Billy Beane’s method of rating players reveals what metrics can do in hiring
By Craig Johnson
Brad Pitt plays him in the movie, Moneyball. But that’s not his claim to fame. Oakland A’s General Manager Billy Beane shot into the limelight because he popularized a new method of rating players in baseball: sabermetrics.
Like many other business managers, Billy Beane grappled with scarce resources. He needed the kind of money the Oakland A’s didn’t have to recruit. So he began using sabermetrics, a new method that gave the team a winning streak in the 2002 season after a shaky start. This was the beginning of the player selection trend that has since inﬁltrated the sport. This statistical technique helped him spot undervalued players.
Before Beane, baseball’s old guard had its own ways of choosing major league players. They relied on traditional rankings and intuition on who would do well on their team. Employers in other industries take a similar tack, often relying on their intuition to spot good employees — although experts say relying on gut instinct alone in making hiring decisions can create diﬃculties.
In Beane’s case, he was grappling with less money and competition from richer teams. The scarcity of resources had him turn to an already existing method that helped turn around the sport’s thinking on how it chooses its players. Beane’s story is built up to dramatic heights in the movie Moneyball, which covers the 2002 season of the Oakland A’s baseball team and is based on a book of the same name by Michael Lewis.
The ﬁlm contrasts the scouts’ old-school practices to “sabermetrics,” portraying the old guard as unreceptive to the analytics, and the A’s got oﬀ to a rocky start in 2002 after ﬁlling out the team using the new statistical approach.
However, the season got better, with the team racking up a 20-game winning streak between Aug. 13 and Sept. 4 — the longest winning streak in American League history. And the A’s did this with a payroll of around $40 million, a paltry sum compared with well-healed teams such as the New York Yankees, which spent about $126 million on its players in the same year. Following the A’s success, the use of such analytics has spread in baseball, with The Associated Press reporting that Beane and his staﬀ helped usher in what has been called the “stats revolution” in baseball.
Use of advanced analytics and others had a large impact on baseball and the way decisions were made in the game, says Vince Gennaro, presi dent and author of the Society for American Baseball Research. “Beane and Mark Shapiro, of the Cleveland Indians, were the two general managers at the time pioneering quantitative analysis,” Gennaro says. “Those two were really taking it to another level.”
There was also more data becoming available and increased computing power and capabilities in the early 2000s. In addition, the stakes were rising because payroll and salaries of players were escalating, making recruiting the right players even more crucial. These factors provided motivation to make data-driven decisions, and today all baseball teams use some form of advanced analytics.
“There’s virtually no one who’s not in the game of advanced analytics anymore,” Gennaro says.
Applying what Beane did to other industries has its challenges, but it’s doable. Each industry is unique, Beane says. However, there are certain commonalities everybody is looking for. “We’re hoping to get the best performance we can in terms of the amount of investment we make,” Beane says. And the aim is to do so in a consistent manner.
Beane believes using an objective analysis, including key performance indicators, provides a consistent process to ﬁnd the right people. He will be speaking at Staﬃng Industry Analysts’ Executive Forum in ChampionsGate, Fla., in February.
Industry notwithstanding, hiring the right person can be tricky. Relying on intuition can increase the odds of a bad hire — which can be costly for any employer, whether they are staﬃng ﬁrms or baseball teams — and hiring managers may be wrong more times than they like.
One recent study claims employers are more focused on hiring someone they would like to hang out with rather than a person who can best do the job. Experts also point to mistakes hiring managers make in interviews, such as focusing on trick questions or spending more time talking than candidates.
Unfortunately, bad hires come with a cost in ineﬃciency, lost opportunities and other problems.
Randy Street, president of ghSMART, a ﬁrm that helps companies select “A” players for their executive ranks, says that making a bad hire on average costs about 15 times a person’s base salary, which includes hard costs such as salary, severance and possible legal fees. It also includes soft costs such as the account lost or customer not won. Costs can be less for a line worker and much more for a CEO.
Worse, a typical manager can make a lot of mistakes basing hiring decisions on gut instinct.
“The average or typical hiring manager hires the wrong person about half the time,” Street says.
Street follows a diﬀerent method from Beane’s. But the outcomes remain measurable even here. He advocates using a checklist approach to hiring where employers have a “mission” or executive summary of the role, list of speciﬁc outcomes for a role and what competencies are required. This process should generate outcomes that can be measured, such as generating 30 leads a month.
In today’s world, analytics touches many industries, even in those where previously it has not played a role. But Beane was at the forefront of a trend that later took oﬀ. The book and movies poured attention on him and his methods, leading to board member positions for Beane at several ﬁrms including Easton-Bell Sports, ProTrade and customer resource management software ﬁrm Netsuite. He also became in demand as a speaker, speaking on the importance of using stats to hire. “In today’s world, how can you not make an objective analysis as part of your decision-making?” Beane asks.
The idea appears to be spreading to the staﬃng industry. A recent survey by Staﬃng Industry Analysts, the publisher of this magazine, revealed that using internal data and analytics metrics ranked among the top three developments that “will very positively impact the performance” of staﬃng ﬁrms’ talent acquisition processes.
At one point, baseball statistics used to be collected simply with the naked eye. “Now we’re using all kinds of tech to gather info on every movement on a baseball ﬁeld,” Beane says. And as technology oﬀers more tools to gather data, the use of statistics will only grow.
Craig Johnson is managing editor, staffing publications, at Staffing Industry Analysts. He can be reached at email@example.com.
Creating a More Accurate Picture
Billy Beane’s success came through using advanced analytics of baseball in ways that others hadn’t scrutinized. Ditto with the staffing industry.
Consider turnover metrics, which refer to how many temp workers leave their assignments for negative reasons (resigned early or were fired) and positive reasons (they completed the assignment or were hired by the client). One problem with this metric is that some assignments don’t have end dates, and the turnover metric seemed to over-accentuate the negative (those who resigned before the end of an assignment), says Chris Hediger, vice president of enterprise solutions at staffing firm Yoh.
Hediger says Yoh fixed the problem when it began also looking at another metric — the average tenure of people who left. It turned out that most contractors were leaving after two or three years on the job. This was good news because it turned out contractors who left had actually stayed on their jobs for longer than average.
“[Combining those metrics] gave a more accurate picture of what was really occurring in the environment,” Hediger says.
When Art (Doesn’t) Imitate Life
If sabermetrics existed when he was growing up, maybe Billy Beane wouldn’t have been a baseball player, according to the movie Moneyball.
The movie also portrays a great deal of conflict between Beane and the old guard used to doing things their way. It also points to difficulties with Art Howe, A’s manager at the time. However, Howe has said in news reports the film doesn’t portray the relationship accurately.
The film flashes back to Beane’s start in baseball when he decided to forsake a scholarship to Stanford University and go into baseball. He was a first round draft pick, but ultimately didn’t meet expectations.
In real life, Beane played for the New York Mets, Minnesota Twins, Detroit Tigers and Oakland A’s. He was a first round draft pick in the 1980 June Free Agent Draft.
Beane retired as an active player in 1990 and joined the A’s front office team. He became general manager in 1997.
He is still going strong. He was named Sporting News’ Major League Baseball Executive of the Year following the A’s 94-win 2012 season. However, the A’s have yet to make it to a World Series under his watch.