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Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Masters in

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Speaker 1: Business with Barry Ritholts on Bloomberg Radio.

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Speaker 2: This week on the podcast Man, was this a fascinating conversation?

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Speaker 2: David Rischer is CEO of Lift since the past three years.

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Speaker 2: He's been on the board for the past five years.

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Speaker 2: What a fascinating discussion about a company that is probably

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Speaker 2: an app on your phone and you may not be

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Speaker 2: aware of all the different things they do, from bike

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Speaker 2: share to autonom's vehicles, to fleet management and everything in between.

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Speaker 2: I thought this was absolutely fascinating, and I think you

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Speaker 2: will also with no further ado, my conversation with Lift's

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Speaker 2: CEO David Risher.

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Speaker 3: Thank you, Berry, Hi, I'm happy to be here.

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Speaker 2: I'm thrilled to have you. Before we start talking about

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Speaker 2: your technology background, I got to roll a little further back.

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Speaker 2: Bachelor's in comparative literature from Princeton. That doesn't sound like

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Speaker 2: the sort of career plan for someone who's going to

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Speaker 2: work his way through technology companies. What was the original idea?

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Speaker 3: So this goes way back, and the funny thing is

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Speaker 3: even to high school. My mother bought an Apple to

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Speaker 3: computer a million years ago to help her run a

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Speaker 3: small business that she was running, and I sort of

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Speaker 3: got into technology that way. I will admit. Part of it,

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Speaker 3: I think is I had terrible handwriting, and so when

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Speaker 3: I used the computer to you know, to print out stuff,

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Speaker 3: you know from my high school, you know, English teacher,

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Speaker 3: she could finally read what I was what I was writing.

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Speaker 3: Probably gave me a better grade as a result. But

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Speaker 3: so I sort of got into computers a little bit

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Speaker 3: as a kid, ended up at Princeton writing my thesis

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Speaker 3: on a computer again, and this is a million years

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Speaker 3: ago when that wasn't normal. And so I found myself

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Speaker 3: just interested in technology. And after you know, going to

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Speaker 3: a consulting firm for a couple of years to learn

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Speaker 3: about the business world and going to business school, I

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Speaker 3: found myself as an intern at Microsoft, you know again

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Speaker 3: back in nineteen ninety it was and sort of the

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Speaker 3: rest is history.

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Speaker 2: So Harvard Business School, we know what that typically leads to.

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Speaker 2: I'm curious, how did the humanity's background help shape the

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Speaker 2: way you think about business, about leadership, about working with people.

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Speaker 2: What was the upside of humanities for you?

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Speaker 3: You know what. I really appreciate the question, and I

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Speaker 3: actually think it's it's more relevant now than ever. Look,

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Speaker 3: the humanities is all about, you know, curiosity and understanding

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Speaker 3: and maybe even empathy. Right, If you read a book,

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Speaker 3: you have to understand you're exposed to different people's perspectives. Right,

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Speaker 3: It's almost like you're crawling inside someone else's brain, particularly

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Speaker 3: if you're reading fiction. And so to a certain extent,

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Speaker 3: I think it's you know, nothing could prepare you better.

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Speaker 3: Now you have to have an analytical brain. You might

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Speaker 3: also have to be good with numbers in business. But

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Speaker 3: the humanities world, I sort of think of it as

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Speaker 3: this kind of magic. You know, vaccination against irrelevant because

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Speaker 3: that curiosity is always going to matter, and it certainly

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Speaker 3: helped me through my whole, my whole career.

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Speaker 2: I love that answer. So you intern at Microsoft, you

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Speaker 2: end up beginning your career there where you helped to

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Speaker 2: launch their first database product, Access. Tell us about that.

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Speaker 3: Sure, So Microsoft was, you know, famously ahead in or

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Speaker 3: at least getting ahead, let's say, with the launch of

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Speaker 3: Windows in word processing, in spreadsheets, of course, And again

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Speaker 3: this is sort of ancient business history, but it's it's

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Speaker 3: sort of a fascinating tale of a technology shift completely

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Speaker 3: reshuffling the deck away from old companies like word Perfect

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Speaker 3: and Lotus one, two three. We don't even know who

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Speaker 3: those companies are anymore because Microsoft took over that space,

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Speaker 3: and it's really because Windows shifted the platform. We might

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Speaker 3: come back to that idea, you know when we talk

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Speaker 3: about autonomous cars, but they didn't have a database, and

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Speaker 3: that was sort of the third big product that a

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Speaker 3: lot of companies wanted. I helped develop it. I was

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Speaker 3: the first product manager on them. And really all that

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Speaker 3: meant is my job was to go around and watch

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Speaker 3: other people you use competing products at the time paradox

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Speaker 3: debase again, products that don't even exist anymore, and try

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Speaker 3: to pay attention to what they were doing with these products,

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Speaker 3: how were they using them, where were they stumbling? And

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Speaker 3: that was my first role, and in a sense it

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Speaker 3: has been, you know, one of the most important jobs

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Speaker 3: I ever had, because it's what sort of taught me

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Speaker 3: about understanding what customers want.

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Speaker 2: Huh. Interesting, And then you founded Microsoft Investor and launched

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Speaker 2: that product. Yeah, that is so far afield from databases.

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Speaker 2: What led to that transition?

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Speaker 3: Okay, so you're making me realize that there's a theme

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Speaker 3: of my life. I hadn't really thought of before, which

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Speaker 3: is platform ships. So when I joined Microsoft, Windows was

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Speaker 3: the product, right, this was the thing that was going

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Speaker 3: to run you know, software, And of course it become

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Speaker 3: incredibly successful. But then, you know, nineteen ninety five, ninety

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Speaker 3: ninety six, ninety ninety seven comes around, the Internet is here,

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Speaker 3: and Microsoft, like any tech company at the time, had

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Speaker 3: to figure out its Internet strategy, and it decided that

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Speaker 3: there were a couple of key products that needed to

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Speaker 3: be available on the World Wide Web. Again, I think

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Speaker 3: the Information super Highway literally was the way people talked

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Speaker 3: about it is crazy, so cliche, so cliche, but there

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Speaker 3: it was no one even knew how to talk about

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Speaker 3: the thing. So anyway, and I had been, you know,

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Speaker 3: a little bit interested in personal finance. U you know,

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Speaker 3: a couple of star threads came together. Microsoft tried to

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Speaker 3: buy a company called into It so very successful, was unsuccessful,

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Speaker 3: blocked because of the Justice Department. And so we decided

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Speaker 3: we need personal finance. And I said, you know what,

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Speaker 3: why don't we develop this product a personal finance product

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Speaker 3: for the Internet, not as package software.

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Speaker 2: Huh really really interesting. And then staying with the theme

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Speaker 2: of platform shifts. Employee number thirty seven at Amazon that

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Speaker 2: is just an absolutely bonker's number. Yeah, senior VP of

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Speaker 2: US Retail. When you joined the firm, revenue was fifteen

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Speaker 2: million dollars. You helped ramp that up to four billion dollars.

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Speaker 2: So that's right obvious question. When you join Amazon, did

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Speaker 2: you have any idea with the behemoth it would become

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Speaker 2: or was it still hey, we're hanging on our fingernails

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Speaker 2: and maybe this will work out, or anywhere in between.

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Speaker 3: It was sort of both at the same time, you know,

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Speaker 3: and it was almost always going to be one or

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Speaker 3: the other. Right, So I remember, I'll tell you a

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Speaker 3: little of the story of how I got there. So

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Speaker 3: my phone ring one day at Microsoft and it's this guy, Jeff,

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Speaker 3: and he's doing a reference check of a woman who

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Speaker 3: used to work actually at Microsoft in the personal finance group.

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Speaker 3: So it all kind of connects, and so we get

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Speaker 3: to talking and one thing leads to another, and he's

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Speaker 3: very precise about the way he's asking questions. Remember, the

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Speaker 3: company had maybe ten people at this point, was very

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Speaker 3: very small, very very small. But he had a big vision.

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Speaker 3: You know, he was going to be Earth's biggest bookstore.

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Speaker 2: Wait, hold on, let me just stop you. When you

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Speaker 2: say this guy Jeff. Yeah, this isn't just some guy

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Speaker 2: in HR Jeff Bezos is calling you to do a

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Speaker 2: background check on a potential hire.

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Speaker 3: That's exactly it. That's exactly so go on, Jeff. So

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Speaker 3: Jeff calls me. At the time, he was just this

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Speaker 3: guy Jeff.

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Speaker 2: Hey, David, some guy named Jeff on the phone, pretty

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Speaker 2: much back background check for an employee. So what was

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Speaker 2: that conversation?

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Speaker 3: Like, well, so he had, you know, to take you

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Speaker 3: back then, but in a sense, it's still the Jeff

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Speaker 3: you know today. He had a plan and it was

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Speaker 3: a twenty five question plan for the phone call, right

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Speaker 3: and to this day, the question I remember the most

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Speaker 3: clearly was it's very clear you were a fan of

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Speaker 3: this person. Give me an example of a job that

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Speaker 3: she wouldn't be a good fit for. And it was

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Speaker 3: such a clever question because inevitably in background checks you're

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Speaker 3: trying to say nice things about the person. But this

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Speaker 3: is an invitation to say, well, you know, maybe you know,

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Speaker 3: a very detail oriented job might not be the best fit,

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Speaker 3: or maybe something that you know manages a lot of people,

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Speaker 3: because she has something like this that would give people

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Speaker 3: a little sense or give him some sense of where

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Speaker 3: an area to probe mort is. Anyway, at the end

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Speaker 3: of that conversation, literally forty five minutes into it, he says,

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Speaker 3: you know, you sound like a good guy. Said, oh,

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Speaker 3: you sound like a good guy as well. And so

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Speaker 3: a couple of days later, he and McKenzie his wife

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Speaker 3: at the time, and Jen my wife currently still and

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Speaker 3: I went out to dinner, got to know each other,

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Speaker 3: and over the course of the next year, got to

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Speaker 3: know each other a little bit better. And then I

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Speaker 3: ended up applying for this job to help to help

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Speaker 3: Amazon grow beyond just books. That was really the job.

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Speaker 2: And how'd that work out? Worked out?

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Speaker 3: Pretty well? Yeah, it worked out pret but you know what,

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Speaker 3: it wasn't obvious at the time. So, you know, he

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Speaker 3: during the interview, I remember, he said, look, if we

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Speaker 3: play our cards right, and as you say, it was

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Speaker 3: a fifteen point six million dollar store at the time,

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Speaker 3: so tiny, tiny little thing. He said, if we play

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Speaker 3: our cards right, maybe by the year two thousand, this

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Speaker 3: is a nineteen ninety six, we might be a billion

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Speaker 3: dollar company. Maybe maybe, but a lot has to go

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Speaker 3: right in order for that to happen. Obviously, we got there,

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Speaker 3: and then we got you know, far beyond. But there

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Speaker 3: were all kinds of people who, frankly were sort of

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Speaker 3: rooting for our failure. You know, competitors, you know, Barnes

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Speaker 3: and Noble at the time, a bunch of Wall Street

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Speaker 3: analysts who thought this was just you know, some sort

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Speaker 3: of crazy ponzis. Can know where it was.

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Speaker 2: Buy anything on the Internet. What are you guys doing?

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Speaker 2: This is a dumb idea.

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Speaker 3: Yeah, totally, totally well. And not only that, but also

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Speaker 3: the costs are going to be huge. You're gonna have

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Speaker 3: to build out of the distribution centers and warehouses sometime.

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Speaker 3: You know, this cost of it. The internet is unproven technology,

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Speaker 3: all sorts of things.

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Speaker 2: No one's giving you a credit card over the correct

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Speaker 2: I remember getting from my college roommate, which was decades

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Speaker 2: before Amazon formed an Amazon Gift certificate. And the first

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Speaker 2: time you go through the experience of buying something, it's like, oh,

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Speaker 2: this makes perfect sense. I don't have to I don't

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Speaker 2: have to go to the store, I don't have to

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Speaker 2: waste time. This is great. I mean, there's certain stores

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Speaker 2: are fun to browse, but like the mundane sort of stuff.

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Speaker 2: He was just decades ahead of everybody else.

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Speaker 3: In that way, and in realizing that it's really the

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Speaker 3: customer experience and customer obsession that's going to drive your

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Speaker 3: continued growth because all those things are true. And as

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Speaker 3: he would say famously, you're always one click away from competition.

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Speaker 3: So that's the downside, right is how do you continue

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Speaker 3: to compete in a world where theoretically someone else could

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Speaker 3: start having someone else could start, and someone else can start,

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Speaker 3: and you don't have any geographic advantage over them.

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Speaker 2: And they kind of owned that space for the longest time. Really,

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Speaker 2: it was only the pandemic where people were out of

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Speaker 2: things that it forced everybody all right, now I have

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Speaker 2: a Target account, Now I have a Walmart account, Now

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Speaker 2: anybody else who could deliver. And what's been surprising is

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Speaker 2: how they've just powered right through hasn't really slowed them

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Speaker 2: down very much.

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Speaker 3: That's right, that's right.

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Speaker 2: So you go from Amazon, you kind of tap out.

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Speaker 2: A couple of years later, you teach at the University

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Speaker 2: of Washington's Business School. You were elected Professor of the

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Speaker 2: Year in two thousand and four, and then you spend

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Speaker 2: thirteen years running World Reader, a nonprofit dedicated to helping

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Speaker 2: children learn to read and underserved communities. This is yet another.

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Speaker 3: Chef, right, yep?

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Speaker 2: What was it? Just like, all right, I have my

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Speaker 2: Microsoft stock, came in Amazon recovered from the dot com implosion.

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Speaker 2: That's doing fine. I could just do something for fun.

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Speaker 2: What was the what was the shift? Thinking behind the shift?

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Speaker 3: You know, you know, it wasn't that. Actually it was

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Speaker 3: sort of a different thing. So you asked me, you know,

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Speaker 3: a couple of questions ago, what my career idea was

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Speaker 3: as a kid. Honestly, if I had had to guess,

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Speaker 3: I might have said, you know, I'll be maybe I'll

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Speaker 3: be an English professor someday or something like that. Like

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Speaker 3: I'd wanted to teach and I loved reading, and so

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Speaker 3: this was a way for me to bring together a

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Speaker 3: couple of different things in my life. Obviously books and

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Speaker 3: literacy because that was sort of the passion and focus,

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Speaker 3: but also technology. The thesis of the company was kids

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Speaker 3: are going to read using tech, and that's how it's

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Speaker 3: gotten to be, you know, millions and millions of kids

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Speaker 3: later are all reading on the platform. It started out

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Speaker 3: with Kindle, a product I know something about because of

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Speaker 3: my Amazon days, and brought you know, sort of technology

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Speaker 3: and reading together. So that was really the focus.

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Speaker 2: And then what ultimately ended up bringing you back into

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Speaker 2: the corporate sector after you know, a long time. I'm

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Speaker 2: in academia and nonprofits.

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Speaker 3: Yeah, so so here it was. You know, one day

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Speaker 3: my phone rings and a guy named Sean agerwal Is

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Speaker 3: on the other end of the line. Sean and I

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Speaker 3: had worked together many years before, back at Amazon. He

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Speaker 3: was my kind of finance partner. He had subsequently become

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Speaker 3: an investor and then the board chair of Lyft, and

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Speaker 3: he and John and Logan the co founders of Lyft.

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Speaker 3: Really we're looking to do something quite unusual at the

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Speaker 3: board level, which was bring someone in who is a

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Speaker 3: real customer advocate. So boards, you know, for those of

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Speaker 3: you who haven't gotten a chance to be exposed to

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Speaker 3: a board, you know, they typically are made up by

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Speaker 3: you know, kind of finance people, you know, business strategists,

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Speaker 3: you know, maybe you know, maybe people who have built

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Speaker 3: companies before. But often by the time you get to

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Speaker 3: sort of the board level of a company, you're pretty

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Speaker 3: far away from the customer. And John and though and

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Speaker 3: again to their credit, said you know what, we need

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Speaker 3: some more customer advocacy right from the top. We need

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Speaker 3: some more support frankly for that kind of vibe as

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Speaker 3: well as someone who'd helped scale a company like Amazon.

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Speaker 3: You know, I also learned a lot about competing at

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Speaker 3: Microsoft and even at world Reader. You know World Reader nonprofits.

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Speaker 3: People sort of look at them and think they're not

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Speaker 3: very much. But it's very, very difficult to actually scale

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Speaker 3: a nonprofit because the funding is always tightened so forth.

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Speaker 3: So I think they were looking for someone with a

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Speaker 3: combination of scaling experience but also real customer advocacy, and

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Speaker 3: so I joined the board as a result.

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Speaker 2: And then eventually a couple of years later, you get

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Speaker 2: offered the role of CEO. What was that, like? How

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Speaker 2: did that come about? Frequently board members, or I should

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Speaker 2: say infrequently board members become CEO. Is that doesn't sound usual?

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Speaker 3: Yeah? Yeah, so finnally enough. And this one, I'll sort

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Speaker 3: of slow the story down again or this time because

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Speaker 3: it actually was Sean Agerwall again. So same board chair,

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Speaker 3: he calls me up. It happened to be on Valentine's Day,

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Speaker 3: of all day, so I remember the day in twenty

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Speaker 3: twenty three. And then the backstory here is John and

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Speaker 3: Logan again, the co founders have left. This is what

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Speaker 3: they had been doing for fifteen years, NonStop. It was

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Speaker 3: literally their first job out of college founding this whole

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Speaker 3: new company. You know, was standing the onslaugh on an

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Speaker 3: incredibly competitive environment, an incredibly operationally complex environment, twenty four

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Speaker 3: hours a day, seven days a week, for a year.

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Speaker 3: After a year, so at the end of the prior year,

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Speaker 3: they said to the board, you know what, it's time

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Speaker 3: for us to move on. We've sort of done what

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Speaker 3: we need to do. And frankly, the company is going

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Speaker 3: through a bit of a tough time financially and operationally,

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Speaker 3: and I think they realized that they were sort of

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Speaker 3: getting to the end of what they could really where

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Speaker 3: they could really help. So the board did what it does.

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Speaker 3: You know, boards do this. They form a special committee,

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Speaker 3: they start to recruit look around. I wasn't on the committee.

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Speaker 3: I was sort of watching, you know, from from a side.

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Speaker 3: But as they say, then my phone rings one day

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Speaker 3: and a Shawan on the phone with John and Logan

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Speaker 3: and they basically say, you know what we've been thinking

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Speaker 3: and as we've been looking at external people, frankly, we

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Speaker 3: think we might have the right person to at least

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Speaker 3: apply for the job. Let's be clear, apply for the

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Speaker 3: job sitting right here, you know, on the board and

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Speaker 3: I said, what are you talking about? They said, we're

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Speaker 3: talking about you, David. I said, absolutely not really. Your

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Speaker 3: frust reaction was, hey, thanks, but no things. Zero percent chance,

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Speaker 3: zero percent. Wow. I literally said, you should hang up

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Speaker 3: the phone right now because you got better things to do.

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Speaker 3: There's just no way. But you know what, as the

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Speaker 3: day wore on, I found myself saying, you know what,

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Speaker 3: this is a really interesting opportunity. How many people, you know,

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Speaker 3: get this opportunity to run it? And I never run

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Speaker 3: a public company before. I mean, my god. But at

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Speaker 3: the same time, I had learned some things at Microsoft,

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Speaker 3: I learned some things at Amazon, I learned some things

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Speaker 3: at World Reader. I learned some things in various different

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Speaker 3: ways of my life. And I had a lot of

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Speaker 3: passion for the company having been on the board, and

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Speaker 3: also a real understanding that as a board member you

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Speaker 3: really only have so much power and influence. It's fairly limited.

