Uber Office

Uber – do they have a viable business model?

In late 2016 an editor (Yves Smith) on the website Naked Capitalism published a series of posts from transport industry veteran, Hubert Horan. There were originally four posts. A further two were added to address commentary from Naked Capitalism readers and from industry journalists.

The series has generated considerable comment and debate. There is considerable overlap and repetition in the posts. Here is a summary version. The four posts have been brought together, edited and precised. Hopefully the overall gist of the article is maintained and Hubert’s claims, explanations and conclusions remain intact.

We will critique the article in future posts.

Summary of Article by Hubert Horan on Naked Capitalism.

PART ONE

Published financial data shows that Uber is losing more money than any start-up in history. The losses are driven by Uber’s strategy of capturing market share from existing operators through undercharging by billions of dollars a year.

Uber is a private company and does not publish its results nor does it need to be audited in accordance with generally accepted accounting principles (GAAP) or satisfy the SEC’s reporting standards for public companies. However some summary data is in the public domain and the analysis below (in $m’s) is based on this information.

1H12 2H12 1H13 2H13 1H14 2H14 1H15 2H15 1H16
Passenger Payments 613.0 2344.3 3660.8 8800.0
% retained by driver 83% 83% 82% 77%
Uber Revenue 3.6 12.6 32.3 72.1 102.6 392.4 662.6 733.4 2060.0
Uber Costs 11.4 23.7 47.7 113.4 263.6 796.6 1381.3 3330.0
EBITAR (7.8) (11.1) (15.4) (41.3) (161.0) (404.2) (718.7) (1270.0)
EBITAR % (217%) (88%) (48%) (57%) (157%) (103%) (108%) (62%)

The majority of media coverage presumes Uber is following the path of prominent digitally-based start-ups such as Amazon, whose large initial losses transformed into strong profits within a few years. This presumption is contradicted by Uber’s financial results. The results show large losses through 2015, with Uber spending one and a half to double to amount it brings in in revenue. The improvement in 2016 can be explained by Uber-imposed cutbacks to driver compensation. Drivers had been retaining 82%-83% of customer payments (fares plus tips). Uber reduced this to 77% in 2016.

Thus Uber’s current operations depend on $ billions in subsidies, funded out of the $13 billion in cash its investors have provided. Uber passengers were paying only 41% of the actual cost of their trips; Uber was using these subsidies to undercut fares and provide more capacity than the competitors who had to cover 100% of their costs out of passenger fares.

Many other tech start-ups lost money as they pursued growth and market share, but losses of this magnitude are unprecedented. In its worst-ever four quarters, in 2000, Amazon had a negative 50% margin, losing $1.4 billion on $2.8 billion in revenue. 2015 was Uber’s fifth year of operations; at that point in its history Facebook was achieving 25% profit margins.

No Evidence of the Rapid Margin Improvement That Drove Other Tech Start-ups to Profitability

There is no evidence that Uber’s rapid growth is driving the rapid margin improvements achieved by other prominent tech start-ups as they “grew into profitability.”  Uber appears to lack the major scale and network economies that allowed digitally-based start-ups to achieve rapid margin improvement.

Uber’s EBITAR contribution margin improved from negative 108% in the first half of 2015 to negative 62% in the first half of 2016, but this margin improvement is explained by Uber imposed cuts in driver compensation. As shown in Exhibit 3, Uber only allowed drivers to retain 77% of each passenger dollar in 2016, down from 83% in 2014-15. If drivers had retained 83% of 2016 passenger payments, Uber’s EBITAR contribution would have been negative $1.8 billion, and its EBITAR margin would have fallen to negative 122%. Uber’s EBITAR margin did not improve because its productive efficiency or market performance was improving; Uber was simply claiming a higher share of each revenue dollar and giving less to drivers.

If rapid growth could not drive major margin improvements between 2012 and 2016, there is no reason to believe that Uber will suddenly find billions in scale economies going forward. Fundamentally digital companies like Amazon, EBay, Google and Facebook had massive operating scale economies because the marginal cost of expanded operations was close to zero.

By contrast, in the hundred years since the first motorized taxi, there has been no evidence of significant scale economies in the urban car service industry. That explains why successful operators did not expanded to other cities and why there was no natural tendency towards concentration in individual markets. Drivers, vehicles and fuel account for 85% of urban car service costs. None of these costs decline significantly as companies grow. As the P&L data above demonstrates, Uber has not discovered a magical new way to drive down unit costs.

