Predicting Voluntary Turnover Risk with People Analytics


Sit back, close your eyes, and take a moment to think about your organization. You likely have departments that run more smoothly than others. Some may have more experienced teams, and others may boast more engaged employees overall. There are warning signs of voluntary turnovers, such as few opportunities for development or advancement and below-average pay and benefits. But can you, with any degree of certainty, predict which of those departments, teams, or individual employees are most at risk of high turnover? And even if you can, do you think you would know early enough to make a significant change before the turnover occurs?

Through the use of predictive people analytics, companies can now analyze turnover risk within their organization, before it’s too late.

Low Unemployment Means High Voluntary Turnover Risk
As of November 2019, the U.S. unemployment rate was 3.6% – the lowest it’s been since 1969. That means it’s a job-seeker market with plenty of choices, especially for people with advanced degrees, and as turnover continues to plague in-demand, high-skill industries such as technology (13.2%), financial services (10.8%), and healthcare (9.4%). HR professionals even cited retention and turnover as their top challenges for the third year in a row in a recent Society for Human Resource Management (SHRM)/Workhuman Employee Recognition Survey.

That turnover is inconvenient, sure, but it’s also expensive. According to the SHRM report, the average cost to hire ranges from a little more than $4,400 up to nearly $15,000, depending on the position. While that number includes advertising the role, interviewing, and background checks, it doesn’t include the lost value the previously held position brought to the bottom line and the costs inherent in onboarding and helping a new person settle in.

Also, Deloitte says it takes 94 days to fill an opening for highly skilled positions such as engineers, researchers, and scientists, which is a long time for such a role to sit vacant in today’s fast-paced world of work. So, how do you get ahead of voluntary turnover before it happens?

How People Analytics Can Help
Many organizations do not realize the wealth of data at their fingertips, especially if they engage their people with employee recognition. Once a properly designed and funded peer-to-peer recognition program – in which employees can show gratitude and reward each other for a job well done – has been in effect for six months to a year, it begins to generate enough data to show which employees and departments are connected and engaged at work – and which aren’t. On average, if a person receives seven to 10 recognition awards spread out over 12 months, the likelihood that they will resign from their role is cut in half. Voluntary turnover rates for new hires, who are most likely to leave in the first 90 to 120 days of employment, are cut dramatically when they receive a few awards early in their tenure.

Industrial-organizational psychologists and data scientists can help organizations translate the reach, frequency, and value of this employee recognition and reward programs into tangible business outcomes. By using predictive people analytics in conjunction with the data each program generates, we can see those employee connections and how work is happening in real-time – and use that information to analyze turnover risk within an organization.

Learn More: 5 Steps to Get Started with HR Analytics

One method is to assign each individual employee a score – red, yellow, or green – that correlates to how likely that person is to leave based on their connections and activity within the organization. Leaders and managers can then see where each group falls on the scale. Teams with more “green” employees are happier and less likely to experience voluntary turnover, while teams with more “red” employees are at a higher risk of turnover.

The potential for applying these predictive analytics within organizations is nearly unlimited. In addition to the cost savings, think back to the last time a key employee unexpectedly resigned. You may have felt lost and deserted, or like you were left without a point person. How nice would it be to have the insight you need to make changes before you experience abrupt departures? Wouldn’t it feel good to know you’re creating the type of work environment in which people feel loyal, connected to company values and shared purpose, and at home with their colleagues?

Predictive people analytics paired with skilled data analysis can do that. The savings – on both finance and human level – are enormous.


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