Uber President on Travis, China & Self-Driving | Why Autonomy Is Existential | How to Beat DoorDash

Andrew Macdonald: I think membership is the most efficient long-term consumer lever that we've got. And the reason for that is like ultimately we we are looking at like IGB as a critical input metric for any dollar I deploy... membership just gets better over time. The reason it gets better over time is, you know, if Harry becomes a member, not only do you ride more next month, but actually that cohort of members we acquired in that month tends to ride more over time. They can solve and part of that is because they're consolidating more of their mobility business onto Uber. Part of it is because actually that you get some Uber Eats benefits with your membership program, too. So now you start using Uber Eats instead of DoorDash or Deliveroo. And so the LTV of Harry just goes up over time with membership. You're less likely to churn. You're more resilient from a market share perspective. Like there's all these downstream long-term impacts that sort of multiply the value of that first dollar I put in.

Andrew Macdonald: Membership just gets better over time. The reason it gets better over time is, you know, if Harry becomes a member, not only do you ride more next month, but actually that cohort of members we acquired in that month tends to ride more over time. They can solve and part of that is because they're consolidating more of their mobility business onto Uber. Part of it is because actually that you get some Uber Eats benefits with your membership program, too. So now you start using Uber Eats instead of DoorDash or Deliveroo. And so the LTV of Harry just goes up over time with membership. You're less likely to churn. You're more resilient from a market share perspective. Like there's all these downstream long-term impacts that sort of multiply the value of that first dollar I put in.

Andrew Macdonald: It's like a class of classic innovator's dilemma problem, right? Which is like the thing you've already built is so big that it just swallows up your organizational capacity to do anything else. And even if you're able to stand up other businesses, it's impossible for those businesses to get the resourcing, attention, distribution, marketing dollars, engineering capacity, whatever it is, it just gets swallowed up by the whole. And part of it is just even management focus, right? Like it's very hard to focus on the new thing when you've got this like $225 billion blob you've got to manage over here. So, how do you solve that? I mean, we run a program called growth bets, which is, you know, intended very much to incubate new businesses within Uber.

Andrew Macdonald: It's like a class of classic innovator's dilemma problem, right? Which is like the thing you've already built is so big that it just swallows up your organizational capacity to do anything else. And even if you're able to stand up other businesses, it's impossible for those businesses to get the resourcing, attention, distribution, marketing dollars, engineering capacity, whatever it is, it just gets swallowed up by the whole. And And part of it is just even management focus, right? Like it's very hard to focus on the new thing when you've got this like $225 billion blob you've got to manage over here. So, how do you solve that? I mean, we we we run a program called growth bets, which is, you know, intended very much to incubate new businesses within Uber... basically what we try to do is, a um create dedicated resources. So, you know, if I've got 2,000 people, you know, made up number, but 2,000 people that work on our mobility business, I want to try to have, you know, 100 to 150 of them working on the new stuff, the small stuff, the stuff that we don't have product market fit or unit economics figured out, but that could be a big future business. Um but it requires like dedicated capacity and thinking.

Andrew Macdonald: I would say price. Um And the reason our IR team won't love that answer is because when you start talking about price in the context of public markets, people are like, 'Oh, you're going to get into a price war and like margins are going to come down and like it's a less attractive business.' But that's not really what I mean. What I mean by price is when you think about the businesses we operate, um primarily, you know, mobility and delivery, the vast majority of the transactions in delivery of things or the vast majority of the transactions in transportation broadly happen at a price point that is like way lower than our core products, right? Like taking an Uber X to and from work every day in New York City for like 35 bucks a direction, that's still a luxury product, right? The vast majority of transportation in New York City is not happening at that price point. And so, if we want to get to 500 million users, and we want to go from people using us on average, you know, six times a month to using us on average 25 times a month, the average cost of that transaction has to come down.