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Speaker 3: But as a CEO it's a different thing. So anyway,

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Speaker 3: one thing led to another. I applied and went through

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Speaker 3: kind of a harrowing experience but ended up getting the job.

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Speaker 2: Huh really really fascinating. So we mentioned earlier you joined

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Speaker 2: the board in twenty twenty one, you're named CEO in

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Speaker 2: twenty twenty three. When you joined the company, they were

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Speaker 2: still reeling from the pandemic and all the factors that

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Speaker 2: that drove the company was losing not only losing money

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Speaker 2: but also losing market share to their big competitor Uber.

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Speaker 2: What did you find when you looked under the hood?

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Speaker 2: What surprises were awaiting you as CEO?

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Speaker 3: So the first maybe meta observation, and you're teeing it up,

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Speaker 3: is gosh, you're on the board of a company for

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Speaker 3: a couple of years. You kind of think you know

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Speaker 3: the company. You don't really know the company. I mean,

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Speaker 3: if any board members are out there, you think you do,

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Speaker 3: and you probably have a pretty good sense of certain things.

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Speaker 3: But you get in there and everything is ten times

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Speaker 3: you know, bigger, worse, better, all the things than you realize. Okay,

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Speaker 3: what did I see? I saw a company that had

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Speaker 3: some real innovative spirit at its core. Remember Lyft was

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Speaker 3: actually the one that really revolutionized ride share. So the

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Speaker 3: other guys they came up with a sort of black

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Speaker 3: car concept and you know, black car on an app,

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Speaker 3: but it was really Lyft that said, you know what

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Speaker 3: it can be anyone with a prius, you know what

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Speaker 3: I mean, anyone can pick up. So this company had

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Speaker 3: innovated from the early days, but honestly, it's innovated spirit

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Speaker 3: had maybe gotten a little the best of it, tried

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Speaker 3: few too many things, spread a little too thin, losing share,

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Speaker 3: and its core business, as you say, not priced well,

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Speaker 3: you know, not paying competitively. So a number of different

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Speaker 3: just basic issues. So what do we do the first

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Speaker 3: frankly couple of weeks. Well, first thing is lower prices.

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Speaker 3: We were just priced too high. That'd be really yeah,

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Speaker 3: I can't operate.

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Speaker 2: And did you do a big instead of announcements around that,

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Speaker 2: because twenty twenty three is still kind of a blur

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Speaker 2: to me.

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Speaker 3: So we didn't. And here's why. In order to withstand

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Speaker 3: a price drop, because it's a very competitive business and

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Speaker 3: you're doing a lot of volume, so if you drop

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Speaker 3: your price, you've got to make sure you can pay

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Speaker 3: for We had to do some other things as well.

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Speaker 3: So for example, we had to reduce our cost significantly,

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Speaker 3: so we laid off about it's about a third of

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Speaker 3: the company and yeah, twenty six percent actually of the company,

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Speaker 3: and I think about a three hundred and thirty million

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Speaker 3: dollars of savings. That was a very very significant shock

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Speaker 3: to the company. By the way, we also had to

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Speaker 3: raise driver pay, so we had a lot to pay for.

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Speaker 2: We also used simultaneously lowing prices for lift and yet

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Speaker 2: bumping up prices for drug That's right. That sounds like

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Speaker 2: that's going to cause us a big problem for profits.

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Speaker 3: So that's exactly right. So in order to pay for it,

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Speaker 3: you have to figure out how to pay for it.

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Speaker 3: And frankly, our cost structure was just sort of out

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Speaker 3: of control. We were doing too many things, We had

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Speaker 3: too many people, and by the way, those people were

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Speaker 3: all working remotely, which makes it quite difficult to really

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Speaker 3: kind of change the culture to a customer obsessed culture,

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Speaker 3: which was my other big thing. So and by the way,

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Speaker 3: we were also overpaying in stock based compensation, which was

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Speaker 3: bugging investors. So in the first couple of months, you know,

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Speaker 3: it wasn't really the time to be bragging. It was

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Speaker 3: the time, frankly, to be saying, Okay, we've got some

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Speaker 3: things to fix, and let's really focus on that. So first,

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Speaker 3: you know, call it you know, thirty sixty ninety days.

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Speaker 3: It's fixing some basics, but also reorienting the company back

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Speaker 3: towards its customer obsessed roots. And I'm still very I

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Speaker 3: guess i'd say proud of this. The second the first

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Speaker 3: meeting I had of the day was literally getting my

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Speaker 3: computer or my laptop, and a second meeting ten o'clock

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Speaker 3: in the morning Monday morning, I said, let's start talking

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Speaker 3: about a product that's now called Women plus Connect, trying

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Speaker 3: to get drivers and women riders.

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Speaker 2: Such a great idea, especially given the mayhem across the

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Speaker 2: street from it.

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Speaker 3: I appreciate your saying that, and it's it really matters

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Speaker 3: and so.

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Speaker 2: And this is something the company and I'm sorry to interrupt, please,

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Speaker 2: it's very visible on the app, like that choice, which

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Speaker 2: shows some thoughtfulness. And oh there's this problem. How about

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Speaker 2: we have send a woman drive for you and you

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Speaker 2: don't have to worry about what you're hearing about elsewhere exactly.

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Speaker 2: It just makes so much sense.

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Speaker 3: So I really appreciate you saying that. It was an

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Speaker 3: easy decision. From that sense, all you have to do

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Speaker 3: is talk to ten women and say we you know,

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Speaker 3: what do you think? And they say wow, gosh, particularly

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Speaker 3: late at night, maybe in a new city, maybe after

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Speaker 3: a long day. It's just not my jam to be

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Speaker 3: talking to a dude sor ry dudes, you know like that.

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Speaker 3: But but but sometimes the easiest ideas are also the

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Speaker 3: most complicated. There are all sorts of potential legal issues,

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Speaker 3: all sorts of operational issues. They're even to a certain

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Speaker 3: extent cultural issues of like is this going to be okay?

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Speaker 3: But I was like, you know what, I think it's

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Speaker 3: going to be okay. I think it's going to be okay.

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Speaker 3: So that was an early decision we made. It came

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Speaker 3: that was in April twenty twenty three. We launched that

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Speaker 3: later that year, and it was really exciting for the

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Speaker 3: company to say, you know what, we can do big

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Speaker 3: things again and we can start to innovate again on

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Speaker 3: behalf of customers. Huh.

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Speaker 2: Kind of fascinating. Coming up, we continue our conversation with

432
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Speaker 2: David Rischer, CEO of Lyft, discussing the future of ride

433
00:20:20,000 --> 00:20:23,960
Speaker 2: share technology. I'm Barry rid Holts. You're listening to Masters

434
00:20:23,960 --> 00:20:36,520
Speaker 2: in Business on Bloomberg Radio. I'm Barry Ridolts. You're listening

435
00:20:36,560 --> 00:20:40,160
Speaker 2: to Masters in Business on Bloomberg Radio. My special guest

436
00:20:40,200 --> 00:20:43,520
Speaker 2: this week is David Rischer. He is the CEO of Lyft,

437
00:20:43,600 --> 00:20:48,280
Speaker 2: one of North America's largest and fastest growing ride sharing network.

438
00:20:48,440 --> 00:20:50,960
Speaker 2: So over the next year or so, you return lift

439
00:20:51,000 --> 00:20:54,800
Speaker 2: to profitability. On the most recent reported quarter, first quarter

440
00:20:54,840 --> 00:20:58,520
Speaker 2: twenty twenty six, over twenty eight million active riders, nearly

441
00:20:58,560 --> 00:21:02,760
Speaker 2: five billion in gross books, one point seven billion in revenues,

442
00:21:02,840 --> 00:21:05,560
Speaker 2: just about one hundred and thirty three million in eb

443
00:21:05,560 --> 00:21:10,320
Speaker 2: of the profits. So the combination of restructuring the company,

444
00:21:10,800 --> 00:21:18,600
Speaker 2: attracting higher paying more drivers, and discounting prices for riders

445
00:21:19,000 --> 00:21:22,480
Speaker 2: put you on the right foot. How do you build

446
00:21:22,520 --> 00:21:25,080
Speaker 2: on that? What's the next step to maintain that momentum?

447
00:21:25,200 --> 00:21:28,080
Speaker 3: Well, so, in some sense nothing changes. In some sense

448
00:21:28,119 --> 00:21:30,840
Speaker 3: everything changes. Okay, So what doesn't change customer obsession is

449
00:21:30,880 --> 00:21:32,720
Speaker 3: still driving profitable growth. That's just going to be a

450
00:21:32,720 --> 00:21:35,040
Speaker 3: theme I just go with forever. I you know, maybe

451
00:21:35,040 --> 00:21:36,840
Speaker 3: I've drank a lot of the Jeff Bezos cool egg,

452
00:21:36,840 --> 00:21:39,280
Speaker 3: but it seems to be working out pretty well. So

453
00:21:39,600 --> 00:21:43,399
Speaker 3: so one other financial metric that has been interesting to

454
00:21:43,400 --> 00:21:45,880
Speaker 3: watch is when I joined, we were losing about three

455
00:21:45,960 --> 00:21:48,119
Speaker 3: hundred million dollars, consuming abot three hundred million dollars in

456
00:21:48,119 --> 00:21:51,080
Speaker 3: cash over twelve months. We're now jettering about one point

457
00:21:51,119 --> 00:21:53,960
Speaker 3: one billion dollars in cash over the over twelve months. Okay,

458
00:21:54,160 --> 00:21:56,600
Speaker 3: so what that allows us to do is invest in

459
00:21:56,640 --> 00:21:59,240
Speaker 3: the future. What does that look like. Certainly it looks

460
00:21:59,240 --> 00:22:01,520
Speaker 3: like internationalks mansion. So that's been one thing we've been

461
00:22:01,520 --> 00:22:03,800
Speaker 3: at for about the last year, which is, you know,

462
00:22:04,160 --> 00:22:07,360
Speaker 3: Lift was sort of almost say, caught a little bit

463
00:22:08,320 --> 00:22:10,800
Speaker 3: in sort of a US centric view of the world,

464
00:22:11,280 --> 00:22:13,399
Speaker 3: and it just doesn't make sense. Once you have a

465
00:22:13,440 --> 00:22:16,400
Speaker 3: product that scales really well and it's sort of a

466
00:22:16,440 --> 00:22:19,359
Speaker 3: fixed cost based type of thing, you really want it

467
00:22:19,400 --> 00:22:21,240
Speaker 3: to be around as much the world as possible so

468
00:22:21,440 --> 00:22:24,280
Speaker 3: you can run as much volume through that platform as possible.

469
00:22:24,359 --> 00:22:26,520
Speaker 3: So we bought a company called free Now last year.

470
00:22:26,720 --> 00:22:30,400
Speaker 3: It's a European taxi aggregator free Now Free Now Yeah, yeah.

471
00:22:30,480 --> 00:22:33,920
Speaker 3: It is Europe's biggest taxi aggregator, which means that if

472
00:22:33,960 --> 00:22:35,439
Speaker 3: you want a taxi and you're in a place like

473
00:22:35,480 --> 00:22:39,280
Speaker 3: Barcelona or London or pick your favorite city. They operated

474
00:22:39,359 --> 00:22:41,359
Speaker 3: nine countries, the free nowp is going to be your

475
00:22:41,359 --> 00:22:43,280
Speaker 3: best way to get it. That gives us a great

476
00:22:43,320 --> 00:22:46,600
Speaker 3: platform for expansion, even when it comes to autonous vehicles.

477
00:22:46,640 --> 00:22:48,480
Speaker 3: We'll come back to that, I'm sure you know. In

478
00:22:48,520 --> 00:22:50,720
Speaker 3: a couple of seconds. So that's one direction of expansion.

479
00:22:50,760 --> 00:22:54,080
Speaker 3: You think of that as out overseas. Another dimension is

480
00:22:54,200 --> 00:22:56,359
Speaker 3: up up market. You just kind of refer to this

481
00:22:56,440 --> 00:23:00,640
Speaker 3: soft again. It's sort of started. Its tradition was as

482
00:23:00,760 --> 00:23:04,639
Speaker 3: kind of a relatively inexpensive, very available ride share option,

483
00:23:05,000 --> 00:23:06,919
Speaker 3: but it wasn't as strong and kind of the black,

484
00:23:07,080 --> 00:23:09,520
Speaker 3: you know, kind of luxury segment. We bought a company

485
00:23:09,520 --> 00:23:12,440
Speaker 3: called TBR last year. TBR is a high end chow

486
00:23:12,480 --> 00:23:14,840
Speaker 3: for a company. We also have a very very good

487
00:23:14,880 --> 00:23:16,879
Speaker 3: lift black product. In fact, if you're listening to this,

488
00:23:17,160 --> 00:23:19,680
Speaker 3: I promise, if you haven't tried it, give it a try.

489
00:23:19,720 --> 00:23:21,600
Speaker 3: I think you'll like. It's actually our highest rated product.

490
00:23:21,720 --> 00:23:23,199
Speaker 3: You know, a nice black car comes and pick you up,

491
00:23:23,240 --> 00:23:26,399
Speaker 3: picks you up. So that's another area of expansion for

492
00:23:26,480 --> 00:23:29,080
Speaker 3: us because that gives us frankly more margin to play with,

493
00:23:29,160 --> 00:23:31,480
Speaker 3: but it also allows us to talk to a segment

494
00:23:31,520 --> 00:23:33,760
Speaker 3: that we haven't talked to very much. And then of

495
00:23:33,760 --> 00:23:37,840
Speaker 3: course autonomous vehicles. So these are all nice uses of cash.

496
00:23:38,040 --> 00:23:40,159
Speaker 3: Once you're generating cash, you can start to either acquire

497
00:23:40,160 --> 00:23:42,120
Speaker 3: companies or you can invest in things that then grow,

498
00:23:42,440 --> 00:23:44,359
Speaker 3: you know, build sort of the next chapter of growth.

499
00:23:44,560 --> 00:23:50,359
Speaker 2: So I appreciate you mentioning the various tiers. There's this

500
00:23:50,520 --> 00:23:54,160
Speaker 2: tendency to think of the consumer, especially the American consumer,

501
00:23:54,680 --> 00:23:57,600
Speaker 2: as one thing, but we both know that's not true.

502
00:23:57,920 --> 00:23:59,760
Speaker 2: You get to crunch a whole lot of data. What

503
00:23:59,760 --> 00:24:04,399
Speaker 2: do you seeing in terms of income, geography various times

504
00:24:04,400 --> 00:24:07,440
Speaker 2: a day? Like what do the metrics tell you about

505
00:24:07,560 --> 00:24:11,680
Speaker 2: the different flavors of consumers using lift?

506
00:24:11,960 --> 00:24:14,840
Speaker 3: Yeah, this is such an interesting issue and it's not

507
00:24:15,000 --> 00:24:17,280
Speaker 3: something I really appreciated. We're going to do about a

508
00:24:17,320 --> 00:24:19,720
Speaker 3: billion rides this year, and so to your point, with

509
00:24:19,760 --> 00:24:22,000
Speaker 3: a billion rides, you kind of get a sense of

510
00:24:22,080 --> 00:24:24,520
Speaker 3: how people are spending their time during the day. So

511
00:24:24,640 --> 00:24:26,520
Speaker 3: I'll tell you two things that are growing quite quickly.

512
00:24:26,600 --> 00:24:29,639
Speaker 3: One is party time. And it might be funny to

513
00:24:29,680 --> 00:24:31,639
Speaker 3: start there, but party time, so I actually say what

514
00:24:31,720 --> 00:24:34,200
Speaker 3: that means. What that means is a Thursday night for

515
00:24:34,240 --> 00:24:36,280
Speaker 3: a really Friday night and Saturday night. Call it nine

516
00:24:36,280 --> 00:24:39,480
Speaker 3: to midnight. And it is really interesting. I think this

517
00:24:40,280 --> 00:24:43,440
Speaker 3: not just post COVID, but I think frankly, a little

518
00:24:43,480 --> 00:24:46,320
Speaker 3: bit of app fatigue is driving people to say, you

519
00:24:46,320 --> 00:24:48,720
Speaker 3: know what, let's actually get out and spend our lives

520
00:24:48,760 --> 00:24:50,480
Speaker 3: out in the real world instead of spending all of

521
00:24:50,480 --> 00:24:53,320
Speaker 3: our lives on apps. So I think that's actually I'm

522
00:24:53,400 --> 00:24:55,160
Speaker 3: quite comforted by that, and it's actually a big part

523
00:24:55,160 --> 00:24:57,000
Speaker 3: of our sort of overall purpose is to serve and

524
00:24:57,000 --> 00:24:59,159
Speaker 3: connect people. A lot of passionate about that. At the

525
00:24:59,160 --> 00:25:01,159
Speaker 3: same time, commute well, and I do think this is

526
00:25:01,160 --> 00:25:03,359
Speaker 3: a certain post COVID thing where people were sort of thinking,

527
00:25:03,400 --> 00:25:05,240
Speaker 3: maybe we'll just be in our houses the rest of

528
00:25:05,280 --> 00:25:07,359
Speaker 3: our life working remotely. It turns out a lot of

529
00:25:07,359 --> 00:25:09,280
Speaker 3: companies and a lot of people are saying, I want

530
00:25:09,320 --> 00:25:11,200
Speaker 3: to get back to work. And I think these things

531
00:25:11,240 --> 00:25:13,960
Speaker 3: are somewhat connected. Sorry for sounding a little bit like

532
00:25:13,960 --> 00:25:16,600
Speaker 3: a social psychologist a little bit, but I mean, gosh,

533
00:25:16,640 --> 00:25:18,920
Speaker 3: I'm met my wife at Microsoft. You know, a lot

534
00:25:18,960 --> 00:25:22,280
Speaker 3: of people have really significant life events that happen at

535
00:25:22,320 --> 00:25:24,760
Speaker 3: work that are not just work right, and so I

536
00:25:24,760 --> 00:25:26,360
Speaker 3: think there's a little bit So anyway, when I look

537
00:25:26,359 --> 00:25:28,920
Speaker 3: at things like commute hours, and then travel continues to

538
00:25:28,960 --> 00:25:31,840
Speaker 3: be really strong as well, I think, and this is look, I'm,

539
00:25:31,880 --> 00:25:33,760
Speaker 3: you know, million years old now. When I was a kid,

540
00:25:33,880 --> 00:25:35,439
Speaker 3: the idea of you know, getting on a plane and

541
00:25:35,440 --> 00:25:37,520
Speaker 3: going overseas was I mean, I might as well say

542
00:25:37,560 --> 00:25:39,760
Speaker 3: you'll go to the moon. Now, you know, twenty and

543
00:25:39,760 --> 00:25:41,399
Speaker 3: thirty year olds, they're like, yeah, I'll sort of take

544
00:25:41,440 --> 00:25:43,760
Speaker 3: a trip overseas, or I'll go to you know whatever,

545
00:25:43,880 --> 00:25:46,120
Speaker 3: Nashville for the weekend or something. So anyway, I think

546
00:25:46,119 --> 00:25:48,320
Speaker 3: these are pretty big, you know, real societal shifts as

547
00:25:48,359 --> 00:25:50,120
Speaker 3: people want to kind of be out in the real world.

