Am I that predictable? AI can predict when you’ll quit with 95% accuracy
For many, quitting a job is one of the hardest decisions they’ll ever make; for others it’s like changing a pair of socks. But what we all have in common, no matter how many self-help books we imbibe: is that we are predictable.
IBM, using probably the most famous AI computer, Watson, has created a ‘predictive attrition program’ which can predict when employees are about to leave the company at a rate of 95%. It can also suggest further actions by HR staff to stop the person from leaving.
The program is being championed by IBM CEO Ginni Rometty, who stated in March 2019 that the program had so far saved $300 million USD in attrition costs stemming from costs in relation to things like training and loss of income. This is not to mention the institutional knowledge that employees take with them, but also the morale damage to other employees of losing a work mate.
IBM is now offering the solution to external clients. They haven’t provided Colonel Sanders’ secret recipe as to how the patented program works, but they have revealed some of the more obvious data sets on which the program operates, which are:
1) Time since last promotion compared to peers
2) Time since last change in employer
3) Commute time
5) Compensation overall
6) Compensation compared to peers
If you own a company or if you’re in HR, it may be time to start measuring these factors to see where the pain points are, and then seeing what good can be done with the data.
For example, with overtime and commute time, a ‘flexible’ working approach. For promotions, it could be a matter of either promoting the person or mentoring the employee into a position where they can be promoted.
Whatever knowledge emerges from the data, can be used to provide a better workplace for employees; so they don’t fly the coop.
Felix Blumer is a Consultant at Rutherford, the Legal and Compliance executive recruitment specialists.