Scholarly research strongly suggests that happiness at work depends greatly on feeling a sense of agency. If the tools now being developed and deployed really can get more people into better-fitting jobs, then those people’s sense of personal effectiveness will increase. And if those tools can provide workers, once hired, with better guidance on how to do their jobs well, and how to collaborate with their fellow workers, then those people will experience a heightened sense of mastery. It is possible that some people who now skate from job to job will find it harder to work at all, as professional evaluations become more refined. But on balance, these strike me as developments that are likely to make people happier.
Because the algorithmic assessment of workers’ potential is so new, not much hard data yet exist demonstrating its effectiveness. The arena in which it has been best proved, and where it is most widespread, is hourly work. Jobs at big-box retail stores and call centers, for example, warm the hearts of would-be corporate Billy Beanes: they’re pretty well standardized, they exist in huge numbers, they turn over quickly (it’s not unusual for call centers, for instance, to experience 50 percent turnover in a single year), and success can be clearly measured (through a combination of variables like sales, call productivity, customer-complaint resolution, and length of tenure). Big employers of hourly workers are also not shy about using psychological tests, partly in an effort to limit theft and absenteeism. In the late 1990s, as these assessments shifted from paper to digital formats and proliferated, data scientists started doing massive tests of what makes for a successful customer-support technician or salesperson. This has unquestionably improved the quality of the workers at many firms.
Teri Morse, the vice president for recruiting at Xerox Services, oversees hiring for the company’s 150 U.S. call and customer-care centers, which employ about 45,000 workers. When I spoke with her in July, she told me that as recently as 2010, Xerox had filled these positions through interviews and a few basic assessments conducted in the office—a typing test, for instance. Hiring managers would typically look for work experience in a similar role, but otherwise would just use their best judgment in evaluating candidates. In 2010, however, Xerox switched to an online evaluation that incorporates personality testing, cognitive-skill assessment, and multiple-choice questions about how the applicant would handle specific scenarios that he or she might encounter on the job. An algorithm behind the evaluation analyzes the responses, along with factual information gleaned from the candidate’s application, and spits out a color-coded rating: red (poor candidate), yellow (middling), or green (hire away). Those candidates who score best, I learned, tend to exhibit a creative but not overly inquisitive personality, and participate in at least one but not more than four social networks, among many other factors. (Previous experience, one of the few criteria that Xerox had explicitly screened for in the past, turns out to have no bearing on either productivity or retention. Distance between home and work, on the other hand, is strongly associated with employee engagement and retention.)
When Xerox started using the score in its hiring decisions, the quality of its hires immediately improved. The rate of attrition fell by 20 percent in the initial pilot period, and over time, the number of promotions rose. Xerox still interviews all candidates in person before deciding to hire them, Morse told me, but, she added, “We’re getting to the point where some of our hiring managers don’t even want to interview anymore”—they just want to hire the people with the highest scores.
The online test that Xerox uses was developed by a small but rapidly growing company based in San Francisco called Evolv. I spoke with Jim Meyerle, one of the company’s co‑founders, and David Ostberg, its vice president of workforce science, who described how modern techniques of gathering and analyzing data offer companies a sharp edge over basic human intuition when it comes to hiring. Gone are the days, Ostberg told me, when, say, a small survey of college students would be used to predict the statistical validity of an evaluation tool. “We’ve got a data set of 347,000 actual employees who have gone through these different types of assessments or tools,” he told me, “and now we have performance-outcome data, and we can split those and slice and dice by industry and location.”
Evolv’s tests allow companies to capture data about everybody who applies for work, and everybody who gets hired—a complete data set from which sample bias, long a major vexation for industrial-organization psychologists, simply disappears. The sheer number of observations that this approach makes possible allows Evolv to say with precision which attributes matter more to the success of retail-sales workers (decisiveness, spatial orientation, persuasiveness) or customer-service personnel at call centers (rapport-building). And the company can continually tweak its questions, or add new variables to its model, to seek out ever stronger correlates of success in any given job. For instance, the browser that applicants use to take the online test turns out to matter, especially for technical roles: some browsers are more functional than others, but it takes a measure of savvy and initiative to download them.
There are some data that Evolv simply won’t use, out of a concern that the information might lead to systematic bias against whole classes of people. The distance an employee lives from work, for instance, is never factored into the score given each applicant, although it is reported to some clients. That’s because different neighborhoods and towns can have different racial profiles, which means that scoring distance from work could violate equal-employment-opportunity standards. Marital status? Motherhood? Church membership? “Stuff like that,” Meyerle said, “we just don’t touch”—at least not in the U.S., where the legal environment is strict. Meyerle told me that Evolv has looked into these sorts of factors in its work for clients abroad, and that some of them produce “startling results.” Citing client confidentiality, he wouldn’t say more.
