Much of the attention paid to big-data initiatives has focused on the opportunities to find new customers, develop new products, increase sales, drive operational efficiencies, and even analyze the weather.
Now, another big-data opportunity is suddenly generating conversation, and it's overdue. Think back to any company meeting you have attended, and you'll recall the CEO saying something along the lines of, "Our greatest assets walk out the door at 5 o'clock." I'll admit that some CEOs are just slinging the you-know-what when they say it's their employees that matter most. Also, plenty of employees will counter that they wish their workday ended at 5:00 p.m.
However, great employees who are properly utilized can drive a company's success. So, it does make sense that effective use of big-data analytics in human resources applications could help to address most of the other opportunities that we are already targeting with analytics.
In recent years, HR has turned to analytics for three primary purposes. First, there is the recruiting aspect. You come up with good queries to sniff out potential employees through services such as LinkedIn. Then HR would examine a job candidate's digital footprint by searching across various online platforms to see how active they are in social media -- if that was relevant to the job at hand -- or they would look for reasons not to hire someone. That's where photos from drunken college nights or hate-the-boss Facebook posts have come back to haunt people. The third use of analytics has tended to be in employee evaluations.
Now, a new set of analytics applications is emerging in the HR field, even as the original three uses gain in popularity.
As reported by The New York Times, big-data analytics is starting to dispel some workplace myths, improving the hiring process, the employee retention rate, and the overall management of people.
For example, the NYT explains how the long-held belief that job hoppers make for bad hires is one myth. Apparently, research has shown that there is no correlation between job history -- presumably meaning frequency of changes rather than actual performance -- and future behavior.
In retrospect, that finding passes a reality check. I've known job hoppers who worked out just fine in a new role and became loyal employees, often because the fit and the timing were right in that they wanted to establish roots. At the same time, I've known people who worked at a single company for 20 years who just couldn't adapt to a new employer, typically because the new company didn't do things in ways to which they were accustomed. I'm sure you have heard, "At my old company we did it this way."
The NYT also noted that analytics offer a company insight, not just into who to hire, but organizational issues, such as what type of manager they need in a call center.
A blog by The Economist cites additional research that showed that many people with criminal records (who so many employers shun) actually make good employees, at least in call centers. Again, that makes some sense when you consider that many people who have been to prison find they fit well into a structured life. It may not be commonly known, but a certain percentage of paroled inmates commit new crimes just to get back to that structured environment. Call centers, with the scripts and routines, can be pretty structured worlds.
There also are examples of companies using big-data to identify the common characteristics that exemplify a good employee for their particular environment. (No, they aren't the same for all companies, or even across job titles within a single company.)
While employers are finding new ways to use big-data analytics in the HR sector, software and service providers are looking at how they can grow their businesses through HR-focused analytics. The NYT cites IBM's acquisition of HR company Kenexa, which has data on something like 40 million job applicants, employees, and managers. Oracle, SAP, and even the dating service eHarmony have their sights set on HR analytics.
HR analytics certainly can't be relied upon to tell us definitively that a particular job candidate will be a good worker, or that all managers should have the same characteristics. However, there now is evidence that analytics can reduce overall employee churn. Plus, analytics can dispel myths about hiring and management, and they might just open a company's eyes to new sources for hiring, ways to retain good employees, and some tricks of the trade that might make everyone a bit more productive.