Title Inside the wacky world of weird data: What's getting crunched
Publication Date 2014-02-12
Text Weird human resources
Start with some of the strangest findings about how we work. The big data start-up Evolv sifts thought millions of pieces of human resources data from clients looking for insights about who applies for jobs and who succeeds at work. The idea is to help companies decide who to hire, and how to manage their teams. Evolv CEO Max Simkoff said his firm has found a series of surprising insights about corporate hiring, based on companies' own data.
"We've got data on over 3 million employees in a variety of industries and job types," Simkoff said. "Companies have finally honed in on the monthly, weekly and in some cases hourly metrics that measure those employees' productivity."
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One of the most surprising findings is just how easy it can be to tell a good applicant from a bad one with Internet-based job applications. Evolv contends that the simple distinction of which Web browser an applicant is using when he or she sends in a job application can show who's going to be a star employee and who may not be.
Evolv says a willingness to adopt new technology by choosing "nonstandard browsers" like Firefox or Chrome is a powerful predictor of performance. Employees who use them perform better across the board than those who use standard browsers that come with most computers, like Internet Explorer and Safari.
Not only do these employees stay on the job longer, miss less work and adhere better to company protocols, the company says, they provide higher customer satisfaction and close more sales.
Mary Murcott is chief strategy officer at a call center firm called NOVO 1, which hired Evolv to help it retain its workers and hire new people who would stay.
The company found several trends in play: Workers over the age of 30 or 40 had about half the attrition rate as younger workers. The more rank-and-file employees switch around among managers, the longer they seemed to stay with the firm. And although the firm had long been open to rehiring workers who had left, Evolv concluded that rehires left the company 44 percent faster than new hires, which made Murcott rethink her openness to ex-employees.
"That has helped us understand where we got our top people and where we got people that were not great," Murcott said. "And so we've moved our recruiting dollars and our job-sourcing dollars to other avenues."
What's more, Murcott said her firm has been able to focus its hiring on an unusual pool of applicants who are usually overlooked by corporate hiring managers: the long-term unemployed.
Working with Evolv, the company has developed hiring tests that de-emphasized traditional measures that have not proved effective, such as education and work experience, and emphasized personality and skills-based measures.
"We had a 55-year-old woman come in the other day—she hadn't been able to find a job, she hadn't been in the workforce, she hadn't had any job experience, and we hired her as a customer service representative," Murcott said. "So here's woman that couldn't get a job, that everybody's denying, and we were able to put her on the job. She's doing great."
But here's the weirdest thing Evov said it has discovered: Criminals can make better employees than anyone else. Evolv calculates that employees with criminal backgrounds are 1 to 1.5 percent more productive on the job than people without criminal records, and the firm said that difference in a large company "could result in tens of millions in profit and loss gain."
Evolv CEO Simkoff says he's not sure why that's the case, but he guesses it's because such employees feel a sense of loyalty to the companies that took the risk to hire them.
But won't companies be reluctant to hire criminals? Simkoff said companies sometimes don't want to hear advice that they should be hiring more criminals. "But I tell them their own data is showing this—if they want to save $10 million a year, they should make the change. But what they do with the data is ultimately up to them."
Veterans of the Obama presidential campaigns—which created new ways of drilling down into databases and social media to find and motivate potential voters—have seeded a slew of new big-data analytics firms hoping to do the same for paying clients. One of them is Michael Simon, who worked on the Obama '08 campaign and is now a co-founder of the data analytics firm HaystaqDNA.
Simon and his firm are looking at new ways to isolate demographic groups—slices of American society so small that they might not have been detected by traditional polling, but can now be identified and reached using technology. It's the kind of thing that can be as useful to corporate marketing folks looking for customers as it is for politicians looking for votes.
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"We're trying to understand how people who otherwise look alike are actually different, and you really need to dive beneath the surface," Simon said.
In one recent project, Haystaq used Google Earth images of California to find homes with solar panels on the roofs. After teaching their computers to distinguish between solar panels and other things that look similar from above, like skylights and pools, they are cross-referencing the solar panel homes with publicly available name and address information for those houses.
As a result the firm will have a list of everyone in California—and eventually the whole country—who owns a residential solar panel.
The fact that someone would buy a solar panel tells you a lot about the type of person they are: likely environmentally conscious and with enough disposable income to spend on an expensive piece of technology. Solar panel owners make up their own tiny demographic—and by scouring satellite images, marketers can now find them individually.