Workers are quitting their jobs at record rates, thanks to a tight labor market and high confidence that moving on will also mean moving up, particularly in pay.
Besides leaving in search of more money, recent job-quitters have also cited toxic work environments and limited room for growth as major reasons for putting in their notice.
For employers, this kind of insight might only become clear during an employee’s exit interview, if at all. But with the help of artificial intelligence and machine learning, researchers have developed an algorithm that may be a better predictor of when a worker is at risk of quitting.
That could be a good thing — for employers and employees alike. By understanding who’s at risk of leaving, companies may be able to pinpoint the main reasons why employees are seeking other opportunities. If they’re willing to invest in retention, they’ll avoid the time and financial cost of replacing workers. The flip side, of course, is that employers have to put measures in place to improve employee satisfaction, whether that’s in the form of better compensation, workplace culture or career advancement.
Here’s how digging into the data could help businesses and workers thrive.