The first time I wrote about Uber was in June, 2014. The Wall Street Journal had posted a column entitled Uber’s $18.2B Valuation is a Head Scratcher , which led to an easy rejoinder: Why Uber is Worth $18.2 Billion . Given that Uber is today worth $53.2 billion on the open market, that one turned out pretty well.

A month later I felt even better about my piece when Bill Gurley, the legendary venture capitalist, wrote his own rebuttal of an Uber skeptic . Gurley was gentle in his takedown of NYU Stern professor Aswath Damodaran, writing in the introduction:

It is not my aim to specifically convince anyone that Uber is worth any specific valuation. What Professor Damodaran thinks, or what anyone who is not a buyer or seller of stocks thinks, is fairly immaterial. I am also not out to prove him wrong. I am much more interested in the subject of critical reasoning and predictions, and how certain assumptions can lead to gravely different outcomes. As such, my goal is to offer a plausible argument that the core assumptions used in Damodaran’s analysis may be off by a factor of 25 times, perhaps even more. And I hope the analysis is judged on whether the arguments I make are reasonable and feasible.

Gurley’s arguments, which focused on Damodaran’s assumptions around Uber’s total addressable market ($100 billion, the same as taxis) and terminal market share (10%) were clearly correct: Uber is already at a $50+ billion gross bookings run rate, and has around 70% of the market. Damodaran’s assumptions, rooted in the analog world, were sorely mistaken.

At the same time, while Gurley didn’t make any specific assertions about Uber’s valuation, surely he must have expected it would have increased by more than 192% in the following five years; I certainly did. To be sure, there were rather significant intervening events, specifically Uber’s disastrous 2017 , where the company endured seemingly endless scandals, lost its CEO, and worst of all, gave life to Lyft, its most important competitor which, at the beginning of that year, was on the verge of going out of business. It is very fair to argue that Uber without an at-scale competitor is a much more valuable company.

That noted, this line from Gurley’s article stands out to me today more than ever:

I am much more interested in the subject of critical reasoning and predictions, and how certain assumptions can lead to gravely different outcomes.

Just because Uber’s critics were wrong to assume that the service was analogous to taxis does not mean that those of us on the other side — not only of the Uber question but of a host of other similar companies that straddle the physical and digital worlds — were completely right in our assumptions either. The opposite of an old-world company is not necessarily a tech company. It is something we haven’t quite seen before, and applying either old-world rules or tech rules is a mistake.

AB 5 and Worker Classification

This idea of the old classifications not quite making sense, and the need for something new, should feel quite familiar in the context of Uber: it is precisely the issue surrounding Uber’s drivers.

Earlier this month California passed AB 5 , which codified a California Supreme Court decision setting forward a three-part test to determine whether or not a worker is an independent contractor or an employee (with all of the attendant regulation and taxes that go along with that classification). From the decision :

Under this test, a worker is properly considered an independent contractor to whom a wage order does not apply only if the hiring entity establishes: (A) that the worker is free from the control and direction of the hirer in connection with the performance of the work, both under the contract for the performance of such work and in fact; (B) that the worker performs work that is outside the usual course of the hiring entity’s business; and (C) that the worker is customarily engaged in an independently established trade, occupation, or business of the same nature as the work performed for the hiring entity.

The question as to whether the new law applies is closer than it seems: on one hand, Uber et al 1 really do give drivers, who use their own equipment, flexibility as far as hours go, and while there are rules to be followed while on the job, it is the former that is usually the more important standard. Plus drivers famously drive for multiple companies; the need to compete for their presence on the platform (more on this in a bit) is one of the big reasons why Uber is so unprofitable.

That means that (B) is the question: if Uber is in the transportation business, then drivers are workers; Uber, though claims its business “is serving as a technology platform for several different types of digital marketplaces.” As I wrote in a Daily Update :

It’s not an entirely irrational argument. For example, consider the rate: Uber’s point is that not that it sets the rate, but rather the rate is the market-clearing price that maximizes the amount of revenue drivers earn. The idea is that if drivers could set their own prices — a common objection to drivers being independent contractors is that they cannot — a negotiation would occur between customers and drivers until a price was agreed upon; over time this price would be equalized across drivers and riders. Uber’s argument is that it dramatically accelerates this process and in fact makes the market possible, since the level of coordination necessary to reach a market-clearing price at scale would be impossible otherwise.

