The Great Tech Deflation
How the tech industry could suffer massive layoffs
In 2018, I worked for a company called Storyblocks as SVP of Product and Engineering. I helped grow our company from 10 employees to just over 100, and $10m of revenue to $30m+ over the course of 5 years. So it sounded like a success on paper (and it was…the company exited for close to $100m a couple years later). However, we plateaued. We were the number one subscription-based stock media site and yet our growth slowed substantially once we hit $30m of revenue (we’d run out of new products to launch). We had the possibility to generate large profits of $5–10m per year on that $30m revenue number. We were in the classic “cash cow” quadrant of the BCG growth share matrix.
To generate those profits, however, we needed to lay off about half the company. And we totally could have done it without impacting the top line much. Fast forward 4–5 years and Storyblocks suffered two massive layoffs, proving my point from 2018.
The Tyranny of the S-curve
To understand how this applies to the tech industry, we need to understand the S-curve phenomenon.
Almost all successful products and services go through a typical S-curve growth cycle. Initially, the product is rolled out to early adopters. Then it starts to take off and has a period of “hocky stick” growth. And then the growth tapers off. This is almost a law of nature. iPhone is one of the most successful products of all time but even it has run into the S-curve phenomenon.
So how do companies keep growing over time if the S-curve dynamic ultimately wins? The answer so far has been by stacking products and S-curves. Apple launches the iPod, then the iPhone, then the iPad, then the iWatch and so on. Amazon launches for books, then an expanded product line, then Amazon Web Services, etc.
What happens when companies run out of natural adjacencies to launch new S-curves? Simple: the successful ones try to take over other companies’ S-curves. Google launches YouTube.tv to compete with the typical TV offerings. Amazon offers its Prime Video to compete with Netflix and Disney+. Microsoft offers Azure to compete with Amazon Web Services. And so on.
What happens when companies run out of competitive S-curves to take over? They can try to go after new markets like Meta is with its Metaverse/VR/AR play but that can be super expensive (Meta is losing more than $10B dollars per year on this bet).
Very few technology S-curves remain
Data suggests that there are very few technology S-curves that remain. Let’s look to the startup world for a moment, specifically the amount of Series A funding over time.
As you can see, the size of Series A funding for startups has more than tripled in the last 10 years, from ~$6m in 2012 to ~$19m in 2021. That strongly suggests that the low hanging fruit for S-curves has been picked. Going after the same type of opportunities requires three times as much capital today as it did 10 years ago.
And then there are the high profile examples of potential S-curves:
- Metaverse/AR/VR: capital expenditures of $10B+ per year by Meta to get a potential S-curve off the ground (though it’s far from certain that it will succeed)
- Self-driving cars: capital expenditures of over $10–20B to date. Full self-driving capabilities, despite Tesla’s so-named functionality, still remain elusive.
- Interplanetary space travel: the idea that humans should travel to other planets has been around since the beginning of the space age in the 1950s. So far humanity has invested $10B’s in making space travel happen and yet we still don’t have interplanetary travel (though we’ll see what happens with SpaceX).
- Generative AI: capital expenditures of $100m’s per year to build, train, and operate models. While super successful from a consumer adoption perspective, the business value around generative AI has yet to be proven.
All of these cost a ridiculous amount of money to get off the ground compared to startups a generation ago. So it’s showing both in startup data and in the high profile investments made by large tech companies that products on new S-curves are becoming increasingly fewer and harder to launch.
No more S-curves, so what?
So what happens if there are no more (or at least very few) S-curves? A few things:
- Big tech companies become cash cows, with lower growth but high profitability
- Medium-size tech companies still riding on venture funding are at risk of dying out unless they cut costs
- Startups chasing ever more elusive and expensive S-curves face an extinction-level event
All three of these forces will lead to an implosion in the tech job market. Why? I like to use an analogy between building a house and plumbers and building tech products and software engineers. When you’re building the house, you need plumbers to lay the initial piping. It’s a good amount of work. However once the house is built, you only need to call a plumber once or twice a year to fix up a leak. It’s very similar with tech products. The initial build can be fairly expensive but once a product is built, it’s generally pretty cheap to just keep the lights on. Historically tech companies have reinvested their software engineers to build ever-increasingly less important features (think S-curve plateau) but at some point they’re going to realize what’s happening and just have a few engineers stick around to keep the lights on. And thus a massive layoff of tech talent because there aren’t more S-curves to chase.
The layoffs have started
We’ve already had a good number of layoffs. In the past year: Meta laid off 10k+ employees; Amazon laid off almost 30k employees; Google laid off 10k+ employees. Disney laid off 5k+ employees. And so on. See this TechCrunch article for more details. Also, see the chart below from layoffs.fyi:
Let’s look at hiring patterns of the big tech companies over the past few years (source for Meta).
Does this additional headcount drive comiserate bottom line results? Unlikely. Most of the main products offered by these companies have change relatively little in the past 4 years. Elon Musk proved that Twitter (now X) was substantially overstaffed by laying off >50% of it’s work force and having operations remain more or less unchanged. To quote Musk, Twitter had “a lot of people doing things that didn’t seem to have a lot of value.” Furthermore, he went on to say “I think that’s true probably at most Silicon Valley companies, maybe not to the degree to which it was at Twitter.” So Musk also thinks many tech companies are overstaffed.
When will the mass layoffs happen? Hard to know. After all the market can stay irrational longer than you can stay solvent as they say. Perhaps they will start happening in 2024/2025. Or perhaps the pain is stretched over the next decade. But at some point the tyranny of the S-curve will rule the tech industry.
