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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 Ritholtz on Bloomberg Radio.

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Speaker 2: This week on the podcast, you had another extra special guest.

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Speaker 2: Henry Ward is CEO and co founder of Karta. They're

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Speaker 2: the company that keeps track of cap tables, compensation, valuation,

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Speaker 2: liquidity for over fifty thousand private companies.

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Speaker 3: They work with eighty five.

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Speaker 2: Hundred investment firms and over two and a half million

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Speaker 2: equity holders to track all of this crucial information. It's

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Speaker 2: kind of hard to imagine that they were doing this

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Speaker 2: manually with stock certificates before Karter came along and digitized

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Speaker 2: everything and put along on the cloud.

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Speaker 3: Fascinating company. Fascinating guy.

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Speaker 2: I thought this was really a great conversation with no

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Speaker 2: further ado. The CEO and co founder of Cars, Henry Ward,

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Speaker 2: Welcome to Bloomberg.

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Speaker 4: Thanks for having me.

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Speaker 2: But I want to start talking a little bit about

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Speaker 2: your education and background. A bachelors in mathematics and computer

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Speaker 2: science from University of Michigan Go Blue, and MSc in

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Speaker 2: Market Finance from ed HC.

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Speaker 3: I am less.

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Speaker 2: Familiar with ed Heck than I am with you, Mish.

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Speaker 3: What was the original career plan.

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Speaker 2: You know.

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Speaker 4: I went to you Versus in Michigan originally to be

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Speaker 4: a math major. Technically, my degree on my transcript says

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Speaker 4: the Bachelors of General Studies, because at that time to

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Speaker 4: get a math degree you were in the Literature of

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Speaker 4: Science and Arts college and you had to take two

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Speaker 4: years of a foreign language. And I failed Japanese three times,

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Speaker 4: tried Spanish, failed that twice. And my counselor was at

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Speaker 4: the time I was supposed to go in the Marines,

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Speaker 4: and they said, look, I said to my counselor, I

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Speaker 4: just need to graduate. And they said, well, look, if

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Speaker 4: you switched a general studies degree, you can graduate because

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Speaker 4: you have enough credits. It's kind of a generalist degree

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Speaker 4: because you took a bunch of math, computer science, and linguistics,

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Speaker 4: and you can graduate next year. And I said, let's

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Speaker 4: do that. So it was me and thirteen football players

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Speaker 4: that graduated with a general studies degree that year. But

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Speaker 4: my passion had always been math. I thought I'd be

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Speaker 4: a mathematician. My roommate was a computer scientist. He got

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Speaker 4: me into computers, and then I went in a software engineering.

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Speaker 3: So two questions. First, did you end up in the Marines.

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Speaker 4: I joined the Marines out of high school as an enlistedment.

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Speaker 4: I went to Paris Island, and then I later went

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Speaker 4: into what's called Platoon Leader's Course, which is like the

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Speaker 4: Marine Corps version of Ratzia. I did that. But when

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Speaker 4: I finally graduated, and sometimes I regret this, you know,

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Speaker 4: you kind of look back at old decisions. And at

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Speaker 4: the time, four years, four more years, and the Marine

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Speaker 4: seemed like an eternity. Right now it seems like nothing.

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Speaker 3: Book of an Eye gone, right.

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Speaker 4: Yeah, I ended up deciding to pay back my my

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Speaker 4: GI bill because this is two thousand. I graduated in

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Speaker 4: nineteen ninety nine. My signing bonus paid off my entire

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Speaker 4: college debt at the time, and I decided to go

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Speaker 4: that route.

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Speaker 3: So it was the signing bonus. Where'd you go?

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Speaker 4: I went to a company called Trilogy out of Houston, Texas,

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Speaker 4: and it was an incredibly formative experience for me. It

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Speaker 4: was a very smart company. They were going to be

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Speaker 4: the Google of the South. Provided reasons it didn't quite

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Speaker 4: work out for them. The CEO is still there though,

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Speaker 4: running Trilogy and it's a great private, privately held company.

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Speaker 4: But yeah, that's what took me in Texas.

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Speaker 2: So I hear you saying you didn't do well with languages,

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Speaker 2: with Japanese, with Spanish. But am I reading this correctly?

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Speaker 2: Did you get your masters your MSc in France?

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Speaker 4: Yeah? I did because the business schools in France are

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Speaker 4: mostly taught in English, and English is hard enough for me,

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Speaker 4: so I had to stick with an English business school.

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Speaker 4: The plan was never to go to business school. I

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Speaker 4: wanted to ride my bicycle in southern France, a big

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Speaker 4: tour de France. Watch here. I loved riding my bike.

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Speaker 4: My fiance now x ex wife was like, well, hey,

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Speaker 4: if we're going to go, I convinced her to come

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Speaker 4: with me. We're going to be productive. Let's go to

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Speaker 4: business school while you train for the iron Man and

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Speaker 4: do all those things.

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Speaker 1: And you do.

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Speaker 4: Yeah, so we But it's a French business school, so

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Speaker 4: there wasn't a lot of work. There was a lot

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Speaker 4: of riding at a lot of eating bread. It was

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Speaker 4: a great couple of years.

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Speaker 2: So that's a kind of fascinating mix of technical, financial,

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Speaker 2: financial training, marines and overseas study. How did that experience

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Speaker 2: shape the way you think about building companies?

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Speaker 4: You know, I realized pretty quickly I'm not good at

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Speaker 4: the military. My father was an army officer for a

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Speaker 4: long time, and he used to tell me, you know,

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Speaker 4: and the difference between military life and civilian life is

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Speaker 4: in military life you're you're judged on the worst thing

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Speaker 4: you do. In civilian life, for certainly, in startups, you're

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Speaker 4: judge on the best thing you do. And I'm very

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Speaker 4: much I do one or two things really well versus

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Speaker 4: I do many things, you know, not wrong. And so

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Speaker 4: I quickly realized the military was not not the right

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Speaker 4: place for me. Investment banking was not the right place

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Speaker 4: for me. I went to an investment bank after grad school,

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Speaker 4: and then I discovered entrepreneurship sort of accidentally, and I realized,

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Speaker 4: this is what I was meant to do, successful or unsuccessful,

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Speaker 4: this is what I was meant to do.

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Speaker 2: So, so let's talk about the predecessor firm to Karta

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Speaker 2: second site, a portfolio optimization platform. You launched that not

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Speaker 2: long after grad school. How did that experience influence how

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Speaker 2: you approached the next venture. How did it affect what

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Speaker 2: your plans were for scaling Karta?

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Speaker 4: So the idea for a second site was it was

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Speaker 4: like a wealth front or a better meant one of

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Speaker 4: these robo advisors. But you know, Andy and Josh did

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Speaker 4: a much better job than I did. My company failed,

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Speaker 4: and what kind of rose out of the ashes of

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Speaker 4: that was and I got through the Trapha depression after

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Speaker 4: closing it was I couldn't imagine doing anything else as

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Speaker 4: a completely failed founder. I just wanted to do it again.

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Speaker 4: And Karta came out of that experience, and it was

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Speaker 4: one of these interesting things where the conventional wisdom for

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Speaker 4: founders is you fall in love with the problem, and

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Speaker 4: entrepreneurship is a vehicle with which that solved that problem.

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Speaker 4: I was different. I fell in love with entrepreneurship. I

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Speaker 4: fell in love with building a startup, and I just

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Speaker 4: needed a problem. The problem was a vehicle with which

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Speaker 4: to be a founder, and that really shapes how Karda

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Speaker 4: is today. We're a heat seeking missile going after any

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Speaker 4: problem we can find to solve to keep the business

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Speaker 4: moving forward. And I talk a lot to early stage

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Speaker 4: founders about this is which one are you? Are you

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Speaker 4: in love with the being a founder? Are you in

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Speaker 4: love with the problem? And both come with strength and witnesses.

