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The human resources department is known for being touchy-feely, but in the age of big data, it’s becoming a bit more cold and analytical. From figuring out what schools to recruit from to what employees should be offered flexible work arrangements, data analytics are helping HR professionals make more informed decisions.

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Jonah Hill in a scene from ‘Moneyball’.

The success of Oscar nominated film Moneyball isn’t hurting either, said James Raybould, director of insights at LinkedIn. The movie, based on the Michael Lewis book, tells the true story of Oakland A’s General Manager Billy Beane. Using statistical analysis, Beane was able to recruit undervalued baseball players and lead his underfunded baseball club to the playoffs.

“We’re seeing a lot of companies actually aspire to that movie,” he said last week during a panel on big data at the Impact 2012: The Business of Talent conference convened by consulting group Bersin & Associates. “How do I make Moneyball for HR?”

Capital One, the credit card company and bank, has automated data reports on employee attrition, headcount and promotions. It is also beginning to analyze the characteristics of its most successful employees, like what schools they went to and what their majors were, said Mark Williams, statistical analysis manager for workforce analytics at Capital One. “Now we’re going back through resumes and creating a lot of that data,” he said.

In the wake of the financial crisis, when the compensation structure of many banks were criticized for incentivizing excessive risk-taking, Williams has also been asked to do an analysis of how pay is linked to sales performance.

“We do risk very well; we don’t lend to people who won’t pay us back…. Part of that is we have really good governance over our credit models; we have a staff of statisticians and that’s their job,” he said. “What I’m looking to do is a very similar thing in creating a governance process around some of the risk metrics for compensation.”

The big data revolution is just beginning to penetrate the HR industry, said Josh Bersin, chief executive and president of Bersin & Associates. Some companies have a progressive view of how data analytics can help their HR departments. Most don’t. “Of the companies we talk to, five to 15% are very sophisticated at analyzing people data,” he said.

At Luxottica Group, the Milan-based eyeglasses conglomerate, data analytics have disproven assumptions about gaps within the company’s recruiting strategy, said Sean Dineen, vice president of talent management and organizational development.

The data showed it took an average 96 days to fill a position with an external candidate. The management team believed that the company’s recruiters acted too slow, but a statistical analysis found hiring managers dragged their feet about making decisions about who to hire, Dineen said. It now takes the company 46 days to hire external candidates.

Luxottica, the parent company of brands like Ray-Ban and Oakley, is also using analytics to see how well it is does in promoting its best employees. “Are we actually moving high potential people?” he said. “Why is this person [who rates highly] in the way we evaluate talent in the same job they were four years ago?”

Joseph Walker covers technology for FINS.com, The Wall Street Journal’s jobs and career website.

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Editor’s Note: TechCrunch columnist Semil Shah currently works at Votizen and is based in Palo Alto. You can follow him on Twitter @semil

“In the Studio” opens its doors this week to one of Silicon Valley’s most quietly active venture capitalists who, after years working in technology operations for major networking companies, a stint with an Asian telecom giant, and nearly a decade investing in mobile, gaming, digital media, and networking companies, is paying particular attention to the implications of big data and the potential opportunities they create.

For the past decade, Ping Li has been investing in across a broad range of technology companies with Accel Partners, where he is a general partner. Since their defining Series A investment in Facebook, the firm has been on a roll, opening offices in New York City and expanding its footprint overseas, all while maintaining their anchor in the middle of Palo Alto’s University Avenue. And, over the past few years, Accel has also developed an interest in “big data.”

The term “big data” is thrown around often in conversation or at tech conferences, but despite the generalizations and hype, significant opportunities exist for entrepreneurs and investors alike. Last year, I attempted to analyze how big data impacted the consumer web and concluded that while opportunities were abundant, very few were in a positions to capitalize on them given the scarcity of talent in these specific areas of the consumer web.

Li and his partners at Accel are certainly looking at big data as it applies to consumer products — the massive amounts of unstructured social data we are all generating through social media and applications, waiting to be harvested. On the enterprise side of things, however, Li believes big data is on the verge of going mainstream, where datasets and analytical tools will soon be available to everyone, igniting new waves of innovation that could disrupt major public companies from the platform all the way to the application layer.

In this conversation, Li shares his views on the big data landscape and also offers subtle advice to potential founders looking into the space. Having the benefit to see many big data technologies and applications over the past few years, he has developed a keen sense of what minefields founders need to look out for when creating these technologies. To take things a step further, Li and his partners at Accel launched a $100M Big Data Fund, invested in creating an ecosystem of academics, technologists, and thought-leaders, and are hosting a private conference at Stanford on May 9 on this topic (technologists working on big data who would like to attend can contact Accel directly through the conference site).

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Motion games offer many new challenges for game designers. Some thoughts on surviving (and thriving) in a controller-less world.

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