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Google Algorithm Can Tell if You're About to Quit

Google Algorithm Can Tell if You're About to Quit

May 21, 2009

‘New algorithm can help Google answer complex staffing questions and identify employees most likely to quit.’ -

Google is the cream of the internet search and advertising crop and got to its top spot on the backs of a large group of dedicated and talented employees. Some of the very same employees that helped Google get where it is today are now leaving the company in increasing numbers.

The Wall Street Journal (WSJ) reports that Google is concerned that the loss of top staffers could hurt its long-term viability and ability to compete in the market. To help find the solution to the problem, Google is applying a new algorithm to mine employee data.

Google claims that its new algorithm can identify which of its 20,000 employees are most likely to resign. Exactly what the formula looks at is unknown, Google officials declined to comment on what the formula looks at reports the WSJ.

The inputs that the algorithm works form that are known are employee surveys and peer reviews. According to Google, the algorithm has already identified some employees that are most likely to quit and employees that feel underused. Feeling underused is reportedly a top reason employees leave.

Edward Lawler from the Center for Effective Organizations at the University of Southern California said, “They [Google] are clearly ahead of the curve, but a lot of companies are waking up to the fact that there is a lot of modeling that can provide you with critical data on human capital.”

Google’s Laszlo Bock said, “[the algorithm can] get inside people’s heads even before they know they might leave.”

Google is justified in its fear of losing top employees and engineers. A migration of early and many important Google employees has been occurring as Googlers move to greener pastures with new startups like Twitter and Facebook. Google has even found that its infamous perks are no longer good enough to keep top talent in place.

© 2009, DailyTech

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