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Uber’s Strategy for Global Success

How can Uber adapt its business model to compete in unique global markets?

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As Uber entered unique regional markets around the world – from New York to Shanghai, it has adapted its business model to comply with regulations and compete locally. As the transportation landscape evolves, how can Uber adapt its business model to stay competitive in the long term?

Harvard Business School assistant professor Alexander MacKay describes Uber’s global market strategy and responses by regulators and local competitors in his case, “ Uber: Competing Globally .”

HBR Presents is a network of podcasts curated by HBR editors, bringing you the best business ideas from the leading minds in management. The views and opinions expressed are solely those of the authors and do not necessarily reflect the official policy or position of Harvard Business Review or its affiliates.

BRIAN KENNY: The theory of disruptive innovation was first coined by Harvard Business School professor Clayton Christensen in his 1997 book, The Innovator’s Dilemma . The theory explains the phenomenon by which an innovation transforms an existing market or sector by introducing simplicity, convenience, and affordability where complication and high cost are the status quo. Think Netflix disrupting the video rental space. Over the years, the term has been applied liberally and not always correctly to other examples, but every so often, an idea comes along that really fits the bill. Enter Uber, the ridesharing behemoth that turned the car service industry on its head. In a few short years after launching in 2010, Uber became the largest car service in the world, as measured in ride count. Last year, Uber drove 6.2 billion riders. Today’s case takes us to London in 2019, where Uber is facing the latest in a long list of challenges from regulators threatening their ability to continue operating in that important market. In this episode of Cold Call , we welcome Alexander MacKay to discuss the case entitled, “Uber: Competing Globally.” I’m your host, Brian Kenny, and you’re listening to Cold Call on the HBR Presents network.

Alexander MacKay is in the strategy unit at Harvard Business School. His research focuses on matters of competition, including pricing, demand, and market structure. Alex, thanks for joining us on Cold Call today.

ALEX MACKAY: Thank you, Brian. Very happy to be here.

BRIAN KENNY: The idea of Uber seems so simple, but it was revolutionary in so many ways. And Uber has been in the headlines many times for both good and bad reasons in its decade of existence. So we’re going to touch on a lot of those things today. So thanks for sharing the case with us.

ALEX MACKAY: Brian, I’m very happy to. It’s a little funny, we’ve actually started to see the first few students who have never hailed a traditional taxi in our classrooms. So I think increasingly, the contrast between the two is going to be pretty difficult for people to fully understand.

BRIAN KENNY: Let me ask you to start by telling us what your cold call would be when you set up the class here.

ALEX MACKAY: The case starts off with the current legal battle going on in London. And so the first question I just ask to start the classroom is: What’s the end game for Uber in London? What do they look like 10 years from now? In the midst of this ongoing legal battle, there has been back and forth, some give and take from both sides, Transportation for London, and also on the Uber side as well. And there’s actually a recent court case that has allowed Uber to have a little more time to operate. They bought about 18 more months of time, but this has been also brought with additional, stricter scrutiny, and 18 months from now, they’re going to be at it again trying to figure out exactly what rules Uber’s allowed to operate under.

BRIAN KENNY: It seems like 18 months in the lifetime of Uber is like a decade. Everything seems to happen so quickly for this company. That’s a long period of time. What made you decide to write this case? How does it relate to the work that you’re doing in your research?

ALEX MACKAY: A big focus of my research is on competition policy, particularly the realms of antitrust and regulation. And here we have a company, Uber, whose relationship with regulation has been really essential to its strategy from day one. And I think appreciating the effects of regulation and how its impact Uber’s performance in different markets, is really critical for understanding strategy and global strategy broadly.

BRIAN KENNY:  Let’s just talk a little bit about Uber. I think people are familiar with it, but they may not be familiar with just how large they are in this space. And the space that they’ve sort of created has also blown up and expanded in many ways. So how big is Uber? Like what’s the landscape of ridesharing look like and where does Uber sit in that landscape?

ALEX MACKAY: Uber globally is the biggest ridesharing company. In 2018, they had over $10 billion in revenue for both ridesharing and their Uber Eats platform. And you mentioned in the introduction, that they had over 6 billion rides in 2019. That’s greater than 15 million rides every day that’s happening on their platform. So really, just an enormous company.

BRIAN KENNY: So they started back in 2010. It’s been kind of an amazing decade of growth for them. How do you explain that kind of rapid expansion?

ALEX MACKAY: They were financed early on with some angel investors. I think Kalanick’s background really helped there to get some early funding. But one of the critical things that allowed them to expand early into many markets that helped their growth was they’re a relatively asset light company. On the ground, they certainly need sales teams, they need translation work to move into different markets, but because the main asset they were providing in these different markets was software, and drivers were bringing their own cars and riders were bringing their own phones, the key pieces of hardware that you need to operate this market, they really didn’t have to invest a ton of capital. In fact, when they launched in Paris, they launched as sort of a prototype, just to show, “Hey, we can do this in Paris without too much difficulty,” as their first international market. So being able to really scale it across different markets really allowed them to grow. I think by 2015, their market cap was $60 billion, five years after founding, which is just an incredible rate of growth.