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Speaker 4: If you're in love with being and the problem, you

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Speaker 4: know you're passionate of the problem. You'll grind through the

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Speaker 4: bad stages of being a founder to solve this problem.

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Speaker 4: The downside is if the problem isn't actually that valuable,

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Speaker 4: you kind of get stuck entrenched in this problem, and

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Speaker 4: many founders burn and crash in that. The other side

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Speaker 4: for me is, you know, because I'm not I'll do

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Speaker 4: I'll work on any problem to move the company forward.

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Speaker 4: There's often not a coherent strategy. It's like I'll grab

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Speaker 4: a problem over here, I'll grab a problem over there,

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Speaker 4: And you can see it in the kind of diversity

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Speaker 4: for a five hundred million dollar business. We have a

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Speaker 4: large number of SKUs and business lines, and it's because

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Speaker 4: we shoot out a lot of different targets.

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Speaker 2: So let's talk about the initial target. How did you

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Speaker 2: come up with the idea?

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Speaker 3: Hey, these cap.

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Speaker 2: Tables, all the data around comp and valuation and VC investing,

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Speaker 2: No one is really tracking this in a consistent, intelligent way.

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Speaker 3: Like what was that aha moment?

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Speaker 4: I was working with Menu Kumar over at Canine Ventures

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Speaker 4: on my previous company, and when we shut that down

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Speaker 4: and we were talking about what am I going to

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Speaker 4: do next? He pointed out this cap table problem and

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Speaker 4: was like, hey, this is a real problem. I think

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Speaker 4: you should solve it. Really Yeah, yeah, I'll invest in it.

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Speaker 4: And he gave me this problem set to go after

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Speaker 4: and I spent a few months working on it and

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Speaker 4: learning about it. What was really interesting was the first

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Speaker 4: version of it was not cap table, so that's what

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Speaker 4: everybody knows us for. The first version actually was PayPal

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Speaker 4: for equity. It was instead of back then you used

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Speaker 4: to mail a paper stock certificate, just like we used

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Speaker 4: to do with the railroads, and your cost fifty dollars

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Speaker 4: in FedEx pise in one hundred bucks for the paralegal

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Speaker 4: to print it, and somebody had to file it in

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Speaker 4: a cabinet. And we were like, we said, hey, why

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Speaker 4: are we email or you know FedExing paper stock certificates.

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Speaker 4: Let's just email it. And that was the initial idea,

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Speaker 4: and we realized companies didn't care that much. We thought

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Speaker 4: the competition was FedEx. They didn't care that much about it.

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Speaker 4: But they said, well, hey, if you're emailing all this stuff,

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Speaker 4: can you just put all of it into a table

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Speaker 4: and show it to me. And we're like, yeah, we

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Speaker 4: can do that. That sounds pretty good. That was the

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Speaker 4: thing that had product market fit was just showing them

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Speaker 4: everything we issued. And then once you had the cop table,

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Speaker 4: the company my heat seeking missile instincts were like, well,

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Speaker 4: what else could we do? And then we launched four

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Speaker 4: nine A and stock ops and expense accounting and employee

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Speaker 4: management and card total compensation and QSBS and suddenly you

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Speaker 4: could do so many things around this core system of

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Speaker 4: record called the cop table.

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Speaker 2: Huh so fascinating. What was it like scaling that? What

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Speaker 2: sort of technology issues did you run into? How much

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Speaker 2: of the data you were finding was it all hand

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Speaker 2: assembled or was there any mass amount of data that

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Speaker 2: made it easy to navigate? What were the next few steps?

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Speaker 4: Like I often tell earlier stage founders, you know, being

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Speaker 4: a you know, we're about two thousand employees now, the

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Speaker 4: problems I deal with they're no different than the early stage.

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Speaker 4: They're just bigger, faster, harder, but they're the same set

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Speaker 4: of problems. I do the same thing every day that

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Speaker 4: an early stage founder does, and it's really simple. Talk

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Speaker 4: to customers, figure out their problems, solve the product, build

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Speaker 4: the product to solve their problems, and make them happy.

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Speaker 4: And that's just it. It's just rinse and repreat Everything

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Speaker 4: else is just you know, overhead to building a building

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Speaker 4: a company. And so these days, you know, I'm in

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Speaker 4: New York for a few days. Half my meetings are

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Speaker 4: our customer meetings.

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Speaker 2: So this isn't just obviously public companies. This is public

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Speaker 2: and private companies. How do they differ? My assumption is

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Speaker 2: it's easy to track and access public companies data.

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Speaker 3: What do you do on the private side?

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Speaker 4: So public company data and you know, Bloomberg is a great,

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Speaker 4: you know example of this is so ubiquitous, and how

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Speaker 4: do we manage this incredible set of data across fassive

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Speaker 4: ecosystems and networks in the public markets. Private markets is

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Speaker 4: very different. It's it's private. There's no central place to

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Speaker 4: access all this data. We have a lot of the

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Speaker 4: data on what's happening in the private markets, particularly around

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Speaker 4: venture capital and private equity, but because it's private, we

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Speaker 4: can't share it. And that is the very unique interesting

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Speaker 4: thing about what we do is we track all the

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Speaker 4: much of the same data that like a Bloomberg would track,

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Speaker 4: but we can't share it with anybody. And that's the

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Speaker 4: that's many people have asked me, Hey, how come we

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Speaker 4: haven't done blockchain? You know, blockchain seems like an obvious

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Speaker 4: thing for a cap table to be put on. And

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Speaker 4: the reason is our customers pay us to fix things

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Speaker 4: when they're broken, and don't tell any about tell don't

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Speaker 4: tell anybody about it. And blockchain is immutable and public,

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Speaker 4: and that's that's the big difference between private and public.

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Speaker 3: Really interesting.

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Speaker 2: What was the hardest problem in assembling a private market

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Speaker 2: set of data and cap tables across the whole technology ecosystem.

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Speaker 4: The big issue we had early was what I'll call

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Speaker 4: the de materialization of private stocks. So the model that

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Speaker 4: we think we look at is when Nixon pulled us

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Speaker 4: off the gold standard, he de materialized cash. You know,

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Speaker 4: now the Federal Reserve could just create cash because cash

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Speaker 4: was now put into the cloud. They could create money,

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Speaker 4: they could do what they could move money around without

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Speaker 4: actually moving physical inventory. They de materialized cash and gold

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Speaker 4: and put it in the cloud. And this was in

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Speaker 4: the seventies. We think of us as doing the same thing.

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Speaker 4: Was everything in private markets until Karta was cash, it

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Speaker 4: was paper equity, it was contracts, it was PDFs, it

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Speaker 4: was documents, and we de materialized that. We put it

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Speaker 4: all in the cloud. So now everything could be moved

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Speaker 4: around seamlessly. Getting the ecosystem of venture capital to believe

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Speaker 4: in the de materialization of private equity and private capital

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Speaker 4: was the hardest part because it sounds crazy today, but

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Speaker 4: in twenty twelve and thirteen, lawyers were like, no, but

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Speaker 4: you have to have a green stock certificate within a

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Speaker 4: broader around it, Like that's what we've been doing, literally

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Speaker 4: for two hundred years. Like who are you to change this?

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Speaker 4: I would have thought.

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Speaker 2: If anybody would be amenable to let's go from physical

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Speaker 2: paper to digital, it would be Silicon Valley venture capitalists.

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Speaker 2: They were pushing back, or their lawyers were pushing back.

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Speaker 4: The lawyers are pushing back, but even the adventure capitalists,

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Speaker 4: because the venture capitalists are very interesting because they are

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Speaker 4: stewards of what the future will be and prognosticators of it,

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Speaker 4: but they're not users of it. And it's one of

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Speaker 4: these things I say a lot about AI is everybody

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Speaker 4: thinks AI will change everybody's job except their own, and

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Speaker 4: venture is the same, like, oh, you know, all the

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Speaker 4: companies should be using technology, but we don't because we're professionals.