Andrew Macdonald: the car the car the individually owned car is the most inefficient asset that anyone owns, and certainly at any level of price point, right? It sits idle 98% of the day. Depreciating. It's depreciating. The ongoing operating costs are actually high, even if you're not driving it, you're paying for that insurance clip. Um which I which is why I do think in some future world, maybe not five years, but 15 or 20 years, everyone's going to be like Harry. Nobody's going to own a car. Nobody's going to have their driver's license because you'll be able to get around. And I think bikes and scooters will be part of that. I think autonomous vehicles will be part of that. I think public transportation will be a big part of that. But I I don't think you need to own a car.

Andrew Macdonald: All that is to say, I remember the last few weeks in the negotiation, we were burning 52 million a week in China just on price subsidies because there was this heated behind the scenes battle happening to get to the best economics in the ultimate sort of surrender or ultimate sort of truce. Um, so that was crazy. Another story I heard which I thought was nuts, and this was not a Uber story. But, you know, before like when when Uber and Didi did our deal, um, we were the two largest players. But before there was a third player, I think it was called Kuaidi, and Didi and Kuaidi merged. Um, and they sort of merged the companies, they did a deal, you're combining HR systems, and they realized that like of like the 2,000 employees here and the 2,000 employees here, there were like 200 employees that were on both payrolls.

Andrew Macdonald: I remember the last few weeks in the negotiation, we were burning 52 million a week in China just on price subsidies because there was this heated behind the scenes battle happening to get to the best economics in the ultimate sort of surrender or ultimate sort of truce. Um, so that was crazy. Another story I heard which I thought was nuts, and this was not a Uber story. But, you know, before like when Uber and Didi did our deal, we were the two largest players. But before there was a third player, I think it was called Kuaidi, and Didi and Kuaidi merged. Um, and they sort of merged the companies, they did a deal, you're combining HR systems, and they realized that like of like the 2,000 employees here and the 2,000 employees here, there were like 200 employees that were on both payrolls.

Andrew Macdonald: the point around like ROI, for me it's a couple things. One is at the end of the day, we do want to get efficiency, or we want to get new and cool stuff built, and we are seeing examples of that every single day. We have stood up a pod of 30 of our best AI engineers that are partnered with business people, or partnered with folks in the G&A functions, to go in and go process by process, and start sort of ground up with AI. How do you improve that process? And if you can take like a capital allocation process, like every week we're allocating pricing dollars across thousands of markets globally, and I can take that from being a 15-hour process to a 2-hour process, which is what we've done. That is tremendous tangible ROI, cuz now you get 2 days of someone's time back... the way companies ultimately have to extract AI efficiency, at least from like a pure OPEX perspective, is just in your target setting, hold the constraints tighter. Like, if we really believe that AI is making our employees 10% or 20% or 30% more efficient, then next year we should just not increase head count. Or we should increase it by 2% instead of 10%.

Andrew Macdonald: If you can take like a capital allocation process, like every week we're allocating pricing dollars across thousands of markets globally, and I can take that from being a 15-hour process to a 2-hour process, which is what we've done. That is tremendous tangible ROI, cuz now you get 2 days of someone's time back. Um if you're able to take a forecasting process, which our finance team is constantly reforecasting every inch of our business, uh and you're able to turn that from 8 hours of work into 2 hours of work, you're able to now do that not only with more precision, cuz you can put an additional layer of nuance into those forecasts, but you're just able to have your folks do other stuff. There's clear ROI there. If you're able to take marketing QA from 2 weeks to 2 days, like there's so many examples of that that we see.

Andrew Macdonald: The natural question is, 'Okay, great. Like, how many of those people can I take out of my organization so that I get the cost back and that flows through to the bottom line or I can put it into other things?' But formulaically doing that is really hard cuz guess what? The 8 hours of value that was created or the 8 hours of excess time gets filled with some other activity, which is also like presumably high value. And maybe before wouldn't have got done to or wouldn't have been done to a level of precision. So, it's just very hard. So, I think the way companies ultimately have to extract AI efficiency, at least from like a pure OPEX perspective, is just in your target setting, hold the constraints tighter.