Who Is Driving the Great Resignation?

According to the U.S. Bureau of Labor Statistics, 4 million Americans quit their jobs in July 2021. Resignations peaked in April and have remained abnormally high for the last several months, with a record-breaking 10.9 million open jobs at the end of July. How can employers retain people in the face of this tidal wave of resignations?

Addressing the root causes of these staggering statistics starts with better understanding them. To explore exactly who has been driving this recent shift, my team and I conducted an in-depth analysis of more than 9 million employee records from more than 4,000 companies. This global dataset included employees from a wide variety of industries, functions, and levels of experience, and it revealed two key trends:

1. Resignation rates are highest among mid-career employees.

Employees between 30 and 45 years old have had the greatest increase in resignation rates, with an average increase of more than 20% between 2020 and 2021. While turnover is typically highest among younger employees, our study found that over the last year, resignations actually decreased for workers in the 20 to 25 age range (likely due to a combination of their greater financial uncertainty and reduced demand for entry-level workers). Interestingly, resignation rates also fell for those in the 60 to 70 age group, while employees in the 25 to 30 and 45+ age groups experienced slightly higher resignation rates than in 2020 (but not as significant an increase as that of the 30-45 group).

There are a few factors that can help to explain why the increase in resignations has been largely driven by these mid-level employees. First, it’s possible that the shift to remote work has led employers to feel that hiring people with little experience would be riskier than usual, since new employees won’t have the benefit of in-person training and guidance. This would create greater demand for mid-career employees, thus giving them greater leverage in securing new positions.

It’s also possible that many of these mid-level employees may have delayed transitioning out of their roles due to the uncertainty caused by the pandemic, meaning that the boost we’ve seen over the last several months could be the result of more than a year’s worth of pent-up resignations.

And of course, many of these workers may have simply reached a breaking point after months and months of high workloads, hiring freezes, and other pressures, causing them to rethink their work and life goals.

2. Resignations are highest in the tech and health care industries.

We also identified dramatic differences in turnover rates between companies in different industries. While resignations actually decreased slightly in industries such as manufacturing and finance, 3.6% more health care employees quit their jobs than in the previous year, and in tech, resignations increased by 4.5%. In general, we found that resignation rates were higher among employees who worked in fields that had experienced extreme increases in demand due to the pandemic, likely leading to increased workloads and burnout.

Employers Must Take a Data-Driven Approach to Improving Retention

These trends highlight the importance of taking a data-driven approach to determining not just how many people are quitting, but who exactly has the highest turnover risk, why people are leaving, and what can be done to prevent it. The details will look different in every organization, but there are three steps that can help any employer more effectively leverage data to improve employee retention:

1. Quantify the problem.

Before you can determine the underlying causes of turnover at your organization, it’s critical to quantify both the scope of the problem and its impact. First, calculate your retention rate using the following formula:

Number of Separations per Year ÷ Average Total Number of Employees=Turnover Rate

You can use similar formulas to identify how much of your turnover is coming from voluntary resignations, versus from layoffs or firings. This will help you gain visibility around exactly where your retention problem is coming from.

Next, determine the impact of resignations on key business metrics. When employees leave an organization, remaining teams often find themselves without key skillsets or resources, negatively impacting everything from quality of work and time-to-completion to bottom-line revenue. It’s important to track how increased turnover correlates with changes in other relevant metrics in order to get a full picture of the costs of resignations.

For example, a trucking company I worked with identified that what appeared to be a small increase in turnover due to a nationwide driver shortage was in fact costing them millions of dollars in hiring and training resources. Quantifying the problem both helped leaders get the internal buy-in necessary to address it, and informed decisions around what kind of retention interventions would be most effective.

2. Identify the root causes.

Once you’ve identified the scope of your retention problem, it’s time to conduct a detailed data analysis to determine what’s really causing your staff to leave. Ask yourself which factors could be driving higher resignation rates? Exploring metrics such as compensation, time between promotions, size of pay increases, tenure, performance, and training opportunities can help to identify trends and blind spots within your organization. You can also segment employees by categories such as location, function, and other demographics to better understand how work experiences and retention rates differ across distinct employee populations.

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This analysis can help you identify not just which employees have the highest risk of resigning, but also which of these employees can likely be retained with targeted interventions. For example, after extensive analysis, the trucking company found that drivers who had less experience and a remote supervisor were much more likely to resign than more-experienced drivers and those receiving in-person support.

3. Develop tailored retention programs.

Now that you’ve identified the root causes of turnover at your organization, you can begin to create highly customized programs aimed at correcting the specific issues that your workplace struggles with most. For example, if you discover that people of color are leaving your organization at a higher rate than their white peers, a DEI-focused approach may be called for. If you find that time between promotions correlates strongly with high resignation rates, it may be time to rethink your advancement policies.

Importantly, you may discover through this process that a lack of effective data infrastructure is hampering your ability to make these sorts of data-driven decisions. One higher-level intervention that may be necessary before you can begin any sort of targeted campaign is to invest in an organized, user-friendly system for tracking and analyzing the metrics that will inform your retention efforts.

Adopting a truly data-driven retention strategy isn’t easy, but it’s worth the effort to do it right, especially in the current market. After implementing a targeted retention campaign based on a detailed analysis of key metrics, the trucking company I worked with saw a 10% reduction in driver resignations, even in the face of fierce competition from other employers. With greater visibility into both how serious your turnover problem really is, and the root causes that drive it, you’ll be empowered to attract top talent, reduce turnover costs, and ultimately build a more engaged and effective workforce.