Who Is Driving The Great Resignation
Who Is Driving The Great Resignation
The U.S. Bureau of Labor has released statistics showing  that about 4 million workers across the United States quit their previous jobs in July 2021. In fact, resignations have been abnormally high for months, reaching their peak in April of last year. Almost 11 million jobs have been lost by the end of the summer. This trend is not only apparent in North America, but has become a global phenomenon.
In this time of crisis, what can employers do to retain their top talent — particularly when faced with what’s now being called ‘The Great Resignation’ or ‘The Great Reshuffle’?
Before we can address the causes behind such staggering labour statistics, we must first understand them. With that in mind, we'll explore the key drivers behind this current shift in the job market.
Mid-Career Workers Are Quitting The Most.
When it comes to resignation rates across different ages, it's become clear that employees who are 30-45 years old have been resigning the most. And this is atypical because turnover is generally the highest among the youngest workers.
However, the number of resignations among 20-25-year-olds have actually decreased in the same period — with the most likely causes being lower demand for entry-level employees and high financial uncertainty.
Interestingly enough, resignations were also lower among people 60-70 years old. So, what are the factors that have caused mid-level employee resignations to skyrocket past other age groups?
First of all, it's quite possible that the worldwide shift to remote work has also made employees wary of hiring people with less experience because there are fewer opportunities for in-person guidance and training. As a result, demand for mid-level candidates has risen — giving these people more leverage when they apply for new positions.
Healthcare And Tech Industries Have The Most Resignations.
Naturally, not all companies have been hit by the pandemic in the same way. In finance and manufacturing, for instance, resignation rates have actually decreased — while they’ve risen in industries like tech and healthcare. In healthcare, burnout and insanely high workloads due to the pandemic have likely caused most of the resignations — while the shift to remote work has provided tech workers with more leverage and job opportunities than ever before, likely causing them to seek greener pastures.
A Data-driven Approach To Retention Is Necessary.
These very specific trends show the vital need for implementing a data-driven approach to tackling the Great Resignation. Data analytics don’t just show us precisely who’s quitting — but also what kind of employees have the highest turnover risk, how resignations can be prevented, and why employees are leaving their companies. While these details are different for every business, there are certain steps companies can take to leverage their data more efficiently in an effort to increase worker retention.
Quantifying The Issue.
Before you can tackle the problems that are causing a turnover at your company, you need to see the scope of the issue and its impact. First, you need to calculate your retention rates using a simple formula:
Number of yearly resignations ÷ number of employees = the yearly turnover rate
Once you have some visibility on your retention problem, you need to see how resignations are affecting your key business metrics. Once a skilled employee leaves a company, the team that remains frequently finds itself lacking crucial resources or skill sets — which negatively affects everything from bottom-line revenue to time-to-completion and the overall quality of work.
Finding The Root Causes.
When you have a firmer grip on the scope of the retention issue, your company needs to go through a detailed data analysis, whose results will be the root causes of your staff leaving. Consider the factors that could be driving your resignation rates upwards. In the process, explore the obvious metrics like training opportunities, time-to-promotion, size of salary increases, average compensations, etc.
Segmenting your employees further into cohorts like function, location, and similar demographics will also show you how retention rates go up and down between different employee populations.
In the end, you’ll know which employees are the likeliest to resign — and what you can do about it through targeted interventions.
Creating Custom Retention Programs.
Now that you have the root causes of your employee retention problem in hand, you can start creating custom-tailored retention programs that tackle the specific problems plaguing your workplace the most.
For instance, if certain minorities are quitting more than their white colleagues, the company probably needs a more DEI-focused approach. Or, if your data analysis has revealed the high resignation rates are correlated with higher times between promotions, revamping your advancement policies is probably necessary.
Particularly in this post-pandemic time, creating a real data-driven retention program is far from easy. However, investing in the effort right now will yield tangible results fairly quickly. Even when faced with fiercely competitive offers from other employers, your workers will think twice about leaving the company once they see things improving. In the end, you will likely have a more effective, engaged, and loyal workforce.
In todays’ employee market where the power is in the hands of those skilled workers who are seeking new employment, it is more important than ever for employers to do two things right: 1) engage your people and create a sense of belonging, so they don’t want to leave and take all their knowledge with them, and 2) get new hires up to speed as soon as possible to ensure business continuation and productivity.
As an employee experience platform, Qualee can help companies of all sizes to drive continuous engagement, gather actionable insights, and curate exciting journeys, with the ultimate goal of maximising organisational alignment and belonging throughout the employee lifecycle. Sign up for a Starter Plan today!