Imagine using data to pinpoint the most high-performing employees and keep them satisfied?

A startup called Evolv is building technology to make that possible, and it has raised $15 million in a fourth funding round led by Vantage Point Capital.

“We prevent the wrong person ending up in the wrong job,” said Max Simkoff, the company’s founder and CEO, in an interview.

Evolv’s team of data scientists have developed software they claim can increase workforce tenure by an average of 15 percent and workforce performance by 5 percent. The product compiles data from disparate sources and makes recommendations.

“It’s hard to understand why it’s radically predictive, but it’s radically predictive,” said Jim Meyerle, Evolv’s cofounder.

More specifically, the in-house data science team will extract information like termination history and performance data, then combine it with relevant econometrics, like gas prices and nationwide unemployment rates. To bolster the data sets, Evolv pushes out surveys to its customers’ employees about social media usage, work history, and other core traits and competencies.

Evolv showcases how “big data can be leveraged to improve stagnant business processes,” said Bill Harding, Managing Director, VantagePoint Capital Partners, and a newly-appointed member of the company’s board of directors.

Since forming in 2007, the company has scored some high-profle contracts with household-name customers, such as Xerox, that pay a six figure sum for an annual subscription.

Evolv’s San Francisco-based team will use the cash at its disposal to build out its sales and marketing team, and expand internationally. Previoius investors, GGV, Khosla and Lightspeed Ventures, also participated in this latest funding round.

In November, we reported on Evolv’s partnership with The Wharton School of business. The effort was not just about helping Fortune 500 companies recruit talent and boost productivity — there are tools like SAP’s SuccessFactors and Oracle-owned Taleo for that. Instead, the partners were looking to better understand (and potentially combat) high attrition rates in US workplaces.

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