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Speaker 2: We don't need it.

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Speaker 3: Exactly, we're smarter than every Exactly what was the aha?

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Speaker 2: Moment where that ecosystem that was kind of pushing back

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Speaker 2: said oh this is really useful and helpful.

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Speaker 3: Yes, let's materialized, let's go digital.

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Speaker 4: It was the grassroots. The way we got it going

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Speaker 4: was the grassroots efforts of startups saying hey, they didn't

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Speaker 4: understand that they were buying into a de materialization model.

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Speaker 4: But what they understood was, hey, I can track my

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Speaker 4: cap table cheaper, faster, better on Karta than anything else.

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Speaker 4: And so they just came to us. That was the wedge.

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Speaker 4: Thet kind of the golden phrase is you know, come,

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Speaker 4: come for the tools, stay for the network. So the tool,

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Speaker 4: the wedge was just better cap table management for one

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Speaker 4: tenth the cost. And then the network is once everybody

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Speaker 4: started converging on the cap tables, it became the new standard.

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Speaker 4: So now it's a weird world, just like it's a weird, weird,

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Speaker 4: weird world to say that, you know, we had paper

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Speaker 4: stocks or to give it so and that was the

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Speaker 4: right way to do it. It is now a weird

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Speaker 4: world to say, oh, well, why wouldn't we put it

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Speaker 4: in the database on the cloud.

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Speaker 2: And that becomes a self reinforcing flywheel. You get a

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Speaker 2: critical mass and then you could go out in all

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Speaker 2: sorts of directions from that.

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Speaker 4: That's right, and nobody knows that better than Bloomberg and

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Speaker 4: mister Bloomberg, because that's exactly what Bloomberg did.

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Speaker 3: That's exactly right. Started with the data. Coming up, we

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Speaker 3: continue our.

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Speaker 2: Conversation with Henry Ward, CEO and co founder of Karda,

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Speaker 2: talking about how a simple cap table management became an

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Speaker 2: essential part of the startup world.

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Speaker 3: I'm Barry Ridults.

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Speaker 2: You're listening to Masters of Business on Bloomberg Radio.

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Speaker 3: I'm Barry Ridolts.

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Speaker 2: You're listening to Masters in Business on Bloomberg Radio. My

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Speaker 2: extra special guest today is Henry Ward.

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Speaker 3: He is the CEO and co founder of Karta.

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Speaker 2: They help manage cap tables and so much more when

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Speaker 2: it comes to both public and private corporate data.

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Speaker 3: So let's talk a little bit about this.

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Speaker 2: You start with a simple capital table management kind of

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Speaker 2: unglamorous but sounds important.

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Speaker 3: Essential.

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Speaker 2: Hey, I need to know how many shareholders I have,

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Speaker 2: who owns what, what vcs, what employees own, how much stocked?

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Speaker 2: Like I would have thought that was around for thirty

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Speaker 2: forty years. How has nobody been doing that for you know,

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Speaker 2: you could practically go back to, you know, the launch

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Speaker 2: of Intel forty years ago.

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Speaker 3: How has this not been a thing?

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Speaker 4: One of the most common questions I got when I

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Speaker 4: was raising money in the early days for this idea was, hey,

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Speaker 4: this sounds kind of obvious. Why has nobody done this before?

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Speaker 4: And I my answer was somewhat cheeky, and I would say,

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Speaker 4: how would I know I'm doing it? And you know,

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Speaker 4: I'm the last person in the world that would know

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Speaker 4: the answer this. You should ask the six point nine

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Speaker 4: billion other people in the world that haven't been who

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Speaker 4: chose not to, And I'm I'm a least qualified person.

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Speaker 4: I think it's just one of these innovator dilemma problems

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Speaker 4: that the people that should have solved this should have

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Speaker 4: been the investment banks. It should have been the CC changes.

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Speaker 4: Maybe I'm in the VCS. Yeah, somebody should have solved it.

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Speaker 4: But you know, who's going to do paper stock certificates

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Speaker 4: like it?

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Speaker 2: Just it's so somebody had to have a clerk or

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Speaker 2: a junior researcher putting this together somewhere and had to

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Speaker 2: realize there was some value to both the firm and

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Speaker 2: various outside startups for it.

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Speaker 3: It's kind of shocking for sure.

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Speaker 4: But your point so well made, Bary is the kind

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Speaker 4: of person that would be filing paper stock certificates would

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Speaker 4: never come up with the idea of replacing them. And

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Speaker 4: so you need this. This is the magic of a founder,

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Speaker 4: a visionary founder, is you need that connection of they

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Speaker 4: know enough about technology to know what technology can do,

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Speaker 4: but they don't know enough about the current process us

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Speaker 4: that they think it's unchangeable. And that's the you know,

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Speaker 4: there's certain level of intelligence and a certain level of

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Speaker 4: stupidity that you need to get that chemical quotient right.

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Speaker 2: So how did you convince investors that hey, this is worthwhile,

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Speaker 2: this should exist. It doesn't please invest in this, it's

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Speaker 2: worth building.

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Speaker 4: Most investors said, hey, the even I believe you can

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Speaker 4: build a cap table product and make some money and

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Speaker 4: sell it, but the market size is too small. How

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Speaker 4: many cap tables can you actually sell? And the pitch was, well, hey,

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Speaker 4: this is this is a two part story. Part one

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Speaker 4: is win the cap tables. Part two is if you

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Speaker 4: win the cap tables, then we can go build at

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Speaker 4: the time what we call the NASDAQ for private markets,

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Speaker 4: the stock exchange to trade these shares, and our thesis

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Speaker 4: then was the reason why there were many stock market

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Speaker 4: companies before us, but none of them actually owned the settlement.

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Speaker 4: They hadn't owned the cap table itself, and so they

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Speaker 4: had the match and settle these things offline. And by

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Speaker 4: owning the cap table, we could digitize the entire settlement

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Speaker 4: process for these companies. But you had to do the

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Speaker 4: hard work of winning the cop table business first. We

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Speaker 4: were wrong. It turned out the cap table business was

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Speaker 4: way bigger than we and investors thought. Today it's a

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Speaker 4: three hundred and fifty million dollar business, but the stock

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Speaker 4: market that everybody thought was going to be, you know,

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Speaker 4: a billion dollar business is zero for us.

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Speaker 3: That's unbelievable.

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Speaker 2: The you know, vcs love to toss around tam total

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Speaker 2: addressable market again, kind of shocking that people right in

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Speaker 2: the middle of this, surrounded by tens of thousands of

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Speaker 2: companies in California and Silicon Valley, completely underestimated the total

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Speaker 2: addressable market.

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Speaker 3: That's just shocking to me.

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Speaker 2: Let's talk about the income stream you set up. In

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Speaker 2: the beginning, this was a fee per stock certificate business.

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Speaker 2: You guys changed this to a subscription model. Tell us

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Speaker 2: about the factors that drove those changes and how it

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Speaker 2: affected the steadiness of your income stream.

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Speaker 4: Yeah, so we thought we were competing against FedEx, and

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Speaker 4: so instead of paying sixty dollars to FedEx, to FedEx

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Speaker 4: the stocks are dada, You'll pay us twenty dollars to

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Speaker 4: email it. It worked that people would pay for it.

