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URL:  http://boards.fool.com/change-coming-to-some-hr-depts-31007009.aspx

Subject:  Change Coming to Some HR Depts Date:  12/5/2013  1:42 PM
Author:  tjscott0 Number:  53442 of 60049

http://www.theatlantic.com/magazine/archive/2013/12/theyre-w...

Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed.

By one estimate, more than 98 percent of the world’s information is now stored digitally, and the volume of that data has quadrupled since 2007. Ordinary people at work and at home generate much of this data, by sending e-mails, browsing the Internet, using social media, working on crowd-sourced projects, and more—and in doing so they have unwittingly helped launch a grand new societal project. “We are in the midst of a great infrastructure project that in some ways rivals those of the past, from Roman aqueducts to the Enlightenment’s Encyclopédie,” write Viktor Mayer-Schönberger and Kenneth Cukier in their recent book, Big Data: A Revolution That Will Transform How We Live, Work, and Think. “The project is datafication. Like those other infrastructural advances, it will bring about fundamental changes to society.”

Some of the changes are well known, and already upon us. Algorithms that predict stock-price movements have transformed Wall Street. Algorithms that chomp through our Web histories have transformed marketing. Until quite recently, however, few people seemed to believe this data-driven approach might apply broadly to the labor market.


You can now find dedicated analytics teams in the human-resources departments of not only huge corporations such as Google, HP, Intel, General Motors, and Procter & Gamble, to name just a few, but also companies like McKee Foods, the Tennessee-based maker of Little Debbie snack cakes.

make no mistake: during the next five to 10 years, new models will be created, and new experiments run, on a very large scale. Will this be a good development or a bad one—for the economy, for the shapes of our careers, for our spirit and self-worth? Earlier this year, I decided to find out.

Ever since we’ve had companies, we’ve had managers trying to figure out which people are best suited to working for them.

“I think an HR person from the late 1970s would be stunned to see how casually companies hire now,” Peter Cappelli told me—the days of testing replaced by a handful of ad hoc interviews, with the questions dreamed up on the fly.

Perhaps the most widespread bias in hiring today cannot even be detected with the eye. In a recent survey of some 500 hiring managers, undertaken by the Corporate Executive Board, a research firm, 74 percent reported that their most recent hire had a personality “similar to mine.”Lauren Rivera, a sociologist at Northwestern, spent parts of the three years from 2006 to 2008 interviewing professionals from elite investment banks, consultancies, and law firms about how they recruited, interviewed, and evaluated candidates, and concluded that among the most important factors driving their hiring recommendations were—wait for it—shared leisure interests. Lacking “reliable predictors of future performance,” Rivera writes, “assessors purposefully used their own experiences as models of merit.” Former college athletes “typically prized participation in varsity sports above all other types of involvement.” People who’d majored in engineering gave engineers a leg up, believing they were better prepared.

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.


There is a lot more at the link. I would recommendation that you read the entire article if you have an interest in this subject.
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