BRIAN KENNY: So they’re the biggest car service in the world, but they don’t own any cars. Like what business are they really in, I guess is the question?

ALEX MACKAY: They’re certainly in the business of matching riders to drivers. They’ve been able to do this in a way that doesn’t require them to own cars, just through the use of technology. And so what they’re doing, and this is I think pretty well understood, is that they’re using existing capital, people who have cars that may be going unused, personal cars, and Uber is able to use that and deploy that to give riding services to different customers. Whereas in the traditional taxi model, you could have taxis that you didn’t necessarily own, but you leased them or you rented them, but they had the express purpose of being driven for taxi services. And so it wasn’t using idle capital. You kind of had to create additional capital in order to provide the services.

BRIAN KENNY: So you mentioned Travis Kalanick a little bit earlier, but he was one of the co-founders of the company, and the case goes a little bit into his philosophy of what expansion into new markets should look like. Can you talk a little bit about that?

ALEX MACKAY: Certainly. Yeah. And I think it might even be helpful to talk a bit about his background, which I think provides a little more context before Uber. He dropped out of UCLA to work on his first company, Scour, and that was a peer-to-peer file sharing service, a lot like Napster, and actually predated Napster. And where he was operating was sort of an evolving legal gray area. Eventually, Scour got sued for $250 billion by a collection of entertainment companies and had to file for bankruptcy.

BRIAN KENNY: Wow.

ALEX MACKAY: He followed that up with his next venture, Red Swoosh, and that was software aimed at allowing users to share network bandwidth. So again, it was a little bit ahead of its time, making use of recent advances in technology. Early on though, they got in trouble with the IRS. They weren’t withholding taxes, and there were some other issues with his co-founder, and there was sort of a bad breakup between the two. Despite this, he persevered and ended up selling the company for $23 million in 2007. And after that, his next big thing was Uber. So one thing I just want to point out is that at all three of these companies, he was looking to do something that leveraged new technology to change the world. And by nature, sometimes businesses like that operate in a legal gray area and you have very difficult decisions to make. Some other decisions you have to make are clearly unethical and there’s really no reason to make some of those decisions, like with the taxes and with some other things that came out later on at Uber, but certainly one of the things that any founder who’s looking to change the world with a big new technology company has to deal with, is that often, the legal framework and the regulatory framework around what you’re trying to do isn’t well established.

BRIAN KENNY: Obviously drama seems to follow Travis where he goes. And his expansion strategy was pretty aggressive. It was almost like a warlike mentality in terms of going into a new market. And you could sort of sum it up as saying ask forgiveness. Is that fair?

ALEX MACKAY: Yeah. Yeah. Ask for forgiveness, not permission. I think they were really focused on winning. I think that was sort of their ultimate goal. We describe in the case there’s this policy of principle confrontation, to ignore existing regulations until you receive pushback. And then when you do receive pushback, either from local regulators or existing sort of taxicab drivers, mobilize a response to sort of confront that. During their beta launch in 2010, they received a cease-and-desist letter from the city of San Francisco. And they essentially just ignored this letter. They rebranded, they used to be UberCab, and they just took “Cab” out of their name, so now they’re Uber. And you can see their perspective in their press release in response to this. They say, “UberCab is a first to market cutting edge transportation technology, and it must be recognized that the regulations from both city and state regulatory bodies have not been written with these innovations in mind. As such, we are happy to help educate the regulatory bodies on this new generation of technology and work closely with both agencies to ensure compliance.”

BRIAN KENNY: It’s a little arrogant.

ALEX MACKAY: Yeah, so you can see right there, they’re saying, what we’re operating in is sort of this new technology-based realm and the regulators don’t really understand what’s going on. And so instead of complying with the existing regulations, we’re going to try to push regulations to fit what we’re trying to do.

BRIAN KENNY: The case is pretty epic in terms of it sort of cuts a sweeping arc across the world, looking at the challenges that they faced with each market they entered, and none more interesting I think the New York City, which is obviously an enormous market. Can you talk a little bit about some of the challenges they faced going into New York with the cab industry being as prevalent as it was and is?

ALEX MACKAY: Yeah, absolutely. I mean, I think it’s pretty well known for people who are familiar with New York that there were restrictions on the number of medallions which allowed taxis to operate. So there was a limited number of taxis that could drive around New York City. This restriction had really driven up the value of these medallions to the taxi owners. And if you had the experience of taking taxis in New York City prior to the advent of Uber, what you’d find is that there were some areas where the service was very, very good. Downtown, Midtown Manhattan, you could almost always find a taxi, but there are other parts of the city where it was very difficult at times to find a cab. And when you got in a cab, you weren’t sure that you were always going to be given a fair ride. And so Uber coming in and providing this technology that allowed you to pick up a ride from anywhere and sort of track the route as you’re going on really disrupted this market. Consumers love them. They had a thousand apps signups before they even launched. Kalanick mentioned this in terms of their launch strategy, we have to go here because the consumers really want us here. But immediately, they started getting pushback from the taxicab owners who were threatened by this new mode of transportation. They argued that they should be under the same regulations that the taxis were. And there were a lot of local government officials that were sort of mobilized against Uber as well. De Blasio, the Mayor of New York, wrote opinion articles against Uber, claiming that they were contributing to congestion. There was a lot of concern that maybe they had some safety issues, and the taxi drivers and the owners brought a lawsuit against Uber for evading these regulations. And then later on, and this was the case in many local governments, de Blasio introduced a bill to put additional restrictions on Uber that would make them look a lot more like a traditional taxi operating model, with limited number of licenses and strict requirements for reporting.

