Why Can’t Uber Make Money? — Revisited

In 2017, I penned an article in Forbes titled Why Can’t Uber Make Money? At the time, Uber’s co-founder/CEO Travis Kalanick (TK) had recently been forced to resign, but the press was still covering his titillating bro culture peccadillos, and speculating on how Uber might change under his successor, Dara Khosrowshahi (DK). Fast forward five years, and the public’s schadenfreude for Kalanick’s self-destructive behavior is still alive and well as captured in the recent release of Showtime’s limited series Super Pumped: The Battle for Uber.

But my attention — then and now — has been elsewhere, pondering Uber’s elephant in the room — why the company has lost more money than any tech venture in history (yes, even more than WeWork), before and after Travis’ combative reign. Lest there be any doubt that the answer goes far beyond CEO personalities, Uber’s board deliberately chose a CEO successor with anti-Travis bona fides in virtually every respect: Khosrowshahi is preternaturally polite, cheerful, deliberative, analytic, humble, empathetic, and moralistic. And yet, Uber’s financial performance remains beyond disappointing. In fact, the company has lost more money¹ and burned more operating cash in the five years of Dara’s leadership than in the seven years under Travis.

Uber Revenue and Operating Income¹, 2014–2021
($, millions)

As dismal as it has been, Uber’s financial performance is not an anomaly. Urban mobility is intrinsically a tough business to make money, and no one has cracked the nut of achieving consistent profitability at scale. Not Didi, despite its 90+% market share (after Uber abandoned China in 2016) in the largest ridehail market in the world. Nor Ola, the largest indigenous ridehail provider in India. Nor Grab in Southeast Asia, or Gett and Bolt in Europe. Nor Cabify in South America, or Lyft in North America.

What all these ridehailing companies share in common is weak business fundamentals, characterized by:

• Largely undifferentiated service
• Low customer and driver loyalty
• Limited economies of scale, yielding stubbornly high variable costs and rendering loyalty/reward programs expensive and/or ineffective
• Weak network effects, given highly localized operating territories and multi-homing by both riders and drivers
• Relentless price competition to attract riders
• Perennial need for sizable incentive/bonus payments to recruit and retain drivers, given chronic dissatisfaction with compensation and intense competition for drivers from other gig economy companies (e.g. Instacart, DoorDash, Amazon Flex)
• Scalability constraints in major metro areas — bounded by limits on road capacity and driver supply
• Growing global regulations targeting ridehailing’s negative externalities (congestion, emissions, public safety), and adequate compensation and benefits for a growing body of city workforces.

True, some ridehail providers (e.g. Uber, Grab, Ola) also operate last-mile delivery businesses which may weaken bottom-line results. But Khosrowshahi has been unwaveringly bullish on the value of combining ridehailing and delivery, noting prior to the pandemic that Uber Eats is “ exploding in a good way,” and that its symbiotic businesses ideally position the company to weather the challenging business environment during the pandemic and beyond.

But if history is any guide, making money in last-mile delivery will prove to be at least as challenging as ridehailing. Bolting an inherently undifferentiated, inefficient, and expensive delivery service onto restaurants and local merchants whose thin margins and relatively low customer order values make the economics of third-party delivery tenuous at best, and all the more so with consumer belt-tightening in weakening economies worldwide.

As a reminder, last-mile delivery businesses have struggled for decades to find the right formula for success against a long list of failures. From Kozmo, Webvan, and Urbanfetch, who flamed out during the dot-com bubble, to the more recent bankruptcies of Sprig, Maple, Munchery, Foodora, Buyk and Fridge No More, profits and survival have proved elusive. Amazon, a paragon of operational excellence, tried its hand at meal delivery for four years, before shutting down its US Restaurants division in 2019. And none of the remaining major restaurant, grocery, or instant delivery players have been able to consistently earn profits before or even during the pandemic, despite unimaginably favorable, if tragic business circumstances.

In the US, delivery market leader Doordash has failed to create enough value to adequately reward all stakeholders — consumers, couriers, restaurants/ merchants, and company shareholders — forcing it to play one off against another, in what has become a long-running pursuit of profitless growth. Uber has similarly struggled with its unprofitable Eats business, consistently earning lower take rates² and adjusted EBITDA margins on delivery than in ridehailing.

