Forget the prestigious college degree. Skip the unpaid internship at a respected company. Those things are headed the way of fancy résumé paper. In the future, whether or not you land your dream gig will depend more on how often your retweets get retweeted, how far you live from the office, or how you answer multiple-choice questions designed to assess your empathy, sociability, and ability to deal with repetitive tasks in highly regulated environments.
Companies such as Xerox, The Wall Street Journal recently reported, now pay more attention to a candidate’s “personality” than they do to his work experience—at least when they’re looking for people to staff their customer service call centers. Such screenings are not only about temperament. Employers are also evaluating how a worker’s commute might affect his loyalty and which social networks he participates in. With mountains of data at their fingertips, work force analytics consultants can now determine what attributes and propensities are associated with success in a given position. If you possess those attributes and propensities, congratulations, you start on Monday.
This is not an entirely new development. In 1830 George Combe, one of England’s most prominent phrenologists, explained that he could tell if a prospective servant was conscientious or untrustworthy by examining the bumps and bulges on his head. Nearly a century later, advocates of deterministic skull measurement continued to tout its potential as a human resources tool, with a letter writer in The Phrenological Journal describing it as an efficiency tool on par with typewriters and telephones. “It seems but a short time in the future,” the correspondent suggested hopefully, “when our favorite Science will have the confidence of business men to such an extent that an applicant will be asked, ‘Have you a scientific description of your Mental and Physical qualities?’ ”
Given contemporary harassment laws, extended head fondling as a means of assessing potential hires should probably be avoided. But while phrenology never caught on in the workplace, the desire to take a quick, quantitative, predictive measure of would-be workers never died. As Annie Murphy Paul documents in her 2004 book The Cult of Personality Testing, psychometric visionaries throughout the 20th century invented instruments such as the Minnesota Multiphasic Personality Inventory (MMPI) and the Myers-Briggs Type Indicator (MBTI) in their efforts to map the human psyche. Business interests saw the utility of these tools, which sort disparate individuals into more general stock-keeping categories that are easier to track and manage.
Like George Combe, commercial outfits that adopted tests like the MMPI and MBTI hoped to divine the intrinsic nature of potential employees. Were they honest or deceitful? Were they dependable, obedient, outgoing? Or would they take a lot of sick days, spend too much time at lunch, and steal company property?
While critics have repeatedly challenged the efficacy of these tests, today’s advocates say the evaluation process has fundamentally changed because so much more data are available. Imagine, for example, a database of 10,000 individuals who have proven themselves to be effective call-center employees. A company might have access to their personality test results, their training records, the performance metrics that are kept on them each month as they go about their jobs, and so on. Data scientists analyze this information in myriad ways, eventually detecting useful trends.
Employees who live within 10 minutes of the office may be 20 percent likelier to stay at the company at least six months than ones who live 45 minutes away or further. Employees who have a college degree may be less inclined to stick with a call-center job than those who do not. According to The Wall Street Journal, Evolv, the company assisting Xerox in its recruitment efforts, determined that the ideal candidate to staff the company’s call centers “uses one or more social networks, but not more than four.”
As more companies adopt this approach to recruitment, expect a parallel push to expand employee protection laws. Not getting a job because your car is 12 years old or because you live 40 miles away from the office may not seem as unjust as not getting a job because of your race, sex, or religious beliefs, but it’s still untethered to performance and comportment.
Yet ultimately what this approach represents is a move away from the white-collar shamanism that informs traditional hiring practices—the ritual of the firm handshake, the incantatory power of résumé action verbs like iterate and prioritize. In contrast, work force analytics aims to scrutinize call-center employees as closely as post-Moneyball general managers scrutinize shortstops, using as many quantifiable characteristics as possible. “The hourly workforce is tremendous in the richness of data available to evaluate,” an Evolv white paper reads. “For a given hourly employer there are billions and sometimes trillions of data points that can be systematically evaluated to understand and then optimize the workforce.”
While surveillance of such magnitude may conjure grim visions of intrusively, oppressively optimized cubicle serfs desperately trying to meet call quotas, there are liberating, empowering aspects to this kind of data analysis. For example, by analyzing thousands of work histories, Evolv determined that there is “very little relationship between the number of jobs an employee has held and their current tenure,” and that “companies that screen out job hoppers and the unemployed have been needlessly limiting their candidate pool.” Even more strikingly, Evolv suggests that while many companies refuse to hire applicants who have criminal records, including some who have only been arrested, its analysis shows that “crimes committed before a person entered the workforce had no predictive value for any counterproductive workplace behaviors,” and that “people with records who stay arrest-free for four to five years are only as likely as the average person to be arrested again.”
While Evolv specializes in hourly workforces, other companies are applying similar techniques to other sectors. SHL, a London-based firm that specializes in “talent management solutions,” used data “from almost 4 million assessments in close to 200 countries” to determine what characteristics define employees with top-level leadership potential and where the greatest reserves of such individuals can be found. Among its conclusions: Mexico, Turkey, and Egypt “have the greatest source of potential future leaders.” In addition, SHL found that while the “difference in leadership potential for women and men is less than 1 percent, men hold senior positions 3 to 1 over women.”
In this new world of data-driven hiring practices, Ivy League degrees and résumés that boast stints at marquee companies won’t matter as much as new metrics that have been designed to show a person’s fundamental attributes and abilities over time. In theory, at least, more people will have more opportunities as Big Data reveals that talent can come from anywhere.
Of course, as the Moneyballization of the workplace proceeds, what this also means is that soon we’ll no longer be able to hide our career .290 on-base percentage with an artfully worded résumé. Our proficiencies and weaknesses will be far more transparent, just as they’ve been for professional athletes ever since baseball card publishers started routinely printing statistics on the backs of cards in the early 1950s.
While such transparency will punish employees who aren’t quite living up to their reputations, it will benefit those who are truly providing value. More important, it will help companies operate more efficiently, which will in turn provide benefits to us all.