BRIAN KENNY: And this is the same scenario that’s going to play out almost with every city that they go into because there is such an established infrastructure for the taxi industry in those places. They have lobbyists. They’re tied into the political networks. In some instances, it was revealed that they’ve been connected with organized crime. So not for the faint of heart, right, trying to expand into some of the biggest cities in the United States.

ALEX MACKAY: Absolutely. Absolutely. And what’s sort of fascinating about the United States is it’s actually a place where a company can engage in this battle over regulation on the ground. And de Blasio writes his opinion article and pushes forward this bill. Uber responds by taking out an ad campaign, over $3 million, opposing these regulations and calling out de Blasio. So again, we sort of have this fascinating example of Uber mobilizing their own lobbyists, their lawyers, but also public advertising to sort of convince the residents of New York City that de Blasio and the regulators that are trying to come down on them are in the wrong.

BRIAN KENNY: Yeah. And at the end of the day, it’s consumers that they’re really making this appeal to, because I guess my question is, are these regulations stifling innovation? And if they are, who pays the ultimate price for that, Uber or the consumer?

ALEX MACKAY: Consumers definitely loved Uber. And I don’t think any of the regulators were trying to stifle innovation. I don’t think they would say that. I think their biggest concern, their primary concern was safety, and a secondary and related concern here was losing regulatory oversight over the transportation sector. So this is a public service that had been fairly tightly regulated for a long time, and there was some concern that what happens when this just becomes almost a free market sector. At the same time, these regulators have the lobbyists from the taxicab industry and other interested parties in their ear trying to convince them that Uber really is like a taxi company and should be regulated, and really emphasizing the safety concerns and other concerns to try to get stricter regulations put on Uber. And part of that may be valid. I think you certainly should be concerned about safety and there are real concerns there, but part of it is simply the strategic game that rivals are going to play between each other. And the taxicab industry sees Uber as a threat. It’s in their best interest to lobby the regulators to come down on Uber.

BRIAN KENNY: And what’s amazing to me is that while all this is playing out, they’re not turning their tails and running. They’re continuing to push forward and expand into other parts of the world. So can you talk a little bit about what it was like trying to go into countries in Latin America, countries in Asia, where the regulations and the regulatory infrastructure is quite different than it is in the US?

ALEX MACKAY: In the case, we have anecdotes, vignettes, one for each continent. And their experience in each continent was actually pretty different. Even within a continent, you’re going to have very different regulatory frameworks for each country. So we sort of pick a few and focus on a few, just to highlight how the experience is very different in different countries. And one thing that’s sort of interesting, in Latin America, we focus on Bogota in Colombia, and what’s sort of interesting there is they launched secretly and they were pretty early on considered to be illegal, but they continue to operate despite the official policy of being illegal in Colombia. And they were able to do that in a way that you may not be able to do it so easily in the United States, just because of the different layers of enforcement and policy considerations that are present in Colombia and not necessarily in the United States. Now, when I talk about the current state of Uber in different countries, this is continually evolving. So they temporarily suspended their operations early in 2020 in Columbia. Now they’re back. This is a continual back and forth game that they’re playing with the regulators in different markets.

BRIAN KENNY: And in a place like Colombia, are they not worried about violence and the potential for violence against their drivers?

ALEX MACKAY: Absolutely. So this is true sort of around the world. I think in certain countries, violence becomes a little bit more of a concern. And what they found in Colombia is they did have more incidents where taxi drivers decided to take things into their own hands and threaten Uber drivers and Uber riders, sometimes with weapons. Another decision Uber had to make that was related to that was whether or not to allow riders to pay in cash. Because in the United States, they’d exclusively used credit cards, but in Latin America and some other countries like India, consumers tended to prefer to use cash to pay, and allowing that sort of opened up this additional risk that Uber didn’t really have a great system in place to protect them from. Because when you go to cash, you’re not able to track every rider quite as easily, and there’s just a bigger chance for fraud or for robbery and that sort of thing popping up.

BRIAN KENNY: Going into Asia was also quite a challenge for them. Can you talk a little bit about some of the challenges they faced, particularly in China?