Despite the company’s chronic underperformance, Uber’s two CEOs have doggedly painted a bright picture of the company’s utopian future.

For example, in 2015, Travis Kalanick asked us to “imagine cities where traffic speeds along smoothly and quietly, even at rush hour, allowing cities to reclaim the space once wasted on garages and lots and meters to build new parks and schools and where you can choose to live or start a business anywhere you want because transportation to and from will always be one tap away.”

Four years later (2019), Dara Khosrowshahi upped the ante, hyperbolizing, “we don’t just want to be your Amazon of transportation but also your Google of transportation. It’s no longer just ordering a taxi from an app. There’s Uber Copter coming to New York City for helicopter rides to the airport, and Uber Eats delivered by drone in San Diego. New self-driving cars are coming back online. And starting soon with Uber Air we want to take the transportation grid into the third dimension.”

But it hasn’t worked out that way. Not even close.

Over the past two years, DK has sold Uber’s autonomous vehicle research and urban air vehicle businesses at fire-sale prices, divested its e-scooter/bicycle micro-mobility subsidiary, retreated from more than a dozen deeply unprofitable ridehail and delivery markets in Southeast Asia, India, and Europe, and laid off 14% of Uber’s workforce. In addition, Khosrowshahi has doubled down on Uber’s asset-light business model, resisting investments in dark kitchens or micro-fulfillment centers, as several competitors have.

Despite these broad cost-cutting moves, Wall Street’s growing impatience with profitless growth has taken a heavy toll on Uber’s stock — currently trading below half its IPO listing price. Responding to the “seismic shift” in market sentiment, Khosrowshahi announced last month that Uber would slash marketing and incentive spending, rein in hiring and “make sure our unit economics work before we go big.”

But the question remains, why can’t Uber make money despite the fact that the company already is big — on track this year to generate $125 billion in gross bookings and over $30 billion in revenue from 25 million rides and deliveries served per day?

The answer lies in two enduring realities.

1. Uber’s business model is fundamentally weak

2. Gig worker cost savings don’t solve the root causes of Uber’s chronic underperformance.

Uber’s business model is fundamentally weak
The six key assumptions underlying Uber’s value proposition, first advanced by Travis Kalanick, and still guiding the company under his successor have all proven to be demonstrably false in theory and practice.

1. Uber’s asset-light business model and strong network effects will yield huge economies of scale, creating unassailable first-mover advantages in each of the markets it enters.
2. Uber’s prodigious fundraising will yield ample reserves to drive competition from the market and establish global monopoly control and pricing power
3. Uber’s scale advantage and sophisticated AI algorithms will power a superior service, translating into shorter wait times for passengers and drivers, and improved driver productivity, which in turn will allow Uber to achieve the trifecta of low fares, attractive driver compensation, and corporate profitability.
4. With consumers on its side, municipal governments will be unwilling or unable to restrict its ever-expanding operations, even after recognizing that Uber’s business priorities conflict with public policy goals for sustainable, efficient modes of public transportation and adequate compensation for a large and growing sector of city employment.
5. Product line extensions making Uber “the Amazon of transportation” will provide profitable growth opportunities to offset lingering losses in the core ridesharing business
6. Over the longer term, the combination of readily available funds from capital markets and retained corporate earnings will fund a seamless transition to autonomous vehicle operations, promising an even more Utopian future.

There are so many flaws in these asserted value propositions, that it’s hard to know where to begin. But let’s start by noting that Uber’s “breakthrough” business model did not fundamentally change the cost of providing taxi service, as much as shift the burden from the company to contracted drivers, who in fact are likely to face higher operating costs as individuals than would be experienced by professionally managed vehicle fleets.

Add to that the high overhead costs fueling Uber’s growth-at-all-costs strategy — its 2019 SG&A weighed in at 79% of revenue — in stark contrast to the iconically dumpy dispatch office depicted in the 1980’s hit TV series Taxi, leaving many observers (myself included) wondering how Uber could afford to pay its drivers more while charging passengers 30%-50% less than legacy taxi operators through most of the company’s formative years.