The press has reported numerous unsubstantiated assertions that Uber was on the verge of profitability, or that operations in individual markets were profitable. In September 2015, Travis Kalanick said that Uber’s North American operations would be profitable by early 2016, but did not explain whether this meant actual profitability or an artificial interim contribution measure such as EBITAR or positive cash-flow. Uber has not presented any evidence that Kalanick’s promise has been achieved.

Since Uber’s corporate expenses cannot be directly linked to current operations in specific markets, it would be easy to claim positive contribution numbers from one market despite overall losses. An article reporting Uber’s 2015 losses said “the company expects older markets in developed countries to generate billions of dollars in profit in the coming years.” but the profit improvement needed to convert today’s $ billions losses into a $ billions profit would require some combination of the most staggering efficiency gains in the history of private enterprise and/or large fare increases. Fares would need to have quadrupled to have produced a $2 billion profit in 2015.

Uber’s refusal to consider an IPO may best be explained by the recognition that publishing detailed, audited financial data confirming these massive losses and the complete lack of progress towards profitability could undermine public confidence about its inevitable march to industry dominance.

Uber’s growth to date is explained by its willingness to engage in predatory competition funded by investors pursuing industry dominance.

PART TWO

Unlike other well-known tech “unicorns,” Uber has not created a new product or redefined a traditional market; it is not disrupting incumbent operators with a new way of doing business but it is driving passengers from point A to point B in cars; just like traditional urban car service operators always have. To achieve the overwhelming industry dominance that Uber is seeking it would need to find ways to provide the service at substantially lower costs.

This article explains the cost structure of traditional operators and evaluates, based on Uber’s actual practices and historical industry evidence, whether Uber has a meaningful cost advantage in any of these cost categories, or the potential to achieve substantially lower unit costs as it grows.

Uber has altered the industry’s longstanding business model

When considering financial and cost data, keep in mind that most taxi services are provided under a two-part business model, the taxi company and the drivers, who are classified as independent contractors. Since the 1970s most traditional taxi companies have actually been leasing companies; drivers pay a fixed lease fee for the use of a vehicle. This covers the costs of the vehicle and maintenance, plus corporate overhead services such as dispatching, branding/marketing and credit card processing. Traditional drivers retain all of the money paid by passengers, but bear the risk that fare revenue on a given shift might not be enough to provide meaningful take home income after covering the leasing fees, petrol and other costs.

The Uber model takes the contracting model further by shifting vehicle costs and capital risk to drivers.

Uber takes 30% of passenger revenue in return for providing corporate overhead services (customer booking, driver allocation, payments processing, trip routing). To evaluate questions of efficiency and competitiveness one needs to consider the entire (corporate and driver) business model since neither business model can work in the marketplace unless both the corporate entities and their driver contractors can achieve reasonable earnings.

There are four major components of urban car service costs, here shown with the percentage split taken from detailed research into traditional operators in San Francisco, Denver and Chicago :

  1. 58% – driver compensation (take home pay plus the benefit costs they must cover)
  2. 9% – fees directly related to passenger service (fuel, credit card fees, tolls, cell phone charges)
  3. 18% – vehicle ownership and maintenance
  4. 15% – corporate overhead and profit (including dispatching and branding/marketing)

In the traditional model the taxi company pays for items 3 and 4. The driver covers items 1 and 2.

In Uber’s model the driver carries costs 1, 2 and 3, Uber only covers cost 4. The Uber model therefore shifts vehicle costs and risks to drivers.

If one examines the four components of industry cost it becomes apparent that Uber not only lacks the major cost advantage that a company seeking to drive incumbents out of business would be expected to have, but actually has higher costs than traditional car service operators, except for item 2, fuel and fees, where no operator can achieve a significant cost advantage.

Higher driver compensation.

Recent in-depth studies from Chicago, Boston, New York and Seattle show that the 58% retained by traditional taxi drivers provides hourly take-home rates in the $12-$17 range (in 2015 dollars) and that full-time drivers only realize those hourly averages if they work 60-75 hours a week. This data is consistent with Census Bureau analysis which estimated the average wages in the broad category of taxi and limousine driver as $32,444 per year and $13.25 per hour (in 2015 dollars).