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Speaker 4: What was really hard about it, though, is it's a

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Speaker 4: transactional business. It's very hard to manage the transactional business,

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Speaker 4: and it was very volatile. And we also quickly realized

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Speaker 4: that we wanted to move to a subscription based business

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Speaker 4: because we needed to bundle other things that were more

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Speaker 4: subscription based, like foreign NA evaluations and expense accounting and

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Speaker 4: other services we were doing. But we were two years

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Speaker 4: in and you know, at the time, I think we

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Speaker 4: had maybe two thousand customers that were all paying us

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Speaker 4: twenty bucks. And we realized this was like a crucible

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Speaker 4: moment for us. If we didn't change the business model,

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Speaker 4: we wouldn't survive, and we emailed all of our customers

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Speaker 4: from me. I emailed all two thousand customers and I said, hey,

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Speaker 4: I made a mistake. I priced this wrong for you,

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Speaker 4: and I need to change from the twenty dollars per

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Speaker 4: certificate to x dollars per year, and everybody had a

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Speaker 4: price that we custom already set up for them, so

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Speaker 4: we didn't even ask them. We just said, we're moving

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Speaker 4: you starting next month to the subscription model. And it

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Speaker 4: was a very scary, scary thing to do because you

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Speaker 4: don't know what your customers are going to do. You

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Speaker 4: literally changed the agreement in the mid flight, and I

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Speaker 4: explained in this long email. I said, I made a mistake.

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Speaker 4: If I keep charging you this way, I'm going to

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Speaker 4: go out of business and I need to move you

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Speaker 4: over to this and I'm very sorry I made this mistake.

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Speaker 4: I hope I understand if you decide to leave us,

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Speaker 4: but I hope you won't. And it was remarkable. We

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Speaker 4: lost almost no customers and I have some of these

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Speaker 4: saved and framed where customers came back and said, you know,

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Speaker 4: we're so glad you did this, because we were wondering

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Speaker 4: if you were going to run out of business like

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Speaker 4: we thought. You know, this pricing was wrong, it didn't

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Speaker 4: make any sense.

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Speaker 2: The subscription model allows them to just keep doing repeat

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Speaker 2: business and no one has to track. Oh, we did

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Speaker 2: these six companies and it's however much it is, No

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Speaker 2: here's a monthly fee, and we can do. As many

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Speaker 2: companies as we.

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Speaker 4: Have, they have a monthly actually annual fee. For most

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Speaker 4: of them, they pay annually. They were new and based

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Speaker 4: on the size of the cap table. At that renewal,

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Speaker 4: they just get a renewal notice. And it's interesting, you know,

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Speaker 4: eight years ago we were ten x cheaper than the lawyers.

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Speaker 4: Now we're still eight x cheaper than the lawyers. But

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Speaker 4: now it's just a different different world. People are used

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Speaker 4: to software now and it's you know, ten years ago

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Speaker 4: is a weird thing for these companies to pay a

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Speaker 4: subscription fee for legal software, and today it's super super common.

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Speaker 3: Do you really think about this as lee software.

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Speaker 2: I mean, it obviously has ramifications in law, but it

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Speaker 2: really seems more like it's a combination of Hey, it's business,

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Speaker 2: it's investing, its accounting. How do you contextualize what space

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Speaker 2: you're actually in.

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Speaker 4: It's a great question. I think we started as legal software,

438
00:23:21,760 --> 00:23:24,440
Speaker 4: and people thought of us as legal software. I think

439
00:23:25,160 --> 00:23:28,560
Speaker 4: over the first five years we transitioned the concept of

440
00:23:28,600 --> 00:23:32,959
Speaker 4: cap table from a legal solution to a financial solution.

441
00:23:33,119 --> 00:23:36,359
Speaker 4: So we sort of categorize ourselves in the fintech world.

442
00:23:37,200 --> 00:23:39,880
Speaker 4: I think today when you look at cap tables, our

443
00:23:39,920 --> 00:23:44,080
Speaker 4: fund administration and fund accounting business, our LP business, and

444
00:23:44,160 --> 00:23:47,520
Speaker 4: all the software that we sell as a platform into

445
00:23:47,520 --> 00:23:52,240
Speaker 4: private private equity, private credit, venture capital. I think of

446
00:23:52,320 --> 00:23:55,800
Speaker 4: us as now as a software infrastructure business, you know

447
00:23:55,840 --> 00:24:00,440
Speaker 4: we sell We're more similar to a net suite or

448
00:24:00,480 --> 00:24:02,919
Speaker 4: even a Google suite than we are to a legal

449
00:24:02,960 --> 00:24:03,560
Speaker 4: tech company.

450
00:24:03,640 --> 00:24:06,480
Speaker 2: Or makes a lot of sense and save on legal fees.

451
00:24:07,840 --> 00:24:11,679
Speaker 2: So back, let's call it about eight years ago. You

452
00:24:11,760 --> 00:24:13,720
Speaker 2: were called e shares.

453
00:24:13,480 --> 00:24:16,840
Speaker 3: Which kind of intuitively makes a lot of sense. What

454
00:24:17,040 --> 00:24:18,359
Speaker 3: was behind the rebranding?

455
00:24:18,359 --> 00:24:21,479
Speaker 2: Why did you go from e shares to karta in

456
00:24:21,560 --> 00:24:22,480
Speaker 2: twenty seventeen.

457
00:24:23,560 --> 00:24:27,679
Speaker 4: The We liked e shares because it was an electronic share,

458
00:24:27,800 --> 00:24:29,320
Speaker 4: you know, instead of paper, and it made a ton

459
00:24:29,359 --> 00:24:31,919
Speaker 4: of sense. In twenty seventeen, we kind of realized we

460
00:24:31,920 --> 00:24:34,359
Speaker 4: wanted to do way more than electronic shares, so we

461
00:24:34,400 --> 00:24:38,119
Speaker 4: knew we needed a new name. We were also pushed

462
00:24:38,119 --> 00:24:41,760
Speaker 4: on it because we didn't own e shares dot com.

463
00:24:41,800 --> 00:24:44,639
Speaker 4: We owned e Sharesinc. Dot com and there was a

464
00:24:44,720 --> 00:24:47,880
Speaker 4: domain squadron on e shares dot com.

465
00:24:47,920 --> 00:24:48,919
Speaker 3: What did they want for it?

466
00:24:49,640 --> 00:24:53,240
Speaker 4: They wanted initially? I think it was a million bucks

467
00:24:53,720 --> 00:24:56,760
Speaker 4: when we had we had two million dollars raised total,

468
00:24:57,720 --> 00:24:59,399
Speaker 4: and then as soon as we raised more money, it

469
00:24:59,400 --> 00:25:02,399
Speaker 4: became ten million dollars. And so it was just every

470
00:25:02,440 --> 00:25:04,600
Speaker 4: single time we were trying to get more and we

471
00:25:04,680 --> 00:25:07,600
Speaker 4: just couldn't couldn't do business. And so we decided we

472
00:25:07,600 --> 00:25:09,879
Speaker 4: need to change the name, and we came up with

473
00:25:09,960 --> 00:25:11,520
Speaker 4: Karta and we were able to buy it for I

474
00:25:11,520 --> 00:25:12,840
Speaker 4: think seventy five thousand bucks.

475
00:25:12,840 --> 00:25:16,800
Speaker 2: And wow, that's fantastic. Did the shares ever get solved?

476
00:25:17,320 --> 00:25:19,200
Speaker 4: I don't think so. It's a great question. I don't

477
00:25:19,200 --> 00:25:21,040
Speaker 4: know if it's still I haven't been there in a

478
00:25:21,119 --> 00:25:21,520
Speaker 4: long time.

479
00:25:21,600 --> 00:25:23,720
Speaker 2: It just goes to show you, you know, you have

480
00:25:23,800 --> 00:25:25,760
Speaker 2: to leave a little bit on money on the table.

481
00:25:25,800 --> 00:25:27,800
Speaker 2: If you try and squeeze every last penny ends up

482
00:25:27,800 --> 00:25:30,960
Speaker 2: with nothing exactly. So you guys, I mentioned in the

483
00:25:31,119 --> 00:25:37,200
Speaker 2: original introduction Karter serves fifty thousand companies, eighty five hundred firms,

484
00:25:37,680 --> 00:25:41,399
Speaker 2: millions and millions of equity holders. Starting out with that

485
00:25:41,480 --> 00:25:45,720
Speaker 2: first two million dollar raise, it appears that you've scaled

486
00:25:45,800 --> 00:25:50,439
Speaker 2: from a little niche solution to a giant platform for

487
00:25:50,520 --> 00:25:51,480
Speaker 2: private companies.

