What Industry and Funding Tell Us About Startup Layoffs
Few startups survive the grueling journey that is entrepreneurship. With record number of people filing for unemployment benefits, a difficult journey has become harder for many startups. TechCrunch published an article showing which job functions within startups have seen the most layoffs. This is an incomplete picture. Different cities and regions have been impacted differently by the coronavirus pandemic. This article explores the impact on different regions and industries as the pandemic and lockdown orders evolved.
Industry and region
While California has had significantly fewer COVID-19 cases than New York, more people have been laid off in California. The majority of layoffs have been in travel, transportation, and consumer. For New York, the industries impacted the most appear to be real estate and fitness. The Chicago area is bearing the brunt of layoffs in retail and food.
Layoff timelines
What effect did the lockdown have on layoffs? The following chart shows the cumulative number of layoffs since the lockdown order. Both New York and Texas had a significant number of layoffs prior to locking down on March 22 and April 2, respectively. California announced their lockdown just three days before New York, but startups waited a bit before announcing layoffs. This could be due to the sunny disposition of Californians or the lower case count resulting in more optimism.
Effect of funding
The next chart shows the number of employees laid off given the funding stage of the startup. Most of the startups with layoffs are between Series B through D. There have also been a smaller number of public companies with massive layoff rounds. This plot hints that there may be more pain in later round startups. For seed and Series A, we need to take the data with a grain of salt, as there is less coverage. The current analysis doesn’t include unconfirmed layoff reports, which probably includes many more startups in these rounds.
Finally, does the amount of money raised have any relationship with the scale of a layoff? Larger companies tend to have more employees, so they can cut shallower at first and see how market conditions develop. As the amount of funding decreases, each employee laid off has a larger percentage impact. However, there doesn’t seem to be a clear pattern. This is reasonable, as I expect the primary drivers to be industry and amount of runway for a given startup. This latter measure is idiosyncratic, which is why startups with 60–450 employees appear to be randomly distributed across 5–50% layoffs.
Methodology
Layoff data is from Layoffs.FYI. Each sample may include number of layoffs, percent laid off, and number of employees. Where possible, I imputed missing values based on what was provided. That said, there are a number of missing data points, so the analysis is rather incomplete. As mentioned previously, a separate dataset from Layoffs.FYI compiles unverified layoffs. When I get a chance, I’ll add that to the analysis and see how it impacts the earlier funding stages.
For state-based analysis, I ignored non-US companies. For the funding-based analysis, all companies in the dataset are used.
Lockdown dates come from this repository and was not verified by me.
Brian Lee Yung Rowe is Founder & CEO of Pez.AI, a chatbot startup focused on increasing remote work productivity. He is also CEO of FundKo, a P2P marketplace re-imagining lending with AI and behavioral finance in a covid world.