At the same time, this sort of argument, technically correct from an economic modeling perspective, suffers from the same flaws as most economic models: the lack of any sort of accounting for the human component. In this case the missing bit, though, is not in the model’s outcome, but rather in the manifestation: the way that Uber is experienced by riders and especially riders is that “Drivers are the face of Uber to consumers” (that quote is from Uber’s S-1 , by the way). Drivers are also indispensable to how Uber actually generates revenue: sure, drivers can and do come and go as they please, and work simultaneously for Uber’s competitors, but to suggest they are a not a part of the “usual course” of Uber’s business seems off.

That is why the best solution to the employment classification question is to realize that neither of the old categorizations fit: Uber drivers are not employees, nor are they contractors; they are neither, and new. A much better law would define this category in a new way that provides the protections and revenue-collection apparatus that California deems necessary while still preserving the flexibility and market-driven scalability that make these consumer welfare-generating platforms possible.

What is Uber?

So what of Uber itself? It is not a taxi company, as noted above, but is it a tech company? I suggested it was a few weeks ago in What Is a Tech Company? :

Uber…checks most of the same boxes:

• There is a software-created ecosystem of drivers and riders.
• Like Airbnb, Uber reports its revenue as if it has low marginal costs, but a holistic view of rides shows that the company pays drivers around 80 percent of total revenue; this isn’t a world of zero marginal costs.
• Uber’s platform improves over time.
• Uber is able to serve the entire world, giving it maximum leverage.
• Uber can transact with anyone with a self-serve model.

A major question about Uber concerns transaction costs: bringing and keeping drivers on the platform is very expensive. This doesn’t mean that Uber isn’t a tech company, but it does underscore the degree to which its model is dependent on factors that don’t have zero costs attached to them.

In fact, I’ve changed my mind: I was right to mention Uber’s costs, and wrong to dismiss them and call Uber a tech company. At the same time, Uber clearly has no analog in the physical world. It is neither, and new — and Uber’s drivers help explain why.

That magical marketplace I described above, where Uber effectively simulates countless one-on-one negotiations between drivers and riders that, on an infinite timescale and with infinite patience, would arrive at the market-clearing price, is very much a technological product. This marketplace leverages today’s paradigm-shifting technologies — smartphones and cloud computing — and is itself software, and thus infinitely leverageable and always improving.

Uber’s financials reflect this: last quarter the company had a gross margin of 51%. That is a fair bit lower than a typical SaaS company’s 70%+ gross margins, but that is primarily because the company’s cost of revenue includes insurance, which scales linearly with revenue. The software behind Uber’s marketplaces scales perfectly.

The problem, though, is that Uber’s financials are an incomplete view on the overall Uber experience, because riders don’t simply pay Uber: they also pay the drivers. And, if you look at Uber’s financials from a rider perspective, 2 the situation looks a lot worse; consider last quarter:

Suddenly that gross margin looks nothing like a software company — and keep in mind this is all Uber has to work with before it gets to its fixed costs. 3 The only way this company works is if it grows to a truly mammoth size such that it has sufficient gross margin to cover fixed costs, but it is that much more difficult to acquire a marginal new customer when you simply don’t have that much margin to play with; spending on sales and marketing simply increases the hill you need to climb!

None of this is to say that Uber is not a viable business: all of Gurley’s arguments about the total addressable market and Uber’s ability to dominate that market still apply, because of technology. Uber is not a taxi company! At the same time, a different sort of valuation metric than that usually applied to tech companies was clearly appropriate as well, as Uber’s adventures on the public market demonstrate. In short, the company was neither, and new.

The Uber Anomaly

The corresponding article to What Is a Tech Company? could very well be What Is a Venture Capital Firm? . If tech companies are characterized by zero marginal costs, increased returns to scale, and ecosystems, venture capital firms match with equity financing (which means capped downside and infinite upside), a Babe Ruth portfolio management approach that focuses on home runs despite the increase in strikeouts, and a focus on iterated games when it comes to exerting power.

That last point is worth dwelling on; in 2017 I described why an iterated game approach mattered for venture capitalists in the context of — you guessed it! — Uber. That was when Gurley’s Benchmark, then Uber’s largest investor, first forced out and then sued Uber’s former CEO Travis Kalanick.