548
00:25:51,160 --> 00:25:53,520
Speaker 2: I'm kind of fascinated by the idea of party time

549
00:25:53,960 --> 00:25:58,800
Speaker 2: because there's always pre drive apps is There's was always

550
00:25:58,800 --> 00:26:03,280
Speaker 2: the question I've had two I guess I'm driving tonight,

551
00:26:03,320 --> 00:26:05,960
Speaker 2: so I stop here. But if you're out on party

552
00:26:06,040 --> 00:26:09,160
Speaker 2: night and you know you're taking a car home, you're

553
00:26:09,320 --> 00:26:11,800
Speaker 2: not afraid about having a second with their drink. You

554
00:26:11,840 --> 00:26:15,080
Speaker 2: can kind of relax a little bit. Getting pulled over

555
00:26:15,440 --> 00:26:19,480
Speaker 2: is not a problem. If you're in somebody else's lift.

556
00:26:19,520 --> 00:26:22,400
Speaker 3: It's exactly right. It's so again if you zoom out,

557
00:26:22,400 --> 00:26:24,880
Speaker 3: so you know, Wall Street looks at companies like ours

558
00:26:24,960 --> 00:26:27,760
Speaker 3: quarter by quarter and it sort of drives you crazy.

559
00:26:27,800 --> 00:26:31,240
Speaker 3: But if you zoom way way out, you know, let's

560
00:26:31,240 --> 00:26:35,200
Speaker 3: look at that from a different dimension. Now, average car

561
00:26:35,280 --> 00:26:37,560
Speaker 3: right now, fifty thousand bucks a year. Okay, average monthly

562
00:26:37,600 --> 00:26:40,320
Speaker 3: payment eight hundred bucks insurance, it cost you another couple

563
00:26:40,359 --> 00:26:43,400
Speaker 3: hundred bucks. Gas might cost you another one hundred bucks

564
00:26:43,480 --> 00:26:45,439
Speaker 3: or so at least now, and then service will cost

565
00:26:45,480 --> 00:26:47,320
Speaker 3: a little bit more of that. Okay, So that's plan A.

566
00:26:47,640 --> 00:26:50,120
Speaker 3: And by the way, if you take on all that responsibility,

567
00:26:50,480 --> 00:26:53,560
Speaker 3: there's no texting and there's no drinking. I mean that's

568
00:26:53,600 --> 00:26:56,880
Speaker 3: right now. Plan B. Pay twenty bucks getting a lift,

569
00:26:56,920 --> 00:26:59,159
Speaker 3: someone else does the driving, text your heart to get content,

570
00:26:59,320 --> 00:27:01,239
Speaker 3: drink as much as you if that's if that's your

571
00:27:01,320 --> 00:27:03,560
Speaker 3: job and it's you know, twenty bucks, not you know,

572
00:27:03,560 --> 00:27:05,800
Speaker 3: eight hundred bucks. Time plus plus plus plus plus. So

573
00:27:06,320 --> 00:27:08,680
Speaker 3: just just looking out again, you're sort of asking about

574
00:27:08,760 --> 00:27:10,800
Speaker 3: kind of segments and sort of you know, maybe a

575
00:27:10,840 --> 00:27:13,360
Speaker 3: little bit the role of technology in society. I think

576
00:27:14,040 --> 00:27:15,880
Speaker 3: I still think we're actually at the at the beginning

577
00:27:15,880 --> 00:27:17,800
Speaker 3: stages of a lot of these changes, and we and

578
00:27:17,880 --> 00:27:19,800
Speaker 3: sometimes again people have been around for a while don't

579
00:27:19,800 --> 00:27:21,639
Speaker 3: even realize how much the world has changed that way.

580
00:27:21,720 --> 00:27:25,040
Speaker 2: Yeah, fascinating data point. I saw it was actually a

581
00:27:25,040 --> 00:27:28,680
Speaker 2: couple of years ago. The number of kids under nineteen

582
00:27:28,880 --> 00:27:32,080
Speaker 2: that haven't gotten a driver's license is kind of like

583
00:27:32,560 --> 00:27:35,360
Speaker 2: when I was growing up, you couldn't wait to get

584
00:27:35,400 --> 00:27:38,440
Speaker 2: your driver's license because that meant freedom. There wasn't an

585
00:27:38,440 --> 00:27:42,240
Speaker 2: internet with three channels, plus some people started getting cable

586
00:27:42,600 --> 00:27:45,360
Speaker 2: like it was a very different world back then. That's right,

587
00:27:45,680 --> 00:27:47,560
Speaker 2: And now it's like, yeah, maybe I'll get a license,

588
00:27:47,600 --> 00:27:50,280
Speaker 2: maybe I won't. How do you think about marketing to

589
00:27:50,359 --> 00:27:51,240
Speaker 2: that demographic?

590
00:27:51,680 --> 00:27:54,200
Speaker 3: Well, so one of the things I learned from Jeff

591
00:27:54,240 --> 00:27:56,760
Speaker 3: again it was, as you can imagine, quite an influential

592
00:27:56,800 --> 00:28:00,280
Speaker 3: boss for me, is you know, build your business is

593
00:28:00,320 --> 00:28:02,840
Speaker 3: on things that don't tend to change, not things that

594
00:28:02,840 --> 00:28:05,000
Speaker 3: are that are sort of ephemeral. So what are some

595
00:28:05,040 --> 00:28:06,800
Speaker 3: things that don't that aren't going to change? Okay, again,

596
00:28:06,800 --> 00:28:08,359
Speaker 3: people are going to want to get out, either to

597
00:28:08,440 --> 00:28:10,760
Speaker 3: the doctor or to you know, go to a bar.

598
00:28:10,840 --> 00:28:13,560
Speaker 3: So that's that's a that's a good bet. People are

599
00:28:13,560 --> 00:28:15,679
Speaker 3: also going to want to save money, and so a

600
00:28:15,720 --> 00:28:17,960
Speaker 3: lot of our focus right now and you're going to

601
00:28:17,960 --> 00:28:21,240
Speaker 3: see started a lot of marketing around this is save

602
00:28:21,359 --> 00:28:24,160
Speaker 3: money check lift. Now. I want to be super clear here,

603
00:28:24,440 --> 00:28:27,000
Speaker 3: it's not if I look at the competitor that we

604
00:28:27,240 --> 00:28:29,399
Speaker 3: always have a better price. Of course, we try to,

605
00:28:29,520 --> 00:28:31,280
Speaker 3: but we don't always you know, sometimes you know, all

606
00:28:31,320 --> 00:28:34,120
Speaker 3: sorts of things happen. But over time, if you check

607
00:28:34,160 --> 00:28:36,840
Speaker 3: both apps, you're going to save some money. And certainly

608
00:28:36,880 --> 00:28:38,400
Speaker 3: compared to buying a car of your own and dealing

609
00:28:38,440 --> 00:28:39,920
Speaker 3: with all the maintenance, you're going to save some money.

610
00:28:39,960 --> 00:28:41,640
Speaker 3: So it's not the only thing I want to say,

611
00:28:41,680 --> 00:28:43,280
Speaker 3: but I actually think it's an important thing to say,

612
00:28:43,320 --> 00:28:46,200
Speaker 3: particularly in a world of sort of some economic instability.

613
00:28:46,320 --> 00:28:47,800
Speaker 3: Is this is a good way for you to save

614
00:28:47,840 --> 00:28:50,160
Speaker 3: some money. And frankly, I'm proud of our cost position.

615
00:28:50,240 --> 00:28:52,320
Speaker 3: I'm proud of our ability to offer a great price

616
00:28:52,360 --> 00:28:54,280
Speaker 3: every single day, you know, billion times a year.

617
00:28:54,360 --> 00:28:58,800
Speaker 2: So let's talk about you versus your competitor. Lift has

618
00:28:58,840 --> 00:29:02,480
Speaker 2: always been framed as of the underdog to uber. Is

619
00:29:02,520 --> 00:29:05,400
Speaker 2: this kind of a coke and PEPSI story? What what

620
00:29:05,480 --> 00:29:09,200
Speaker 2: are the advantages of being number two? Remember the old

621
00:29:09,600 --> 00:29:09,840
Speaker 2: was it?

622
00:29:09,880 --> 00:29:10,360
Speaker 3: Avis?

623
00:29:10,400 --> 00:29:12,520
Speaker 2: We're number two too? We have to try harder.

624
00:29:13,040 --> 00:29:16,440
Speaker 3: Absolutely, So I like being number two. And it's maybe

625
00:29:16,440 --> 00:29:18,040
Speaker 3: a funny thing to say, but I do think it

626
00:29:18,080 --> 00:29:20,120
Speaker 3: means you try harder. You wake up every single morning

627
00:29:20,160 --> 00:29:22,080
Speaker 3: and you say, I got one job, which is to frankly,

628
00:29:22,240 --> 00:29:23,920
Speaker 3: you know, do a great job for my riders and

629
00:29:23,920 --> 00:29:26,920
Speaker 3: my drivers, such that maybe over time I can you know,

630
00:29:27,000 --> 00:29:29,640
Speaker 3: I can, I can overtake the other guys. You know,

631
00:29:30,920 --> 00:29:33,320
Speaker 3: I guess the way to think about that is, I

632
00:29:33,360 --> 00:29:37,040
Speaker 3: think the right number of ride share companies in most

633
00:29:37,080 --> 00:29:40,160
Speaker 3: markets is probably two. You know, it's a it's a

634
00:29:40,240 --> 00:29:43,520
Speaker 3: capital intensive business, not because you own the cars, but

635
00:29:43,520 --> 00:29:45,800
Speaker 3: because you own a lot of server capacity, and you know,

636
00:29:45,880 --> 00:29:48,560
Speaker 3: it's quite complicated to figure out you know, pick up

637
00:29:48,560 --> 00:29:52,080
Speaker 3: and drop off locations and customer service. People leave their

638
00:29:52,120 --> 00:29:54,360
Speaker 3: phones in the car about eight thousand times a week.

639
00:29:54,560 --> 00:29:56,520
Speaker 3: You know, it's just all sorts.

640
00:29:56,200 --> 00:29:58,400
Speaker 2: Of right, especially Friday party night.

641
00:29:58,480 --> 00:29:59,960
Speaker 3: Right there, you go, it all kind of comes together.

642
00:30:00,280 --> 00:30:02,520
Speaker 3: There is something, There is something to that. And by

643
00:30:02,520 --> 00:30:04,320
Speaker 3: the way, we have really cool innovation coming out there.

644
00:30:04,440 --> 00:30:06,520
Speaker 3: We'll bring your phone back to you automatically. But that's

645
00:30:06,520 --> 00:30:10,200
Speaker 3: a separate story. But anyway, so in a funny way,

646
00:30:10,240 --> 00:30:12,240
Speaker 3: it's it's it's not a bad thing to be in

647
00:30:12,600 --> 00:30:14,920
Speaker 3: sort of a two player position because you really only

648
00:30:14,960 --> 00:30:17,719
Speaker 3: have one competitor, and frankly, if you spend too much

649
00:30:17,720 --> 00:30:19,800
Speaker 3: of your time thinking about that one competitor, you're probably

650
00:30:19,840 --> 00:30:22,120
Speaker 3: losing the script. Because guess what, there are a lot

651
00:30:22,120 --> 00:30:24,360
Speaker 3: of drives rides that people aren't even taking on rideshair

652
00:30:24,360 --> 00:30:26,600
Speaker 3: at all. Okay, so you know, back to this question.

653
00:30:26,880 --> 00:30:29,280
Speaker 3: You know we're a customer obsess company, and you know

654
00:30:29,320 --> 00:30:30,640
Speaker 3: this is going to be the thing. This is why

655
00:30:30,680 --> 00:30:33,400
Speaker 3: we're growing, you know, mid single mid double digits, you know,

656
00:30:33,400 --> 00:30:35,720
Speaker 3: fifteen to twenty percent a year on ear. It's why

657
00:30:35,760 --> 00:30:37,920
Speaker 3: we've become profitab it's why we're spinning off cash. And

658
00:30:38,000 --> 00:30:40,360
Speaker 3: I think that is a good place to be, particularly

659
00:30:40,360 --> 00:30:42,200
Speaker 3: when I look at the other guys who I tend

660
00:30:42,200 --> 00:30:44,760
Speaker 3: to think of, frankly as a more I'll call them

661
00:30:44,800 --> 00:30:47,800
Speaker 3: sort of financially and maybe maybe technologically driven. Maybe I

662
00:30:47,840 --> 00:30:50,080
Speaker 3: don't know exactly how they describe themselves, but but I

663
00:30:50,080 --> 00:30:53,400
Speaker 3: don't get the customer obsessed vibe. Huh.

664
00:30:53,440 --> 00:30:58,800
Speaker 2: So that's kind of interesting. Let's talk about an example

665
00:30:58,840 --> 00:31:02,920
Speaker 2: where there's no customer are obsessed vibe. So I use Lyft,

666
00:31:02,960 --> 00:31:07,800
Speaker 2: I use Uber. It feels like on Uber, the way

667
00:31:07,920 --> 00:31:11,360
Speaker 2: it measures time is sort of an alternative reality. Hey

668
00:31:11,440 --> 00:31:13,960
Speaker 2: we'll find a driver in three minutes. It takes nine minutes.

669
00:31:14,000 --> 00:31:17,720
Speaker 2: Hey the car'll be here, but in eleven minutes, it's

670
00:31:17,720 --> 00:31:19,120
Speaker 2: there in twenty three minutes.

671
00:31:18,920 --> 00:31:19,960
Speaker 3: Like they.

672
00:31:21,320 --> 00:31:26,400
Speaker 2: The app is very full of bs. It consistently lies

673
00:31:26,480 --> 00:31:30,160
Speaker 2: I'm curious, it's just just a logistical issue that everybody

674
00:31:30,200 --> 00:31:33,080
Speaker 2: has to deal with. Or and we know a lot

675
00:31:33,200 --> 00:31:36,680
Speaker 2: about the history and culture of your biggest competitor, is

676
00:31:36,720 --> 00:31:40,880
Speaker 2: this a culture problem that you know their history has

677
00:31:41,320 --> 00:31:45,400
Speaker 2: a lot of bad behavior, a lot of let's just

678
00:31:45,440 --> 00:31:49,440
Speaker 2: call it questionable legality. I wouldn't go so far as

679
00:31:49,480 --> 00:31:51,640
Speaker 2: to say fraud, but they did a lot of bad things.

680
00:31:52,240 --> 00:31:55,360
Speaker 2: Does that show up in how the app behaves? Or

681
00:31:55,440 --> 00:31:58,120
Speaker 2: is this just no Google Maps is tough to work with.

682
00:31:58,160 --> 00:32:00,400
Speaker 2: This is a logistical challenge.

683
00:32:00,120 --> 00:32:04,440
Speaker 3: You know it is. It is a logistical challenge. But

684
00:32:04,440 --> 00:32:06,360
Speaker 3: but I think you're Look, I'm not going to character

685
00:32:06,440 --> 00:32:09,200
Speaker 3: you did a marvelous job characterizing me.

686
00:32:09,240 --> 00:32:12,760
Speaker 2: I'm I've got liability for slams.

687
00:32:12,360 --> 00:32:16,520
Speaker 3: Are fantastic, exactly. So Barry's got a whole second.

688
00:32:16,200 --> 00:32:17,960
Speaker 2: Hold on, Well, you were a lawyer, right, yes, yes,

689
00:32:18,400 --> 00:32:21,560
Speaker 2: Oh there we go. But I'm recovered. I understand recovered lawyer.

690
00:32:21,640 --> 00:32:23,520
Speaker 3: But you did just hear a lawyer very carefully parts

691
00:32:23,520 --> 00:32:26,120
Speaker 3: of these words. Okay, listen, I won't comment on that.

692
00:32:26,240 --> 00:32:28,880
Speaker 3: What I will say is we are very focused. For example,

693
00:32:28,880 --> 00:32:31,400
Speaker 3: you're talking about reliability. Oh my goodness, you talk to

694
00:32:31,440 --> 00:32:34,920
Speaker 3: my team and they will, they will they roll their

695
00:32:34,920 --> 00:32:36,240
Speaker 3: eyes maybe would be one way to say it. But

696
00:32:36,240 --> 00:32:39,160
Speaker 3: the number of times I talk about reliability internally is

697
00:32:39,160 --> 00:32:41,480
Speaker 3: is high because I am obsessed by saying we're going

698
00:32:41,520 --> 00:32:43,280
Speaker 3: to make a promise, we're going to meet the promise,

699
00:32:43,320 --> 00:32:44,960
Speaker 3: And starting in a couple of weeks, we're actually starting

700
00:32:44,960 --> 00:32:47,920
Speaker 3: to do some more work to actually surface that promise

701
00:32:47,960 --> 00:32:49,880
Speaker 3: even a little bit more visibly. We do it today

702
00:32:50,160 --> 00:32:52,360
Speaker 3: for airport pickups. If we're more than ten minutes late

703
00:32:52,400 --> 00:32:54,560
Speaker 3: for airport pickups, we pay you up to one hundred bucks,

704
00:32:54,560 --> 00:32:57,400
Speaker 3: no questions asked. Really yep, and we rarely have to

705
00:32:57,400 --> 00:32:59,520
Speaker 3: do that. Our reliability rate is above ninety nine percent

706
00:32:59,520 --> 00:33:02,560
Speaker 3: for schedule report pickups. Yeah, so we're very very focused

707
00:33:02,560 --> 00:33:06,480
Speaker 3: on that. You know, I will say, look at business school,

708
00:33:06,480 --> 00:33:09,920
Speaker 3: there's a very famous class which has a weird technical name,

709
00:33:09,960 --> 00:33:13,640
Speaker 3: but it's basically about incentives and behavior. And what's the

710
00:33:13,680 --> 00:33:16,720
Speaker 3: name of the class, Like I was in physical a

711
00:33:16,720 --> 00:33:18,680
Speaker 3: long time ago, I think it's called CCMO is the

712
00:33:18,880 --> 00:33:20,920
Speaker 3: is the and I don't even remember what it stands

713
00:33:20,960 --> 00:33:24,560
Speaker 3: for anymore. It's probably called something different today, but it

714
00:33:24,600 --> 00:33:28,520
Speaker 3: really is about how incentives drive behavior, you know, financial

715
00:33:28,520 --> 00:33:31,600
Speaker 3: incentives and other incentives, and an incentive alignment and so

716
00:33:31,640 --> 00:33:36,840
Speaker 3: forth and so on. There is an incentive in the

717
00:33:37,120 --> 00:33:41,040
Speaker 3: the sort of the on demand app world not always

718
00:33:41,080 --> 00:33:44,200
Speaker 3: to be truthful because if you if you over promise

719
00:33:44,280 --> 00:33:46,600
Speaker 3: something and then you kind of hook a person in,

720
00:33:46,880 --> 00:33:48,479
Speaker 3: you know, what are they going to do if they

721
00:33:48,520 --> 00:33:50,760
Speaker 3: cancel or whatever. It's just going to take them more time.

722
00:33:50,800 --> 00:33:54,160
Speaker 3: So and that is an evil and pernicious problem that

723
00:33:54,280 --> 00:33:57,640
Speaker 3: is kind of baked into the model, and we just

724
00:33:57,840 --> 00:34:01,240
Speaker 3: reject it wholeheartedly. Doesn't mean we never make a mistake,

725
00:34:01,400 --> 00:34:04,320
Speaker 3: but if your car shows up later then we estimated

726
00:34:04,360 --> 00:34:06,920
Speaker 3: it's not it's because we made a mistake, and we

727
00:34:06,960 --> 00:34:09,240
Speaker 3: are trying over and over and over and over again

728
00:34:09,400 --> 00:34:11,960
Speaker 3: to eliminate those their defects right and then start to

729
00:34:11,960 --> 00:34:12,960
Speaker 3: guarantee it over time.