Uber’s CEOs have answered this question disingenuously, masking the company’s real business intent. The disingenuous part is the claim that Uber’s sophisticated algorithms would dramatically improve driver productivity, thus lowering costs (more trips/hour) and enhancing customer service (lower wait times and fares). In essence, we were asked to believe that with rapidly increasing scale, Uber drivers would be able to find their next fare within moments of completing each trip, and that customers would be whisked to their desired destination within moments of summoning a ride, thus eliminating dreaded deadheading that has dogged the taxi industry for decades. But in reality, Uber’s productivity gains have been modest. For example, in New York, the largest US ridehailing market, the number of ridehailing trips per vehicle per active hour has hovered around 2.0 for the past four years, about 10% lower than for Yellow taxis.

Four factors have limited the productivity gains of ridehailing operations.

• Urban mobility patterns differ markedly by time of day. While Uber’s algorithms can help guide and (financially incentivize) drivers to areas of temporarily high demand, they do not eliminate the intrinsic asymmetries in directional demand. For example, a lucrative 10 PM Uber trip from a downtown bar to a leafy suburb is unlikely to generate a paid return trip to find the next bar patron in need of a ride.
• While it is true that the absence of regulated caps on Uber’s driver supply in most cities (but not NYC) has beneficially extended on-demand ridehailing service to outer boroughs and suburbs, there’s a reason these areas have traditionally been poorly served by taxis. Low-density neighborhoods are not conducive to high utilization operations, resulting in demand-limiting high prices and reduced driver income.
• In theory, Uber’s market share leadership should have positioned the company to deliver superior carpooling service, boosting productivity as measured by passengers served per hour. But in practice, even before the pandemic forced Uber to suspend its carpool operations, the company chose not to prioritize this money-losing service, in the face of widespread passenger and driver resistance
• Given the nature of its asset-light business model, Uber has an incentive to encourage an oversupply of drivers, at the expense of driver productivity. The reason is simple: having more drivers on the road always improves Uber’s service level, demand, and revenue at little company cost, but with exactly the opposite effect on individual driver income and productivity.

Dara Khosrowshahi has often cited improving productivity as a key driver of Uber’s strengthening business outlook, while steadfastly refusing to provide confirming data on consumer prices or driver utilization and pay rates in any of its major markets³. What is known (from secondary sources) is that Uber has been generally increasing ridehailing prices faster than driver compensation since 2018 at the expense of demand growth, in its elusive quest to reach breakeven.

DK is correct in labeling current market sentiments as a “seismic shift.” Until now, Uber has aggressively prioritized global growth over profitability for two reasons. First, in the blitzscale era ushered in by Softbank’s $100 billion Vision Fund launched in 2017, private and public markets showered growth companies with unprecedented amounts of capital and rich valuations. As DK observed shortly after negotiating Softbank’s $9 billion investment in Uber in 2018 (at a valuation one-third higher than its market cap in mid-June, 2022), “rather than having Softbank’s capital cannon facing me, I’d rather have their capital cannon behind me.”

Such outsized investor and company optimism was driven by a misguided belief that strong network effects and scale economies would ultimately propel Uber to winner-take-all (or most) dominance, giving the company near-monopoly control and pricing power in what they claimed to be a $12 trillion accessible market.

This value proposition was prominently featured in Uber’s IPO prospectus, depicting a market dynamic where more drivers would attract more riders, which in turn would attract more drivers…in a virtuous cycle fueling an unstoppable march towards market domination. Ironically, Uber’s direct competitors — Didi and DoorDash — used precisely the same argument and virtually identical graphics in their subsequent IPO prospectuses to argue why they too would achieve market dominance.

Nonetheless, Uber struck a responsive chord with investors, as its promised value-creation drivers did in fact fuel the extraordinary success of trillion-dollar tech enterprises, such as Google, Amazon, and Apple. But Uber’s claim of success-by-association was and is unfounded. Uber’s localized operating territories and multi-homing by both riders and drivers weaken its network effects, while Uber’s highly variable cost structure severely limits scale economies. As such, Uber’s prodigious fundraising only meant that the company could replicate its weak business model in more markets and lose more money faster than anyone else.

