How can big data lead to improvements in companies' staffs?

While companies everywhere are already harnessing the power of big data to improve the way they attract consumers, sell products and provide customer service, they're still just beginning to scratch the surface of what data can do. Another area that's largely gone unexplored so far is human resources - by gathering data on their own employees and using it to perform workplace analytics operations, businesses can make better decisions regarding their strategies for hiring and retaining workers.

It's surprising that so few companies have yet made it a point of emphasis to improve their workforces using data. The information revolution has already made a significant impact in countless other corners of corporate America, so why shouldn't the HR office follow suit? Harvard Business Review recently tried to tackle this question. Tim Ringo, a partner at Maxxim Consulting in London, said that anecdotal knowledge and instinctive action are no longer enough. Businesses must make their personnel decisions based on real information.

"When faced with a major investment decision, how many organizations would bet their success on a gut feeling?" Ringo wrote. "How many organizations would rely mainly on intuition when taking a new product to market? Not many. Yet, when it comes to the workforce - one of a company's most expensive and valuable assets - too many executives rely on hunches, making decisions without making use of relevant data."

Hiring decisions can be among the most critical choices a company makes. One successful pickup can elevate a business to new heights, while one bad one can sink the ship. Yet not enough executives are making the conscious choice to use more analytics to improve their decision-making processes.

If companies used more data in making their personnel decisions, they could improve in a number of areas. Here are a few.

Crafting an overall strategy
All too often, executives make decisions about the overall philosophies of their businesses based on hunches. By using more analytics, they could devise clearer approaches. What's the overall corporate mission statement? What kind of team does a company need to achieve its goals? Where can the right employees be found? Data can answer all these questions.

Improving the recruiting process
Companies often put their job applicants through extensive interviews before making hiring decisions. These interviews, however, are often haphazard and unlikely to find the best candidates. According to Information Management, even Google hardly has a clue - corporate senior VP of people operations Laszlo Bock says that hiring is a "complete random mess" based on guesswork. Perhaps big data could help companies sharpen their strategies, ask the right questions and find the right hires.

Putting people in the right roles
Sometimes, if a certain corporate department is underperforming, the solution isn't to hire more people - it's to reallocate the labor that the company already has. Analytics can help businesses put people in the right roles, so that every department reaches its peak level of performance.

Keeping workers engaged
Especially with prized employees who had real value to their companies, retention is important. No company wants to be losing workers and hiring replacements every other month, so businesses need to keep their current employees engaged and motivated so they stay productive in their current roles. Analytics can help evaluate various ways of improving workplace morale.

Knowing when to make a change
No HR executive should stay married to the present. Sometimes changes are necessary - there are countless times when workers need to be hired, fired, relocated or otherwise shuffled around to keep the business going strong. By using big data, companies can figure out when big or small changes need to be made.

Data can tell a company many things about the quality of its staff. By working to gather more information and ensure data quality as well, businesses can improve their everyday operations.