730
00:34:13,560 --> 00:34:16,200
Speaker 2: So you are crunching a lot of numbers, You're seeing

731
00:34:16,200 --> 00:34:19,239
Speaker 2: a lot of data in real time. I'm kind of

732
00:34:19,280 --> 00:34:24,480
Speaker 2: fascinated by the concept of what at lift HQ the

733
00:34:24,760 --> 00:34:28,759
Speaker 2: dashboard looks like, what sort of data you're you're watching constantly?

734
00:34:28,800 --> 00:34:32,480
Speaker 2: What's the most surprising set of numbers or charts that

735
00:34:32,640 --> 00:34:33,400
Speaker 2: come across that.

736
00:34:34,120 --> 00:34:36,239
Speaker 3: Yeah, this is a great question. I mean, yes, So

737
00:34:36,560 --> 00:34:38,680
Speaker 3: the answer first is just you know, validate. The premise

738
00:34:38,760 --> 00:34:41,000
Speaker 3: is absolutely you know, an enormous amount of real time data,

739
00:34:41,040 --> 00:34:43,040
Speaker 3: you know, two to three million rides every single day

740
00:34:43,440 --> 00:34:46,279
Speaker 3: and now worldwide, so we're very active and in fact,

741
00:34:46,280 --> 00:34:49,120
Speaker 3: we have whole cool maps that are you know, simulations

742
00:34:49,120 --> 00:34:52,080
Speaker 3: in such a behavior, particularly around storms and all sorts

743
00:34:52,080 --> 00:34:55,000
Speaker 3: of crazy steps. Anyway, back to your question, Look, there

744
00:34:55,000 --> 00:34:57,160
Speaker 3: are a couple of metrics that I think might surprise

745
00:34:57,239 --> 00:34:59,319
Speaker 3: you that we pay as much attention to as we do,

746
00:34:59,400 --> 00:35:01,080
Speaker 3: and I'll give you a specific one because it kind

747
00:35:01,080 --> 00:35:04,080
Speaker 3: of helps tell the story. When I joined, about fifteen

748
00:35:04,160 --> 00:35:07,879
Speaker 3: percent of the time drivers would cancel on you. Now

749
00:35:07,920 --> 00:35:10,480
Speaker 3: this is infuriating, really yeah, that high.

750
00:35:10,640 --> 00:35:13,839
Speaker 2: I mean every now and then on your competitor, i'll

751
00:35:13,840 --> 00:35:17,800
Speaker 2: see your cancelation, but typically it's Russia hour, someone's stuck

752
00:35:17,840 --> 00:35:19,400
Speaker 2: on the other side of the city. They're not going

753
00:35:19,480 --> 00:35:22,359
Speaker 2: to make it, so rather than get that ding, they

754
00:35:22,440 --> 00:35:24,080
Speaker 2: just cancel and find someone by them.

755
00:35:24,280 --> 00:35:27,960
Speaker 3: So today's world, it is less than four and a

756
00:35:28,000 --> 00:35:30,560
Speaker 3: half percent on our app. So we've brought it down

757
00:35:30,560 --> 00:35:33,840
Speaker 3: by a factor of three. Yeah, exactly less and so

758
00:35:34,760 --> 00:35:37,839
Speaker 3: oh no, yeah, no, that's it's just slightly around that, Yeah,

759
00:35:38,200 --> 00:35:42,400
Speaker 3: so how have we done that? Well, it's not just

760
00:35:42,640 --> 00:35:44,839
Speaker 3: there on the other side, it's maybe we didn't give

761
00:35:44,880 --> 00:35:49,400
Speaker 3: them enough information right up front, right, so for example,

762
00:35:49,640 --> 00:35:52,200
Speaker 3: how much they're going to make or what neighborhood are

763
00:35:52,200 --> 00:35:54,920
Speaker 3: they going to drop you off at? Maybe and by

764
00:35:55,160 --> 00:35:57,040
Speaker 3: not enough information, maybe we gave it to them, but

765
00:35:57,080 --> 00:35:58,880
Speaker 3: the font was a little bit too small for them

766
00:35:59,040 --> 00:36:00,920
Speaker 3: to see it right, or maybe it wasn't on the screen,

767
00:36:01,040 --> 00:36:03,960
Speaker 3: you know, quite long enough, or maybe we gave you

768
00:36:04,000 --> 00:36:08,000
Speaker 3: a ride that we didn't know was very very unlikely

769
00:36:08,040 --> 00:36:11,400
Speaker 3: for you to want because of your past history or

770
00:36:11,400 --> 00:36:13,759
Speaker 3: whatever it is. So now we spend a lot of

771
00:36:13,920 --> 00:36:16,399
Speaker 3: energy and we've just been grinding away this year after

772
00:36:16,480 --> 00:36:19,200
Speaker 3: year after year because it's so infuriating to riders. That's

773
00:36:19,239 --> 00:36:21,960
Speaker 3: an example of a sort of specific metric that we're

774
00:36:21,960 --> 00:36:23,319
Speaker 3: looking at, you know, by the day.

775
00:36:23,880 --> 00:36:27,880
Speaker 2: Huh. Really really interesting. Two kind of related questions to

776
00:36:28,840 --> 00:36:32,760
Speaker 2: the growth of Lift. Your last quarter's earnings call you said,

777
00:36:33,080 --> 00:36:35,200
Speaker 2: or maybe it was a previous one, twenty seven percent

778
00:36:35,880 --> 00:36:42,360
Speaker 2: of North American rides or linked to a corporate partnership Chase, DoorDash, United, Hilton,

779
00:36:42,400 --> 00:36:46,400
Speaker 2: et cetera. What is that strategy? Is that about customer

780
00:36:46,960 --> 00:36:50,640
Speaker 2: acquisition margin, like what goes into those sort of big partnerships.

781
00:36:50,719 --> 00:36:54,719
Speaker 3: Sure, so you know, as you say, we have, we

782
00:36:54,760 --> 00:36:57,480
Speaker 3: have tens of millions of people who use our service

783
00:36:57,520 --> 00:37:01,360
Speaker 3: every quarter. It's about fifty million a year. And again

784
00:37:01,400 --> 00:37:03,799
Speaker 3: this is back to sort of the Amazon philosophy. You've

785
00:37:03,800 --> 00:37:05,520
Speaker 3: got to compete for those customers, right, You've got to

786
00:37:05,520 --> 00:37:08,520
Speaker 3: compete because you know they have alternatives and in fact,

787
00:37:08,520 --> 00:37:11,720
Speaker 3: there's you know, another company out there that some people know. Okay,

788
00:37:12,000 --> 00:37:14,840
Speaker 3: So one of the ways you compete is you say, gosh,

789
00:37:14,880 --> 00:37:17,520
Speaker 3: it's not just about the ride, it's about the relationship.

790
00:37:17,560 --> 00:37:20,240
Speaker 3: And maybe it's a relationship you already have with another company.

791
00:37:20,280 --> 00:37:23,000
Speaker 3: So you mentioned United Airlines. United Airlines has now been

792
00:37:23,040 --> 00:37:25,040
Speaker 3: a partner of ours for about the last six months.

793
00:37:25,680 --> 00:37:28,640
Speaker 3: It's been a wonderful partnership already because the United Airlines

794
00:37:28,719 --> 00:37:32,239
Speaker 3: Mileage Plus program is incredibly well built out. People are

795
00:37:32,320 --> 00:37:34,600
Speaker 3: very very loyal to it. What can you do on

796
00:37:34,640 --> 00:37:37,319
Speaker 3: Lyft You can now earn miles so that you can

797
00:37:37,320 --> 00:37:38,520
Speaker 3: take a vacation, you.

798
00:37:38,440 --> 00:37:40,240
Speaker 2: Know, same with Hilton Honors, and same.

799
00:37:40,040 --> 00:37:42,359
Speaker 3: With Hilton Honors exactly. There We've been a partner for many,

800
00:37:42,360 --> 00:37:45,160
Speaker 3: many years. The big innovation on the mileage plus side

801
00:37:45,200 --> 00:37:47,040
Speaker 3: is you can actually spend your miles on lift as well,

802
00:37:47,040 --> 00:37:49,279
Speaker 3: which almost feels like free rides. Right. It's just like,

803
00:37:49,320 --> 00:37:51,400
Speaker 3: you know, you get you know, two hundred miles for

804
00:37:51,440 --> 00:37:53,600
Speaker 3: five hundred miles whatever for taking an airline trip, and

805
00:37:53,640 --> 00:37:55,600
Speaker 3: you spend you know, a small segment of those on

806
00:37:55,719 --> 00:37:59,839
Speaker 3: a lift ride. So these partnerships, you sort of asked

807
00:37:59,840 --> 00:38:04,719
Speaker 3: what their sort of the method behind it is. It's

808
00:38:04,760 --> 00:38:07,840
Speaker 3: about customer acquisition, for sure, but it's also about customer retention,

809
00:38:07,960 --> 00:38:10,200
Speaker 3: you know, because if you're in the United ecosystem or

810
00:38:10,200 --> 00:38:13,920
Speaker 3: on the DoorDash side, or Hilton or Alaska Airlines or

811
00:38:14,000 --> 00:38:16,440
Speaker 3: built primarily here in New York City and other cities

812
00:38:16,440 --> 00:38:18,839
Speaker 3: where they are active, and you want to either earn

813
00:38:18,960 --> 00:38:21,399
Speaker 3: or burn miles or points, I'm more a great place

814
00:38:21,440 --> 00:38:21,680
Speaker 3: to do that.

815
00:38:22,000 --> 00:38:26,240
Speaker 2: Huh. Really really kind of interesting. I read an article

816
00:38:26,280 --> 00:38:30,160
Speaker 2: from Reuter's Smaller US markets and college towns have been

817
00:38:30,239 --> 00:38:36,120
Speaker 2: meaningful growth drivers. Curious, why are those markets underpenetrated? What

818
00:38:36,120 --> 00:38:37,160
Speaker 2: did you guys figure out that?

819
00:38:37,680 --> 00:38:40,800
Speaker 3: So part of it there has been just a little

820
00:38:40,800 --> 00:38:42,840
Speaker 3: bit of you know, you might say, neglect from the

821
00:38:42,920 --> 00:38:46,080
Speaker 3: right business for a while, and we realized about eighteen

822
00:38:46,120 --> 00:38:49,920
Speaker 3: months ago that a large part of the town. Just

823
00:38:50,640 --> 00:38:53,160
Speaker 3: to frame this again, total addressable mark total, this warm

824
00:38:53,160 --> 00:38:56,239
Speaker 3: market exactly about one hundred and sixty billion rides a

825
00:38:56,280 --> 00:38:58,040
Speaker 3: year that people take in their private cars across the

826
00:38:58,080 --> 00:38:59,840
Speaker 3: United say it one hundred and sixty billion. And remember

827
00:39:00,120 --> 00:39:01,839
Speaker 3: do a billion, the other guys might do three or four,

828
00:39:02,040 --> 00:39:03,840
Speaker 3: maybe two or three billions. So four billion out one

829
00:39:03,880 --> 00:39:06,160
Speaker 3: hundred sixty million, Okay, So there's a lot of adjustable

830
00:39:06,239 --> 00:39:09,120
Speaker 3: market left for us to go to. And we've been

831
00:39:09,160 --> 00:39:11,320
Speaker 3: in places like New York and San Francisco and Chicago

832
00:39:11,400 --> 00:39:13,560
Speaker 3: for over a decade right now. But some of these

833
00:39:13,560 --> 00:39:16,920
Speaker 3: smaller towns, you know, the Indianapolis of the world, the

834
00:39:16,960 --> 00:39:19,400
Speaker 3: Saint Louis Is the world, as well as college towns

835
00:39:19,400 --> 00:39:21,560
Speaker 3: where basically, you know, nobody has a car compared to

836
00:39:21,600 --> 00:39:24,520
Speaker 3: the population. You know, they just look like good opportunities

837
00:39:24,560 --> 00:39:28,399
Speaker 3: for us. They're complicated from a marketplace management perspective because

838
00:39:28,440 --> 00:39:31,360
Speaker 3: anytime you go to a newer geography, you've got a first,

839
00:39:31,360 --> 00:39:33,759
Speaker 3: make sure you've got enough drivers because otherwise it takes

840
00:39:33,760 --> 00:39:35,759
Speaker 3: too long to get picked up, and you've got to

841
00:39:35,760 --> 00:39:38,160
Speaker 3: make sure you've got enough riders because then driver. If not,

842
00:39:38,200 --> 00:39:40,560
Speaker 3: then riders drivers won't make enough money. So it's it's

843
00:39:40,640 --> 00:39:43,120
Speaker 3: quite complex to invist. The chicken and egg problem is

844
00:39:43,160 --> 00:39:45,160
Speaker 3: the chicken egg from over and over again, which again

845
00:39:45,239 --> 00:39:47,920
Speaker 3: is why back to an earlier part of the conversation,

846
00:39:48,239 --> 00:39:50,279
Speaker 3: it's really quite hard at this point to come into

847
00:39:50,280 --> 00:39:52,279
Speaker 3: the market fresh. You know, you're not going to find

848
00:39:52,320 --> 00:39:54,319
Speaker 3: a lot of folks who want to come into a

849
00:39:54,360 --> 00:39:56,920
Speaker 3: well served market. But anyway, so we just started to

850
00:39:56,920 --> 00:40:00,440
Speaker 3: focus on and our data scientists and our mar marketers

851
00:40:00,640 --> 00:40:02,400
Speaker 3: really kind of went to town and it's been a

852
00:40:02,719 --> 00:40:03,560
Speaker 3: big source of growth.

853
00:40:03,680 --> 00:40:07,080
Speaker 2: Huh, really really interesting. Coming up, we continue our conversation

854
00:40:07,239 --> 00:40:12,319
Speaker 2: with David Rischer, CEO of Lyft, discussing the future of

855
00:40:12,400 --> 00:40:16,799
Speaker 2: transportation technology. I'm Barry Ridults. You're listening to Masters in

856
00:40:16,880 --> 00:40:31,920
Speaker 2: Business on Bloomberg Radio. I'm Barry Ridults. You're listening to

857
00:40:32,040 --> 00:40:36,920
Speaker 2: Masters in Business on Bloomberg Radio. My extra special fascinating

858
00:40:36,960 --> 00:40:40,080
Speaker 2: guest is David Riescher. He is the CEO of Lyft,

859
00:40:40,120 --> 00:40:45,480
Speaker 2: and we have been discussing the future of transportation technology.

860
00:40:46,080 --> 00:40:48,279
Speaker 2: We have to talk about AI. We have to talk

861
00:40:48,280 --> 00:40:51,680
Speaker 2: about autonomous vehicles. But before we do, I have to

862
00:40:51,760 --> 00:40:56,080
Speaker 2: ask you two really interesting questions. One is, how do

863
00:40:56,120 --> 00:41:01,600
Speaker 2: you solve the problem of even so people leaving their

864
00:41:01,640 --> 00:41:04,719
Speaker 2: phones in the car and when they get out and

865
00:41:04,880 --> 00:41:06,840
Speaker 2: suddenly it's a big penal. They asked, somebody has to

866
00:41:06,840 --> 00:41:11,200
Speaker 2: come either drop off the phone or whatever. How do you,

867
00:41:11,480 --> 00:41:15,719
Speaker 2: as a customer obsessed company, how do you solve that problem.

868
00:41:15,920 --> 00:41:18,400
Speaker 3: I so love this question because it is an experience

869
00:41:18,560 --> 00:41:20,880
Speaker 3: every single one of us has had, and it is

870
00:41:20,920 --> 00:41:24,440
Speaker 3: both infuriating and incredibly stressful because all of a sudden

871
00:41:24,520 --> 00:41:27,120
Speaker 3: you realize, oh my god, my entire life is driving

872
00:41:27,120 --> 00:41:29,000
Speaker 3: in the wrong direction and I don't even know how

873
00:41:29,000 --> 00:41:31,040
Speaker 3: to contact the company at this point, okay.

874
00:41:31,000 --> 00:41:32,760
Speaker 2: Close to the number is on your phone.

875
00:41:33,160 --> 00:41:34,840
Speaker 3: And the phone is in the car, and you're like,

876
00:41:34,920 --> 00:41:36,840
Speaker 3: I want to hold my phone to call the phone,

877
00:41:36,840 --> 00:41:38,839
Speaker 3: but I can't do that. It's very, very stressful. So

878
00:41:38,920 --> 00:41:41,160
Speaker 3: here's what we've done. We actually are working. We're doing

879
00:41:41,520 --> 00:41:43,640
Speaker 3: a huge amount of work on this just to be

880
00:41:43,680 --> 00:41:46,839
Speaker 3: really customer set. The first thing is automatic detection. So

881
00:41:47,400 --> 00:41:49,720
Speaker 3: if the phone starts to travel away with the driver

882
00:41:50,080 --> 00:41:53,359
Speaker 3: after you know you've been dropped off, yeah, that immediately

883
00:41:53,440 --> 00:41:56,480
Speaker 3: automatically alerts the driver there's probably a phone in your backseat.

884
00:41:57,040 --> 00:41:58,960
Speaker 3: It requires a little bit of work on the rider's side.

885
00:41:59,000 --> 00:42:00,640
Speaker 3: We're still trying to figure out how to riders to

886
00:42:00,640 --> 00:42:02,879
Speaker 3: opt into this because they have to share a little

887
00:42:02,880 --> 00:42:05,880
Speaker 3: bit more information. But we're still working on that. But

888
00:42:05,920 --> 00:42:08,680
Speaker 3: regardless of whether it happens automatically or manually, the second

889
00:42:08,680 --> 00:42:10,600
Speaker 3: thing is we've got a whole web portal, so you

890
00:42:10,600 --> 00:42:12,200
Speaker 3: don't actually have to use your phone. You can and

891
00:42:12,239 --> 00:42:14,200
Speaker 3: you don't have to log in. But really the big

892
00:42:14,239 --> 00:42:17,600
Speaker 3: innovation is this. We used to have it's called sort

893
00:42:17,640 --> 00:42:20,160
Speaker 3: of out of band, so the whole like return the

894
00:42:20,200 --> 00:42:23,520
Speaker 3: phone thing, it becomes almost a separate process. And frankly,

895
00:42:23,560 --> 00:42:24,960
Speaker 3: in the past it's almost felt like a bit of

896
00:42:24,960 --> 00:42:27,480
Speaker 3: a negotiation with you in the driver and nobody liked it.

897
00:42:27,480 --> 00:42:29,160
Speaker 3: The drivers didn't like it because it felt like it

898
00:42:29,200 --> 00:42:31,160
Speaker 3: was sort of an annoyance. The riders didn't like it

899
00:42:31,200 --> 00:42:33,080
Speaker 3: because they're like, oh my god, I sort of feel

900
00:42:33,080 --> 00:42:35,560
Speaker 3: like I'm being held hosted here, a terrible thing. Now

901
00:42:35,640 --> 00:42:38,640
Speaker 3: it's a whole automated process, and basically what we realize

902
00:42:38,680 --> 00:42:41,160
Speaker 3: is we should just treat it like any other ride.

903
00:42:41,200 --> 00:42:43,440
Speaker 3: So it's basically the phone is getting a ride back.

904
00:42:43,480 --> 00:42:45,879
Speaker 3: So what you get to say as a rider is yes,

905
00:42:45,920 --> 00:42:48,000
Speaker 3: please bring my phone back. I know exactly how much

906
00:42:48,080 --> 00:42:49,560
Speaker 3: is going to cost. It's going to cost just the

907
00:42:49,600 --> 00:42:51,560
Speaker 3: exact same amount as if I'd taken a ride to

908
00:42:51,600 --> 00:42:53,920
Speaker 3: that exact place where the phone is, and the driver

909
00:42:54,000 --> 00:42:55,799
Speaker 3: gets it in their queue, just like they would get

910
00:42:55,800 --> 00:42:59,080
Speaker 3: any other ride request, and it gets returned to you typically.