During his tenure, DK has valiantly tried to shift the narrative away from Uber’s predictably mounting losses to make the case that Uber’s success is just around the corner, trying several themes on for size: 1) We serve a $12 trillion TAM; 2) We’re becoming the Amazon of transportation; 3) Look at Uber Eats growth!; 4) We’re ideally positioned to weather the storm; 5) Ridehailing is coming back! (conveniently pegged against the depths of the pandemic); and most recently, 6) Uber is recession-resistant.

Giving credit where it's due, Uber has, in fact, been remarkably effective in controlling its narrative. Until recently, the company has enjoyed widespread admiration manifest in favorable press coverage, fawning business school case studies, and consistently high equity analyst ratings, all extolling the company’s innovativeness, operational excellence, and significant societal impact. What little opprobrium the company faced tended to dwell on the company’s toxic cultural heritage, which Dara Khosrowshahi was presumed to have fixed with his inaugural pledge to “Do the right thing. Period.”

But Khosrowshahi’s perennial cheerleading is now wearing thin, amid growing skepticism that Uber will be able to achieve anywhere near the growth and profits required to justify even its current depressed valuation. This leaves Uber in the uncomfortable position as other players in the mobility and last-mile delivery space: needing to squeeze drivers, merchants (and more recently customers) in vain pursuit of elusive profits and growth.

Inexorably, investors will have to come to terms with what value to place on what appears to be a pricey, slow-growing, and barely (at best) profitable taxi and delivery service, reminding us once again that business models matter. Look. Out. Below.

Gig worker cost savings don’t solve the root causes of Uber’s chronic underperformance

No company has been more responsible for the rapid rise of the gig economy than Uber. While independent contractor (IC) labor has been utilized in a wide array of industries for decades, Uber is notable for the massive scale of its IC workforce (approximately 5 million worldwide) and the extent to which it relies on algorithmic management tools.

In what has now become standard operating procedure in the mobility and delivery sectors, virtually every aspect of driver work conditions — task assignments, compensation, routine communications, performance monitoring, and first-level disciplinary actions are controlled by opaque machine algorithms.

From its inception, IC labor has been integral to Uber’s business strategy, operations, and financial performance — and has served the company and most drivers well. For Uber, IC labor has enabled the company to rapidly scale at low cost, while dynamically balancing driver supply and customer demand.

And an overwhelming majority of drivers prefer the flexibility of independent contractor work over employee classification, reflecting the prevalence of part-time gig work. For example, Uber recently reported that only 9% of its California drivers use the online platform for 40+ hours per week, and on average, tend to drive only nine out of every 13 weeks.

But despite these apparent gig worker benefits, there are downsides for both Uber and its drivers. IC drivers must be willing to accept considerable uncertainty in take-home earnings, which are controlled by a corporate entity with every incentive to exploit strong asymmetric information advantages to minimize driver pay.

As for Uber, relying on an asset-light business model with IC labor locks the company into an undifferentiated product with chronically poor financial performance, poor labor relations, and exceptionally high worker turnover. While Uber’s top and bottom lines would undoubtedly be worse if forced to rely on employee labor, IC labor does not solve Uber’s intrinsic business model weaknesses

• Relatively undifferentiated service
  Because IC drivers can and usually do multi-home with several ridehail and delivery operators, competitors can offer nearly equivalent service levels, even with smaller scale.⁴ As such, Uber is forced to compete for drivers (and customers) on a relatively even playing field, trip-by-trip in every market it serves.
• Recurring driver acquisition costs
  Uber must thus rely on a costly array of driver incentives — hotspot bonuses, time-of-day boosts, consecutive ride bonuses, and longer-term quests — to attract and lock in adequate driver supply. This sets up a predictable cycle of on-again/off-again incentive programs, where Uber boosts bonuses when it needs additional driver supply, then cuts back to restore adequate margins, which invariably necessitates subsequent bonuses to continuously rebalance supply and demand.
• Strained driver relations
  Moreover, the asymmetric information advantage that Uber exploits to design bonus programs that maximize driver appeal, while minimizing actual payouts. has a corrosive effect on driver satisfaction over time. Examples of the algorithmic gamification techniques uses Uber were described in a recent Bloomberg article:
  [T]he platforms keep tabs on drivers’ every move: the percentage of available pickups that they accept; the time of day they typically work; the neighborhoods they prefer; the ratings passengers assign after a ride…The platforms send push notifications to drivers who are about to log off, telling them how close they are to advancing to the next performance tier, which unlocks benefits such as the ability to see a trip’s duration and direction. Or, as in a video game, bonus offers pop up: $30, say, for completing 10 consecutive rides…What should be a straightforward chance to make more money can be a Kafka-esque ritual benefiting the platforms more than the drivers…But the thresholds for qualifying for various perks can be stringent, such as needing to accept 9 out of 10 rides or keeping an almost-perfect customer rating. And after a “qualifying” period (Uber’s is three months), the score resets.
  