A venture capitalist will invest in tens if not hundreds of companies over their career, while most founders will only ever start one company; that means that for the venture capitalist investing is an iterated game. Sure, there may be short-term gain in screwing over a founder or bailing on a floundering company, but it simply is not worth it in the long-run: word will spread, and a venture capitalists’ deal flow is only as good as their reputation…

The entire point of venture investing is to hit grand slams, and that calls for more swings of the bat. After all, the most a venture capitalist might lose on a deal — beyond time and opportunity cost, of course — is however much they invested; the downside is capped. Potential returns, though, can be many multiples of that investment. That is why, particularly as capital has flooded the Valley over the last decade, preserving the chance to make grand slam investments has been paramount. No venture capitalist wants to repeat Sequoia’s mistake: better to be “nice”, or, as they say in the Valley, “founder friendly.”

Uber, though, was different:

Uber’s most recent valuation of $68.5 billion nearly matches the worth of every successful Benchmark-funded startup since 2007. Sure, it might make sense to treat company X and founder Y with deference; after all, there are other fish in the pond. Uber, though, is not another fish: it is the catch of a lifetime.

That almost assuredly changed Benchmark’s internal calculus when it came to filing this lawsuit. Does it give the firm a bad reputation, potentially keeping it out of the next Facebook? Unquestionably. The sheer size of Uber though, and the potential return it represents, means that Benchmark is no longer playing an iterated game. The point now is not to get access to the next Facebook: it is to ensure the firm captures its share of the current one.

As I’ve noted, that valuation proved to be faulty; at the same time, $53.2 billion is still a huge amount of money, and probably wouldn’t have changed Benchmark’s calculation. The real takeaway, though, is that Uber was not a typical Silicon Valley startup. No, they weren’t a taxi company, but they weren’t a tech company either, they were something new, and that meant a new kind of investor. Enter SoftBank.

Vision Fund

Masayoshi Son, Softbank’s CEO and the driving force behind Vision Fund, told Bloomberg a year ago that he wanted to “go big bang”:

SoftBank’s massive bet in WeWork is emblematic of Son’s overall approach. “Why don’t we go big bang?” he told Bloomberg in an interview last year when asked about his investing style, and added that other venture capitalists tend to think too small. His goal of swaying the course of history by backing potentially world-changing companies requires that those companies make large outlays in areas from customer acquisition to hiring talent to research and development, a spending tactic that he acknowledged sometimes brings him into conflict with other investors.

“The other shareholders, they try to create clean, polished little companies,” Son said. “And I say: ‘Let’s go rough. We don’t need to polish. We don’t need efficiency right now. Let’s make a big fight. Let’s make a big, successful—a big win.’”

In fact, the “other shareholders” that Son derides are trying to create tech companies: up-front fixed costs to develop software, with high gross margins once it is sold. These are the companies that require investors that have all of the qualities I detailed above: a desire for equity, a willingness to risk strikeouts while swinging for home runs, and the decency that comes from playing an iterated game.

Vision Fund is none of these things. It doesn’t just want equity, it wants preferred equity with a ratchet, to guarantee they get theirs first. Moreover, it seeks to not only invest in winners, but also to leverage its capital to make winners, by forcing competing companies to merge. And, because of this, Vision Fund is very much not playing an iterative game: it will do whatever it takes to win the markets it invests in, including deposing of founders who become a liability.

The problem, though, is Vision Fund may have confused “big capital needs” with “big opportunity”. What is striking about the firm’s portfolio is the paucity of “tech companies”. Almost everything falls in the “Neither and New” category defined by Uber: entire categories like real estate and logistics are defined by their interaction with the physical world, almost everything in the consumer category uses technology to enable real-world services, and the other major category, fintech, by definition needs huge amounts of capital. Most of these companies may have income statements that seem attractive in isolation, but when viewed from a total revenue perspective 4 in fact have extremely low gross margins (relative to tech companies) and very high marginal costs.

The question for Softbank then is how many markets are there the size of transportation, with the possibility of taking a large enough chunk to make the economics work (leaving aside the fact that Softbank is underwater on its Uber investment)? The Vision Fund is invested in OpenDoor , for example, which is in an even larger market than transportation (residential real estate), but with much less potential transaction volume; Zillow, which followed OpenDoor into the “iBuyer” market, has a market cap of only $6 billion, in part because of investor skepticism about margins.