ALEX MACKAY: They had very different experiences in each country in Asia. China was a unique case that is very fascinating, because when Uber launched there, there were already existing technology-based, you might call them, rideshare companies, that were fairly prominent, Didi and Kuaidi, And these companies later merged to be one company, DiDi, which is huge. It’s on par with Uber in terms of its global presence as a ridesharing company. When Uber launched there, they didn’t fully anticipate all the changes they would have to make to going into a very different environment. In China, besides having established competitors, Google Maps didn’t work, and they sort of relied on that mapping software to do their location services. So they had to completely redo their location services. They also, again, relied on credit cards for payments, and in China, consumers increasingly used apps to do their payments. And this became a little bit of a challenge because the main app that Chinese customers used, they used WeChat and Alipay primarily, they were actually owned by parent companies of the rival ridesharing company. So Uber had to essentially negotiate with its rivals in order to have consumers pay for their ridesharing services. And so here are a few sort of localization issues that you could argue Uber didn’t fully anticipate when they launched. The other thing about competing in China that’s sort of interesting is that Chinese policy regarding competition is very different from policy in the United States and much of Europe. For the most part, there’s not the traditional antitrust view of protecting the consumers first and foremost. That certainly comes into play, but the Chinese government has other objectives, including promoting domestic firms. And so if you think about launching into a company where there’s a large established domestic rival that certainly increases the difficulty of success, because when push comes to shove, the government is likely to come down on the side of your rival, which is the domestic company, and not the foreign entrant.

BRIAN KENNY: Yeah, which is understandable, I guess, to some extent. This sounds exhausting, to be sort of fighting skirmishes on all these fronts in all these different places in the world. How does that affect the morale or tear at the fabric maybe of the culture at a company like Uber, where they’re trying to manage this on a global scale and running into challenges every step of the way?

ALEX MACKAY: It certainly has an effect. I think Uber did a very good job at recruiting teams of people who really wanted to win. And so, if that’s the consistent message you’re sending to your teams, then these challenges may be actually considered somewhat exciting. And so I think by bringing in that sort of person, I think they actually fueled this desire to win in these markets and really kept the momentum going. One of the downsides of this of course is that if you exclusively focus on winning and getting around the existing regulations, there does become this challenge of what’s ethical and what’s not ethical? And in certain business areas, there actually often is a little bit of a gray line. I mean, you can see this outside of ridesharing. It’s a much broader thing to think about, but regulation of pharmaceuticals, regulation of use of new technologies such as drones, often the technology outpaces the regulation by a little bit and there’s this lag in trying to figure out what actually is the right thing to do. I think it’s a fair question whether or not you can disentangle this sort of principle of confrontation that’s so pervasive throughout the company culture when it comes to regulation from this principle confrontation of other ethical issues that are not necessarily business driven, and whether or not it’s easy to maintain that separation. And I think that’s a fair question, certainly worthy for debate. But what I think is important is you can set up a company where you are abiding by ethical issues that are very clear, but you’re still going to face challenges on the legal side when you’re developing a new business in an area with new technology.

BRIAN KENNY: That’s a great insight. I mean, I found myself asking myself as I got through the case, I can’t tell if Uber is the victim or the aggressor in all of this. And I guess the answer is they’re a little bit of both.

ALEX MACKAY: Yeah. I think it’s fair to characterize them as an aggressor, and I think you sort of need to be if you want to succeed and if you want to change the world in a new technology area. In some sense, they’re a victim in that we’re all the victim as consumers and as firms of regulations that are sometimes difficult to adapt in real time to changing market conditions. And there’s a good reason why they are sticky over time, but sometimes that can be very costly. Going back to something we talked about earlier, I think there are hardly any consumers that wanted Uber kicked out of New York City. I think everyone realized this was just so much superior to any other option they had, that they were really willing to fight to keep Uber around in the limited ways they could.

BRIAN KENNY: So let’s go back to the central issue in the case then, which is, how important is it to them, in terms of their global strategy, to have a presence in a place like London? They’re still not profitable by the way, we should point that out, that despite the fact that they are the largest in the space, they haven’t turned the corner to profitability yet. I would imagine London’s kind of important.

ALEX MACKAY: Absolutely. London is a key international city, and a presence there is important for Uber’s overall brand. So many people travel through London, and it’s a real benefit for anyone who travels to be able to use the same service at any city you stop in. At the same time, they’re facing these increasing regulatory pressures from London, and so it’s a real question whether or not, 10 years from now, they look substantially different from the established taxi industry that’s there. And you can kind of see this battle playing out across different markets. As another example, in Ghana. When they entered there, they actually entered with a framework for understanding. They helped build the regulations for ridesharing services in Ghana when they entered. But over time, that evolved to additional restrictions as the existing taxi companies pushed back on them. So I think a key lesson here in all of this is that the regulations that you see at any given point in time aren’t absolutely fixed, for anyone starting a technology-based company, there will be regulations that do get created that affect your business. Stepping outside of transportation, we can see that going on now with the big tech firms and sort of the antitrust investigations they’re are under. And the policymakers in the US and Europe are really trying to evolve the set of regulations to reflect the different businesses that Apple, Facebook, Microsoft, Google are involved in.

BRIAN KENNY: One thing we haven’t touched on, and it’s not touched on in the case obviously because it just sort of started fairly recently, is the pandemic and the implications of the pandemic for the rideshare industry as fewer people find themselves in need of going anywhere. Have you given any thought to that and whether that’s going to have any effect on the regulations?