At start-up Uber needed to subsidize driver compensation to get drivers to abandon other operators and sign up with Uber. In a competitive market drivers would have no incentive to drive for Uber if it paid the same as traditional operators, especially as Uber require that the driver carries the car financing risk.

Higher vehicle costs.

It is unlikely that hundreds of thousands of independent, poorly financed Uber drivers could achieve lower vehicle ownership, financing and maintenance costs than professional fleet managers at a traditional operator. Shifting operating costs and capital risk from Uber’s investors onto its drivers does not eliminate those costs from the overall business model and it actually makes them higher.

The traditional transport industry depends on centralized management using sophisticated systems to ensure that capital assets are fully utilized and tightly scheduled around market demand. The Uber business model implies that these industries are wrong; decentralizing asset purchasing, maintenance and scheduling to isolated low-wage workers could reduce costs and create an efficiency gain large enough to outperform incumbent operators.

Higher dispatch and corporate costs.

Traditional taxi owners take 15 cents of each passenger dollar to cover dispatching, corporate overhead and profit while Uber currently takes double, at 30 cents. But even so, Uber’s costs are so much higher it still loses money.  This despite the fact they provide less than half the service of traditional companies (Uber does not lease and maintain the fleet). Unlike traditional cab companies, Uber fees need to cover the cost of global marketing, software development, branding, lobbying programs and the market development costs of Uber’s expansion into new cities.

Uber Used “Strategic Misinformation” to attract drivers

Uber’s above-market pay premium created a Catch-22. Although it fuelled the rapid growth that was critical to its growth and valuation it also meant Uber had a large cost disadvantage in the biggest cost category. The risk was that cutting driver compensation back to market levels would halt growth.

Uber dealt with this Catch-22 with a combination of deception and dishonesty, exploiting the natural information asymmetries between individual drivers and a large, unregulated company. Drivers for traditional operators had not needed to understand the vehicle maintenance and depreciation costs they needed to deduct from revenue in order to calculate their take home pay.

Claims of higher driver pay used by Uber to attract drivers misrepresented gross receipts as net take-home pay. They failed to disclose the substantial financial risk its drivers faced given Uber’s freedom to cut their pay or terminate them at will. Uber claimed “[our} driver partners are small business entrepreneurs demonstrating across the country that being a driver is sustainable and profitable…the median income on UberX is more than $90,000/year/driver in New York and more than $74,000/year/driver in San Francisco” even though it had no drivers with earnings anything close to these levels.

After these claims were debunked Uber responded with allegedly academic research (which Uber administered and paid for) which claimed Uber drivers earned more than traditional taxi drivers but made no effort to calculate actual net earnings. They also ignored the fact that Uber salaries were subsidized while traditional taxi salaries were constrained by actual passenger revenues.

In mid-2015, after hundreds of thousands of drivers were locked in to vehicle financial obligations, Uber eliminated driver incentive programs and reduced the standard driver share of passenger fares from 80 to 70 percent. This transfer of passenger dollars from Uber drivers to Uber investors drove all a 2016 margin improvement, but also eliminated most of the economic incentive that got drivers to switch to Uber in the first place.

An external study of actual driver revenue and vehicle expenses in Denver, Houston and Detroit in late 2015, estimated actual net earnings of $10-13/hour, at or below the earnings from the studies of traditional drivers in Seattle, Chicago, Boston and New York.

Uber cannot grow into profitability

Many start-up companies experience large initial losses but use scale and/or network economies to improve cost competitiveness and margins as they grow. But as noted in the first article in this series, the urban car service industry has never displayed evidence of significant scale economies. Uber’s financial results show none of the margin improvements that would occur if strong scale economies existed.

Uber’s economics are fundamentally different from other well-known start-ups that successfully used scale economies to grow into profitability. These were companies in fields such as social media or online retailing whose purely digital products could be expanded globally (and into new markets) at extraordinarily low marginal cost. Unlike an urban car service provider, direct labour was a tiny component of these companies’ overall cost structure, and most had no competition (entirely new products like EBay or Facebook) or were facing competition with enormously higher direct operating costs (online retailers vs. brick-and-mortar incumbents).

