How to Predict and Prevent Employee Turnover

What would you do if you could predict how key milestones along the employee experience would play out? How would seeing the future help your human resources team, and your business overall, perform better?

The employee experience starts from candidacy, into onboarding, development, engagement, and inevitably, exit. No matter how great an employee’s experience from the time they start, people will leave your company for one reason or another at some point.

Predictive analytics, a capability available in the Culture Amp platform, can now tell you which employees are most at risk of leaving, and more importantly, the reasons why, so you can take immediate action to improve employee retention. This, along with data from other employee surveys, can help you transform the employee experience for better.

Forecasting and reducing employee turnover

It’s likely that you have many data points already to help you identify who’s likely to leave your company. For example, answers to the employee engagement survey question “I see myself at [company] in two years time” can tell you whether people intend to stay or might have one foot out the door.  

What predictive analytics allows you to do is locate the subtler signals – like shifting patterns over several engagement surveys – that act together in a more sophisticated way. These patterns indicate whether people may leave and why. Culture Amp’s proprietary algorithm takes into account a range of obvious and subtle signals to sense turnover risks.

This forecasted prediction is two-fold:

  1. Which groups are most likely to leave
  2. What to focus on in order to keep them

If you can predict people problems, like your finance department all being on the brink of a walkout, you can prevent business problems, like being left high and dry without vital employees.

Predictive analytics for all companies

Predicting things like employee turnover was once a capability reserved for big enterprises. Those companies with the budget to pay consultants to conduct analysis. However, even withing this pay-to-play model, those companies would only get insights for the time of their contract with a consultant.

Alternatively, companies would hire in-house people analytics and data science teams who could perform these analyses over time. Without this support, most other companies were left in the dark when it came to making predictions about employee turnover.

At Culture Amp, we’re bringing predictive analytics to all companies, no matter their size, or industry. Our dataset leverages the collective intelligence of thousands of companies and over 3 million individual employees. Previously even in-house teams and consultants wouldn’t have had access to a dataset of that size.

Transform the employee experience

Rather than racing to keep your best people onboard, predictive analytics helps you know specifically which groups are at greatest risk. You’ll be empowered to focus your efforts and initiatives where it matters – keeping your best employees engaged and extending their tenure.

Want to learn more about going beyond insight and bringing foresight to your people analytics? Get in touch.

 

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Jason McPherson

Jason McPherson

Dr. Jason McPherson is Culture Amp's Chief Scientist. His PhD in Psychology focused on developing computer-game-like cognitive ability tests. Combining psychology, technology, and data science, he works with some of Culture Amp's most innovative customers to create products aimed at educating and empowering people geeks.

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