911
00:42:59,120 --> 00:43:01,120
Speaker 3: I was just looking at this data and it changes

912
00:43:01,160 --> 00:43:02,960
Speaker 3: every single week. But we're now getting to the point

913
00:43:02,960 --> 00:43:06,400
Speaker 3: where a large percentage of our phones are being rider's

914
00:43:06,400 --> 00:43:08,840
Speaker 3: phones are being delivered back within an hour, which is

915
00:43:08,880 --> 00:43:09,839
Speaker 3: the apps of cold Stand.

916
00:43:09,880 --> 00:43:15,040
Speaker 2: So let's use technology and cut that on the app

917
00:43:15,280 --> 00:43:18,839
Speaker 2: opt in to avoid leaving your phone in the car

918
00:43:19,040 --> 00:43:21,799
Speaker 2: via Bluetooth, not on each ride, but just once on

919
00:43:21,840 --> 00:43:25,000
Speaker 2: the app, and then when the person when the ride

920
00:43:25,120 --> 00:43:28,919
Speaker 2: is over, you've arrived and the person gets out, if

921
00:43:28,960 --> 00:43:32,560
Speaker 2: the phone doesn't leave the car right there, and then

922
00:43:32,800 --> 00:43:36,080
Speaker 2: the driver should lower the window and say, hey, you

923
00:43:36,239 --> 00:43:39,560
Speaker 2: let that car you're in the back seat. If that technology,

924
00:43:40,000 --> 00:43:43,520
Speaker 2: and that doesn't seem like you're changing or creating new technology,

925
00:43:43,920 --> 00:43:47,000
Speaker 2: You're just applying existing technology. Why take an hour? Why

926
00:43:47,080 --> 00:43:48,000
Speaker 2: not take thirty seconds?

927
00:43:49,080 --> 00:43:51,480
Speaker 3: And this is now where you realize that all technology

928
00:43:51,520 --> 00:43:54,480
Speaker 3: problems are ultimately human problems because in order for that

929
00:43:54,520 --> 00:43:56,919
Speaker 3: to happen, a person has to have opted in. They've

930
00:43:56,920 --> 00:43:59,760
Speaker 3: got to click a button. Most people are either skeptical

931
00:43:59,760 --> 00:44:02,000
Speaker 3: of that or they're not paying attention. So now that's

932
00:44:02,040 --> 00:44:03,600
Speaker 3: our trick, is to try to figure out a way

933
00:44:03,640 --> 00:44:05,960
Speaker 3: to really encourage people to do that. As you say,

934
00:44:06,000 --> 00:44:07,440
Speaker 3: you only have to do it once. But that's going

935
00:44:07,520 --> 00:44:09,200
Speaker 3: to be the next big, next big focus.

936
00:44:09,280 --> 00:44:11,600
Speaker 2: So let's stay with that theme before we really move

937
00:44:11,680 --> 00:44:16,200
Speaker 2: too far away from people and towards technology. You drive

938
00:44:16,520 --> 00:44:19,839
Speaker 2: for lift every six weeks or so, which seems kind

939
00:44:19,880 --> 00:44:23,839
Speaker 2: of bonkers. What what have you learned sitting in that

940
00:44:23,960 --> 00:44:27,120
Speaker 2: seat that you can't learn from the executive suite or

941
00:44:27,120 --> 00:44:27,759
Speaker 2: the boardroom?

942
00:44:28,120 --> 00:44:32,640
Speaker 3: So much, so much? And I know, uh, you know,

943
00:44:32,800 --> 00:44:35,320
Speaker 3: we're all busy people, you know. Here, I am busy

944
00:44:35,440 --> 00:44:38,200
Speaker 3: senior executive CEO of company. And my god, you know what,

945
00:44:38,680 --> 00:44:41,359
Speaker 3: I got time, right, I got time. I can't jump

946
00:44:41,400 --> 00:44:43,200
Speaker 3: in the car. So and here's why. So I learned

947
00:44:43,200 --> 00:44:45,160
Speaker 3: stuff about being a driver and I learned something about

948
00:44:45,160 --> 00:44:47,040
Speaker 3: being a rider every single time. So I'll give you

949
00:44:47,080 --> 00:44:49,360
Speaker 3: an example of each very quickly. On the driver side,

950
00:44:49,680 --> 00:44:52,680
Speaker 3: I learned how important a feature is that we've developed

951
00:44:52,680 --> 00:44:56,520
Speaker 3: over years and refined called uh stay within area. And

952
00:44:56,560 --> 00:44:59,080
Speaker 3: that's because there are actually two features next to each other,

953
00:44:59,120 --> 00:45:00,840
Speaker 3: one stay with a narrow one arrive on time. Let

954
00:45:00,880 --> 00:45:02,759
Speaker 3: me actually focus on a arrive on time. What that

955
00:45:02,800 --> 00:45:04,640
Speaker 3: means is I've got a kid to pick up at

956
00:45:04,640 --> 00:45:06,160
Speaker 3: the end of the day, or I've got a date

957
00:45:06,160 --> 00:45:07,799
Speaker 3: with my wife tonight, or I've got a doctor's when

958
00:45:07,800 --> 00:45:09,920
Speaker 3: I'm a three o'clock in the afternoon, and so I

959
00:45:10,000 --> 00:45:11,960
Speaker 3: need to figure out a way to organize my life

960
00:45:12,000 --> 00:45:14,400
Speaker 3: such as my last ride is going to put me,

961
00:45:14,640 --> 00:45:16,080
Speaker 3: you know, right where I need to be by a

962
00:45:16,080 --> 00:45:18,680
Speaker 3: certain time that you know, if I look at the

963
00:45:18,680 --> 00:45:20,799
Speaker 3: gig economy, one of the real gifts of the gig

964
00:45:20,800 --> 00:45:23,759
Speaker 3: economy is it allows you to integrate your work into

965
00:45:23,800 --> 00:45:26,080
Speaker 3: your life in new ways. Again, I don't have to

966
00:45:26,080 --> 00:45:27,560
Speaker 3: call my boss and tell them I'm going to be

967
00:45:27,600 --> 00:45:29,279
Speaker 3: late today. I don't have to do anything like that.

968
00:45:29,400 --> 00:45:31,120
Speaker 3: But sometimes I do have other things in my life.

969
00:45:31,200 --> 00:45:33,960
Speaker 3: Maybe it's another job, maybe it's an obligation with my

970
00:45:34,080 --> 00:45:35,600
Speaker 3: you know, with my parents, or whatever it might be.

971
00:45:35,640 --> 00:45:38,799
Speaker 3: So anyway, that's a feature. It worked pretty well when

972
00:45:38,840 --> 00:45:41,200
Speaker 3: I started. It works very well now, And in part

973
00:45:41,200 --> 00:45:42,799
Speaker 3: it's because I give a lot of feedback to the

974
00:45:42,800 --> 00:45:44,440
Speaker 3: team about how to how to make that better and

975
00:45:44,480 --> 00:45:47,600
Speaker 3: how important it is to get that exactly right. And

976
00:45:47,640 --> 00:45:50,120
Speaker 3: then on the rider's side, I mean, every time I

977
00:45:50,160 --> 00:45:52,839
Speaker 3: take you a rider in the car, and of course

978
00:45:52,840 --> 00:45:54,960
Speaker 3: I asked them why they chose us versus the other guys.

979
00:45:55,280 --> 00:45:58,239
Speaker 3: Sometimes it's because they say, oh, Chase Sapphire Reserve. I'm

980
00:45:58,280 --> 00:46:00,719
Speaker 3: a Chase Saffire Reserve a car holder, and you guys

981
00:46:00,760 --> 00:46:02,400
Speaker 3: have a relationship with them. That's great. That gives me

982
00:46:02,440 --> 00:46:04,000
Speaker 3: a little bit of data of how important it is.

983
00:46:04,080 --> 00:46:07,120
Speaker 3: That's a points relationship, points relationship, and you get all

984
00:46:07,120 --> 00:46:08,960
Speaker 3: sorts of You get ten dollars every single month to

985
00:46:09,080 --> 00:46:11,440
Speaker 3: use as lift credit. And look, I can look at

986
00:46:11,440 --> 00:46:13,319
Speaker 3: the data just like anyone else and realize the number

987
00:46:13,360 --> 00:46:15,319
Speaker 3: of people who are using that. But there's just no

988
00:46:15,400 --> 00:46:20,000
Speaker 3: substitute hearing somebody you know go off about how they much,

989
00:46:20,040 --> 00:46:22,120
Speaker 3: how much they love that card and how important that

990
00:46:22,200 --> 00:46:24,960
Speaker 3: partnership is to them. As a generic example. And then

991
00:46:25,000 --> 00:46:28,120
Speaker 3: a specific example involved a woman that I gave a

992
00:46:28,200 --> 00:46:30,279
Speaker 3: ride to. This is now about almost two years ago,

993
00:46:30,320 --> 00:46:32,680
Speaker 3: but it still really, you know, kind of resonates with

994
00:46:32,760 --> 00:46:35,520
Speaker 3: me where she would wake up every single morning and

995
00:46:35,880 --> 00:46:38,239
Speaker 3: depending on what the price was of getting from her

996
00:46:38,239 --> 00:46:41,080
Speaker 3: home to her job, because the prices would bounce around

997
00:46:41,080 --> 00:46:43,920
Speaker 3: a lot, she would either take a lift or maybe

998
00:46:43,920 --> 00:46:46,839
Speaker 3: take the other guys, or drive herself or stay home.

999
00:46:47,200 --> 00:46:49,239
Speaker 3: And it was a source of stress and concerned her

1000
00:46:49,360 --> 00:46:51,200
Speaker 3: every single day. She would literally wake up an hour,

1001
00:46:51,600 --> 00:46:53,040
Speaker 3: you know before she had to leave, just to sort

1002
00:46:53,040 --> 00:46:55,279
Speaker 3: of check prices. And it just made me realize how

1003
00:46:55,320 --> 00:47:01,080
Speaker 3: much surge pricing is is customer hostile, nobody nobody like.

1004
00:47:01,200 --> 00:47:03,480
Speaker 2: It starts to drizzle a little bit and suddenly it's

1005
00:47:03,480 --> 00:47:07,359
Speaker 2: a thirty dollars surcharge, and I know people are infuriated

1006
00:47:07,400 --> 00:47:07,759
Speaker 2: by it.

1007
00:47:07,719 --> 00:47:10,279
Speaker 3: And they should be. And here's the problem. This is

1008
00:47:10,280 --> 00:47:12,960
Speaker 3: the difference between you know, if you're an economist, you

1009
00:47:13,040 --> 00:47:16,239
Speaker 3: love this, right. It's all supply demand balancing in real time.

1010
00:47:16,280 --> 00:47:19,640
Speaker 3: It's just unbelievable, like a like a perfect science experiment.

1011
00:47:19,719 --> 00:47:21,400
Speaker 3: And if you're a real person, it just it just

1012
00:47:21,440 --> 00:47:24,560
Speaker 3: bugs a crappety you. So it really drove home to

1013
00:47:24,600 --> 00:47:26,480
Speaker 3: me how frustrating this was. And it was literally a

1014
00:47:26,520 --> 00:47:28,600
Speaker 3: Friday morning when this woman had donuts and she was

1015
00:47:28,640 --> 00:47:32,080
Speaker 3: bringing them in to see a coworker for his birthday

1016
00:47:32,200 --> 00:47:33,839
Speaker 3: and she's like, I can't work from home today. I'm

1017
00:47:33,880 --> 00:47:36,320
Speaker 3: so glad that Lyft was, you know, was reasonably priced.

1018
00:47:36,320 --> 00:47:38,720
Speaker 3: So that's what's led us to both take about fifty

1019
00:47:38,719 --> 00:47:40,719
Speaker 3: million dollars a year out of surge pricing. We've really

1020
00:47:40,760 --> 00:47:42,239
Speaker 3: tried to get rid of it as much as we can,

1021
00:47:42,520 --> 00:47:45,160
Speaker 3: can't completely eliminate it, and also introduce a product called

1022
00:47:45,160 --> 00:47:46,799
Speaker 3: price lock that allows you to lock in a price

1023
00:47:46,840 --> 00:47:47,279
Speaker 3: on a route.

1024
00:47:47,840 --> 00:47:50,520
Speaker 2: So tell us a little bit about price lock. What

1025
00:47:50,560 --> 00:47:52,799
Speaker 2: does that do? Yeah, so I'm not familiar with that

1026
00:47:52,920 --> 00:47:54,520
Speaker 2: aspect of the yep yep.

1027
00:47:54,560 --> 00:47:56,600
Speaker 3: So what it's really meant for people who commute the

1028
00:47:56,640 --> 00:47:58,719
Speaker 3: same root every day and they don't want the route

1029
00:47:58,760 --> 00:48:00,680
Speaker 3: to go from twenty to thirty to four because you

1030
00:48:00,719 --> 00:48:02,560
Speaker 3: say it right, and by the way, to be very clear, like,

1031
00:48:02,600 --> 00:48:05,000
Speaker 3: there are good reasons for surge pricing, right, it's a

1032
00:48:05,120 --> 00:48:07,839
Speaker 3: very good way for us to encourage drivers to drive

1033
00:48:07,920 --> 00:48:10,520
Speaker 3: when there's more demand than their supply. But because it's

1034
00:48:10,560 --> 00:48:12,719
Speaker 3: very frustrating for riders, we want to give people a

1035
00:48:12,719 --> 00:48:14,480
Speaker 3: way to kind of opt out of it. So for

1036
00:48:14,480 --> 00:48:16,480
Speaker 3: a given route, you know, from point A to point B,

1037
00:48:16,800 --> 00:48:18,960
Speaker 3: if you want to lock in a price, we basically say,

1038
00:48:19,040 --> 00:48:20,919
Speaker 3: here's the average price over the course of a month.

1039
00:48:21,040 --> 00:48:22,680
Speaker 3: If you want to lock in, I think it costs

1040
00:48:22,719 --> 00:48:25,560
Speaker 3: four ninety nine a month per root. That's all it takes.

1041
00:48:25,560 --> 00:48:27,279
Speaker 3: And it's been super popular for people who just want

1042
00:48:27,320 --> 00:48:28,200
Speaker 3: to get that out of their lives.

1043
00:48:28,280 --> 00:48:31,759
Speaker 2: Huh, really really really kind of interesting. So let's talk

1044
00:48:31,800 --> 00:48:35,560
Speaker 2: a little bit about autonomous driving. I was in San

1045
00:48:35,600 --> 00:48:40,120
Speaker 2: Francisco last month. Way mos are everywhere, that's right. Tell

1046
00:48:40,200 --> 00:48:43,200
Speaker 2: us a little bit about what lift wants to do

1047
00:48:43,320 --> 00:48:47,359
Speaker 2: with autonomous vehicles or these just shiny objects or these

1048
00:48:47,440 --> 00:48:47,960
Speaker 2: the future.

1049
00:48:48,440 --> 00:48:51,040
Speaker 3: They're the future. They're the future. It will take a

1050
00:48:51,080 --> 00:48:53,120
Speaker 3: long time for this future to come. It will be

1051
00:48:53,280 --> 00:48:56,120
Speaker 3: very unevenly distributed, but they are the future. And the

1052
00:48:56,480 --> 00:49:00,360
Speaker 3: basic reason why is they are a reliable product, and

1053
00:49:00,360 --> 00:49:01,480
Speaker 3: they're a safe product.

1054
00:49:01,640 --> 00:49:04,520
Speaker 2: You know, it's safer than human drivers. They are substantially right.

1055
00:49:04,800 --> 00:49:07,480
Speaker 3: And it's because they not only know the policies, but

1056
00:49:07,480 --> 00:49:09,320
Speaker 3: they follow the policies. You know, they tend to follow

1057
00:49:09,320 --> 00:49:11,239
Speaker 3: the rules and they don't get distracted, you know. So

1058
00:49:11,560 --> 00:49:13,719
Speaker 3: not to say some crazy thing won't happen one time

1059
00:49:13,760 --> 00:49:16,080
Speaker 3: out of a million, but ninety nine point nine nine

1060
00:49:16,160 --> 00:49:17,799
Speaker 3: nine percent of the time they'll do the thing that

1061
00:49:17,840 --> 00:49:19,600
Speaker 3: you expect a car to do, which is, you know,

1062
00:49:19,680 --> 00:49:22,319
Speaker 3: keep it. It's it's right or safe. So so okay,

1063
00:49:22,360 --> 00:49:25,680
Speaker 3: so that's that is coming. So now, you know, as

1064
00:49:25,680 --> 00:49:28,640
Speaker 3: a as a business person, you know, you have you

1065
00:49:28,680 --> 00:49:30,680
Speaker 3: have a choice to make, right. You can either embrace

1066
00:49:30,719 --> 00:49:34,239
Speaker 3: this or you can sort of not. And and the

1067
00:49:34,280 --> 00:49:35,640
Speaker 3: thing is, in a sense it's a choice, but in

1068
00:49:35,640 --> 00:49:39,640
Speaker 3: another sense it's not. Because you've seen Kodak you know whatever,

1069
00:49:39,719 --> 00:49:40,959
Speaker 3: full right, But by.

1070
00:49:40,840 --> 00:49:44,239
Speaker 2: The way, Kodak invented the digital camera but didn't want

1071
00:49:44,239 --> 00:49:46,759
Speaker 2: to accounibalize their own film business, and how did that

1072
00:49:46,800 --> 00:49:47,160
Speaker 2: work out?

1073
00:49:47,520 --> 00:49:49,719
Speaker 3: Exactly? Not not so well. And then you look, on

1074
00:49:49,760 --> 00:49:52,560
Speaker 3: the other hand at maybe a company like Netflix that

1075
00:49:52,719 --> 00:49:55,719
Speaker 3: invented the DVD by mail business just sort of you know,

1076
00:49:56,440 --> 00:49:59,360
Speaker 3: you know, sort of set Blockbuster aside, but did such

1077
00:49:59,400 --> 00:50:02,640
Speaker 3: a good job surfing from that to you know, streaming

1078
00:50:02,719 --> 00:50:05,160
Speaker 3: and now to original content. Right, they're a great company

1079
00:50:05,880 --> 00:50:09,719
Speaker 3: in so many ways, but they were they were relentless,

1080
00:50:09,800 --> 00:50:12,759
Speaker 3: fearless about cannibalizing their own business to sort of, you know,

1081
00:50:13,480 --> 00:50:15,480
Speaker 3: get to the next thing. So that's the shift that

1082
00:50:15,520 --> 00:50:18,520
Speaker 3: we're right in the early early early days of it

1083
00:50:18,560 --> 00:50:21,239
Speaker 3: will be another platform shift. But we're in a very

1084
00:50:21,280 --> 00:50:24,360
Speaker 3: fortunate position. And here's why. You know, we have millions

1085
00:50:24,360 --> 00:50:29,040
Speaker 3: of riders, We have millions of billions, billions of data

1086
00:50:29,080 --> 00:50:31,799
Speaker 3: points about pickup and drop off location and pricing and

1087
00:50:31,800 --> 00:50:33,760
Speaker 3: so forth and so on, and we have a whole

1088
00:50:33,800 --> 00:50:36,400
Speaker 3: subsidiary called flex Drive that does fleet management, which I

1089
00:50:36,440 --> 00:50:38,719
Speaker 3: can come back to in a couple of seconds. But

1090
00:50:38,760 --> 00:50:40,840
Speaker 3: these are going to be some of the building blocks

1091
00:50:40,880 --> 00:50:43,480
Speaker 3: of the self driving or I really should say hybrid

1092
00:50:43,520 --> 00:50:46,239
Speaker 3: network of the future, because that's the last thing I'll say.

