Latest Tech Layoff Trends in Three Charts
“Twitter slashes nearly half its workforce.” “Meta lays off more than 11,000.” “Amazon reportedly plans to lay off about 10,000.” The November headlines were full of tech companies announcing layoffs. And only the biggest tech employers made the news; small tech startups trimming already lean staffs were hidden in the deluge.
For some companies, layoffs weren’t triggered by an actual drop in revenue. Rather, the action was akin to when a flight attendant warns passengers to make sure their seatbelts are snug in preparation for possibly bumpy skies ahead. The bumps don’t always emerge, but it’s best to be ready. And venture capitalists have been warning their portfolio companies since mid-year to be prepared to tighten their belts.
One young tech product manager who recently survived a nearly 25 percent cut at her workplace told me that the experience has been “very sad and disheartening.”
“It’s a very different company,” she said. “We’re now trying to be focused on moving forward by rebuilding and restructuring our teams.”
“I guess I’m seeing Silicon Valley history in the making,” she continued. “This was just content we heard about in Econ class, so it’s an interesting time to be living through it all.”
Whether November’s layoff wave represented a peak in workforce slashing or bigger cuts are on the way is yet to be determined. It will be months before we’ll be able to look back with full perspective on this turbulent time for the engineering workforce.
But we can try to get a sense of just how big, proportionally, this current wave of layoffs is and how fast it came on.
There’s not a central layoff reporting database that tracks the numbers, though federal and some state laws require advance notification of mass layoffs in so-called “WARN” notices. So I asked Intellizence, an AI startup that provides market intelligence services for corporate clients, to pull together layoff data for August through November.
Intellizence gathered this data from WARN filings, news reports, and press releases, using AI-based tools to automatically extract key details and remove duplicates. The numbers are those reported or announced at the time and may refer to recent or planned layoffs. When a layoff was reported as a percentage of employees instead of a number, the system attempted to translate it based on publicly available workforce data; this was not always possible. (For Twitter, with the news full of multiple announcements, the data here reflects the widely reported 50 percent workforce reduction.)
So this data, which covers the U.S. and Canada and reflects news from some 160 companies, is not comprehensive, but the sheer change in magnitude of layoff activity is telling.