Men Lie, Women Lie, Numbers Don’t. – Why We Need Better Hiring Data
9 out of 10 Hiring decisions are still based on “gut instinct.” This isn’t only a huge problem; it’s downright scary—and really expensive too.
As recruiters and hiring managers we all make mistakes. That’s just human nature. Unintended bias just royally screws up our judgment. As it turns out, humans are very good at specifying the requirements and not too bad at eliciting information. Unfortunately we’re very bad at weighing the results. The brilliant cognitive psychologist Amos Tversky calls this “creeping determinism,” our instinct to fit the fits to the scenario. When hiring and managing employees, maybe we should call it “creepy determinism!” Relying on gut instinct and making decisions without the help of scientific data is inarguably one of the worst decisions that managers make.
Here’s why ignoring the data is dangerous
All you need to do is ask any manager the probability of success for a candidate he just hired and he’ll likely tell you the odds range from 70% to a sure bet. Why else would he hire him (or her?) And yet reality tells us a very different story. One out of every 5 new hires quit within 45 days and 1/3 are gone within 6 months. Failure is even higher for executives who have a 50% failure rate within 18 months. With the cost of hiring mistakes spiraling out of control and time-to-fill rates at an all-time high, human fallibility is a big deal. Human tendency takes whatever facts fit our view of the world and neglects whatever doesn’t fit neatly into a convincing and rational-sounding story. Alternatively, evidence-based hiring overwhelmingly produces better results ranging from 20% to 50% higher performance and retention.
Let’s not completely ignore our gut
Don’t get me wrong, gut instinct as a biological function has kept us alive and safe. We need to be able to make quick decisions to avoid or escape danger, even before we can back up that instinct with evidence. But when it comes to talent management, impulsivity and bias has no place. It’s time to heed the advice of Tversky who said “the handwriting is on the wall but the ink is invisible.” It’s time to integrate what we are good at as humans with hard data to make the best recruiting, selection, and retention decisions possible.
It’s time to let computers do the heavy lifting
Imagine taking tons of historical data— top performing employees and matching them with factors such as managers, teams, revenues, pay, accidents, injuries and even commute times—and turn that data into a reliable and repeatable “special formula” that predicts with high probability the employees most likely to succeed and stay.
How much more productive would your organization be if you could simply ask the likes of Siri or Alexa:
“Who are the top candidates I should hire?”
And she responds with “Robert would be an excellent fit for your company, he will be 82% engaged after 90 days and won’t show a flight risk for 42 months,” within seconds she continues “Just don’t pair him with Alice, his performance rating would decline to 64%. Pair him with a team managed by Susan and he will perform the best.”
Who wouldn’t want data like that?
The truth is the top 200 companies in the world are already getting data like this with predictive people analytics. They have been going this for a few years now. The good news is you can too, even if you aren’t in the top 200. There have always been people ahead of the curve, and people behind the curve… but predictive people analytics has already begun shifting that curve at a breakneck pace.
Is your company using predictive people analytics?
Please leave a comment below with your thoughts on the future of hiring decisions.