ALEX MACKAY: It certainly could. Uber is in a somewhat fortunate position, at least if you judge by their market capitalization, with respect to the pandemic. Initially their stocks took a pretty big hit, but rebounded pretty quickly, and part of this is because the primary part of their business is the transportation through Uber X, but they do also offer the delivery services through Uber Eats, and that business has really picked up during this pandemic. There’s certainly a mix of views about the future, but I think most people do believe that at some point we’ll get back to business as usual, at least for Uber services, when we come up with a vaccine. I think most people anticipate that they’ll be resuming use of Uber once it becomes safe to do so. And I think, to be frank, a lot of people already have resumed using Uber, especially people who don’t have cars or who see it as a valuable alternative or a safer alternative to public transit.

BRIAN KENNY: Yeah, that’s a really good point. And the Uber Eats thing is interesting as another example of how it’s important for businesses to re-imagine the business that they’re in because that, in many ways, may be helping them through a really tough patch here. This has been a really interesting conversation, Alex, I want to ask you one final question, which is, as the students are packing up to leave class, what’s the one thing you want them to take away from the case?

ALEX MACKAY: So I would hope the students take away the importance of regulation in business strategy. And I think the case of Uber really highlights that. And if you look at the conversation around Uber I’d say for the first 10 years of their existence, it was essentially around the superiority of their technology and not so much how they handled regulation. If you think back to the cease-and-desist letter that San Francisco issued in 2010, if Uber had simply stopped operations then, we wouldn’t have the ridesharing world that we have today. So their strategy of principle confrontation with respect to regulation was really essential for their future growth. Again, this does raise important ethical considerations as you’re operating in a legal gray area, but it’s certainly an essential part of strategy.

BRIAN KENNY: Alex, thanks so much for joining us on Cold Call today. It’s been great talking to you.

ALEX MACKAY: Thank you so much, Brian.

BRIAN KENNY: If you enjoy Cold Call, you might like other podcasts on the HBR Presents Network. Whether you’re looking for advice on navigating your career, you want the latest thinking in business and management, or you just want to hear what’s on the minds of Harvard Business School professors, the HBR Presents Network has a podcast for you. Find them on Apple podcasts or wherever you listen. I’m your host, Brian Kenny, and you’ve been listening to Cold Call , an official podcast of Harvard Business School on the HBR Presents Network.

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Uber: An Empire in the Making?

By: Salvatore Cantale, Sarah Hutton

The case study is set in early December 2014. Uber has just completed a round of funding and as a result has an eye-watering valuation of US$41 billion. The case initially explains the service Uber…

• Length: 8 page(s)
• Publication Date: May 25, 2015
• Discipline: Strategy
• Product #: IMD784-PDF-ENG

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The case study is set in early December 2014. Uber has just completed a round of funding and as a result has an eye-watering valuation of US$41 billion. The case initially explains the service Uber offered to its riders and then gives an overview of the origins and early growth of the company, as well as some insights into the influence of co-founder and CEO, Travis Kalanick, on the company culture. The following section outlines the characteristics of the traditional taxi industry, which was initially Uber's primary competitor. Details of Uber's disruptive business model are implicit in the case but the components are not spelled out to the reader. Rather, the intention is to draw this out in small group or plenary discussions through the assignment questions. The case goes on to review more recent growth, outlining some of the PR issues the company has faced with respect to aggressive business practices and questions around its data privacy policies. A possible softening of management's approach is suggested in the final section.

Learning Objectives

Participants gain insights into which components of Uber's business model were instrumental in disrupting an established and protectionist industry globally. They will also see how the model was continually evolving. Although Uber initially clearly operated in one closely defined sector, its future strategic direction lay in broader, diverse activities and markets. Participants will consider the strategic options for companies facing a new entrant that is re-inventing the rules of engagement.

May 25, 2015 (Revised: Dec 12, 2016)

Discipline:

Geographies:

United States

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Transportation and distribution

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The magic behind Uber’s data-driven success

Uber, the ride-hailing giant, is a household name worldwide. We all recognize it as the platform that connects riders with drivers for hassle-free transportation. But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success.

Uber’s DNA as an analytics company

At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B. With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price. But the simplicity ends there. Every transaction, every cent matters. A ten-cent difference in each transaction translates to a staggering $657 million annually. Uber’s prowess as a transportation, logistics and analytics company hinges on their ability to leverage data effectively.

The pursuit of hyperscale analytics

The scale of Uber’s analytical endeavor requires careful selection of data platforms with high regard for limitless analytical processing. Consider the magnitude of Uber’s footprint. 1 The company operates in more than 10,000 cities with more than 18 million trips per day. To maintain analytical superiority, Uber keeps 256 petabytes of data in store and processes 35 petabytes of data every day. They support 12,000 monthly active users of analytics running more than 500,000 queries every single day.

To power this mammoth analytical undertaking, Uber chose the open source Presto distributed query engine. Teams at Facebook developed Presto to handle high numbers of concurrent queries on petabytes of data and designed it to scale up to exabytes of data. Presto was able to achieve this level of scalability by completely separating analytical compute from data storage. This allowed them to focus on SQL-based query optimization to the nth degree.

What is Presto?

Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes. It excels in scalability and supports a wide range of analytical use cases. Presto’s cost-based query optimizer, dynamic filtering and extensibility through user-defined functions make it a versatile tool in Uber’s analytics arsenal. To achieve maximum scalability and support a broad range of analytical use cases, Presto separates analytical processing from data storage. When a query is constructed, it passes through a cost-based optimizer, then data is accessed through connectors, cached for performance and analyzed across a series of servers in a cluster. Because of its distributed nature, Presto scales for petabytes and exabytes of data.

