Wednesday, December 19, 2018

Resisting the urge for an Uber repost.


I'm already having trouble trimming Yves Smith's excellent take-down to excerpt length, so I'll limit myself to links to some similar points we've made in the past.


Ponzi Thresholds

They lose money on every ride but they make it up in volume

Even evil plans require a certain level of competence

A follow-up to Mark's post

And the especially relevant What almost everyone gets wrong about Uber and driverless cars


Uber Is Headed for a Crash

Uber has never presented a case as to why it will ever be profitable, let alone earn an adequate return on capital. Investors are pinning their hopes on a successful IPO, which means finding greater fools in sufficient numbers.

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Nor, after a certain point, does adding more drivers. Uber does regularly claim that its app creates economies of scale for drivers — but for that to be the case, adding more drivers would have to benefit drivers. It doesn’t. More drivers means more competition for available jobs, which means less utilization per driver. There is a trade-off between capacity and utilization in a transportation system, which you do not see in digital networks. The classic use of “network effects” referred to the design of an integrated transport network — an airline hub and spoke network which create utility for passengers (or packages) by having more opportunities to connect to more destinations versus linear point-to-point routes. Uber is obviously not a fixed network with integrated routes — taxi passengers do not connect between different vehicles.

Nor does being bigger make Uber a better business. As Hubert Horan explained in his series on Naked Capitalism, Uber has no competitive advantage compared to traditional taxi operators. Unlike digital businesses, the cab industry does not have significant scale economies; that’s why there have never been city-level cab monopolies, consolidation plays, or even significant regional operators. Size does not improve the economics of delivery of the taxi service, 85 percent of which are driver, vehicle, and fuel costs; the remaining 15 percent is typically overheads and profit. And Uber’s own results are proof. Uber has kept bulking up, yet it has failed to show the rapid margin improvements you’d see if costs fell as operations grew.

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Uber has raised an unprecedented $20 billion in investor funding — 2,600 times more than Amazon’s pre-IPO funding. This has allowed Uber to undercut traditional local cab companies, whose fares have to cover all costs, as well as have more cars chasing rides than unsubsidized operators can. Recall that for any transportation service, there is a trade-off between frequency of service and utilization. Having Uber induce more drivers to be on the road to create fast pickups means drivers on average will get fewer fares.

If Uber were to drive all competitors out of business in a local market and then jack up prices, customers would cut back on use. But more important, since barriers to entry in the taxi business are low, and Uber lowered them further by breaking local regulations, new players would come in under Uber’s new price umbrella. So Uber would have to drop its prices to meet those of these entrants or lose business.

Moreover, Uber is a high-cost provider. A fleet manager at a medium-scale Yellow Cab company can buy, maintain, and insure vehicles more efficiently than individual Uber drivers. In addition, transportation companies maintain tight central control of both total available capacity (vehicles and labor) and how that capacity is scheduled. Uber takes the polar opposite approach. It has no assets, and while it can offer incentives, it cannot control or schedule capacity.

The only advantage Uber might have achieved is taking advantage of its drivers’ lack of financial acumen — that they don’t understand the full cost of using their cars and thus are giving Uber a bargain. There’s some evidence to support that notion. Ridester recently published the results of the first study to use actual Uber driver earnings, validated by screenshots. Using conservative estimates for vehicle costs, they found that that UberX drivers, which represent the bulk of its workforce, earn less than $10 an hour. They would do better at McDonald’s. But even this offset to the generally higher costs of fleet operation hasn’t had an meaningful impact on Uber’s economics.

But, you may argue, Uber has all that data about rides! Certainly that allows it to be more efficient than traditional cabs. Um, no. Local ride services have backhaul problems that no amount of cleverness can remedy, like taking customers to the airport and either waiting hours for a return fare or coming back empty, or daily urban commutes, where workers go overwhelmingly in one direction in the morning rush and the other way in the evening. Similarly, Uber’s surge pricing hasn’t led customers to change their habits and shift their trips to lower-cost times, which could have led to more efficient utilization. If Uber had any secret sauce, it would have already shown up in Uber revenues and average driver earnings. Nine years in, and there’s no evidence of that.
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Uber has gone to some length to avoid publishing financial information on a consistent basis over time, a big red flag. One telling example: In late 2016, Uber targeted a share offering to high-end retail investors, which were presumably even dumber money than the Saudis that had invested in its previous round. Nevertheless, both JP Morgan and Deutsche Bank turned down the “opportunity” to market Uber shares to their clients, even though this could jeopardize their position in a future Uber IPO. Why? The “ride sharing” company supplied 290 pages of verbiage, but not its net income or even annual revenues.
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But what about driverless cars? Let’s put aside that some enthusiasts like Apple co-founder Steve Wozniak now believe that fully autonomous cars are “not going to happen.” Fully autonomous cars would mean Uber would have to own the cars. The capital costs would be staggering and would burst the illusion that Uber is a technology company rather that a taxi company that buys and operates someone else’s robot cars.




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