Running Your Business

Employee Turnover Calculations: Can Predictive Technology Save Talent?

  • U.S. Department of Labor data indicates that employees are quitting their jobs at the highest rate in 17 years

  • 85 percent of employees are disengaged at work, costing American businesses $7 trillion annually in lost productivity

  • Machine learning and big data offer the best chance for employers to predict employee turnover

Posted by April 29, 2018

Employee turnover calculations are useful for measuring and predicting how many employees will be around in the immediate future. Combined with machine learning and big data, it’s possible to use such calculations to plan future hiring efforts—that is, if human resource leadership adopts (and makes the best use of) this technology.

Employee Turnover Rate Has Been Rising

Having a strong organization requires a skilled and loyal workforce; something that is becoming rarer in a candidate-driven market. According to the U.S. Department of Labor’s monthly Job Openings and Labor Turnover Survey (JOLTS), December 2017 marked the highest rate of Americans voluntarily leaving jobs for new opportunities in 17 years. With the turnover rate rising, how can an organization stay ahead of the competition and keep good people?

Some human resource leaders see calculating employee turnover as a futile effort. They believe that if an employee is going to quit, he or she will do so no matter what the employer does to prevent it. However, this is not the case.

There are many predictors of an employee who is showing the signs of happiness and security in a job versus those who are disconnected and headed for the door. However, these can be complex and are often difficult to spot until it’s too late.

How Employee Engagement Ties Into Employee Retention

Poor employee engagement is one of the symptoms of an employee retention issue. Gallup research indicates that 85 percent of employees are “not engaged or actively disengaged” in their jobs. This costs businesses $7 trillion in lost revenues annually due to lower than average levels of engagement and productivity. However, many organizations have come to accept this as the “norm” and do not have effective employee engagement programs in place to address this issue.

The Basic Formula for Calculating Employee Turnover

It’s important that employee turnover calculations take place as part of an overall strategy to retain and engage a workforce. The basic mathematics can be helpful, but might not be entirely accurate, as there are many factors that lead to long-term retention.

In order to determine the retention rate, break down the numbers by department or divisional teams. Subtract the number of terminated employees in the last 12 months from the number of employees who have worked for the company for at least one year. This should give you a basic percentage of your retention rate. It will also highlight any obvious trends. For example, maybe one department tends to have a higher turnover rate than others.

Technology and Data Make It Easier to Predict Employee Retention

Thankfully, machine learning systems are increasingly being used to perform employee turnover calculations and predict the likelihood that an employee may quit. When tied into always-on employee engagement software and human resource information systems, this can be a powerful tool for improving the workplace based on actual employee performance and feedback.

Machine learning can monitor certain trends over time, automatically watching for signs of employee disengagement and performance setbacks. For example, an employee may begin arriving late to work on a regular basis and failing to meet deadlines. Machine learning bots can notify human resources that there is a potential problem and an intervention can take place before the employee resigns.

Every opportunity to save a good employee from leaving the organization is worthwhile. The challenge is seeing beyond employee replacement and recruitment efforts and looking internally at what the organization is doing to create an outstanding employee experience. According to Henry G. Jackson, CEO and president of the Society for Human Resource Management (SHRM), “The skills shortage will be an ever-present challenge for employers. Winning at talent today means taking an end-to-end approach to finding, developing and engaging our workforces.”

When human resource leaders fully utilize big data tools and machine learning, the technology can provide a much more accurate way to predict employee turnover—and it enables them to take swift action to reconnect with an employee.

You may also like