488
00:25:52,119 --> 00:25:55,640
Speaker 3: What was the biggest growth pains in that scaling that up.

489
00:25:56,480 --> 00:26:00,399
Speaker 4: It's all of them. We scaling a company. I think.

490
00:26:01,720 --> 00:26:03,960
Speaker 4: I love Jensen and Nvidia. And I got to see

491
00:26:04,040 --> 00:26:07,800
Speaker 4: him speak and you know, someone asked him about what

492
00:26:07,840 --> 00:26:09,720
Speaker 4: do you do it again? And you know, he's one

493
00:26:09,760 --> 00:26:12,840
Speaker 4: of the most successful entrepreneurs of our generation. And he goes,

494
00:26:12,880 --> 00:26:14,480
Speaker 4: if I knew what it would take, I wouldn't have

495
00:26:14,560 --> 00:26:18,600
Speaker 4: done it again. Really, and yeah, and you know it's

496
00:26:19,040 --> 00:26:21,800
Speaker 4: I think Mark and Reeson calls it. It's it's eating

497
00:26:21,840 --> 00:26:24,439
Speaker 4: glass until you enjoy the taste of your own blood.

498
00:26:25,000 --> 00:26:28,199
Speaker 4: So it's you know, every day there's sort of this

499
00:26:28,320 --> 00:26:30,080
Speaker 4: funny thing where people are like, well, what was it

500
00:26:30,160 --> 00:26:32,920
Speaker 4: like to scale? And I'm like, I'm still doing it,

501
00:26:32,960 --> 00:26:37,040
Speaker 4: like you know, and and it's you know, getting in

502
00:26:37,119 --> 00:26:39,960
Speaker 4: at you know, ten o'clock last night from a four

503
00:26:40,000 --> 00:26:44,840
Speaker 4: am start. It's you know, talking to customers, it's hiring, firing,

504
00:26:45,160 --> 00:26:48,840
Speaker 4: you know, uncomfortable conversations, you know, bored mechanics. It's it's

505
00:26:48,880 --> 00:26:51,439
Speaker 4: all the same. It's just more harder, faster.

506
00:26:51,880 --> 00:26:54,680
Speaker 2: Is in Reason's quote, eating glass till you like the

507
00:26:54,720 --> 00:26:55,560
Speaker 2: taste of your own blood.

508
00:26:55,600 --> 00:26:57,840
Speaker 3: Is that accurate or is it a little hyperbolic?

509
00:26:58,359 --> 00:26:58,760
Speaker 1: Uh?

510
00:26:58,880 --> 00:27:00,960
Speaker 4: You know? I think so I talk a lot to

511
00:27:01,200 --> 00:27:04,520
Speaker 4: founders about this where the founders that want to be

512
00:27:04,520 --> 00:27:07,320
Speaker 4: founders for the money. We all know that the expected

513
00:27:07,400 --> 00:27:11,879
Speaker 4: value of being an entrepreneurs is below pursuing a career,

514
00:27:11,960 --> 00:27:13,840
Speaker 4: far far below the better business.

515
00:27:13,880 --> 00:27:17,120
Speaker 2: Well, such a large percentage fail at the gate, so

516
00:27:17,680 --> 00:27:20,760
Speaker 2: we all the survivorship bias of we see the ones

517
00:27:20,800 --> 00:27:23,680
Speaker 2: that have succeeded. That's just the top of the iceberg.

518
00:27:23,720 --> 00:27:25,959
Speaker 2: You don't see everything below the waterline.

519
00:27:25,520 --> 00:27:27,600
Speaker 4: One hundred percent. And then when you see the ones

520
00:27:27,640 --> 00:27:31,000
Speaker 4: that succeeded, sort of by definition, the ones that succeeded

521
00:27:31,000 --> 00:27:34,000
Speaker 4: made it look easy, right, because it's like we're on

522
00:27:34,160 --> 00:27:36,119
Speaker 4: podcasts doing doing all of these things.

523
00:27:36,160 --> 00:27:39,200
Speaker 2: They found the right niche, they pivoted appropriately, they built

524
00:27:39,240 --> 00:27:40,920
Speaker 2: what was needed, and the market rewarded.

525
00:27:41,080 --> 00:27:44,640
Speaker 4: That's exactly how. That's exactly right. And when I look

526
00:27:44,680 --> 00:27:48,320
Speaker 4: at my history, I know how lucky I got. Like

527
00:27:48,400 --> 00:27:51,080
Speaker 4: there's so many forks in the road that boy, if

528
00:27:51,080 --> 00:27:53,320
Speaker 4: I had flipped heads instead of tails, I would not

529
00:27:53,400 --> 00:27:55,800
Speaker 4: be here. And I had to flip you know, I

530
00:27:55,840 --> 00:27:58,399
Speaker 4: had to flip tails thirty two times in a row

531
00:27:58,880 --> 00:27:59,959
Speaker 4: to get to where I am.

532
00:28:00,160 --> 00:28:02,280
Speaker 2: I'm let me interrupt you a second, because I just

533
00:28:02,320 --> 00:28:05,560
Speaker 2: have to share this. So I've done five hundred and

534
00:28:05,600 --> 00:28:08,920
Speaker 2: fifty six hundred of these and I've heard that exact

535
00:28:08,960 --> 00:28:12,480
Speaker 2: thing over and over again. And the first couple of

536
00:28:12,520 --> 00:28:16,760
Speaker 2: times I heard it, especially from billionaires, I'm like, yeah, yeah,

537
00:28:16,800 --> 00:28:19,320
Speaker 2: false humility. But then when I start hearing it from

538
00:28:19,359 --> 00:28:21,919
Speaker 2: more people, from guys like you who are in the

539
00:28:22,000 --> 00:28:25,840
Speaker 2: trenches chewing on glass, It's like, and my own experience

540
00:28:25,880 --> 00:28:29,639
Speaker 2: as an entrepreneur, you really smart, and hard work is

541
00:28:29,760 --> 00:28:33,280
Speaker 2: just table stakes. You really have to get lucky, and

542
00:28:33,320 --> 00:28:37,639
Speaker 2: people don't understand the role of serendipity in how things

543
00:28:37,720 --> 00:28:38,200
Speaker 2: work out.

544
00:28:38,560 --> 00:28:41,440
Speaker 4: One of my favorite other quotes is both Duringham the

545
00:28:41,600 --> 00:28:46,480
Speaker 4: Comedia said, you know, don't take advice from successful people,

546
00:28:46,760 --> 00:28:50,040
Speaker 4: because it's like listening to Taylor Swift's they follow your dreams.

547
00:28:51,120 --> 00:28:53,080
Speaker 4: Or the lottery winner goes, you know what you should do,

548
00:28:53,400 --> 00:28:55,520
Speaker 4: so everything you own and buy lottery tickets.

549
00:28:55,640 --> 00:28:57,840
Speaker 3: That's right, that's an XKCD.

550
00:28:58,920 --> 00:29:00,840
Speaker 2: They told me I would never win, but I kept

551
00:29:00,880 --> 00:29:03,800
Speaker 2: out right here I am today exactly. No, it's one

552
00:29:03,840 --> 00:29:06,920
Speaker 2: hundred percent true. Listen, there's so much more signal in

553
00:29:06,960 --> 00:29:09,560
Speaker 2: the failures than the wrong and the success is because

554
00:29:09,760 --> 00:29:12,000
Speaker 2: success maybe it was skill, maybe was luck.

555
00:29:12,080 --> 00:29:12,560
Speaker 3: We don't know.