1093
00:50:46,280 --> 00:50:48,600
Speaker 3: Just as sort of intro self driving cars are going

1094
00:50:48,600 --> 00:50:50,880
Speaker 3: to come little by little by little by little, human

1095
00:50:50,960 --> 00:50:53,319
Speaker 3: drivers are going to be around for a long, long,

1096
00:50:53,320 --> 00:50:55,799
Speaker 3: long time. There is not enough self driving cars in

1097
00:50:55,880 --> 00:50:59,279
Speaker 3: any given market to satisfy peak demand on you know,

1098
00:50:59,320 --> 00:51:01,600
Speaker 3: Friday afternoon at five o'clock rush hour or what have you.

1099
00:51:01,760 --> 00:51:04,759
Speaker 2: So this is not a three, four or five year transition.

1100
00:51:04,880 --> 00:51:06,880
Speaker 2: This is a ten to twenty year transition. Is that

1101
00:51:06,920 --> 00:51:07,359
Speaker 2: about right?

1102
00:51:07,480 --> 00:51:10,040
Speaker 3: Think about it as a decade transition. Yeah. And even again,

1103
00:51:10,200 --> 00:51:12,360
Speaker 3: the word transition I think is maybe, you know, not

1104
00:51:12,440 --> 00:51:17,000
Speaker 3: quite right, because the economics of an expensive car don't

1105
00:51:17,040 --> 00:51:19,040
Speaker 3: really lend themselves to having a whole bunch of them

1106
00:51:19,080 --> 00:51:22,000
Speaker 3: sitting around at two in the morning empty. You really,

1107
00:51:22,080 --> 00:51:24,480
Speaker 3: I think, want a hybrid network for a long long

1108
00:51:24,520 --> 00:51:27,560
Speaker 3: time for human reasons too, right, You might want someone

1109
00:51:27,560 --> 00:51:29,520
Speaker 3: to help you with your luggage, or maybe even someone

1110
00:51:29,520 --> 00:51:31,880
Speaker 3: to ask you how your day was. But the economics

1111
00:51:31,920 --> 00:51:33,960
Speaker 3: of it make it such that it's much more likely

1112
00:51:34,080 --> 00:51:35,759
Speaker 3: this will be a hybrid network for at least a

1113
00:51:35,800 --> 00:51:36,919
Speaker 3: decade or more.

1114
00:51:37,360 --> 00:51:41,759
Speaker 2: So that kind of raises an interesting question. What exactly

1115
00:51:41,880 --> 00:51:45,000
Speaker 2: is Lyft? We know it's a ride hailing company, it's

1116
00:51:45,040 --> 00:51:50,280
Speaker 2: also a transportation market clearing mechanism, it's a consumer brand,

1117
00:51:50,600 --> 00:51:55,120
Speaker 2: and it's also a logistics platform. Like where is the

1118
00:51:55,120 --> 00:51:56,440
Speaker 2: future growth coming from?

1119
00:51:56,760 --> 00:51:58,719
Speaker 3: I mean, you know a little all the above, right,

1120
00:51:58,800 --> 00:52:01,000
Speaker 3: So as you say, I mean the thing people know

1121
00:52:01,200 --> 00:52:04,640
Speaker 3: lift the most for are you know, human driven cars,

1122
00:52:05,000 --> 00:52:07,040
Speaker 3: you know, picking you up and dropping off. And as

1123
00:52:07,080 --> 00:52:08,960
Speaker 3: we were just saying, that will become a mix of

1124
00:52:09,040 --> 00:52:12,239
Speaker 3: human driven and you know, frankly robot driven cars. What

1125
00:52:12,280 --> 00:52:14,440
Speaker 3: you may not know is Lyft also runs the bike

1126
00:52:14,480 --> 00:52:17,160
Speaker 3: shore system. Here in New York City where we're.

1127
00:52:16,640 --> 00:52:19,200
Speaker 2: City bikes are run by Lyft. I do not know that.

1128
00:52:19,080 --> 00:52:21,640
Speaker 3: That's exactly right. So we run city Bike, We run

1129
00:52:21,680 --> 00:52:24,000
Speaker 3: the program in San Francisco, we run the program in Chicago,

1130
00:52:24,760 --> 00:52:27,920
Speaker 3: we run the program in Boston, in Portland, Oregon. And

1131
00:52:27,960 --> 00:52:31,560
Speaker 3: then we also supply the technology and the bikes in London,

1132
00:52:31,719 --> 00:52:35,200
Speaker 3: in Barcelona, in Madrid, you know, many many countries around

1133
00:52:35,200 --> 00:52:38,480
Speaker 3: the world. This may seem like sort of a small thing,

1134
00:52:38,680 --> 00:52:40,399
Speaker 3: but if you've been to a city like New York

1135
00:52:41,040 --> 00:52:43,960
Speaker 3: or London, you'll know that cities are very very aware

1136
00:52:44,040 --> 00:52:46,920
Speaker 3: that they want sort of multimodal transportation. So that's going

1137
00:52:47,000 --> 00:52:48,680
Speaker 3: to be, you know, a big part of our future

1138
00:52:48,719 --> 00:52:51,399
Speaker 3: as well. And then look, you know, someday, who knows,

1139
00:52:51,440 --> 00:52:54,239
Speaker 3: maybe boats, maybe vertical takeoff, airlines, you know, who knows.

1140
00:52:54,280 --> 00:52:55,880
Speaker 3: But I will tell you that our real focus right

1141
00:52:55,920 --> 00:52:58,759
Speaker 3: now and we will always be is this. This is

1142
00:52:58,800 --> 00:53:01,600
Speaker 3: our sort of purpose is sur and connecting. I want

1143
00:53:01,640 --> 00:53:03,480
Speaker 3: people to be out and about and connect with each

1144
00:53:03,520 --> 00:53:05,759
Speaker 3: other in any possible way we can. That's really what

1145
00:53:05,800 --> 00:53:06,120
Speaker 3: I want.

1146
00:53:06,239 --> 00:53:09,839
Speaker 2: So you mentioned London, Yeah, what are the plans for

1147
00:53:10,160 --> 00:53:14,880
Speaker 2: by do robotoxis in robo in London. This is going

1148
00:53:14,920 --> 00:53:18,680
Speaker 2: to be a pilot program that could potentially scale up

1149
00:53:18,760 --> 00:53:21,440
Speaker 2: dramatically like the Weimos in San Francisco.

1150
00:53:21,760 --> 00:53:24,160
Speaker 3: That's right. So again, let's think about the self driving

1151
00:53:24,200 --> 00:53:27,880
Speaker 3: car world for a couple of minutes. The technology is

1152
00:53:27,920 --> 00:53:31,040
Speaker 3: being developed worldwide. It's being developed in the United States.

1153
00:53:31,120 --> 00:53:34,960
Speaker 3: Weaimo of course is the leader, really the worldwide leader. Zooks,

1154
00:53:35,200 --> 00:53:38,000
Speaker 3: which is owned by Amazon, is much much smaller, but

1155
00:53:38,040 --> 00:53:40,400
Speaker 3: you know, trying very hard to come up behind Waimo.

1156
00:53:40,640 --> 00:53:42,759
Speaker 3: And then there'll be you know, many others, including maybe

1157
00:53:42,800 --> 00:53:44,640
Speaker 3: in Nvidia and companies that aren't even really in the

1158
00:53:44,640 --> 00:53:47,560
Speaker 3: space now, but we'll want to sell their technology to

1159
00:53:47,680 --> 00:53:52,560
Speaker 3: different Oh yeah, it's different car manufacturers. There's also technology

1160
00:53:52,600 --> 00:53:56,240
Speaker 3: coming out of China by do is sort of the Google.

1161
00:53:56,840 --> 00:53:59,040
Speaker 3: You think of it as kind of the alphabet of China.

1162
00:54:00,320 --> 00:54:02,200
Speaker 3: And there are many many others. There's a company called

1163
00:54:02,200 --> 00:54:04,000
Speaker 3: we Ride. There's a company called Pony, There's a company

1164
00:54:04,000 --> 00:54:07,120
Speaker 3: called Momenta. There's a company called Jie. I was just

1165
00:54:07,160 --> 00:54:09,200
Speaker 3: in China a couple of weeks ago looking at the

1166
00:54:09,320 --> 00:54:13,880
Speaker 3: incredible just growth of technology there, both hardware and software

1167
00:54:13,920 --> 00:54:17,680
Speaker 3: type technology. Okay, so that's all background. It's going to

1168
00:54:17,680 --> 00:54:22,040
Speaker 3: be deployed worldwide and in the United States, Chinese technology

1169
00:54:22,080 --> 00:54:24,759
Speaker 3: is not super welcome for obvious reasons, but Europe is

1170
00:54:24,800 --> 00:54:27,680
Speaker 3: taking maybe a little bit of a more sort of

1171
00:54:27,719 --> 00:54:30,400
Speaker 3: economical approach where they're kind of looking at different technology

1172
00:54:30,400 --> 00:54:33,640
Speaker 3: providers and saying, let's experiment. So in London we're partners

1173
00:54:33,680 --> 00:54:36,120
Speaker 3: with by Do. By Do has a very very highly

1174
00:54:36,120 --> 00:54:39,239
Speaker 3: regarded self driving platform and we're just in the early

1175
00:54:39,320 --> 00:54:41,520
Speaker 3: days of rolling it out there. It's called an art

1176
00:54:41,680 --> 00:54:43,840
Speaker 3: six car. This is sort of behind the scenes stuff

1177
00:54:44,000 --> 00:54:46,840
Speaker 3: and it literally just rolling off boats right now and

1178
00:54:46,840 --> 00:54:48,239
Speaker 3: it'll be commercialized next year.

1179
00:54:48,680 --> 00:54:53,480
Speaker 2: So I'm looking at the current crop of autonomous vehicles,

1180
00:54:53,920 --> 00:54:59,080
Speaker 2: which are essentially converted traditional cars, But you really do

1181
00:54:59,160 --> 00:55:02,160
Speaker 2: you need that front driver's see? Can you change up

1182
00:55:02,200 --> 00:55:05,920
Speaker 2: the internal layer? Like what are autonomous vehicles going to

1183
00:55:05,960 --> 00:55:09,799
Speaker 2: look like? Not in twenty sixty but in a couple

1184
00:55:09,840 --> 00:55:10,240
Speaker 2: of years.

1185
00:55:10,320 --> 00:55:13,400
Speaker 3: Yeah. So again, it's such an interesting time to be

1186
00:55:13,440 --> 00:55:16,080
Speaker 3: in this industry. And it's exactly you know, as you're saying, like,

1187
00:55:16,120 --> 00:55:18,120
Speaker 3: do you really need a steering wheel? Do you really

1188
00:55:18,160 --> 00:55:21,640
Speaker 3: need you know, accelerator and breaks? You know? Zeokes as

1189
00:55:21,680 --> 00:55:23,680
Speaker 3: they say they're in Amazon subsidiary, they would say you

1190
00:55:23,719 --> 00:55:25,960
Speaker 3: absolutely don't. And they have a purpose built vehicle that

1191
00:55:26,000 --> 00:55:29,640
Speaker 3: doesn't have either one of those things now for regulatory reasons,

1192
00:55:29,640 --> 00:55:33,640
Speaker 3: for human acceptance reasons, and so forth, for manufacturing reasons,

1193
00:55:33,880 --> 00:55:35,759
Speaker 3: that's going to be slower to roll out because you

1194
00:55:35,800 --> 00:55:38,520
Speaker 3: can't rely on, you know, the big OEMs to produce

1195
00:55:38,520 --> 00:55:41,400
Speaker 3: a car like that that's its own vehicle. So I

1196
00:55:41,400 --> 00:55:42,879
Speaker 3: think what you're going to see over the next three

1197
00:55:42,920 --> 00:55:45,800
Speaker 3: to five years is an enormous amount of new innovation

1198
00:55:46,120 --> 00:55:49,399
Speaker 3: in the in the car space. It won't just be

1199
00:55:49,480 --> 00:55:51,480
Speaker 3: you know, there won't be a driver. It'll be you know,

1200
00:55:51,520 --> 00:55:54,560
Speaker 3: you'll have seats that face each other. You know, you'll

1201
00:55:54,560 --> 00:55:57,080
Speaker 3: have seats that completely recline because you've got more space

1202
00:55:57,120 --> 00:56:00,200
Speaker 3: in there. You'll have different luggage configurations. You'll have some

1203
00:56:00,239 --> 00:56:02,200
Speaker 3: of them will feel more like you know, party buses,

1204
00:56:02,239 --> 00:56:04,160
Speaker 3: some of them maybe you know, corporate shuttles that just

1205
00:56:04,160 --> 00:56:06,279
Speaker 3: don't have drivers. A lot of new stuff is going

1206
00:56:06,360 --> 00:56:08,640
Speaker 3: to come in the next couple of years, step by step,

1207
00:56:08,680 --> 00:56:10,560
Speaker 3: because again, you know, hardware is hard. It takes a

1208
00:56:10,560 --> 00:56:12,239
Speaker 3: long time to build it out. But you know, you

1209
00:56:12,280 --> 00:56:13,680
Speaker 3: look five years out and I think you're going to

1210
00:56:13,719 --> 00:56:15,239
Speaker 3: see a lot of cars look pretty different from what

1211
00:56:15,280 --> 00:56:15,840
Speaker 3: you see today.

1212
00:56:16,280 --> 00:56:20,719
Speaker 2: I'm unfamiliar with Zekes and Amazon's relationship with them. But

1213
00:56:20,800 --> 00:56:24,279
Speaker 2: if I recall correctly, Amazon was an early investor, took

1214
00:56:24,280 --> 00:56:25,080
Speaker 2: a big chunk.

1215
00:56:24,840 --> 00:56:26,120
Speaker 3: Of Rivian, that's right.

1216
00:56:25,920 --> 00:56:29,760
Speaker 2: And all of the electric Amazon delivery vehicles you see

1217
00:56:30,000 --> 00:56:35,040
Speaker 2: are essentially the Rivian platform repurposed for commercial use. That's right,

1218
00:56:36,280 --> 00:56:39,800
Speaker 2: Zooks plus Rivian is that the direction Amazon is going?

1219
00:56:39,920 --> 00:56:44,400
Speaker 2: And do you guys, does Lift whose CEO has a

1220
00:56:44,440 --> 00:56:48,440
Speaker 2: relationship with Jeff have a relationship with Amazon.

1221
00:56:49,040 --> 00:56:51,080
Speaker 3: We do have a relationship with Amazon. Of course we're

1222
00:56:51,120 --> 00:56:56,600
Speaker 3: huge consumers of AWS, which is andy current CEOs you know,

1223
00:56:56,680 --> 00:57:00,719
Speaker 3: kind of kind of pride and enjoy and for sure

1224
00:57:00,760 --> 00:57:03,479
Speaker 3: we'll end up using uh, you know, we'll look, everyone

1225
00:57:03,640 --> 00:57:05,799
Speaker 3: is going to end up partnering with everyone. That's That's

1226
00:57:05,840 --> 00:57:08,040
Speaker 3: the interesting space we're in right now is if you're

1227
00:57:08,080 --> 00:57:09,960
Speaker 3: in the if you're in the business of developing a

1228
00:57:10,000 --> 00:57:12,920
Speaker 3: self driving car, it's billions of dollars of R and

1229
00:57:13,000 --> 00:57:15,200
Speaker 3: D billions of dollars, and so you want as many

1230
00:57:15,239 --> 00:57:17,920
Speaker 3: customers as possible. And then if you're in our business

1231
00:57:17,960 --> 00:57:20,480
Speaker 3: and the business of moving people around and connecting people,

1232
00:57:20,760 --> 00:57:23,520
Speaker 3: you want to have multiple suppliers of that technology so

1233
00:57:23,560 --> 00:57:26,760
Speaker 3: you're not beholden to anyone. Some of that is just

1234
00:57:26,880 --> 00:57:28,960
Speaker 3: being you know, a smart you know, business person. But

1235
00:57:29,000 --> 00:57:31,400
Speaker 3: some of it also is you know, technology goes through

1236
00:57:31,440 --> 00:57:33,120
Speaker 3: its own you know, fits and starts. Look at what

1237
00:57:33,160 --> 00:57:35,640
Speaker 3: happens with the airline business when all of a sudden,

1238
00:57:36,000 --> 00:57:37,480
Speaker 3: you know, Boeing has a problem with one of its

1239
00:57:37,640 --> 00:57:40,200
Speaker 3: its units. Uh, you know, they stop manufacturing those for

1240
00:57:40,240 --> 00:57:43,120
Speaker 3: a time or they're grounded. So I don't want to overdramatize,

1241
00:57:43,120 --> 00:57:45,160
Speaker 3: but you know, anytime new technology comes out, you're going

1242
00:57:45,240 --> 00:57:46,840
Speaker 3: to find you know, some of that happens as well.

1243
00:57:46,880 --> 00:57:49,600
Speaker 3: So all of us are kind of in multiple Uh

1244
00:57:49,640 --> 00:57:52,680
Speaker 3: you know, let's say maybe polyamus relationships might be one

1245
00:57:52,680 --> 00:57:53,600
Speaker 3: way to well.

1246
00:57:53,520 --> 00:57:56,240
Speaker 2: Don't you have to be play? You can't lock into

1247
00:57:56,280 --> 00:58:00,760
Speaker 2: platform dependency too early, otherwise you end up owning beta

1248
00:58:00,840 --> 00:58:03,240
Speaker 2: max and what good is that? And I know half

1249
00:58:03,280 --> 00:58:04,600
Speaker 2: our audience has no idea what.

1250
00:58:04,600 --> 00:58:05,160
Speaker 3: The hell that is?

1251
00:58:05,240 --> 00:58:07,200
Speaker 2: So there we go it old school reference. Yeah, but

1252
00:58:07,200 --> 00:58:11,479
Speaker 2: what I mean when you commit one way? So let's

1253
00:58:11,480 --> 00:58:16,040
Speaker 2: talk a little more about the autonomous ride hailing. What

1254
00:58:16,120 --> 00:58:18,760
Speaker 2: are the big concerns? Is it safety? Is it regulation?

1255
00:58:19,040 --> 00:58:23,200
Speaker 2: Is it winning the consumer's trust? What are the economics

1256
00:58:23,200 --> 00:58:24,560
Speaker 2: of managing a fleet like that?

1257
00:58:25,440 --> 00:58:27,880
Speaker 3: Again, so many interesting questions here. Let's start with the

1258
00:58:27,880 --> 00:58:30,400
Speaker 3: customer side of things, right, So the first order of

1259
00:58:30,440 --> 00:58:33,920
Speaker 3: business has to be building customer trust and adoption for

1260
00:58:33,960 --> 00:58:36,840
Speaker 3: this new technology, because you know, it's a car that

1261
00:58:36,920 --> 00:58:39,520
Speaker 3: drives itself, which is magical but also can be a

1262
00:58:39,520 --> 00:58:42,200
Speaker 3: bit intimidating or you know, even scary for people who

1263
00:58:42,280 --> 00:58:45,040
Speaker 3: you haven't seen the technology. Lift obviously has a lot

1264
00:58:45,080 --> 00:58:47,480
Speaker 3: of value to add right there, because it's a brand

1265
00:58:47,480 --> 00:58:50,040
Speaker 3: that already people trust, they understand, you'll be able to

1266
00:58:50,080 --> 00:58:52,160
Speaker 3: opt in or opt out of getting it. I was

1267
00:58:52,200 --> 00:58:54,200
Speaker 3: just in Atlanta a couple of weeks ago, or we're

1268
00:58:54,520 --> 00:58:58,120
Speaker 3: have an experiment, small deployment with a company called Mame Mobility,

1269
00:58:58,360 --> 00:59:01,280
Speaker 3: which is also in the self driving car space. They're Toyota,

1270
00:59:01,360 --> 00:59:04,040
Speaker 3: Siennas they pull up to you and all of a

1271
00:59:04,040 --> 00:59:05,760
Speaker 3: sudden you get in. It's kind of a whole different

1272
00:59:05,760 --> 00:59:07,960
Speaker 3: type of experience from which you've probably experienced in the past.

