Skip to Content

The Machine-Readable Workforce

Companies are analyzing more data to guide how they hire, recruit, and promote their employees.

Xerox is screening tens of thousands of applicants for low-wage jobs in its call centers using software from a startup company called Evolv that automatically compares job seekers against a computer profile of the ideal candidate.

According to these data, culled from studying job records of many similar workers, past experience working in call centers isn’t a good predictor of success. Instead, a person should be a “creative” type, though not too inquisitive. Participating in one social network like Facebook is a plus, but involvement in too many is a negative. A short commute is a must—that means a person is less likely to quit before Xerox can recoup its cost to train them.

While personality exams aren’t new to business, large employers like Xerox are beginning to embrace a concept called “workforce science” that promises to make performance reviews and judging résumés far more data-driven. One of the best-known attempts to hire and fire by the numbers is at Google, whose HR department, called “People Operations,” has turned hiring into a kind of engineering project, using computer models to determine how many times each candidate should be interviewed, how larges raises should be, and nearly every other personnel decision.

Evolv, based in San Francisco and founded in 2007 bases its advice on data gleaned from tens of thousands of employee files on hourly workers, who also make up 60 percent of the United States workforce. Applicants have to take a half-hour online test that ranks them against a profile of a successful call-center worker. Evolv has raised $42 million from investors. Another startup, Gild, has begun using software to score computer programmers who place their work in public repositories, locating job candidates whose résumés might otherwise end up in a trash bin (see “A Startup That Scores Job Seekers, Whether They Know It or Not”).

Lawyers who practice anti-discrimination law are watching these trends. While it’s legal to give aptitude tests, hiring based on a computer’s assessment of seemingly unconnected factors—like how many social networks you join—could raise new questions. “They’re creating these big databases of people,” says Christopher Moody, an employment lawyer in Los Angeles. “More and more companies are doing pre-employment testing. Whether this really indicates some job-related quality in the applicant is questionable.”

It’s easy to see why Xerox wants to turn to automated methods. Although it still sells photocopiers, Xerox has also become one of the world’s largest outsourcing companies (see “Q&A: Ursula Burns” and “The Empire Strikes Back”). It provides services like running customer service centers, handling health claims, and processing credit-card applications that brought in $11.5 billion in revenue last year.

That business relies on a huge workforce of 54,000 customer service agents, and because of high attrition in hourly jobs (pay in the U.S. ranges from $9 to $20 an hour), Xerox will have to replace 20,000 of them this year, says Teri Morse, vice president for recruiting at Xerox Services. Morse says employees that stay less than six months cause a loss for Xerox, due to the expense of training them.

Since the company began pilot tests of Evolv’s analytics software two years ago, Morse says employees are on average staying longer at Xerox and their performance is 3 to 4 percentage points better, as measured by factors like how many complaints they resolve or how long it takes to handle a call. The software has also started to influence other subtle factors, like what time of year Xerox hires people.

Morse says basing decisions on data means Xerox has been able to broaden the base of people it will consider for hourly jobs, including those who have been unemployed for long periods. But the data also rules people out. Morse says Xerox today won’t even look at résumés of those who score in the “red” category of Evolv’s initial behavioral assessment, a 30-minute online exam that workers fill out at home. “Individuals that test strongly perform better and survive longer,” she says. Early on, while piloting the system, Morse says Xerox still hired against the advice of the data. Now, she says, “people who do poorly we no longer hire.”

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

It’s time to retire the term “user”

The proliferation of AI means we need a new word.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.