556
00:29:12,880 --> 00:29:15,480
Speaker 4: Yeah, And what I try to coach, like in my

557
00:29:15,560 --> 00:29:19,480
Speaker 4: Angel investments is I call it, you know, the love

558
00:29:19,520 --> 00:29:21,560
Speaker 4: of the game. And so you know, you see founders

559
00:29:21,560 --> 00:29:22,720
Speaker 4: that I want to be successful. I want to be

560
00:29:22,760 --> 00:29:24,920
Speaker 4: successful founder. I want to make the money, you know.

561
00:29:25,080 --> 00:29:26,560
Speaker 4: And what I always tell them is like, hey, the

562
00:29:26,960 --> 00:29:30,959
Speaker 4: problem with money. Doing this for the money is most

563
00:29:31,040 --> 00:29:34,440
Speaker 4: of your journey, if not all, you're poor your seed stage,

564
00:29:34,440 --> 00:29:36,680
Speaker 4: early stage, you're just poor. And so if you're doing

565
00:29:36,680 --> 00:29:39,560
Speaker 4: it for the money, you kind of quickly lose motivation

566
00:29:39,640 --> 00:29:42,760
Speaker 4: because you're poor for years, right, and then let's say

567
00:29:42,800 --> 00:29:45,320
Speaker 4: you're one of the lucky for you to get successful. Well,

568
00:29:45,600 --> 00:29:47,640
Speaker 4: now you're rich. And so if you do it for

569
00:29:47,680 --> 00:29:50,760
Speaker 4: the money, now you have no reason to do it

570
00:29:50,760 --> 00:29:53,920
Speaker 4: anymore because you've got the money. And the people that

571
00:29:54,040 --> 00:29:56,920
Speaker 4: are successful over time in this business do it for

572
00:29:56,960 --> 00:29:59,280
Speaker 4: the love of the game, like I. You know, I

573
00:29:59,360 --> 00:30:01,040
Speaker 4: do it because I of chewing glass.

574
00:30:01,960 --> 00:30:03,640
Speaker 2: You know, my wife and I were having a conversation

575
00:30:03,760 --> 00:30:05,920
Speaker 2: the other day about when we were poor, and I

576
00:30:05,960 --> 00:30:11,280
Speaker 2: mean really poor. And the really challenging thing is when

577
00:30:11,280 --> 00:30:13,520
Speaker 2: you're in the thick of it, you don't know that

578
00:30:13,560 --> 00:30:14,400
Speaker 2: it's going to work out.

579
00:30:14,520 --> 00:30:16,640
Speaker 3: You have no idea. Hey, am I going to get

580
00:30:16,680 --> 00:30:17,480
Speaker 3: that lucky break?

581
00:30:17,600 --> 00:30:21,880
Speaker 2: Is the right client, partner, customer going to come along

582
00:30:21,960 --> 00:30:24,640
Speaker 2: and give me that critical mass to go to the

583
00:30:24,680 --> 00:30:29,360
Speaker 2: next level. So not only you poor, but the outcome

584
00:30:29,480 --> 00:30:32,440
Speaker 2: is wholly unknown. And so if you don't love it,

585
00:30:32,520 --> 00:30:33,240
Speaker 2: then what are you?

586
00:30:33,280 --> 00:30:33,960
Speaker 3: What are you doing?

587
00:30:34,040 --> 00:30:37,040
Speaker 4: It's right, you're poor, and you're it's you're living in

588
00:30:37,080 --> 00:30:40,280
Speaker 4: constant uncertainty. Uncertainty absolutely, And I think what people forget is,

589
00:30:40,320 --> 00:30:43,160
Speaker 4: you know, I'm not poor anymore, but I still live

590
00:30:43,200 --> 00:30:45,840
Speaker 4: in uncertainty, and you know, I don't know what's going

591
00:30:45,880 --> 00:30:48,800
Speaker 4: to happen. You know, I'm trying to build a bigger business,

592
00:30:48,840 --> 00:30:51,720
Speaker 4: you know, and and the water water mark keeps going up,

593
00:30:51,880 --> 00:30:54,480
Speaker 4: and so like if if in three years the water

594
00:30:54,520 --> 00:30:56,720
Speaker 4: mark isn't higher, I will feel like I failed the

595
00:30:56,800 --> 00:30:59,720
Speaker 4: last three years. And I think that's the you know,

596
00:30:59,760 --> 00:31:02,240
Speaker 4: that's the essence of being entrepreneurs. The watermark keeps going

597
00:31:02,320 --> 00:31:03,280
Speaker 4: up and you keep going up.

598
00:31:04,040 --> 00:31:05,760
Speaker 3: Really quite fascinating.

599
00:31:06,040 --> 00:31:10,240
Speaker 2: I want to dive into the world of private companies

600
00:31:10,280 --> 00:31:13,440
Speaker 2: and alts, but before we do that, I just had

601
00:31:13,440 --> 00:31:18,000
Speaker 2: to ask you a data question. My assumption is accessing

602
00:31:18,120 --> 00:31:21,840
Speaker 2: reliable and clean data has to be the lifeblood of

603
00:31:21,920 --> 00:31:25,800
Speaker 2: what you're doing. How challenging is that? How many different

604
00:31:25,800 --> 00:31:27,520
Speaker 2: inputs do you guys have to track?

605
00:31:27,640 --> 00:31:31,320
Speaker 4: At Karta, I have a perspective on software and data

606
00:31:31,360 --> 00:31:34,640
Speaker 4: businesses that might be a bit provocative, which is I'll

607
00:31:34,680 --> 00:31:38,520
Speaker 4: make this statement that software businesses cannot be data businesses.

608
00:31:39,200 --> 00:31:44,400
Speaker 4: And the reason is if a software business has customer data,

609
00:31:45,000 --> 00:31:48,000
Speaker 4: they get that customer data by selling software and service

610
00:31:48,040 --> 00:31:51,880
Speaker 4: to this customer. And if they monetize that data. On

611
00:31:51,920 --> 00:31:54,160
Speaker 4: the other side, if their left hand is we will

612
00:31:55,160 --> 00:31:59,320
Speaker 4: keep your data confidential and as part of our software

613
00:32:00,240 --> 00:32:02,320
Speaker 4: service to you. But then with the right hand they're

614
00:32:02,320 --> 00:32:05,760
Speaker 4: selling that data, it cannibalizes their software business because the

615
00:32:05,760 --> 00:32:08,000
Speaker 4: customers won't trust them now because they're now giving them

616
00:32:08,000 --> 00:32:10,800
Speaker 4: their data. Which is why Karta does not have a

617
00:32:10,920 --> 00:32:13,200
Speaker 4: data product. We have tons of data, we do not

618
00:32:13,320 --> 00:32:17,400
Speaker 4: have a monetizable data product. Interesting, we only sell workflow

619
00:32:17,480 --> 00:32:22,960
Speaker 4: or business operations software. It's hard to think of a

620
00:32:23,000 --> 00:32:28,000
Speaker 4: business that sells actual software and also sells data. I

621
00:32:28,040 --> 00:32:30,560
Speaker 4: can't think of any even Bloomberg started really as a

622
00:32:30,640 --> 00:32:34,560
Speaker 4: data business. The non existence non existence of something that

623
00:32:34,640 --> 00:32:37,560
Speaker 4: is not proof that it cannot exist. But my best

624
00:32:37,560 --> 00:32:40,840
Speaker 4: example of why my theory that software businesses and data

625
00:32:40,840 --> 00:32:46,000
Speaker 4: businesses cannot coexist in one company is Salesforce. If anybody

626
00:32:46,040 --> 00:32:49,160
Speaker 4: would launch a data product so funny, it would be Salesforce,

627
00:32:49,520 --> 00:32:53,720
Speaker 4: And in thirty years they have not, and I don't

628
00:32:53,760 --> 00:32:56,560
Speaker 4: think they ever will. And I think the day Salesforce

629
00:32:56,640 --> 00:32:59,280
Speaker 4: launches a successful data business, I will be eating my

630
00:32:59,320 --> 00:33:01,400
Speaker 4: words and I will be wrong. But I don't think

631
00:33:01,440 --> 00:33:03,240
Speaker 4: software businesses can become data businesses.