The evolution of Presto at Uber

Beginning of a data analytics journey.

Uber began their analytical journey with a traditional analytical database platform at the core of their analytics. However, as their business grew, so did the amount of data they needed to process and the number of insight-driven decisions they needed to make. The cost and constraints of traditional analytics soon reached their limit, forcing Uber to look elsewhere for a solution.

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. While this side-by-side strategy enabled data capture, they quickly discovered that the data lake worked well for long-running queries, but it was not fast enough to support the near-real time engagement necessary to maintain a competitive advantage.

To address their performance needs, Uber chose Presto because of its ability, as a distributed platform, to scale in linear fashion and because of its commitment to ANSI-SQL, the lingua franca of analytical processing. They set up a couple of clusters and began processing queries at a much faster speed than anything they had experienced with Apache Hive, a distributed data warehouse system, on their data lake.

Continued high growth

As the use of Presto continued to grow, Uber joined the Presto Foundation, the neutral governing body behind the Presto open source project, as a founding member alongside Facebook. Their initial contributions were based on their need for growth and scalability. Uber focused on contributing to several key areas within Presto:

Automation: To support growing usage, the Uber team went to work on automating cluster management to make it simple to keep up and running. Automation enabled Uber to grow to their current state with more than 256 petabytes of data, 3,000 nodes and 12 clusters. They also put process automation in place to quickly set up and take down clusters.

Workload Management: Because different kinds of queries have different requirements, Uber made sure that traffic is well-isolated. This enables them to batch queries based on speed or accuracy. They have even created subcategories for a more granular approach to workload management.

Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data. Large, untested workloads run the risk of hogging all the resources. In some cases, the queries run out of memory and do not complete.

To address this challenge, Uber created and maintains sample versions of datasets. If they know a certain user is doing exploratory work, they simply route them to the sampled datasets. This way, the queries run much faster. There may be inaccuracy because of sampling, but it allows users to discover new viewpoints within the data. If the exploratory work needs to move on to testing and production, they can plan appropriately.

Security: Uber adapted Presto to take users’ credentials and pass them down to the storage layer, specifying the precise data to which each user has access permissions. As Uber has done with many of its additions to Presto, they contributed their security upgrades back to the open source Presto project.

The technical value of Presto at Uber

Analyzing complex data types with presto.

As a digital native company, Uber continues to expand its use cases for Presto. For traditional analytics, they are bringing data discipline to their use of Presto. They ingest data in snapshots from operational systems. It lands as raw data in HDFS. Next, they build model data sets out of the snapshots, cleanse and deduplicate the data, and prepare it for analysis as Parquet files.

For more complex data types, Uber uses Presto’s complex SQL features and functions, especially when dealing with nested or repeated data, time-series data or data types like maps, arrays, structs and JSON. Presto also applies dynamic filtering that can significantly improve the performance of queries with selective joins by avoiding reading data that would be filtered by join conditions. For example, a parquet file can store data as BLOBS within a column. Uber users can run a Presto query that extracts a JSON file and filters out the data specified by the query. The caveat is that doing this defeats the purpose of the columnar state of a JSON file. It is a quick way to do the analysis, but it does sacrifice some performance.

Extending the analytical capabilities and use cases of Presto

To extend the analytical capabilities of Presto, Uber uses many out-of-the-box functions provided with the open source software. Presto provides a long list of functions, operators, and expressions as part of its open source offering, including standard functions, maps, arrays, mathematical, and statistical functions. In addition, Presto also makes it easy for Uber to define their own functions. For example, tied closely to their digital business, Uber has created their own geospatial functions.

Uber chose Presto for the flexibility it provides with compute separated from data storage. As a result, they continue to expand their use cases to include ETL, data science , data exploration, online analytical processing (OLAP), data lake analytics and federated queries.

Pushing the real-time boundaries of Presto

Uber also upgraded Presto to support real-time queries and to run a single query across data in motion and data at rest. To support very low latency use cases, Uber runs Presto as a microservice on their infrastructure platform and moves transaction data from Kafka into Apache Pinot, a real-time distributed OLAP data store, used to deliver scalable, real-time analytics.

According to the Apache Pinot website, “Pinot is a distributed and scalable OLAP (Online Analytical Processing) datastore, which is designed to answer OLAP queries with low latency. It can ingest data from offline batch data sources (such as Hadoop and flat files) as well as online data sources (such as Kafka). Pinot is designed to scale horizontally, so that it can handle large amounts of data. It also provides features like indexing and caching.”

This combination supports a high volume of low-latency queries. For example, Uber has created a dashboard called Restaurant Manager in which restaurant owners can look at orders in real time as they are coming into their restaurants. Uber has made the Presto query engine connect to real-time databases.

To summarize, here are some of the key differentiators of Presto that have helped Uber:

Speed and Scalability: Presto’s ability to handle massive amounts of data and process queries at lightning speed has accelerated Uber’s analytics capabilities. This speed is essential in a fast-paced industry where real-time decision-making is paramount.

