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World’s largest social network leverages, among many platforms, social signals and predictive analytics to find talent
Call it the “Moneyball” approach to finding talent.
In the 2011 award-winning film, Brad Pitt starred as a baseball coach who relied on crunching data to find new players. Facebook is doing almost the same thing.
The social networking giant uses recruiting software from Entelo, which analyzes “social signals and predictive analytics” to help companies find talent.
“We love data for recruiting, and finding the right talent at the right time to help us scale,” said Facebook Recruiting Manager Tim Diss during
Human Resource Executive magazine’s 17th annual HR Technology Conference and Exposition. “The more that we know about people on the front end, the more we can cut down time” to hire.
Entelo CEO Jon Bischke said, “We can predict when people are coming to market,” by indexing social data at massive scale. Entelo analysts then aggregate information to create what they call “super profiles.” They look at publically available information on social networks and blogs about potential candidates’ professional lives and paint what they call “a 360-degree view” of an individual, Bischke said.
“In 10 minutes, our sourcing team saved hours and hours, so speed is inherent,” Diss added.
Entelo also uses predictive analytics to help customers identify which employees are most likely to leave their jobs, calling that data “leading indicators of when a person is coming into the market,” Bischke said.
For example, are employees updating their LinkedIn profiles, connecting with recruiters and companies more often, tweeting more about jobs, answering questions on Quora? Are they making their social presence known by engaging in Twitter chat discussions? “Everything they do publically on the social web can point to whether they are prime to move,” Bischke said.
The length of time in a present position can be an indicator as well. The prevailing wisdom, he said, used to be that people leave their jobs around the four-year mark. But that’s “completely wrong. We looked at millions and millions of resume data” and discovered that “people actually leave their jobs on calendar years, peaking at year one and declining every year after.”
Back to the Future
“We believe that over the next few years, HR systems will be looking at the future,” Bischke said, pointing to another company at the forefront of workforce planning and predictive analytics: Evolv, which was acquired in October by Cornerstone OnDemand, a cloud-based software provider for businesses.
Evolv also helps companies find workers. By leveraging data to determine the relative performance of individuals, it was able to determine that people who live closer to their office will perform better, Bischke said. It also discovered that people who apply for jobs with a nonstandard browser and people who have a felony conviction in their past performed better as well, he said, refuting “some highly held myths.”
As part of its commitment to diversity recruiting, Entelo launched Entelo Diversity, an algorithm to identify talented candidates from underrepresented groups.
“Recruiters have used data for years to source underrepresented groups,” Bischke said, but Entelo goes beyond looking at photos, or whether or not someone attended a women’s or historically black college, or if they’re a member of an “affinity group that singles out race or gender.” The company “analyzes millions of data points to efficiently source candidates from underrepresented groups,” he said.
Aliah D. Wright is an online editor and manager for SHRM.
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