1273
00:59:08,120 --> 00:59:10,560
Speaker 3: But because it's got lyft behind it right on the

1274
00:59:10,560 --> 00:59:12,800
Speaker 3: door already, people sort of say, okay, great, I kind

1275
00:59:12,800 --> 00:59:14,720
Speaker 3: of understand this company and know something about it. Okay,

1276
00:59:14,720 --> 00:59:16,919
Speaker 3: that's great. So then you kind of have to work

1277
00:59:16,960 --> 00:59:19,880
Speaker 3: yourself down the stack. There's all sorts of technology problems

1278
00:59:19,880 --> 00:59:23,040
Speaker 3: that you have to solve as you integrate their platform

1279
00:59:23,200 --> 00:59:25,880
Speaker 3: and us, and then someone's got to manage these cars.

1280
00:59:26,040 --> 00:59:28,000
Speaker 3: And this is worth talking about for a couple seconds.

1281
00:59:28,360 --> 00:59:31,880
Speaker 3: In traditional ride share, the driver is responsible for their

1282
00:59:31,920 --> 00:59:34,080
Speaker 3: own car, right they put gas in it, or they

1283
00:59:34,160 --> 00:59:36,680
Speaker 3: charge up if it's electric, They keep it clean, hopefully

1284
00:59:36,920 --> 00:59:40,160
Speaker 3: they keep it maintained and so forth. But in the

1285
00:59:40,200 --> 00:59:42,440
Speaker 3: self driving space, at least for the next three to

1286
00:59:42,520 --> 00:59:45,360
Speaker 3: five years, most of the car ownership are going to

1287
00:59:45,400 --> 00:59:48,840
Speaker 3: be professional fleet owners. Know they're going to buy twenty fifty,

1288
00:59:48,880 --> 00:59:51,200
Speaker 3: one hundred, five hundred, and they're going to kind of

1289
00:59:51,240 --> 00:59:53,760
Speaker 3: manage these as a fleet, and that means that they've

1290
00:59:53,800 --> 00:59:56,520
Speaker 3: got to be again charged and maintained and cleaned, but

1291
00:59:56,560 --> 00:59:57,680
Speaker 3: they have to be done at kind of at a

1292
00:59:57,760 --> 01:00:00,320
Speaker 3: professional level. That's the sort of stage where we're in.

1293
01:00:00,840 --> 01:00:03,320
Speaker 3: We've had a subsidiary for many years called flex Drive.

1294
01:00:03,720 --> 01:00:06,000
Speaker 3: We actually own about ten thousand cars on the lift

1295
01:00:06,040 --> 01:00:08,360
Speaker 3: platform for drivers who don't want to drive their own car,

1296
01:00:08,680 --> 01:00:11,520
Speaker 3: and we are responsible for maintenance and keeping them cleaned

1297
01:00:11,720 --> 01:00:13,560
Speaker 3: and so forth and so on. So we actually bring

1298
01:00:13,600 --> 01:00:15,160
Speaker 3: a lot to that as well. And I think that's

1299
01:00:15,200 --> 01:00:17,920
Speaker 3: one of the reasons why we like the economic profile

1300
01:00:17,960 --> 01:00:20,800
Speaker 3: of self driving cars. They don't have insurance as high,

1301
01:00:20,880 --> 01:00:24,000
Speaker 3: for example, as personally driven cars. But also we like

1302
01:00:24,040 --> 01:00:26,800
Speaker 3: the economics of our fleet management subsidiary and think we

1303
01:00:26,840 --> 01:00:30,160
Speaker 3: can service these at an industry leading rate and therefore

1304
01:00:30,160 --> 01:00:32,439
Speaker 3: hopefully make more money on the asset than anybody else.

1305
01:00:33,040 --> 01:00:35,200
Speaker 2: Is there still going to be a future for people

1306
01:00:35,280 --> 01:00:39,520
Speaker 2: who today you would think of owner drivers who just

1307
01:00:39,600 --> 01:00:42,840
Speaker 2: want to own autonomous vehicles and lease them out or

1308
01:00:43,480 --> 01:00:46,680
Speaker 2: send them out into the lift network. Like I'm crunching

1309
01:00:46,720 --> 01:00:48,919
Speaker 2: the numbers in my head as we're speaking, and I'm like, oh,

1310
01:00:48,960 --> 01:00:51,960
Speaker 2: that could be a ten to twelve percent return on investment,

1311
01:00:52,360 --> 01:00:55,560
Speaker 2: not bad when bond yields are four percent, three and

1312
01:00:55,600 --> 01:00:56,960
Speaker 2: a half percent, one hundred percent.

1313
01:00:57,040 --> 01:00:58,680
Speaker 3: I mean, there will be a time where, you know,

1314
01:00:58,720 --> 01:01:00,680
Speaker 3: if you fast forward, you know, five years or whatever,

1315
01:01:00,760 --> 01:01:04,200
Speaker 3: maybe more many people individual owners have cars that can

1316
01:01:04,240 --> 01:01:06,439
Speaker 3: drive themselves. And then there's a question to your point

1317
01:01:06,440 --> 01:01:08,640
Speaker 3: of can you put that on the network? The answer

1318
01:01:08,680 --> 01:01:10,160
Speaker 3: is absolutely, you'll be able to put it on the

1319
01:01:10,160 --> 01:01:12,960
Speaker 3: lift network and it'll come back again, cleaned and charged.

1320
01:01:13,000 --> 01:01:15,440
Speaker 3: Because of the flea management side of things.

1321
01:01:15,240 --> 01:01:19,520
Speaker 2: That sounds really really interesting, you know, it's funny because

1322
01:01:19,560 --> 01:01:23,440
Speaker 2: when the ride apps first came out, there was a

1323
01:01:23,800 --> 01:01:27,760
Speaker 2: little bit of a lag before people got comfortable. What

1324
01:01:27,800 --> 01:01:30,439
Speaker 2: do you mean I'm getting into a stranger's car. I

1325
01:01:30,440 --> 01:01:32,800
Speaker 2: imagine we're going to go through the same thing. What

1326
01:01:32,800 --> 01:01:34,880
Speaker 2: do you mean I'm getting into a car with no driver.

1327
01:01:36,560 --> 01:01:40,120
Speaker 2: It feels like the transitions are happening faster and faster,

1328
01:01:40,920 --> 01:01:43,680
Speaker 2: same sort of question. This isn't a ten twenty year thing.

1329
01:01:43,880 --> 01:01:47,920
Speaker 2: This is a couple of years before people are forget

1330
01:01:48,240 --> 01:01:52,760
Speaker 2: people under thirty who adapt so rapidly, the middle part

1331
01:01:52,800 --> 01:01:56,240
Speaker 2: of that age bell curve, the thirty to sixty. They're

1332
01:01:56,240 --> 01:01:58,280
Speaker 2: going to adapt to this pretty quickly over the next

1333
01:01:58,320 --> 01:02:00,760
Speaker 2: couple of years. How do you think about the different

1334
01:02:00,760 --> 01:02:03,960
Speaker 2: segments of consumer when it comes to autonomous driving?

1335
01:02:04,080 --> 01:02:07,120
Speaker 3: Yeah, you know, I think as you're suggesting, you know,

1336
01:02:07,400 --> 01:02:10,040
Speaker 3: younger people do tend to take up new technology, you know,

1337
01:02:10,040 --> 01:02:12,760
Speaker 3: pretty quickly. But in this case, I do believe that

1338
01:02:12,960 --> 01:02:15,440
Speaker 3: many people, after they've had a couple of rides and

1339
01:02:15,480 --> 01:02:18,000
Speaker 3: realize that it feels very safe and reliable, I think

1340
01:02:18,040 --> 01:02:20,960
Speaker 3: they'll flip from skeptic to kind of fans, you know,

1341
01:02:20,960 --> 01:02:24,160
Speaker 3: pretty quickly. Now, I will say policy makers, you know,

1342
01:02:24,240 --> 01:02:27,000
Speaker 3: they have their own you know issues, so and some

1343
01:02:27,080 --> 01:02:28,680
Speaker 3: of that can be very local. So you may find

1344
01:02:28,680 --> 01:02:30,400
Speaker 3: some cities that just say we just don't want them

1345
01:02:30,400 --> 01:02:32,440
Speaker 3: on our streets for a period of time. You may

1346
01:02:32,440 --> 01:02:34,720
Speaker 3: find conversely, other cities that say, bring them because we

1347
01:02:34,720 --> 01:02:36,040
Speaker 3: want to feel like a city of the future. So

1348
01:02:36,040 --> 01:02:37,480
Speaker 3: I think there are going to be some policy issues.

1349
01:02:37,760 --> 01:02:40,120
Speaker 3: There are also some infrastructure issues. Remember that, you know,

1350
01:02:40,280 --> 01:02:44,880
Speaker 3: av's also tend to be evs. Evs require charging. Charging

1351
01:02:44,920 --> 01:02:47,920
Speaker 3: requires infrastructure, and not every city is going to have

1352
01:02:47,960 --> 01:02:51,120
Speaker 3: the amount of electrical power. I mean, this is kind

1353
01:02:51,120 --> 01:02:53,120
Speaker 3: of a side issue. But if you listen to you know,

1354
01:02:53,200 --> 01:02:56,080
Speaker 3: Jensen for example at Nvidia talk about what could end

1355
01:02:56,160 --> 01:02:58,360
Speaker 3: up holding the United States back from its next pick leap,

1356
01:02:58,640 --> 01:03:00,520
Speaker 3: a lot of it comes down to power structure in

1357
01:03:00,920 --> 01:03:03,240
Speaker 3: this country, right, So anyway, so there are many different

1358
01:03:03,320 --> 01:03:05,200
Speaker 3: kind of bits and pieces all the way from consumer

1359
01:03:05,360 --> 01:03:09,440
Speaker 3: adoption to physical infrastructure to policy and so forth. But

1360
01:03:09,520 --> 01:03:11,160
Speaker 3: I think again, over the next three to five years,

1361
01:03:11,200 --> 01:03:12,800
Speaker 3: I think you're going to see a real shift, mostly

1362
01:03:12,840 --> 01:03:14,880
Speaker 3: because consumers are going to try them and like them,

1363
01:03:15,040 --> 01:03:16,680
Speaker 3: and then they're going to be saying, hey, you know,

1364
01:03:16,880 --> 01:03:17,600
Speaker 3: faster please.

1365
01:03:17,960 --> 01:03:21,400
Speaker 2: So here's the crazy thing. About avs that I'm still

1366
01:03:21,480 --> 01:03:25,840
Speaker 2: kind of shocked about that relies on visual on lidar,

1367
01:03:26,000 --> 01:03:29,320
Speaker 2: on radar and all these other technologies, but there isn't

1368
01:03:29,320 --> 01:03:33,000
Speaker 2: a whole lot of infrastructure built into the roadway grid.

1369
01:03:33,480 --> 01:03:38,280
Speaker 2: Wouldn't be that difficult to create a series of RF

1370
01:03:38,360 --> 01:03:45,680
Speaker 2: devices that specifically geared for autonomous vehicles that like, every

1371
01:03:45,760 --> 01:03:48,160
Speaker 2: now and then if you're letting the car drive yourself

1372
01:03:48,720 --> 01:03:53,400
Speaker 2: and there's an exit or a merge or like, it's

1373
01:03:53,480 --> 01:03:58,080
Speaker 2: not great with those sort of things today because there's

1374
01:03:58,120 --> 01:04:03,040
Speaker 2: no real infrastructure. It's relying on a technology not built

1375
01:04:03,040 --> 01:04:07,800
Speaker 2: for autonomous driving. Is there any sort of motion towards Hey,

1376
01:04:07,920 --> 01:04:10,720
Speaker 2: let's everybody that's doing autonomous come up with set of

1377
01:04:10,960 --> 01:04:15,920
Speaker 2: standards and have the government implement this into the highway system.

1378
01:04:16,320 --> 01:04:20,800
Speaker 3: I mean, the short answer is no today and long

1379
01:04:20,920 --> 01:04:24,720
Speaker 3: term for sure. And the reason no today frankly is again,

1380
01:04:25,120 --> 01:04:27,960
Speaker 3: you know, anytime you see these platform ships, you always

1381
01:04:27,960 --> 01:04:30,080
Speaker 3: have competition for sort of who gets to sort of

1382
01:04:30,120 --> 01:04:33,280
Speaker 3: own the platform, right, and individual companies all have a

1383
01:04:33,400 --> 01:04:35,400
Speaker 3: huge incentive to say, you know, I want to do

1384
01:04:35,480 --> 01:04:37,360
Speaker 3: it my way, because if my way becomes the standard,

1385
01:04:37,400 --> 01:04:39,160
Speaker 3: then everyone else kind of follows along me and I

1386
01:04:39,160 --> 01:04:41,680
Speaker 3: get to sort of set the standard. Over time, though,

1387
01:04:41,720 --> 01:04:45,360
Speaker 3: you tend to see that those things that doesn't become

1388
01:04:45,520 --> 01:04:49,000
Speaker 3: a long term competitive advantage typically, particularly for this sort

1389
01:04:49,000 --> 01:04:51,920
Speaker 3: of infrastructure, And so I would fully expect over time,

1390
01:04:52,120 --> 01:04:53,520
Speaker 3: it's just in the same way that you can start

1391
01:04:53,520 --> 01:04:56,000
Speaker 3: to see charging networks kind of harmonize, that you'll see

1392
01:04:56,040 --> 01:04:57,680
Speaker 3: some sort of you know, kind of federal level. But

1393
01:04:58,120 --> 01:04:59,400
Speaker 3: we're years before that, right.

1394
01:04:59,440 --> 01:05:02,440
Speaker 2: We did see that sort of standardization take place in

1395
01:05:02,480 --> 01:05:06,480
Speaker 2: a lot of other technologies, and suddenly you're not competing

1396
01:05:06,600 --> 01:05:10,320
Speaker 2: on a standard, you're competing on highest quality, lowest price,

1397
01:05:10,360 --> 01:05:10,840
Speaker 2: et cetera.

1398
01:05:11,000 --> 01:05:11,520
Speaker 3: Exactly right.

1399
01:05:11,760 --> 01:05:15,200
Speaker 2: But you would think that if the cars literally knew

1400
01:05:15,240 --> 01:05:18,720
Speaker 2: exactly where the road was, it would be even that

1401
01:05:18,800 --> 01:05:19,840
Speaker 2: much safer.

1402
01:05:19,680 --> 01:05:22,080
Speaker 3: You would think. But I would say right now that

1403
01:05:22,280 --> 01:05:26,480
Speaker 3: the technology is evolving so quickly at the car level,

1404
01:05:27,080 --> 01:05:30,080
Speaker 3: and really the safety is very, very, very impressive. And

1405
01:05:30,080 --> 01:05:32,840
Speaker 3: and of course, look, I know, you know, tomorrow morning

1406
01:05:33,080 --> 01:05:35,040
Speaker 3: you're going to open up, you know, a newspaper or

1407
01:05:35,040 --> 01:05:37,000
Speaker 3: an app, and you're going to read about some strange

1408
01:05:37,000 --> 01:05:39,560
Speaker 3: thing that happened, you know, in some strange part of

1409
01:05:39,600 --> 01:05:41,480
Speaker 3: the of the world with a self driving car. And

1410
01:05:41,520 --> 01:05:43,160
Speaker 3: I'm going to tell you that that is going to happen,

1411
01:05:43,320 --> 01:05:46,200
Speaker 3: and that's you know, one in a million as opposed

1412
01:05:46,240 --> 01:05:48,480
Speaker 3: to you know, one in you know hundreds, which happened

1413
01:05:48,480 --> 01:05:49,760
Speaker 3: every single day with human drivers.

1414
01:05:49,840 --> 01:05:54,720
Speaker 2: Yeah, those are the clickbait headlines, not the statistically significant practice.

1415
01:05:54,720 --> 01:05:56,960
Speaker 2: All right, So last question before I get to my

1416
01:05:57,520 --> 01:06:00,840
Speaker 2: favorite questions, I ask, well, my guests, when it comes

1417
01:06:00,840 --> 01:06:06,480
Speaker 2: to transportation technology, what are we not discussing as a society,

1418
01:06:06,520 --> 01:06:09,400
Speaker 2: as a government, as consumers that we really should be.

1419
01:06:09,440 --> 01:06:12,560
Speaker 2: What is kind of getting overlooked in this rush to

1420
01:06:12,640 --> 01:06:15,760
Speaker 2: new technology? It could even be something that you guys

1421
01:06:15,800 --> 01:06:18,600
Speaker 2: are focused on, but a lot of people don't realize

1422
01:06:18,680 --> 01:06:21,320
Speaker 2: is oh no, this is really significant and the public

1423
01:06:21,320 --> 01:06:22,840
Speaker 2: hasn't quite grocked this yet.

1424
01:06:23,000 --> 01:06:26,400
Speaker 3: Yeah, you know, I'm going to come back to the

1425
01:06:26,520 --> 01:06:30,919
Speaker 3: basic role that technology plays in people's lives to help

1426
01:06:30,960 --> 01:06:33,920
Speaker 3: them live their absolute best lives. I'll tell you something

1427
01:06:33,920 --> 01:06:36,120
Speaker 3: that I have a lot of passionate about personally, and

1428
01:06:36,160 --> 01:06:39,000
Speaker 3: that is as people live longer lives, one of the

1429
01:06:39,040 --> 01:06:42,160
Speaker 3: things that is very predictive of their quality of life

1430
01:06:42,280 --> 01:06:44,080
Speaker 3: is how much time they're spending with other.

1431
01:06:43,960 --> 01:06:47,000
Speaker 2: People out socializing.

1432
01:06:45,880 --> 01:06:49,600
Speaker 3: Exactly, very very highly predictive of a healthy long life,

1433
01:06:50,120 --> 01:06:53,360
Speaker 3: and as we as a country are getting older, which

1434
01:06:53,360 --> 01:06:57,120
Speaker 3: we are demographically, that is going to be an enormous

1435
01:06:57,120 --> 01:06:59,880
Speaker 3: shift where you have so many more people in their sixties, seventies,

1436
01:07:00,040 --> 01:07:03,760
Speaker 3: even eighties who want to live healthy, vibrant lives. And

1437
01:07:03,800 --> 01:07:05,440
Speaker 3: so one of the things I'm really quite proud of

1438
01:07:05,520 --> 01:07:08,200
Speaker 3: with Lyft is, you know, Lift Silver is a particular

1439
01:07:08,200 --> 01:07:10,760
Speaker 3: product line that we've developed over the last year that's

1440
01:07:10,800 --> 01:07:13,040
Speaker 3: really focused on, you know, helping older folks get out.