  Add to that anecdotal reports that Uber often throttles trip assignments⁵ for drivers nearing bonus thresholds making it difficult if not impossible to qualify for all-or-nothing payouts, and it’s not surprising that Uber experiences low driver satisfaction and high turnover.
  
  In summary, by adopting an asset-light, IC-driven strategy, Uber has locked into a business model yielding relatively undifferentiated service, relatively high, recurring, and unpredictable costs of customer acquisition on both sides of its marketplace, low customer-facing worker satisfaction, and extremely high driver turnover. These are obviously not ideal characteristics for a services-oriented business.⁶

Will Uber Ever Be Profitable?

The intrinsic weaknesses in Uber’s business model profoundly invalidate every element of its founding value proposition. This reality check also helps explain why every major global urban mobility and last-mile delivery provider utilizing a similar business model has also failed to achieve consistent profitability over the past dozen years.

Does this mean Uber is destined to never reach breakeven? Although the company steadfastly refuses to give guidance on when it expects to reach GAAP profitability, there are signs that it is moving in the right direction. DK is on record as promising to deliver positive free cash flow this calendar year, and Uber’s negative profit margins have been steadily shrinking over the past five years.

To his credit, during the 2020 pandemic business meltdown, DK did unwind many of Uber’s growth-at-all-costs binge investments, and he has more recently pledged to slash operating costs, in response to a seismic shift in investor sentiment.

But, even so, Uber’s structural business model weaknesses are likely to destine Uber to a barely profitable, slow-growth future that doesn’t justify even its current depressed market valuation. The steps Uber has to take to accelerate its path to profitability — raising prices and cutting costs — will clearly stunt growth, leaving the company in a decidedly uncomfortable position of having to choose between profitability OR growth for the foreseeable future. Unfortunately for Uber, investors demand both, forcing Dara to make promises he won’t be able to keep. For now, DK is emphasizing profitability, while still dangling the prospect of “going big” down the road.

To quantify the stakes of this dilemma, even if Uber were to immediately improve its pre-tax profit margin to +6% (a real stretch, given its long track record of double-digit negative margins) and grow its top line by 20% every year over the next decade, a discounted cash flow analysis suggests the company would be still be valued at only $18/share, well below its current depressed stock price.

So what can we expect Uber to do, and what are the consequences for riders and drivers?

Uber does enjoy one crucially important competitive advantage with the potential to significantly improve its near-term profitability. Namely, no one has more data to deeply understand rider and driver behavior.

To see what benefits that knowledge can convey, consider the results of an Uber-sponsored University of Chicago study in 2016 to analyze consumer demand for ridesharing services. Using almost 50 million individual-level observations of transactions on Uber’s platform, the academics were able to analyze the price sensitivity of individual customers and for the market as a whole.

Imagine two customers — Cathy and Bob — who each have submitted hundreds of trip requests on Uber’s platform over the past several years. Cathy is the ultimate loyalist, having confirmed every ride request regardless of price, whether the surge price multiple over base fares was 0, 5X, or anything in between. Given such observed behavior, it’s safe to assume that — by virtue of laziness, high income, or both — Cathy is not a price-sensitive customer.

In contrast, Bob tends to take more time before accepting Uber trips, and in fact has turned down 40% of his ride requests, usually when given a high price. This behavioral pattern clearly signals a price-sensitive customer seeking the best available value.

