Desperately Searching for Scale
By Capital Thinking · Issue #836 · View online
The topic du jour in tech right now is the sudden reappraisal of some high-flying startups based on unit economics / gross margins (e.g. WeWork, Uber, Lyft, DoorDash, Postmates, etc).
How did we get here?
The truth is that software startups never had to worry about gross margins until software started eating the world. Gross margins only became a concern once software blended with physical-world products and services to create new tech-enabled business models.
The Gross Margin Problem
Historically, pure software businesses had perfect gross margins. All the major expense was in creating the first copy; subsequent copies were virtually free. The realization that he could sell cheap mass-market software and make it up in volume made Bill Gates the richest man in the world.
When software moved to the cloud, this dynamic didn’t change. Almost all of the production cost is in creating the product for the first user. Aside from hosting, it is almost free (on an incremental basis) to provision additional users. If anything, the cloud perfected the software business model by making revenue recurring.
As a result, early-stage software startups never needed to have much proficiency in cost accounting. They didn’t really need to know which expenses were overhead versus COGS. They just needed to know their burn and runway.
Similarly, software companies didn’t need to be world-class at driving operational efficiency. There just weren’t that many unit costs to optimize.
And the enormous operating leverage allowed the most successful software companies to be quite lavish in their spending. Hence the Google chefs, Kind bars, and Disneyland-style campuses. Margins were still amazing.
But when software started eating the world, everything changed. Software was just one component of the service being offered. Software might be the disruptive element but it wasn’t the source of unit economics. These new “tech-enabled” businesses had major COGS (e.g. leases at WeWork; drivers at Uber).
The new tech-enabled startups had cost structures more similar to the companies they were disrupting (e.g. commercial landlords; the taxicab industry) but they still thought like software companies. Good for innovation, bad for operational efficiency.
Although growth solves many problems at startups, unit economics is not one of them. When you’re losing money on every transaction, you can’t make it up in volume. In fact, the more revenue that a businesses with negative unit economics generates, the more money it loses.
Growth solves many problems at startups, unit economics is not one of them.
As a result, there is now a painful readjustment happening as many of these companies try to fix unit economics and bring their cost structures in line.
Valuations are similarly being reappraised as investors see through top-line growth that was achieved at the expense of negative unit economics.
So what are the lessons if you’re a tech-enabled startup — one whose product has a meaningful physical-world component?
1) First, you’re going to need a proficiency in cost attribution from the beginning. You’ll need to know your unit costs at a much more detailed level than a typical SaaS startup (which doesn’t have meaningful COGS).
Attribution can be harder than it sounds in the early days of a startup when the finance function is immature. COGS are not typically purchased in units; they’re often bought in larger chunks and unitized based on assumptions that must be verified.
Which costs are one-time and which are ongoing, which are temporarily inflated and which can be brought down with scale, are important to understand. Insights about improvements must be operationalized and measured in a continuous feedback loop.
2) Second, you’re going to have to pay a lot more attention to pricing. In a typical SaaS startup, the goal is just to get over the “penny gap” — prove that there is willingness to pay for the new product and then increase pricing over time.
Tech-enabled startups can’t quite do that because product-market fit based on an artificially low price point could be an illusion. This is the old problem of selling dollar bills for 90 cents — you will appear to have a thriving business. Raise the price to $1.10 and you will see that you have no business.
Photo credit: Danil Shostak on Unsplash