruiters to both Ivy League and second-tier schools to find top M.B.A. prospects. But then it started sifting through its human-resources records, in this case kept in PeopleSoft, to find out exactly which schools most of its recruits had come from, which schools produced employees who stayed with the company longer and which produced the most executives. The company also keeps detailed records on such factors as how many on-site interviews were held and what offers were made and accepted.
The results were eye-opening, says Bill McNeill, head of the company's M.B.A. recruitment program. The study showed that Dow was basically wasting its time at the Ivy League schools. M.B.A. grads from the likes of Harvard and Yale typically didn't want to move to Midland, asked for more money than Dow was willing to pay, and didn't stay in the job as long. (The company would not release percentages.) Dow will typically send recruiters to campuses several times a year to woo top M.B.A.s—McNeill estimates it costs as much as $80,000 to reel in a new hire. After looking at the numbers, the company shifted its resources to universities such as Michigan State, Brigham Young and Purdue where Dow had greater success in attracting and keeping M.B.A.s and other highly sought-after graduates.