There are no scale economies related to the 85% of costs related to direct operations; each shift involves one vehicle and one car regardless of the size of the company. This is why there has been no natural tendency towards significant concentration in individual taxi markets and why taxi companies rarely expanded beyond their original markets.

The productivity of drivers could increase if more off-peak and backhaul passengers could be found, but this revenue productivity is not a function of company size.

Uber’s decentralized business model precludes the efficiencies integrated operators can achieve such as volume purchasing of vehicles and insurance and the use sophisticated systems to optimize asset acquisition and utilization against volatile demand patterns.

Unlike digital companies, Uber actually faces negative expansion economies since each new market raises entirely unique competitive, recruitment and political lobbying challenges. Uber’s unit expansion costs appear to have increased as it has expanded outside the United States.

Uber also has no potential to exploit the network economies that some purely digital companies used to drive major profit improvements. In these cases (EBay’s exchange market, Google’s search function, Facebook’s social media product) the development of a strong user base makes the product significantly more efficient and more attractive to other users. This locks-in existing users, fuels growth, and makes it nearly impossible for later entrants with smaller user bases to compete.

By contrast, neither Uber’s ordering app, nor the ordering apps of other operating companies create these network economies or locks-in users the way EBay and Facebook and Google have. In a competitive market, people will use the app of companies like Uber or American Airlines if they can provide good prices and service, but they won’t therefore abandon Yellow Cab or JetBlue.

PART THREE

Is the Uber business model based on breakthrough product/technological/process innovations?

It must be emphasized that “competitive advantage,” as used in these articles, refers strictly to advantages powerful enough to transform the industry’s competitive dynamic, allowing one company to profitably grow much faster than its competitors.

Unlike previous technology start-ups, Uber has not made specific, detailed claims about the sources of competitive advantage that might explain its rapid growth. While it has discussed aspects of its business model, Uber has not presented evidence about their efficiency/service impacts that independent outsiders could review. There have been many articles in the business press speculating about possible explanations for Uber’s rapid growth, but they ignore the billions in subsidies that have funded growth to date.

If Uber had actually implemented transformative change, evidence of the transformative impact should have already appeared in the financial data presented in the previous two articles.

Uber has been operating since 2010. If Uber had dramatically redefined the product and the market, one would see obvious, tangible evidence of how its service was dramatically different from traditional taxis and one would see demand growth in response to the totally new product offering. If Uber had found ways to produce urban car service significantly more efficiently than incumbents, one would see obvious, tangible evidence of its lower production costs and one would see superior profitability or at least strong, steady margin improvements on a clear path towards sustainable profitability.

In fact, there is no evidence of any of those things. One can observe product and service advantages over traditional operators, but these can been entirely explained by the subsidies. Uber users pay only 41% of the cost of their service. There is no evidence that taxi customers in a competitive market would pay more than twice as much for the service quality advantages Uber investors have been subsidizing.

Uber Has Not Been Exploiting Powerful “Sharing” or “On-Demand Economy” Efficiencies 

Two of the primary narratives constructed to explain Uber’s growth are that it is pioneering the development of the “sharing economy” and the “on-demand economy.”

The alleged basis of the “sharing economy” was that cars were only used 56 minutes a day on average, and that “ridesharing” companies like Uber were creating huge value by exploiting the 97% of the time when cars were idle.

An individual with nothing else to do could decide to use his car to serve Uber passengers for a few hours on an occasional evening, but Uber could never replace all existing taxi capacity nationwide with people driving their personal cars for a few hours when it happened to fit their schedules.

Uber has claimed it designed so that people could just push a button and get a ride, pursuing an “on-demand” model. But the operational costs and challenges of taxi service includes huge demand peaks, unplannable volatility (demand spikes when it rains), and empty backhauls. Mitigating these costs requires advance knowledge of customer demand, and integrated, centralized operations planning.

The instant gratification that “on-demand” services provide make these costs and challenges worse. Resource utilization plummets because more drivers and vehicles must stand by to serve the Saturday night peak, but driver assignments can’t be optimized because people who want to “push a button and get a ride” don’t book their trips in advance. Uber’s on ‘demand’ business model eliminates the possibility of centralized operations planning. The basic economics of “on-demand” services—designed for a narrow set of customers willing to pay a premium for immediate service whenever they feel like it—are incompatible with Uber’s goal of providing a major portion of urban transport infrastructure.

