I saw a tweet from an HR executive that read, ‘>“Do I have data? No, #HR analytics are overrated. I go with my experiences.” I won’t name the executive because I don’t want anyone to troll him online. He is actually a great guy and a friend. However, when I read that tweet, I thought to myself, this is precisely what is wrong with HR. We tend to rely heavily on our feelings and not on people analytics, workplace analytics, or predictive analysis. We think we know all about human behavior. Our past experiences give us the confidence or maybe even arrogance to ignore data. But there are problems with “reading people” or “using our experiences.” Do you know what they are?
Before I discuss the problems with feelings and the benefits of people analytics, let me explain just what people analytics are. Undoubtedly you have heard the term “big data,” which is the process of analyzing and quantifying just about anything from actions and statistics to behaviors. Big data or data analysis is utilized in almost every aspect of our lives, from our social media interactions to our purchasing and eating habits.
Companies use numbers to predict consumer tastes, demands, and tendencies. Sports franchises use people analytics to fill out their rosters and sign players. This was highlighted in the movie “MoneyBall” with Brad Pitt and Jonah Hill, based on the Oakland A’s baseball team. They used predictive analytics and people analysis to predict the number of times a hitter would get on base, a player would make an error, when a pitcher was most effective, and even the tendencies of the opposing team. People analytics can be applied to any organization.
HR professionals believe, based on gut feelings or past experiences, that turnover is based on unhappiness, low wages (competitive pay), or being disgruntled. However, employee attrition could also be based on poor working conditions, unfair treatment, lousy benefit packages, high healthcare costs, no healthcare coverage, glass ceilings, or being poached by other companies. You won’t know until you examine the data. Take Wegmans, for instance, a major grocery chain in the Northeast that co-commissioned a two-part project from CEB to determine why employees stayed with their company. They partnered with another grocery chain to do the same analysis, and split the costs. Both companies shared the data for competitive research. The results concluded that employees joined and stayed for the healthcare benefits. It wasn’t pay or culture, nor was it co-workers and bosses–it was healthcare.
Here’s another example of using people analytics. You may have heard that Google used to ask a wide variety of brain-teaser questions, like “How many golf balls does it take to fill up a yellow school bus?” during its interviews. Recently, Google used years of data analysis to determine what makes a great interview and needless to say, the brain-teasers are now gone. You may say, “I could have told you that.” But could you have told me or Google that less than 14% of their employees have 4-year degrees? People analytics has shown that GPAs, degrees, and test scores are worthless when it comes to job performance.
The problem with using your past experiences, your gut instincts, and your eyes is that you can’t see the future, your gut can’t track trends, and your past experiences aren’t as relevant in today’s world as they once were. The workforce is blended and more unpredictable than ever–if you don’t use analytics, even as gauge, you are missing out on what is truly going on in your workplace. In order to sustain your marketplace and develop it into the future you have to be able to predict behavior, and not just the behavior of a handful of people. You have to be able to predict the actions of a labor force.
In HR, we use pre-employment assessments as the primary form of analytics needed to acquire talent. However, assessments can be incorporated with people analytics for ongoing improvement as well. In this article, we have highlighted examples from Google, Wegmans, and major league baseball as examples of using people analytics to assist with recruiting, talent acquisition, retention, and performance. Although some companies use employee survey data, it is not as relevant because it is based on what an employee tells you and not what they actually do. Exit interview data can be useful, but that information can be tainted because the outgoing employee may be bitter or nonchalant because they are moving on. Performance Improvement Plans (PIPs) and evaluations are historically inaccurate, subjective, and inconsistent.
People analytics is the most reliable form of data because it measures what a person is currently doing. Adding talent assessments to people analytics helps you predict your future talent needs, which is useful when you’re purchasing new technology, executing a change management initiative, developing compensation and benefit packages, and engaging employees.