1441
01:07:13,280 --> 01:07:15,160
Speaker 3: The app's a little easier to use, the cars are

1442
01:07:15,160 --> 01:07:17,400
Speaker 3: really easier to get into, the drivers a little bit

1443
01:07:17,440 --> 01:07:20,560
Speaker 3: more experienced. I think that sort of the intersection between

1444
01:07:21,160 --> 01:07:23,360
Speaker 3: societal trend and the type of work we do in

1445
01:07:23,360 --> 01:07:26,560
Speaker 3: transportation is really quite deep, and you know, maybe just

1446
01:07:26,600 --> 01:07:28,720
Speaker 3: as important ultimately as you know all of our conversation

1447
01:07:28,800 --> 01:07:31,120
Speaker 3: around medicine and so forth and so on, is keeping

1448
01:07:31,160 --> 01:07:33,000
Speaker 3: people out and about. And I know it's you're an

1449
01:07:33,080 --> 01:07:35,640
Speaker 3: or ring where I am as well, it's a uh

1450
01:07:35,880 --> 01:07:36,440
Speaker 3: or maybe or not.

1451
01:07:36,480 --> 01:07:38,840
Speaker 2: I don't know, No, I am. My wife wanted to

1452
01:07:38,840 --> 01:07:41,680
Speaker 2: get so we got a pair and she got bored

1453
01:07:41,800 --> 01:07:44,160
Speaker 2: being told she's stressed all the time and stop wearing it.

1454
01:07:44,200 --> 01:07:46,439
Speaker 2: So now I'm wearing funny, so we both we each

1455
01:07:46,480 --> 01:07:48,040
Speaker 2: have one, and I'm the only one who still.

1456
01:07:47,840 --> 01:07:49,600
Speaker 3: Wears how funny. Okay, actually my wife and I did

1457
01:07:49,600 --> 01:07:51,320
Speaker 3: the same. She said, I get a little tired of saying,

1458
01:07:51,360 --> 01:07:53,120
Speaker 3: you know that it's telling me exactly I'm stressed or

1459
01:07:53,160 --> 01:07:55,280
Speaker 3: I'm not sleeping well. But at least for me, it's

1460
01:07:55,280 --> 01:07:57,600
Speaker 3: a sort of nice nudge to get good sleep and frankly,

1461
01:07:57,680 --> 01:07:59,600
Speaker 3: to kind of keep an active life. And so so

1462
01:07:59,640 --> 01:08:02,480
Speaker 3: I see this space the transplation pieces is somewhat similar, like,

1463
01:08:02,640 --> 01:08:04,560
Speaker 3: I want technology that kind of helps me live my

1464
01:08:04,640 --> 01:08:07,800
Speaker 3: best life, and I think transportation plays a big role there.

1465
01:08:07,920 --> 01:08:10,280
Speaker 2: All right, so let's jump to our speed round our

1466
01:08:10,320 --> 01:08:14,439
Speaker 2: favorite questions, starting with tell us about your mentors who

1467
01:08:14,480 --> 01:08:15,680
Speaker 2: helped shape your career.

1468
01:08:16,120 --> 01:08:19,000
Speaker 3: Oh gosh, I love this question because I think it's

1469
01:08:19,040 --> 01:08:20,639
Speaker 3: so important for us to remember that we all stand

1470
01:08:20,640 --> 01:08:24,800
Speaker 3: on other people's shoulders. A list a few. Of course.

1471
01:08:24,840 --> 01:08:26,720
Speaker 3: I've worked for Jeff Bezos a lot. I've mentioned him,

1472
01:08:26,760 --> 01:08:29,160
Speaker 3: but I wanted other people first, Big Boss, a guy

1473
01:08:29,200 --> 01:08:33,680
Speaker 3: named Todd Nilsen. Todd really taught me the power of

1474
01:08:33,760 --> 01:08:38,040
Speaker 3: a great story and also the importance of really listening

1475
01:08:38,040 --> 01:08:40,960
Speaker 3: and watching closely customers, so he taught me to big

1476
01:08:40,960 --> 01:08:43,559
Speaker 3: things there. And then a guy named Peter Spirow. He

1477
01:08:43,640 --> 01:08:45,439
Speaker 3: was the board chair World Reader for many years. He

1478
01:08:45,479 --> 01:08:46,760
Speaker 3: and I sort of knew each other back in the

1479
01:08:46,760 --> 01:08:49,599
Speaker 3: Microsoft days, but was the board chair for the nonprofit.

1480
01:08:49,640 --> 01:08:52,920
Speaker 3: I ran so focused on the team, so focused on

1481
01:08:52,960 --> 01:08:54,880
Speaker 3: the team. You're only as good as your team. Really

1482
01:08:54,960 --> 01:08:57,439
Speaker 3: learned a ton about management and leadership from Peter.

1483
01:08:57,760 --> 01:09:00,519
Speaker 2: Huh, really interesting. Let's look about books. What are some

1484
01:09:00,560 --> 01:09:02,200
Speaker 2: of your favorites. What are you reading currently?

1485
01:09:02,760 --> 01:09:07,120
Speaker 3: Oh Man, I just finished a book called Good People.

1486
01:09:07,720 --> 01:09:09,559
Speaker 3: So I tend to read some fiction and some nonfiction.

1487
01:09:09,600 --> 01:09:12,000
Speaker 3: So I'm currently reading a book called Apple and China,

1488
01:09:12,400 --> 01:09:15,599
Speaker 3: all about Apple's entrances into China and ultimately the importance

1489
01:09:15,600 --> 01:09:18,519
Speaker 3: that China has and frankly the power that China now

1490
01:09:18,520 --> 01:09:22,599
Speaker 3: has over Apple. And then Good People is a fictional

1491
01:09:22,600 --> 01:09:26,680
Speaker 3: book about an Afghan Afghanian a family from Afghanistan that

1492
01:09:26,680 --> 01:09:30,879
Speaker 3: moves the United States and is either a model family

1493
01:09:33,040 --> 01:09:35,360
Speaker 3: or terrible people. And it's very very hard to know which,

1494
01:09:35,479 --> 01:09:37,040
Speaker 3: and it's sort of the book sort of flips back

1495
01:09:37,040 --> 01:09:38,560
Speaker 3: and forth. Remember when I said the books kind of

1496
01:09:38,600 --> 01:09:41,320
Speaker 3: teach empathy and sort of different respectives. This one does

1497
01:09:41,640 --> 01:09:42,400
Speaker 3: a good job of that.

1498
01:09:42,720 --> 01:09:46,240
Speaker 2: Huh. Really interesting. What about streaming? You listen to any

1499
01:09:46,280 --> 01:09:50,040
Speaker 2: podcasts or Netflix, Amazon, whatever? What keeps you entertained?

1500
01:09:50,880 --> 01:09:53,599
Speaker 3: I do. I am a podcast guy. I have to say, though,

1501
01:09:54,120 --> 01:09:56,080
Speaker 3: I'm kind of traditional when it comes to podcast I

1502
01:09:56,160 --> 01:09:58,599
Speaker 3: listen to The Daily from the New York Times pretty regularly,

1503
01:09:58,840 --> 01:10:00,760
Speaker 3: and I think most of it is because I have

1504
01:10:00,760 --> 01:10:02,400
Speaker 3: so many things in my life that are sort of

1505
01:10:02,880 --> 01:10:05,920
Speaker 3: There's so much content that comes at you that's sort

1506
01:10:05,960 --> 01:10:08,880
Speaker 3: of superficial, and at least with The Daily, I feel

1507
01:10:08,880 --> 01:10:10,960
Speaker 3: like I get to go a little deeper on a subject.

1508
01:10:11,200 --> 01:10:12,280
Speaker 3: You know. It tends to be a kind of a

1509
01:10:12,280 --> 01:10:14,599
Speaker 3: half an hour, you know, deep dive on a particular thing,

1510
01:10:15,000 --> 01:10:17,160
Speaker 3: and I do feel particularly I also read The New

1511
01:10:17,240 --> 01:10:19,400
Speaker 3: York Times. I know it's sort of traditional in that way.

1512
01:10:19,600 --> 01:10:21,320
Speaker 3: So if I read an article and then I kind

1513
01:10:21,320 --> 01:10:22,920
Speaker 3: of hear a podcast on the same topic, I do

1514
01:10:22,960 --> 01:10:25,840
Speaker 3: feel like I've actually gotten maybe a little bit smarter

1515
01:10:25,920 --> 01:10:27,920
Speaker 3: about something, you know, beyond the surface.

1516
01:10:28,280 --> 01:10:31,360
Speaker 2: Let me just push back, ever so slightly on how

1517
01:10:31,400 --> 01:10:34,840
Speaker 2: The Daily has evolved, because when it first came out

1518
01:10:34,880 --> 01:10:38,439
Speaker 2: and I was a regular listener, I don't want anybody

1519
01:10:38,640 --> 01:10:41,920
Speaker 2: telling me about the story that's in the paper that

1520
01:10:42,000 --> 01:10:45,639
Speaker 2: I can read. They used to kind of do the background. Hey,

1521
01:10:45,720 --> 01:10:48,280
Speaker 2: how did you start investigating this? What led to this?

1522
01:10:48,640 --> 01:10:50,920
Speaker 2: Tell us some interesting stuff that didn't make it into

1523
01:10:50,960 --> 01:10:54,679
Speaker 2: the article. It was really inside baseball and that stuff

1524
01:10:54,760 --> 01:10:58,040
Speaker 2: is kind of fascinating now whenever I check it out.

1525
01:10:58,360 --> 01:11:01,479
Speaker 2: It's the person I don't want to say reading the story,

1526
01:11:01,479 --> 01:11:04,639
Speaker 2: but it it feels like they've left a lot of that,

1527
01:11:05,200 --> 01:11:09,280
Speaker 2: you know, behind the scenes stuff back three years ago.

1528
01:11:09,840 --> 01:11:12,360
Speaker 2: It's still It's become one of the biggest podcasts in

1529
01:11:12,360 --> 01:11:12,719
Speaker 2: the world.

1530
01:11:12,760 --> 01:11:15,680
Speaker 3: It's a giant. Yeah, yeah, yeah, that's interesting.

1531
01:11:16,000 --> 01:11:18,320
Speaker 2: Anything else, anything else you listen to or watch.

1532
01:11:19,040 --> 01:11:22,200
Speaker 3: I mean, you know, I'll mindless TV. I love, but

1533
01:11:22,360 --> 01:11:25,040
Speaker 3: I can embarrass myself. But tell me all that that

1534
01:11:25,160 --> 01:11:27,200
Speaker 3: sort of stuff. Yeah, I We'll stick with the daily.

1535
01:11:27,640 --> 01:11:30,559
Speaker 2: We are in the golden age of mindless TV. And

1536
01:11:30,600 --> 01:11:33,960
Speaker 2: it's not you know, if you're watching The Crown, or

1537
01:11:34,120 --> 01:11:39,040
Speaker 2: Landman or three Body Problem. There's so many fascinating shows

1538
01:11:39,040 --> 01:11:42,240
Speaker 2: out there. It's not like garbage Time like it was

1539
01:11:42,360 --> 01:11:43,200
Speaker 2: when I was a kid.

1540
01:11:43,280 --> 01:11:45,040
Speaker 3: You are right about that, and I will say that

1541
01:11:45,040 --> 01:11:47,720
Speaker 3: my wife and I became obsessed with the pit as

1542
01:11:47,720 --> 01:11:50,600
Speaker 3: many people are. It is funny. It almost makes you

1543
01:11:50,600 --> 01:11:53,839
Speaker 3: feel like, you know, halfway to being an er doc myself,

1544
01:11:53,960 --> 01:11:55,760
Speaker 3: by the way you are not, so don't think that

1545
01:11:55,760 --> 01:11:58,719
Speaker 3: that's true. But what is hilarious is my wife's tolerance

1546
01:11:58,720 --> 01:12:01,080
Speaker 3: for some of the gore stuff is a little lower

1547
01:12:01,160 --> 01:12:03,080
Speaker 3: than mine. So she watches the pit with her hand

1548
01:12:03,160 --> 01:12:04,400
Speaker 3: kind of half in front of her face.

1549
01:12:04,240 --> 01:12:06,160
Speaker 2: The whole time. My wife did. We watched the first

1550
01:12:06,200 --> 01:12:09,200
Speaker 2: couple episodes. She's like, this is just too much. It's

1551
01:12:09,240 --> 01:12:12,160
Speaker 2: like you want to relax, and it's very but it's

1552
01:12:12,160 --> 01:12:14,479
Speaker 2: a great cast and it's a great setup for stories.

1553
01:12:15,160 --> 01:12:18,120
Speaker 2: Final two questions, what sort of advice would you give

1554
01:12:18,120 --> 01:12:22,400
Speaker 2: to a recent college grad interested in a career in

1555
01:12:22,600 --> 01:12:25,120
Speaker 2: either technology or business.

1556
01:12:25,439 --> 01:12:30,360
Speaker 3: So my advice here tends to be it's always sort

1557
01:12:30,400 --> 01:12:34,000
Speaker 3: of the same. And here's how there's so much temptation

1558
01:12:34,280 --> 01:12:37,920
Speaker 3: when you're picking your job early on to pick something

1559
01:12:37,960 --> 01:12:39,920
Speaker 3: that that sort of seems like it's going to be

1560
01:12:39,960 --> 01:12:42,120
Speaker 3: good on your resume, or maybe is going to make

1561
01:12:42,120 --> 01:12:44,040
Speaker 3: you a lot of money, whatever it is. This is

1562
01:12:44,080 --> 01:12:46,240
Speaker 3: sort of the temptation because it's so sort of in

1563
01:12:46,280 --> 01:12:49,599
Speaker 3: the air, maybe now more than ever because of social media,

1564
01:12:50,200 --> 01:12:53,599
Speaker 3: and oh man, the people that I see succeed are

1565
01:12:53,640 --> 01:12:56,439
Speaker 3: really the ones that say, yes, I have an economic reality.

1566
01:12:56,439 --> 01:12:58,240
Speaker 3: I have to sort of do better than that. But

1567
01:12:58,360 --> 01:13:01,200
Speaker 3: once the economic you know, reaction has been met, it

1568
01:13:01,280 --> 01:13:03,360
Speaker 3: is all about pick something you think you're really going

1569
01:13:03,439 --> 01:13:05,080
Speaker 3: to love and are going to be good at, are

1570
01:13:05,120 --> 01:13:06,920
Speaker 3: going to be good at. And I say that, like,

1571
01:13:06,960 --> 01:13:09,160
Speaker 3: you have to be a bit introspective of this. You know,

1572
01:13:09,200 --> 01:13:11,680
Speaker 3: maybe you love you know, selling, okay, great, so take

1573
01:13:11,680 --> 01:13:13,720
Speaker 3: a sales job. Maybe you love listening to customers. Great,

1574
01:13:13,720 --> 01:13:16,720
Speaker 3: take maybe a marketing job. Maybe. But I'm trying to

1575
01:13:16,720 --> 01:13:18,200
Speaker 3: make this sound maybe a little bit more interesting than

1576
01:13:18,240 --> 01:13:20,720
Speaker 3: follow your passions, because that's so trite, But there is

1577
01:13:20,840 --> 01:13:23,840
Speaker 3: something to it that really kind of being introspective about

1578
01:13:23,880 --> 01:13:25,240
Speaker 3: what you think you're going to just jump out of

1579
01:13:25,280 --> 01:13:28,280
Speaker 3: bed every morning and love doing tends to be a

1580
01:13:28,360 --> 01:13:31,439
Speaker 3: much more powerful predictor of long term success than people

1581
01:13:31,479 --> 01:13:33,800
Speaker 3: who try to optimize for that short term sort of

1582
01:13:33,800 --> 01:13:35,960
Speaker 3: get rich quick type of thing and then find themselves

1583
01:13:36,040 --> 01:13:39,040
Speaker 3: later realizing, shoot, this isn't really my thing. It's somebody

1584
01:13:39,080 --> 01:13:40,000
Speaker 3: else's thing. Huh.

1585
01:13:40,240 --> 01:13:43,120
Speaker 2: Really really good answer, and our final question, what do

1586
01:13:43,160 --> 01:13:47,439
Speaker 2: you know about the world of consumer facing technology and

1587
01:13:47,680 --> 01:13:50,400
Speaker 2: apps that would have been useful to know twenty five

1588
01:13:50,439 --> 01:13:52,599
Speaker 2: thirty years ago when you were first getting started.

1589
01:13:53,880 --> 01:13:57,479
Speaker 3: Wow. Okay, that's also a really interesting question. You know,

1590
01:13:57,640 --> 01:14:00,840
Speaker 3: I think I've probably gone through a similar arc to

1591
01:14:00,920 --> 01:14:03,840
Speaker 3: other people where I, you know, in the nineties, maybe

1592
01:14:03,880 --> 01:14:07,599
Speaker 3: even early two thousands, was sort of a universal techno optimist.

1593
01:14:07,880 --> 01:14:10,880
Speaker 3: I probably was in the camp that said technology is

1594
01:14:10,920 --> 01:14:14,160
Speaker 3: such a powerful force for the good. And you see

1595
01:14:14,200 --> 01:14:17,880
Speaker 3: me try to harness it with World Reader specifically, of course,

1596
01:14:17,920 --> 01:14:21,120
Speaker 3: trying to technology and get people reading. In that case,

1597
01:14:21,160 --> 01:14:23,880
Speaker 3: it did work. We've gotten over twenty two million people reading,

1598
01:14:23,920 --> 01:14:27,360
Speaker 3: so that's awesome, but oh man, it is hard not

1599
01:14:27,479 --> 01:14:30,080
Speaker 3: to see some of the just terrible costs we've paid

1600
01:14:30,400 --> 01:14:33,080
Speaker 3: as a society. And so I think maybe more of

1601
01:14:33,120 --> 01:14:36,080
Speaker 3: a mindset than a particular thing of just just be

1602
01:14:36,200 --> 01:14:39,760
Speaker 3: really aware that technology is so powerful and man, oh man,

1603
01:14:39,800 --> 01:14:42,400
Speaker 3: with great power comes that great responsibility. And I'm just

1604
01:14:42,439 --> 01:14:45,360
Speaker 3: a big believer that, you know, our best leaders now

1605
01:14:45,360 --> 01:14:48,160
Speaker 3: and I'm not necessarily putting myself in the category but

1606
01:14:48,200 --> 01:14:50,640
Speaker 3: are being really thoughtful about, you know, the good of technology,

1607
01:14:50,640 --> 01:14:52,519
Speaker 3: but also really trying to avoid some of the problems.

1608
01:14:53,080 --> 01:14:56,439
Speaker 2: Good answer David, thank you for being so generous with

1609
01:14:56,479 --> 01:15:01,240
Speaker 2: your time. This has been absolutely fascinating. We have been

1610
01:15:01,320 --> 01:15:04,240
Speaker 2: speaking with David Rischer. He is the CEO of Lift,

1611
01:15:04,680 --> 01:15:08,320
Speaker 2: one of North America's largest ride sharing networks. If you

1612
01:15:08,520 --> 01:15:11,439
Speaker 2: enjoy this conversation, well, be sure and check out any

1613
01:15:11,479 --> 01:15:13,880
Speaker 2: of the six hundred and thirty nine we've done over

1614
01:15:13,880 --> 01:15:20,040
Speaker 2: the past twelve years. You can find those at iTunes, Spotify, YouTube, Bloomberg,

1615
01:15:20,200 --> 01:15:24,040
Speaker 2: wherever you find your favorite podcasts. I would be remiss

1616
01:15:24,080 --> 01:15:26,040
Speaker 2: fine and thank the crack team that helps me put

1617
01:15:26,040 --> 01:15:31,320
Speaker 2: these conversations together each week. Alexis Nordega is my video

1618
01:15:31,560 --> 01:15:35,920
Speaker 2: and podcast producer. Jean Russo is my researcher. Anna Luke

1619
01:15:36,040 --> 01:15:40,560
Speaker 2: is my producer. I'm Barry Britoltz. You're listening to Masters

1620
01:15:40,560 --> 01:15:47,240
Speaker 2: in Business on Bloomberg Radio.