This is the challenge for Vision Fund: yes, these companies have huge capital needs, and yes, the only way they can become successful is if they become so big that their small margins are sufficient to cover their fixed cost, but does that necessarily mean big returns ? Or did Son anchor on “big” without making sure that his adjective of choice attached to the noun — “returns”, as opposed to “needs” or “markets” — that his investors are expecting?

Moreover, it’s not clear how many misses Vision Fund can afford: the Wall Street Journal reported earlier this week that Vision Fund has promised a 7% return a year to 40% of its investors, which means that SoftBank has limited capacity to be patient and wait for home runs — particularly if WeWork starts dragging down the whole fund.

Worse, it’s not clear how many home runs Softbank has. Looking at 29 U.S. tech IPOs since the beginning of 2018, 20 have increased in market cap over their offering price, and all of them are pure tech companies with high margins. 5 Of the nine that have fallen in value, four are marketplace companies 6 , two are hardware companies 7 , and only three are pure tech companies 8 . Son, though, sees pure technology companies as “clean, polished little companies” that are not big enough for Vision Fund. 9

Vision Fund is not a venture capital firm, nor is it a public market-focused hedge fund: it is neither, and new, but it very much remains to be seen if “new” is valuable.

New Lessons

At the same time, this is good news for the tech ecosystem: there is clearly still tremendous opportunity to build “tech companies”, primarily for the enterprise, and Vision Fund won’t be an obstacle. True, there are fewer opportunities in the consumer space, but that is more a consequence of big company dominance than Venture Fund stealing away opportunities with outsized returns relative to capital invested. If anything Vision Fund is stealing duds.

This is also good news for public market investors: despite all of the press about Uber and WeWork, more companies are up post-IPO than down — and the gains are much larger in percentage terms than are the losses. The tech company formula still works.

This is also a lesson for me: I started with an article that I got right, but in retrospect I was only halfway correct. Uber had a large market and there were tech-like dynamics that meant it could get a big part of that market, but margins — both reported, but especially relative to the customer transaction — still matter. I didn’t pay enough attention to them.

It also means I should have been more explicitly skeptical about WeWork ; my goal was to write a contrarian piece exploring the upside, while still being clear that I wouldn’t invest. I did state that, but I wasn’t nearly clear enough about just how absurd the valuation was, because I didn’t spend enough time discussing margins. 10

Going forward I plan to be a lot more skeptical about other tech startups that interface with the real world and the attendant drag on margins that follows; I am not saying that the category isn’t viable, and technology truly makes these companies different than the incumbents in their space, but they are not necessarily tech companies either.

Neither, and new.

I wrote a follow-up to this article in this Daily Update .

1. I am going to use Uber as a stand-in for companies like Lyft, DoorDash, Instacart, etc. for the rest of this article, but everything applies to all of the companies that use “gig” workers [ ↩ ]
2. In this case, the rider perspective includes both Uber riders and also UberEats customers; the two categories are not separated in Uber’s financials [ ↩ ]
3. It should be noted that Uber, rightfully, accounts for driver incentives either as contra-revenue (most of them) or as a cost of revenue (for driver incentives it is unlikely to earn back); the only driver incentives that fall under fixed costs are bonuses to existing drivers for driver referrals [ ↩ ]
4. I.e. the equivalent of gross bookings in the case of Uber [ ↩ ]
5. In order of returns, Zscaler, Anaplan, Smartsheet, Zoom, DocuSign, CrowdStrike, Fastly, SurveyMonkey, Pinterest, Health Catalyst, Medallia, Cloudflare, Carbon Black, Dynatrace, Datadog, PagerDuty, EverQuote, Zuora, Tenable [ ↩ ]
6. UpWork, Eventbrite, Uber, and Lyft [ ↩ ]
7. Sonos and Arlo Technologies [ ↩ ]
8. Pivotal, Dropbox, and Slack [ ↩ ]
9. Interestingly, the one tech company on this list that the Vision Fund owns, Slack, is the worst performing of all the SaaS companies [ ↩ ]
10. I did, though, make clear in a (free) follow-up that the AWS comparison was never intended to be a direct one [ ↩ ]