Ask American businesses their greatest challenge and many will cite unmet workforce needs, often deepest in the realm of technology. More than 600,000 tech jobs are currently unfilled and the U.S. Department of Labor predicts the number will grow to a staggering one million by 2020. With the baseball season now us, I submit that a piece of the solution to the tech talent problem is found in an unexpected place: sabermetrics.
Sabermetrics is the application of statistical analysis to baseball records, perhaps most closely linked in the popular imagination to the book ‘Moneyball’ and the film adaptation that followed. A line from the 2011 movie best exemplifies this theory:
"People are overlooked for a variety of biased reasons and perceived flaws: age, appearance, personality. Bill James and mathematics cuts straight through that. Of the 20,000 notable players for us to consider, I believe that there's a championship team of 25 people we can afford, because everyone else in baseball undervalues them.”
The quote comes from the portrayal of a team analyst who adopted what was, at the time, an uncommon approach to player evaluation and acquisition. Traditional methods of player evaluation and market valuation, his theory explained, are unduly focused on attributes that often do not correlate with a player’s actual success on the field or contribution to team victories.
That traditional model relied heavily on the opinions of scouts and whether a particular player passed “the eye test” -- in other words, does the player look like what we expect a good player to look like. Old school methods also focused on player statistics like batting average that are widely understood but provide less meaningful data than more esoteric statistical measures.
Traditional methods of player evaluation and market valuation...are unduly focused on attributes that often do not correlate with a player’s actual success on the field or contribution to team victories.
With sabermetrics, executives stopped worrying about whether a player met the eye test. They became less attached to popularly understood stats like batting average, instead looking to more complex data like On-base Plus Slugging (OPS) and Wins Above Replacement (WAR). Sabermetrics devotees dismissed the importance of traditional evaluation and trusted their own data-driven measures of production. As a result, they bought the contracts of good players at a low price because their opponents didn’t understand the players’ true value.
Today, sabermetrics is a key component of player evaluation for every Major League Baseball club. The old model has become obsolete. But remarkably, much of American tech hiring still utilizes an evaluation process reminiscent of the pre-sabermetrics era.
The same biased reasons and perceived flaws that kept unorthodox ballplayers out of the big leagues have frequently posed a barrier to a tech career for job seekers with non-traditional credentials.
Sabermetrics and the Moneyball ethos present a superior alternate model for tech hiring. Innovative and forward-looking employers know that traditional markers of job readiness are often poor predictors of job performance, so they focus on digging deeper into harder-to-spot but measurable determinants of skill and competency. Just as it doesn’t really matter whether your corner outfielder looks like a slugger if he is efficient at the plate and in the field, smart employers know that a brand-name college degree is not necessary for their software engineers so long as their code is solid and their drive is strong.
Increasingly, savvy employers and organizations are adopting this model. By evaluating students based on competency and willingness to learn, these employers open doors to a career pathway that discounts educational background and work experience in favor of objective validations of skill. Cutting-edge employers like Express Scripts are heavily supplementing their ordinary tech talent channels by hiring cohorts of developers with atypical backgrounds who demonstrate aptitude and complete accelerated, skill-specific training programs. In the process, these organizations are finding undervalued talent that has been overlooked by firms with a more rigid approach.
By evaluating students based on competency and willingness to learn, these employers open doors to a career pathway that discounts educational background and work experience in favor of objective validations of skill.
Professional sports teams and American businesses both exist in a highly competitive space and are deeply dependent on the quality of their talent. If the brightest lights in a tradition-heavy enterprise like baseball can see the competitive advantage in ditching the eye test for a competency-based model, American employers can certainly build their championship team the same way.
By Jeff Mazur