Uber argues that it is a platform for workers who want to move things, be it people, food, or freight. New revenue-generating businesses can simply be dropped into that system. These unique opportunities, then, will have gravitational power, keeping drivers and users orbiting Uber’s apps. To that point, Uber has grown Uber Eats into a $1.5 billion business. Perhaps in the future, all kinds of work opportunities and services will flow through Uber. It’s the Amazon analogy at play: yesterday books, today everything; today rides, tomorrow everything. What Amazon is for products, Uber could be for (gulp) work.
Even if you don’t believe Uber’s medium-term story, there is still that deus ex machina of the ride-hailing business: self-driving cars. It’s possible that Uber could develop autonomous-vehicle technology, which could (could!) allow the company to increase its margins, keeping the vast majority of the money that riders pay. By some accounts, this is the mega-happy scenario for Uber investors. Revenue and profit would skyrocket without pesky drivers.
But what then of the vaunted platform? How would drivers respond to the erosion of their livelihoods? The entire dynamics of ride-sharing would change, and who is to say that Uber—a company built on labor-market matching—would be as good at running an autonomous car service as Waymo or others, built as self-driving companies from the ground up?
Read: Inside Waymo’s secret world for training self-driving cars
While far from a sure thing, Uber is probably the lowest-risk way of betting on all this: flexible (precarious) labor markets, the dominance of on-demand services in middle-class life, and eventually the automation of a wide swath of jobs.
That qualitative evaluation has to somehow fit into a spreadsheet to justify a given share price. One way analysts model businesses is the discounted-cash-flow method. Basically, they imagine how much money a company could generate in the future, and they work backwards to come up with a fair price today for those hypothetical earnings. The problem with Uber is that—given that it has never made money—these kinds of models can tell you many different things about the value of the company.
For example, you might try, as the NYU finance professor Aswath Damodaran has, to model the company from the top down. First, you come up with a number for the value of the total transportation market Uber could address, then assume a certain market share for the company, and an uneasy path to profitability. Certain changes to any of these numbers—such as making the total market larger—lead to a much higher valuation for the company.
Damodaran also modeled the company from the bottom up. Here, the questions are simple: How much money will it take to acquire a new user, and how much more money can Uber squeeze from its users? Multiply out the different combinations of those two factors, and you get a puzzling table, with valuations stretching from less than $0 all the way up to $140 billion.