632
00:33:03,280 --> 00:33:04,120
Speaker 3: I would imagine that.

633
00:33:04,440 --> 00:33:07,920
Speaker 2: So we use in my shop, we use Salesforce as

634
00:33:07,960 --> 00:33:14,440
Speaker 2: our CRM, very customizable, and they have specific industries that

635
00:33:14,480 --> 00:33:18,840
Speaker 2: they market towards and customize. But the moment it feels

636
00:33:18,960 --> 00:33:22,080
Speaker 2: like your data is being reused, every single one of

637
00:33:22,080 --> 00:33:25,080
Speaker 2: their competitors would say, we keep your data safe, we

638
00:33:25,120 --> 00:33:28,200
Speaker 2: don't monetize the data, give them up on them, come

639
00:33:28,240 --> 00:33:31,480
Speaker 2: to us where we respect privacy. I mean, I think

640
00:33:31,520 --> 00:33:35,200
Speaker 2: the moment anybody tries that their competition is all over.

641
00:33:35,040 --> 00:33:37,640
Speaker 4: There, and you would agree because suddenly you're now on

642
00:33:37,760 --> 00:33:40,400
Speaker 4: every list of every vendor trying to sell software to

643
00:33:40,440 --> 00:33:42,840
Speaker 4: bury and they know everything about you because Salesforce gave

644
00:33:42,880 --> 00:33:43,520
Speaker 4: them your data.

645
00:33:44,160 --> 00:33:47,200
Speaker 2: Not only that, but it's not quite hippa but the

646
00:33:47,280 --> 00:33:50,800
Speaker 2: SEC has privacy requirements, things you're not allowed to share

647
00:33:50,880 --> 00:33:52,880
Speaker 2: when you're supposed to know your client. You have all

648
00:33:52,880 --> 00:33:56,120
Speaker 2: this data, and if one of your vendors is reusing

649
00:33:56,160 --> 00:34:00,600
Speaker 2: that repurposing that data for their own ends, wait that

650
00:34:00,760 --> 00:34:04,880
Speaker 2: not only are you violating our privacy agreement, you're putting

651
00:34:04,880 --> 00:34:06,520
Speaker 2: me underwater with the SEC.

652
00:34:06,600 --> 00:34:09,000
Speaker 3: They may come yell at me, I don't need that often,

653
00:34:09,120 --> 00:34:10,040
Speaker 3: go to your competition.

654
00:34:10,760 --> 00:34:15,880
Speaker 2: Kind of interesting, So let's pivot towards the private markets

655
00:34:15,920 --> 00:34:21,480
Speaker 2: because it's so interesting. You've testified before Congress that startups

656
00:34:21,640 --> 00:34:25,880
Speaker 2: and growth companies back by private capital, that's where most

657
00:34:25,920 --> 00:34:28,480
Speaker 2: of the new job growth comes in the United States.

658
00:34:28,840 --> 00:34:34,480
Speaker 4: Explain, Yeah, you know, public markets is actually a shrinking industry.

659
00:34:34,920 --> 00:34:37,520
Speaker 4: You know, there's fewer public companies today than there were

660
00:34:37,520 --> 00:34:41,719
Speaker 4: ten years ago by quite a big margin. But the

661
00:34:41,800 --> 00:34:46,080
Speaker 4: number of private companies is growing astronomically, and that's largely

662
00:34:46,080 --> 00:34:48,920
Speaker 4: fueled by there's a lot more private capital than there

663
00:34:49,000 --> 00:34:51,839
Speaker 4: used to be to fund these businesses, and there's less

664
00:34:51,840 --> 00:34:55,719
Speaker 4: reasons to go public now. So I think I think

665
00:34:55,719 --> 00:34:58,040
Speaker 4: that will continue to be true. I think it's structurally true.

666
00:34:58,040 --> 00:35:02,520
Speaker 4: When I go to the hill and to our legislators.

667
00:35:03,400 --> 00:35:05,840
Speaker 4: The common response is, well, we just have to push

668
00:35:05,920 --> 00:35:10,680
Speaker 4: more companies to go public. I think it's their belief

669
00:35:10,760 --> 00:35:14,120
Speaker 4: is the public markets is a great product for everyday

670
00:35:14,160 --> 00:35:18,120
Speaker 4: Americans to access growth equity. And I think they're right.

671
00:35:18,320 --> 00:35:20,680
Speaker 4: It is a good product for it. The problem is

672
00:35:20,680 --> 00:35:23,480
Speaker 4: it's not. It's a shrinking product, and most of the

673
00:35:23,480 --> 00:35:26,280
Speaker 4: growth is being happened is happening in the private markets,

674
00:35:26,280 --> 00:35:29,080
Speaker 4: and their attempts to get these companies to go public

675
00:35:29,120 --> 00:35:32,440
Speaker 4: so that there can be retail access to them isn't working.

676
00:35:32,440 --> 00:35:35,359
Speaker 4: It's a little bit like you know the river's coming

677
00:35:35,400 --> 00:35:37,400
Speaker 4: and you've got like one tiny little dam trying to

678
00:35:37,400 --> 00:35:38,200
Speaker 4: hold the water back.

679
00:35:38,520 --> 00:35:40,400
Speaker 2: Let me share a data point that I bet a

680
00:35:40,440 --> 00:35:43,360
Speaker 2: lot of listeners are not familiar with. The US is

681
00:35:43,400 --> 00:35:46,400
Speaker 2: something like four to five percent of the global population,

682
00:35:47,120 --> 00:35:49,400
Speaker 2: where something like twenty four to twenty five percent of

683
00:35:49,440 --> 00:35:53,600
Speaker 2: the global economy global market cap, we're over half. I mean,

684
00:35:53,640 --> 00:35:57,560
Speaker 2: we are wildly disproportionate in our public markets.

685
00:35:58,040 --> 00:36:00,440
Speaker 3: How much bigger does Congress want to make that?

686
00:36:00,800 --> 00:36:03,160
Speaker 2: I mean, what you're describing makes a lot of sense.

687
00:36:03,480 --> 00:36:07,440
Speaker 2: The public markets are enormous. Let's let the private markets

688
00:36:07,480 --> 00:36:08,360
Speaker 2: grow and see where they go.

689
00:36:08,680 --> 00:36:13,480
Speaker 4: Yeah, and that's certainly the message that we're pushing. We

690
00:36:13,560 --> 00:36:16,680
Speaker 4: still have to solve the problem of retail access because

691
00:36:16,680 --> 00:36:20,520
Speaker 4: as the number of public companies is shrinking, that's less

692
00:36:20,719 --> 00:36:23,440
Speaker 4: less and less options for your everyday American to invest

693
00:36:23,440 --> 00:36:26,960
Speaker 4: their money and their retirement. I don't think the answer

694
00:36:27,000 --> 00:36:28,800
Speaker 4: is to try to push more companies to go public.

695
00:36:29,239 --> 00:36:32,200
Speaker 4: I think the answer is to create safe access for

696
00:36:32,239 --> 00:36:35,279
Speaker 4: everyday Americans into private capital. And that's what we spend

697
00:36:35,280 --> 00:36:37,000
Speaker 4: a lot of time lobbying for in Congress.

698
00:36:37,520 --> 00:36:41,640
Speaker 2: Huh really quite fascinating. Coming up, we continue our conversation

699
00:36:41,760 --> 00:36:46,200
Speaker 2: with Henry Ward, CEO and co founder of Carter, talking

700
00:36:46,239 --> 00:36:49,440
Speaker 2: about the rise of private company investing.

701
00:36:49,880 --> 00:36:50,920
Speaker 3: I'm Barry Richards.

702
00:36:50,960 --> 00:37:09,040
Speaker 2: You're listening to Masters Business on Bloomberg Radio. I'm Barry Ridults.