Many more nuanced behavioral characteristics can also be discerned from Uber’s massive customer database, for example recognizing that a customer with weekly trips from home to airport exhibits lower price sensitivity (inferentially for company-reimbursed business travel) than on frequent personal trips to a friend’s house.

Armed with these insights on tens of millions of customers, Uber is in a position to practice what economists call first-order price discrimination — that is, charging each customer prices based on their known willingness to pay (WTP).

The University of Chicago study concluded that if US customers were charged their full WTP for every trip, Uber could generate billions of dollars of incremental revenue (and profits), relative to the standardized prices the company was charging at the time. Since Uber knows more about customer behavior than any of its competitors — particularly those who have been loyal riders — Uber is in the best position to capture the benefits of price discrimination, provided that consumers don’t regularly make the effort to compare competitive ridehail pricing (which most don’t). A recent analysis by Bloomberg Second Measure confirmed that 88% of riders exclusively use the same ridehail provider (usually Uber) within any given month despite significant price differences that exist for many rides. This “lazy loyalty” suggests Uber has a significant opportunity to exploit price discrimination.

Uber can also enhance profitability by exploiting its deep knowledge of differences in driver behavior. Every driver differs in their willingness to work as a function of compensation offered, which economists define as an individual’s reservation price. Whether due to laziness, lack of business savvy, or economic hardship, some drivers will willingly accept ride offers, despite low pay and/or long pickup distances and deadhead returns, while others demand Uber to “show me the money” with attractive terms. By exploiting its detailed knowledge of driver behavior, Uber has a sizeable opportunity to differentiate pay offers to maximize driver supply at minimum cost. After all, why offer all drivers high bonus incentives or short pickup times, when some will drive without them?

Exploiting price discrimination on both sides of its marketplace thus gives Uber the potential to substantially enhance its profitability. And Uber has put itself in an ideal position to do precisely that by decoupling customer pricing from driver compensation. In 2016, Uber implemented “upfront pricing,” whereby each customer was charged a specified price with no reference to time, distance, or surge multiples. At that time, driver compensation was still pegged to time and distance pay rates.

Shortly after this policy change, reports began surfacing that Uber was keeping upwards of 60% of upfront passenger fares on many trips. Uber denied that its algorithms gouged customers or exploited drivers, insisting that its take rates were sometimes higher or lower than historical norms. But in reality, we have to take Uber’s word for it, as only the company has access to its proprietary databases that would allow an accurate assessment of the impacts of Uber’s pricing and pay policies.

Confirming the suspicion that Uber wouldn’t have changed its pricing policies if it weren’t beneficial to the company’s bottom line, Daniel Graf, head of Uber’s marketplace analytics team in 2017, told a Bloomberg reporter that Uber’s pricing techniques had grown incredibly sophisticated, giving the company a competitive advantage in financial engineering to stay ahead of Lyft and other ride-hailing operators.

Since then, Uber has gone on to further decouple passenger fares from driver pay this year by rolling out “upfront pricing” for driver compensation in dozens of US cities. Under this scheme, driver compensation is no longer pegged to base pay rates for time and distance computed at the end of a trip, but rather specified upfront at the time each trip is offered. While drivers are now given more information about the characteristics of trips they are asked to accept or reject, the new policy essentially gives Uber full discretionary control over consumer prices and driver pay, based on opaque and unknown factors.

A recently departed Uber senior executive recently shared with me the observation that “data analysis is in Uber’s DNA, guiding every aspect of how the company is managed.” Given Uber’s urgency to placate anxious investors by accelerating its path to profitability, there is every reason to expect that Uber will increasingly exploit its competitively advantaged discriminatory pricing opportunities on both sides of its marketplace.

How should drivers and consumers respond?

Just as Uber is rightfully looking out for its own interests, Uber’s customers and drivers can and should as well by tapping into valuable resources to help obtain lower consumer prices and higher driver pay.

For drivers, The Rideshare Guy delivers weekly newsletters, blogs, and podcasts providing helpful tips for drivers to take full advantage of Uber’s and Lyft’s ever-changing policy shifts and bonus programs. For example, one obsessively analytical contributor recently shared his meticulous records to illustrate his methods to maximize earnings (often grossing >$50 per online hour) at Uber’s expense. Similarly, Gridwise offers a useful app designed for mobility and delivery drivers to track their pay history and to receive tailored recommendations for improving productivity and compensation.