Self-Service Analytics: Presto has democratized data access at Uber, allowing data scientists, analysts and business users to run their queries without relying heavily on engineering teams. This self-service analytics approach has improved agility and decision-making across the organization.

Data Exploration and Innovation: The flexibility of Presto has encouraged data exploration and experimentation at Uber. Data professionals can easily test hypotheses and gain insights from large and diverse datasets, leading to continuous innovation and service improvement.

Operational Efficiency: Presto has played a crucial role in optimizing Uber’s operations. From route optimization to driver allocation, the ability to analyze data quickly and accurately has led to cost savings and improved user experiences.

Federated Data Access: Presto’s support for federated queries has simplified data access across Uber’s various data sources, making it easier to harness insights from multiple data stores, whether on-premises or in the cloud.

Real-Time Analytics: Uber’s integration of Presto with real-time data stores like Apache Pinot has enabled the company to provide real-time analytics to users, enhancing their ability to monitor and respond to changing conditions rapidly.

Community Contribution: Uber’s active participation in the Presto open source community has not only benefited their own use cases but has also contributed to the broader development of Presto as a powerful analytical tool for organizations worldwide.

The power of Presto in Uber’s data-driven journey

Today, Uber relies on Presto to power some impressive metrics. From their latest Presto presentation in August 2023, here’s what they shared:

Uber’s success as a data-driven company is no accident. It’s the result of a deliberate strategy to leverage cutting-edge technologies like Presto to unlock the insights hidden in vast volumes of data. Presto has become an integral part of Uber’s data ecosystem, enabling the company to process petabytes of data, support diverse analytical use cases, and make informed decisions at an unprecedented scale.

Getting started with Presto

If you’re new to Presto and want to check it out, we recommend this Getting Started page where you can try it out.

Alternatively, if you’re ready to get started with Presto in production you can check out IBM watsonx.data , a Presto-based open data lakehouse. Watsonx.data is a fit-for-purpose data store, built on an open lakehouse architecture, supported by querying, governance and open data formats to access and share data.

1 Uber. EMA Technical Case Study, sponsored by Ahana. Enterprise Management Associates (EMA). 2023.

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Uber business model explained: from start to finish.

By  Nitin Lahoti   In  Blog   Posted  January 2, 2019

What Is Uber’s Business Model? How Uber Works? How Does Uber Make Money? What Is Uber’s Business Strategy? Why Is Uber so Successful?

These are some of the major questions any budding entrepreneur in the on-demand startup space would be curious about, before working on his/her own “Uber for X” business model.

And, rightly so.

Uber’s business model has turned out to be so successful and popular that it has fuelled a new startup economy, the “on-demand economy”.

Having a deeper understanding of Uber’s on-demand business model can play a pivotal role in modeling your own on-demand startup business idea.

As a leading on-demand startup technology development partner, we want to share this knowledge with you through this comprehensive blog post.

Uber Basics – Facts, Figures, Founders & Fundings

Before drilling down into “Uber’s business model” or “How Uber makes money?”, let us gain knowledge about some basics and interesting facts about Uber – from inception to being a multi-billion dollar startup.

Some Trivia

Did you know that Uber was initially called as UberCab?

Originally, the app only had the option to hail a black luxury car.

Founders – Garrett Camp, Oscar Salazar, Travis Kalanick

Founding Year – March 2009

Headquarters – San Francisco Bay Area, U.S.A

Legal Name – Uber Technologies Inc. (Crunchbase)

Total Funding – $24.2B (In 22 funding rounds as of Oct 2018, Crunchbase )

Major Investors – SoftBank Vision Fund, Tencent Holdings, Toyota Motor Corporation, and others.

Current Valuation – $120B (Source – Bloomberg )

Uber’s Business Model – How Uber Works?

Uber is no longer just the on-demand cab hailing service we used to know. It has dipped its toes into other territories as well – from Uber Eats (on-demand food delivery) to Uber Freight (on-demand trucking).

For the matter of simplicity, in this blog, we will focus on Uber’s core business of ridesharing – its business model and how it makes money?

To put it in simple words,

Uber works as a digital aggregator app platform, connecting passengers who need a ride from point A to point B with drivers that are willing to serve them.

“ Passengers ” generate the demand, “ Drivers ” supply the demand and “ Uber ” acts as the marketplace/facilitator to make this all happen seamlessly on a mobile platform.

Kool, right?

Through its model, Uber has been able to generate strong value propositions for both passengers and drivers to get onboard on its platform and create disruption in the taxi/cab industry.

Uber’s Value Proposition for Passengers

• On-demand cab bookings (Convenient)
• Real-time tracking
• Accurate ETAs
• Cashless rides
• Lower wait time for a ride
• Upfront pricing
• Multiple ride options

Uber’s Value Propositions for Drivers

• Flexibility to drive on their own terms
• Better income
• Lower idle time to get new rides
• Training sessions
• Assistance in getting vehicle loans
• Better trip allocation

Uber’s Business Model Canvas – A Visual Snapshot

Click to Enlarge Image

Digging Deep Into Uber’s Revenue Sources – How Uber Makes Money?