Uber’s Use of “Independent” Drivers Is Not an Innovation and Does Not Increase Efficiency

As discussed in the second instalment of this series, the use of independent contractor drivers is not an Uber innovation, although Uber takes the longstanding practice a step further by shifting vehicle costs and capital risks onto its drivers.

Independent contracting makes the integrated network revenue and capital asset management that is central to transport networks impossible. Independent contracting would cripple airline, freight and transit networks since no one would show up to operate trips that were critical to network efficiency but had poor trip revenue.

Uber’s App Is Not a Powerful Technological Breakthrough

Many consumers like Uber’s ordering/dispatching smartphone app, but it has not had any material impact on cost efficiency, and has done nothing to address Uber’s corporate cost disadvantage. It offers useful functionality, but since this software can be, and has been, easily replicated, it cannot create a long-term advantage.

Hundreds of other consumer industries have migrated from telephone ordering to smartphone and internet ordering (pizza delivery, airline booking), but there are no cases where this had a material impact on industry competition.  The major emphasis on the app in pro-Uber articles appears to be symbolic; the app implies the existence of a new modern service.

Uber’s Surge Pricing Does Not Increase Efficiency

Some Uber supporters have falsely claimed that its use of surge pricing is a major breakthrough comparable to variable pricing systems in airlines, hotels and other travel industries. Surge pricing will influence customer’s decisions and smooth out demand.

But research has long demonstrated that the timing of taxi demand is highly inelastic, (people want a cab at a very specific time) so variable fares will not change demand patterns or improve taxi utilization. No level of taxi discount will get anyone to shift their Saturday night plans to midday Tuesday. Uber’s surge pricing simply raises fares (up to eight times normal levels) without prior warning. Given the short notice this does nothing to increase total taxi supply, but redistributes drivers to higher fare areas.

Uber Has Not Solved the Problems of Serving Peak Demand or Low-Density Neighbourhoods

The industry’s biggest service problems—limited and unreliable car availability when demand is highest (you can’t get a cab after dinner on Saturday night, or after your late evening arrival at LaGuardia, or when it is raining), and poor service to lower-density neighbourhoods (including but not limited to low income neighbourhoods) exist because the true cost of providing peak period and low-density neighbourhood service is substantially higher than the fares taxi riders are willing to pay and nothing in Uber’s business model reduces the cost of these services.

Taxi drivers often refuse trips to these low-density neighbourhoods. If taxi companies set fares in line with true service costs, prices to low density neighbourhoods would likely increase 50-100% and peak period prices would be 3-5 times normal levels. As noted, Uber’s surge pricing does not increase efficiency; it simply prices taxis out of the reach of many current users.

PART FOUR

Uber’s investors have been focused on earning strong returns on its $13 billion investment base. If investors can profit by introducing major product/technological process breakthroughs that vastly improve industry efficiency, or if their returns come from providing slightly better service at slightly lower costs in a competitive market, then both consumers and capital accumulators will be better off in most cases.

There is no evidence that Uber’s investors put $13 billion into the company because they thought they could achieve Amazon type efficiency advantages over incumbent urban car service operators. There is no evidence that Uber’s managers or spending priorities were ever focused on creating efficiency improvements or consumer benefits. Unlike past start-ups, Uber made no effort to provide outsiders with evidence that its business model generated powerful efficiency advantages, or that it could provide urban car services at lower cost than incumbents.

From its earliest days, Uber’s investors and managers have recognized that significant investor returns would require global industry dominance and the elimination of longstanding laws and regulations. The presumption is that urban car services can be turned into a “winner-take-all-game”, where the winner can earn sustainable rents once quasi-monopoly industry dominance has been achieved.

The $13 billion in cash its investors provided is consistent with the magnitude of funding required to subsidize the many years of predatory competition required to drive out more efficient incumbents. Uber’s investors did not invest because they thought they could vanquish those incumbents under “level playing field” market conditions; those billions were designed to replace “level playing field” competition with a battle between small scale incumbents struggling to cover their costs and a large company funded by Silicon Valley investors willing to subsidize years of losses.

Photo by 5chw4r7z

Photo by 5chw4r7z

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