For passengers, Obi is a convenient and powerful tool for consumers to automatically request a ride with the provider offering the best price and service level for any given trip. The savings for consumers can be substantial. For example, a recent analysis of over 89,000 Obi trips with roughly equivalent wait times in Uber and Lyft’s four largest US markets in 2019 found that prices differed by >16% on more than half of all trips, and by >25% roughly one-third of the time. With Obi, the ability to find and book the best ridehail alternative for consumers is just one click away.

In short, Uber has every incentive to exploit discriminatory pricing policies, but the company can only succeed if passengers and drivers are willing to accept prices and pay on Uber’s terms. Fortunately, convenient tools are available to level the playing field.

Where are we headed?
In closing, it is useful to contrast Uber’s founding vision with where we are today. Travis Kalanick promised us a world where urban mobility would become as reliable as running water, with rideshare vehicles speeding along even at rush hour, enabling consumers to live, work and play wherever they want because low-cost, speedy transportation would always be just one app-tap away. Dara Khosrowshahi promised to add helicopters, drones, scooters, and bikes to the mix to make Uber the Amazon of transportation for the mass movement of people and goods. Summing up his vision in a candid interview with New York Times columnist Maureen Dowd last year, DK mused: “Right now, I dream about pushing a button and getting a piano delivered to your home in an hour and a half. I think that’d be really cool.”

But instead, Uber is still struggling to prove it can deliver a basic and economically viable ridehail and delivery business, while consumers are left to cope with increasingly costly and unreliable services, and drivers no longer know how much they can earn from trip-to-trip, let alone from week-to-week.

Urban mobility and last-mile delivery have proven to be tough businesses to crack. Uber is trying hard to tilt the deck in their direction. That’s understandable. So should you.
_________________________________________________________________

[1] In the P&L figure shown, Uber’s company-reported profitability has been adjusted in two ways to provide a more accurate reflection of its core business financial performance. First, the 2019 spike in stock-based compensation (SBC) the year Uber went public was adjusted to spread SBC evenly over four years to better reflect when RSUs were likely actually distributed. Second, the volatile unrealized gains and losses in the value of Uber’s non-controlling interest in securities of unrelated businesses have been removed from Uber’s operating income. Uber’s published profitability between 2014 and 2021 was inflated by $8.7 billion in unrealized gains on largely non-tradable securities it obtained in return for abandoning failed operations (e.g. China, Southeast Asia, autonomous vehicle research). In a major reversal, Uber’s reported Q1 2022 earnings were then reduced by $5.9 billion reflecting sharp declines in tech sector market values. These volatile swings in no way reflect Uber’s core business operating results and therefore have been removed in the figure displayed. For more detail, see https://www.nakedcapitalism.com/2022/02/hubert-horan-can-uber-ever-deliver-part-twenty-nine-despite-massive-price-increases-uber-losses-top-31-billion.html

[2] Take rates are defined as segment adjusted net revenue divided by gross bookings

[3] Uber typically cites vague figures on driver pay per utilized hour, but never per online hour — a more meaningful gauge of compensation and productivity.

[4] For example, since Uber doesn’t “own” its multi-homing drivers, Lyft can potentially access nearly as many drivers through its app as Uber, despite having only one-third Uber’s market share. Similarly, since many riders also dual-app and/or respond to frequent promotions from competitors, Uber faces perennially strong price competition.

[5] For example, drivers have reported receiving fewer or less attractive trip offers as they near a consecutive ride bonus (CRB) or being given time-consuming trip offers whose destination does not qualify towards a quest or CRB bonus. Uber does not report data on driver success rates on qualifying for bonus thresholds.

[6] As a relevant contrast, Southwest Airlines disrupted the airline industry by developing an asset-heavy operating strategy that structurally lowered unit costs while devoting obsessive attention to nurturing a customer-friendly employee culture. As a result, Southwest has enjoyed industry-leading profitability, shareholder value growth and employee retention in an industry known for challenging financial performance.