And the real value then?
HR analytics mainly uses data from the HR system. In the case of high turnover or absenteeism, correlations can be investigated with travel distance, age, number of years in office, salary compared to colleagues, absence history and the latest assessments. Data analysts find this far too limited and these kinds of connections actually boring. A good example of this can be seen in an article, which states: "It is not age, intelligence or dedication to the company that determines whether a mailman is good or mediocre, but owning a dog is the best predictor of good performance." I especially wonder how the analysts arrived at a reliable data collection that includes performance, intelligence, dedication and ownership of a dog. And what do you do with that knowledge? “You are a great candidate, smart and dedicated. But guess what, you like cats more than dogs. What a pity.” No, right?
In my opinion, the most important predictor of absenteeism, turnover and performance is not owning a dog, but rather 'the involvement of the employee'. Google knows more about employee engagement than her manager. Google knows what time the employee is at work, how often and at what times she checks her social media, where her friends work and which job sites she visits during and after working hours. What does HR know about her involvement? At best HR asks the employee anonymously once a year and rarely the manager.
Bad manager disastrous for engagement
Research by the Hay group, among others, shows that the most important driver of employee involvement is in the HR system. The manager! The bad manager overloads employees, does not recognize good contributions, does not help with development, is not interested in people, hires the wrong people and does not challenge employees enough. In other words, the bad manager is disastrous for the involvement in his team. Employees therefore do not leave the company, but they leave the manager. The manager is the causal link between absenteeism, leave and poor performance that you are looking for with HR analytics.
The holy grail of HR analytics is prescriptive analytics. The system infers from correlations that you should take measures A, B and C to improve employee engagement, after which turnover, absenteeism and performance improve. Does a good manager need this advice? Probably not, it is precisely the connection with employees – so that he knows what is needed – that makes him a good manager. Does a bad manager make better decisions based on advice from the system? Also not. If the system does the analysis well, the advice will often be that the manager should improve his performance. The bad manager will look for and find all the excuses to disguise his own role.