But as the industry grows, big questions remain about what can be done with this newly discovered trove of data. Bersin's research shows that only four percent of large companies can make meaningful predictions about their workforces, while 90 percent can accurately predict business metrics such as budgets, financial results, and expenses. Can human-resources analytics do enough to capture the behavior and preferences of its endlessly complex subjects: humans?

"It’s one of the few areas of business that hasn’t really been figured out yet," says Bersin. "People are imperfect machines. Nobody ever figures out people completely."

But that doesn't mean companies aren't going to try. On the Big Data front, the company VoloMetrix mines calendar and mailbox data to determine over a hundred predictive indicators. From those indicators, the company works with clients to determine how to solve a given problem, from determining what makes a great salesperson to how emails can be more efficient.

"There are several different types of clients who work with VoloMetrix," says Ryan Fuller, the company's CEO and co-founder. Fuller says that VoloMetrix's clients either have a specific issue they want to employ data mining to solve, or hire the company to look more generally at how to save time. "Once the people analytics data is available, firms can immediately begin making data-driven decisions to improve efficiency and performance," says Fuller.

Some of the surprising results VoloMetrix has found from client datasets challenge conventional workplace wisdom. For example, for a client that wanted to know when the best time of the day was to have meetings, VoloMetrix looked at how disengaged employees were by seeing how many emails they were sending during meetings. At 9 a.m. meetings, roughly 8,500 emails were sent, while meetings at 6 p.m. were only slightly better at 7,000 emails. Meanwhile, employees in meetings between 10 a.m. to 2 p.m. didn't send very many emails—so the company rescheduled for the middle of the day.

In another study, VoloMetrix found that the best employees tend to not only have larger networks within companies than other employees—they also engage more with staff both more senior and junior than themselves. "High performers engage in more of both activities," says Fuller. "Within some companies, high-performing employees engage with senior staff members 28 percent more than low-performers and directly engage with junior staff 16 percent more than low-performers."

As for the problems that Big Data can't solve, small data might help. The company TINYpulse works with 500 companies to take feedback surveys, typically a yearly chore, and turn them into a weekly, anonymous, one-question pop-up. Some of the questions they've asked have garnered some very unconventional, but perhaps incredibly honest, answers. For example: the question “If you were promoted to be your boss's manager in the new year, what's the first thing you would change?"​ The most popular answers ranged from traditional answers such as better pay and hours, to firing and demoting employees who were dead weight. Another unconventional question TINYpulse asks to measure workplace satisfaction is whether employees have interviewed for another job in the past three months.