At a high level, Uber makes money by taking a cut on each ride (shared or individual) from the drivers. However, as we do a detailed analysis we will found that Uber’s revenue model is more complex than just trip commissions.

Trip Commissions

Uber provides the drivers on its platform (also called as partners) with a robust supply of ride requests to accept, fulfill, and make income. While making a booking, the passenger pays Uber for the ride through the app. Uber then transfers the payment to the partner’s account after taking some amount of commission for doing the job of a broker (digital broker if you want to say so).

The commission rates may vary from 15-30 % depending on the market.

Surge Pricing

Dynamic pricing/ surge pricing is a novel concept that has been popularized by Uber and being adopted in other verticals as well, such as food delivery.

Whenever there is a higher demand for cabs than what can be served at that moment (for example, at the airport after a flight lands), the fare goes up based on a surge price calculation algorithm.

Some drivers move to the surge region to earn extra (increases supply) and some passengers opt to wait to get a ride (reduces demand). This way Uber is able to manage the demand-supply mismatch situation better.

Drivers make more money, Uber makes more money and customers spend more money (but get urgent rides).

Premium Rides

Uber offers multiple ride options, from affordable hatchbacks to luxury sedans and SUVs. The profit margin for premium rides are much higher and helps Uber mint more money.

Cancellation Fee

If a passenger cancels a ride after a certain time-frame, say five minutes, he/she is charged a cancellation fee.

Leasing to Drivers

Uber runs a vehicle leasing program in many of its target countries to help new drivers get onboard faster. Drivers have to pay an upfront security deposit for the vehicle and payments are automatically deducted on a weekly basis from the driver’s earnings.

Brand Partnerships/Advertising

Uber is a very popular app with millions of active users. This makes it a good option for brands to do promotions. Its current app interface pushes a feed style layout for intuitive content consumption. Over the period, it may go on to become a strong revenue source by becoming a channel for sponsored content.

Expanding Rapidly With New Business Verticals

As mentioned earlier above, Uber is now much more than just a ridesharing company. It is leveraging it’s underlying technology for cab bookings, like, optimal driver allocation, to new use cases as well.

These new businesses that Uber is building side-by-side have tremendous potential to generate revenue and fuel Uber’s grand ambitions.

Uber is betting big on on-demand food delivery and why not. It’s a logical step for Uber to tap into this enormous market as it aligns with its ridesharing business and helps it utilize its large fleet of drivers. Uber Eats was launched as a separate app in 2016 and is growing in popularity at a rapid rate.

Uber Freight

Uber Freight is basically Uber for trucks. Uber launched its own on-demand trucking app in 2017 with the core idea of seamlessly matching shippers with carriers. If Uber can execute on its strategy to become the freight matching platform of choice, the revenue opportunities are also big.

Key Takeaways for Budding Entrepreneurs From Uber’s Business Model Analysis

Uber got a lot right in its journey towards becoming a pioneer in the on-demand industry today. It has seen its fair share of challenges over the period and been able to maneuver through most of them successfully.

It is a great testament of a tech startup that achieved success with a novel business model and smart execution.

Interesting Read: How to Build an App Like Uber?

Tech entrepreneurs and startups can learn a lot from studying Uber’s business case study. We have tried to make the job easy by putting down a list of key takeaways/ tips from analyzing Uber’s massive success.

Let’s check them out below.

Build Solutions for Real-world Problems

This is somewhat obvious but still needs to be mentioned first. You as an entrepreneur should identify real problems and figure out how technology can be leveraged to solve it, just like Uber used mobile technology to transform on-demand transportation.

Keep Innovating

Uber doesn’t rest on its laurels of being the first prominent rideshare app. Its founders understood really well that the competition will grow over time and they can only stay ahead through continuous product iterations. They keep adding new features to their passenger and driver apps, invest in new technologies and more.

Shoot for Scalability

Building a scalable business model is critical if you are to sustain your startup in the long run. Uber has built its platform in such a way that it is easy for it to expand to new markets and serve multiple users simultaneously with confidence.

Keep Overhead Costs Low

Run a lean business model that doesn’t require large infrastructural investments. Also, for building a tech startup, a skilled workforce is very crucial. This also adds up to your cost overheads in terms of high salary payments. One effective way to stay lean during the initial stages of your product development is by partnering with a third-party technology development company to build the MVP and overtime do in-house hiring.

Wrapping Up!!

The proliferation of the on-demand industry owes a lot to Uber and rightfully so. Uber’s success in many ways started a chain reaction with hundreds of on-demand/ Uber for “X” startups been launched after that and hopefully many more to come.

Specifically, in the on-demand transportation and logistics industry, the effect has been profound. We hope that our analysis of Uber’s business model will become a useful resource for upcoming on-demand startups.

Disclaimer : The information mentioned in this blog is based on the author’s own understanding of Uber’s business model. The facts and figures have been obtained from online research with appropriate credits given wherever required. Please use the information at your own discretion with no liability on the author or the firm.

Author's Bio

Nitin Lahoti is the Co-Founder and Director at Mobisoft Infotech . He has 15 years of experience in Design, Business Development and Startups. His expertise is in Product Ideation, UX/UI design, Startup consulting and mentoring. He prefers business readings and loves traveling.

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