Is There a Force Behind the Great Resignation?
Updated: Dec 26, 2022
People have been quitting jobs all throughout the world in recent months. Many call this "the Great Resignation." Businesses may try everything possible to stop this. When Ian Cook finished his research, almost 9 million people worked in 4,000 companies globally. He wrote an HBR post on some of the most important findings. He also devised a three-step plan for businesses to help them.
It predicts that by July 2021, 4 million Americans will be jobless. In July, there were more open jobs than ever. They peaked in April. Many people are departing from employment at the same time, so employers must discover ways to keep them.
To understand why these stats are so high, one must first analyze them. My colleagues and I analyzed over 9 million employee records from over 4,000 companies to figure out who was behind this new move. This global dataset includes individuals from a wide range of industries, professions, and experience levels. Two important themes emerged:
1. The majority of employees who resign are in the middle of their careers
Between 2020 and 2021, the number of employees aged 30 to 45 who quit increased by nearly 20%. Despite the fact that younger employees have had the highest turnover in the past, our study reveals that resignations among those aged 20 to 25 have decreased (likely due to a combination of their greater financial uncertainty and reduced demand for entry-level workers).
Those aged 60 to 70 resigned at a lower rate than in 2020, whereas those aged 25 to 30 and 45 and up resigned at a somewhat greater rate than in 2020. (However, growth in the 30-45 age range was not as fast.)
The large frequency of mid-level employee resignations may be attributed to a variety of factors. For starters, the shift to remote work may have made firms wary of hiring new employees with little experience since they won't be able to get in-person training and mentoring. This would enhance demand for mid-career workers, giving them more bargaining power when seeking new positions.
Many of these mid-level workers are also likely to have put off quitting their positions owing to the outbreak's uncertainty, culminating in a sudden wave of resignations.
Many of these individuals have had to reassess their career and personal objectives due to heavy workloads, hiring limitations, and other constraints.
2. Most resignations were in the IT and healthcare industries
We also identified considerable differences in turnover rates across businesses in different industries. While resignations in certain industries, such as manufacturing and finance, have decreased somewhat, healthcare professionals have left their jobs 3.6 percent more than the previous year, and technology resignations have increased by 4.5 percent.
Employees in industries that saw large increases in demand as a consequence of the pandemic resigned at higher rates, perhaps due to increased workloads and exhaustion.
Employers must use a data-driven approach to improve retention.
These trends highlight the need of analyzing data to establish not just how many workers are leaving, but who is at the greatest danger of leaving, why they are leaving, and what can be done to prevent it.
Although the circumstances of each company differ, there are three steps that may help any company better use data to increase employee retention:
1. Establish a numerical value for the issue
It's vital to evaluate both the breadth of the issue and its effect before you can figure out what's causing your company's employee turnover. To begin, use the formula below to figure out your retention rate:
Turnover Rate = Number of Employees Separated Per Year x Average Total Employees
Similar formulae may be used to figure out how much of your turnover is due to voluntary resignations rather than layoffs or firings. This will assist you in determining the source of your retention issue.
After that, figure out how resignations affect critical company KPIs. When individuals leave a company, the surviving teams are often left without crucial talents or resources, which has a detrimental effect on everything from job quality and completion time to bottom-line income. To acquire a whole picture of the costs of resignations, it's critical to analyze how increasing turnover corresponds to changes in other key variables.
For example, a trucking firm with which I worked discovered that what looked to be a little increase in turnover owing to a statewide driver shortage was really costing them millions in recruiting and training resources. Quantifying the issue aided leaders in gaining the required internal buy-in to solve it as well as making educated judgments about the most successful retention measures.
2. Figure out what's causing the issue in the first place.
It's time to do a deep data analysis to establish what's truly driving your employees to quit after you've recognized the magnitude of your retention issue. Consider what reasons may be causing increased rates of resignation.
Metrics like remuneration, duration between promotions, pay raise size, tenure, performance, and training opportunities may help you uncover patterns and blind spots in your company. To better understand how work experiences and retention rates change across different employee groups, you may divide workers by categories like geography, function, and other demographics.
This study may help you determine not only which workers are most likely to quit, but also which staff can be kept with focused interventions. The trucking firm, for example, discovered that drivers with less experience and a remote supervisor were considerably more likely to leave than those with more experience and in-person assistance.
3. Create customized employee retention initiatives.
You may start creating highly personalised programs geared at resolving the exact difficulties that your business deals with now that you've discovered the fundamental reasons of turnover. If you notice that individuals of color are departing your company at a greater rate than their white counterparts, a DEI-focused strategy may be necessary. If you see a significant link between time between promotions and high resignation rates, it may be time to reconsider your progression practices.
Importantly, you may realize throughout this process that you are unable to make these kind of data-driven choices due to a lack of appropriate data infrastructure. Investing in an organized, user-friendly system for recording and evaluating the data that will guide your employee retention efforts is one higher-level intervention that may be required before you can launch any type of focused marketing.
It's not simple to implement a really data-driven retention plan, but it's well worth the effort, particularly in this market. Despite heavy competition from other employers, the trucking firm I worked with experienced a 10% drop in driver resignations after adopting a focused retention campaign based on a careful study of key variables. You'll be able to recruit top people, cut turnover expenses, and ultimately establish a more engaged and productive staff with improved insight into both how severe your turnover issue is and the core factors that drive it.