How to predict and prevent employee turnover

Calculating the cost of employee turnover
Everyone agrees that turnover is expensive, but the exact cost is widely debated, falling anywhere between 30%–200% of an employee’s salary. Plus, it can be hard to put an exact number on the impact that turnover can have on employee morale and productivity.

Here at Culture Amp, we have access to a dataset that leverages the collective intelligence of thousands of companies. This means that companies of all sizes—whether you’re an early-stage startup or a large enterprise—can now better understand which factors contribute to employee turnover, anticipate which groups have a high likelihood of leaving, and course correct before it’s too late. Since our data provides insights into which employees are likely to leave according to department, gender, age, and tenure, you may be able to more accurately calculate the anticipated cost of turnover in the near future.

The real reasons people leave
At Culture Amp, we’ve been collecting employee data since 2011 and we have insights from millions of people from the moment they join an organization through to the time they leave. Here’s what our data has taught us about the real reasons people leave an organization.

Lack of belonging

A sense of belonging is crucial for people when they join a company. People who had an early sense that they didn’t belong were three times more likely to leave within the first six months.

Lack of confidence in company leadership

Despite the common myth that people leave managers and not companies, we continue to find in our data that although some people leave because of a manager, they are much more likely to leave because they don’t have confidence in the overall leadership of the company.

Bad first impressions

We’re seeing a growing number of people making decisions about leaving companies early in their tenure. In recent Culture Amp research, we found that around 10% of people were leaving within six months of starting a new job—and many were making the decision to leave within their first six weeks.

Forecasting and reducing employee turnover
At this point, you may be wondering what you can do to keep your employees happy and extend their tenure. We know that waiting for people to resign and chasing them out the door with a better offer doesn’t work—at least not for long. Smart practitioners have always flagged turnover risks, but many haven’t known what to do to avoid regrettable turnover. Instead, they’ve invested in succession planning (or hoping for the best).

While many employee engagement metrics have traditionally told you what happened in the past, there’s now an opportunity to predict what might happen next. Culture Amp’s predictive analytics uses machine learning to identify the people who are likely to leave in the future—and why they’ll leave. Our platform brings together metrics from employee engagement, turnover forecast, manager effectiveness, and diversity & inclusion. We highlight the groups of employees with the highest risk of turnover and our algorithms suggest ways you can intelligently solve these challenges.

Knowing what’s driving turnover empowers you to make critical changes in your organization. Rather than making last-ditch efforts to retain employees who have already made the decision to leave, you can focus on efforts and initiatives that will keep employees engaged and extend their tenure.

Source: https://www.hrdive.com/news/how-to-predict-and-prevent-employee-turnover/553491/

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