703
00:37:09,200 --> 00:37:12,279
Speaker 2: You're listening to Masters in Business on Bloomberg Radio. My

704
00:37:12,640 --> 00:37:15,440
Speaker 2: extra special guest this week is Henry Ward. He's the

705
00:37:15,480 --> 00:37:18,920
Speaker 2: CEO and co founder of Karta. They help manage the

706
00:37:19,000 --> 00:37:23,840
Speaker 2: cap tables for tens of thousands of private companies, thousands

707
00:37:23,840 --> 00:37:28,440
Speaker 2: of investment firms, and millions of equity holders. They do

708
00:37:28,480 --> 00:37:32,520
Speaker 2: a number of other things in terms of tracking compensation, valuation, liquidity,

709
00:37:32,920 --> 00:37:36,800
Speaker 2: all these really fascinating issues. So there are a number

710
00:37:36,800 --> 00:37:43,399
Speaker 2: of companies that bring liquidity to private companies. Sometimes it's

711
00:37:43,520 --> 00:37:48,000
Speaker 2: private equity or some form of a private fund. Other

712
00:37:48,080 --> 00:37:51,200
Speaker 2: times it's individuals who want to participate in companies before

713
00:37:51,239 --> 00:37:54,920
Speaker 2: they go public. What are your thoughts on the future

714
00:37:54,920 --> 00:37:59,560
Speaker 2: of secondary liquidity, both for the investors and employees of

715
00:37:59,560 --> 00:38:03,320
Speaker 2: startup up and for the rest of the investing public

716
00:38:03,640 --> 00:38:05,600
Speaker 2: that wants to participate in these privates.

717
00:38:05,719 --> 00:38:11,160
Speaker 4: Yeah. So, I think I'm one of the maybe top

718
00:38:11,200 --> 00:38:13,320
Speaker 4: five people in the world that have worked on private

719
00:38:13,360 --> 00:38:17,040
Speaker 4: market liquidity. I spent the last ten years working on

720
00:38:17,160 --> 00:38:20,719
Speaker 4: the problem, and I'm of the view now that that

721
00:38:21,600 --> 00:38:27,360
Speaker 4: at least venture startup liquidity will never happen, and at

722
00:38:27,440 --> 00:38:30,160
Speaker 4: least a secondary exchange in the sense that we think

723
00:38:30,160 --> 00:38:33,000
Speaker 4: of public market exchanges. The private markets are so different

724
00:38:33,000 --> 00:38:35,520
Speaker 4: from public it's really kind of the upside down world,

725
00:38:35,600 --> 00:38:37,960
Speaker 4: you know. The In public markets, the price is set

726
00:38:37,960 --> 00:38:39,920
Speaker 4: by the last buyer, not the first. In private markets,

727
00:38:39,920 --> 00:38:42,000
Speaker 4: it's set by the first and not the last. In

728
00:38:42,040 --> 00:38:44,759
Speaker 4: public markets, it's easier to sell one share than one

729
00:38:44,840 --> 00:38:47,359
Speaker 4: hundred million dollars worth of shares. In private market's easier

730
00:38:47,400 --> 00:38:49,120
Speaker 4: to sell one hundred million dollar block than it is

731
00:38:49,160 --> 00:38:52,840
Speaker 4: to sell one one share. You know, in public markets,

732
00:38:53,239 --> 00:38:58,600
Speaker 4: the distribution outcomes is mostly Gaussian normally distributed in private markets,

733
00:38:58,320 --> 00:39:03,360
Speaker 4: it's power line. So all the math that exists in

734
00:39:03,760 --> 00:39:07,319
Speaker 4: modern portfolio finance theory in public markets doesn't work in

735
00:39:07,320 --> 00:39:10,640
Speaker 4: private So it's just it's a very different market infrastructure.

736
00:39:11,800 --> 00:39:14,200
Speaker 4: I think all the attempts they try to create liquidity

737
00:39:13,920 --> 00:39:17,440
Speaker 4: in the venture world will be failed attempts. But I

738
00:39:17,480 --> 00:39:20,000
Speaker 4: hope I'm wrong. I hope I'm just the old inequity.

739
00:39:20,120 --> 00:39:22,399
Speaker 2: Zen seems to have figured this out a while ago.

740
00:39:22,480 --> 00:39:25,319
Speaker 2: They seem to have put together a way to do

741
00:39:25,440 --> 00:39:33,240
Speaker 2: secondaries for creating some liquidity for insiders or employees at companies.

742
00:39:33,280 --> 00:39:36,720
Speaker 2: But it's not like they're a trillion dollar platform. It's

743
00:39:36,840 --> 00:39:40,120
Speaker 2: a little bit of a niche specific focused and there

744
00:39:40,120 --> 00:39:41,200
Speaker 2: are other companies like that.

745
00:39:41,280 --> 00:39:43,800
Speaker 3: I just happen to be thinking of them recently.

746
00:39:45,239 --> 00:39:48,880
Speaker 2: But really, what you're saying is there's a gulf between

747
00:39:49,760 --> 00:39:54,720
Speaker 2: trillions and trillions of dollars in public equity and private stock,

748
00:39:54,800 --> 00:39:56,719
Speaker 2: and never the twain shall meet.

749
00:39:56,960 --> 00:40:01,120
Speaker 4: So in public markets, liquidity begets liquidity, and so it

750
00:40:01,239 --> 00:40:06,080
Speaker 4: centralizes on two exchanges in the US and most regions,

751
00:40:06,080 --> 00:40:10,759
Speaker 4: it centralizes on one. In private markets, what's happened is

752
00:40:10,760 --> 00:40:13,800
Speaker 4: there's equities and there's many others. There's many many small

753
00:40:14,160 --> 00:40:17,960
Speaker 4: niche businesses doing secondaries. It does happen, but liquidity, it

754
00:40:17,960 --> 00:40:22,120
Speaker 4: does not get liquidity. As soon as one of these

755
00:40:22,160 --> 00:40:25,120
Speaker 4: companies starts to scale, all the competitors come around and

756
00:40:25,160 --> 00:40:28,439
Speaker 4: they devolve back down to a niche business. And that's

757
00:40:28,520 --> 00:40:31,800
Speaker 4: just the market structure. Is that any company that actually

758
00:40:31,800 --> 00:40:36,920
Speaker 4: starts to scale in the private markets, it actually it degenerates.

759
00:40:37,760 --> 00:40:42,120
Speaker 4: We've seen so many examples of private market liquidity providers,

760
00:40:42,480 --> 00:40:45,600
Speaker 4: you know, come in hot, get really a quick start,

761
00:40:45,719 --> 00:40:48,520
Speaker 4: and then once they hit scale, it falls down. And

762
00:40:48,520 --> 00:40:50,520
Speaker 4: so you see so many of these small businesses that

763
00:40:50,560 --> 00:40:53,000
Speaker 4: will always stay small businesses. I don't think there's an

764
00:40:53,040 --> 00:40:54,960
Speaker 4: opportunity for someone to consolidate the market.

765
00:40:55,160 --> 00:40:59,920
Speaker 2: There's been so much focus on privates and alternatives. Does

766
00:41:00,040 --> 00:41:01,720
Speaker 2: is this intensity of interest?

767
00:41:01,840 --> 00:41:03,040
Speaker 3: Does this surprise you at all?

768
00:41:03,160 --> 00:41:06,080
Speaker 2: Or you've been up to your chin in this for

769
00:41:06,239 --> 00:41:08,799
Speaker 2: a decade and what took everybody so long?

770
00:41:09,680 --> 00:41:12,520
Speaker 4: We've been in this up to up to my chin,

771
00:41:12,560 --> 00:41:16,520
Speaker 4: as you say, for a decade plus, So it's not

772
00:41:16,560 --> 00:41:20,280
Speaker 4: surprising what I think is really we're in a moment

773
00:41:20,320 --> 00:41:22,640
Speaker 4: of time and the speed that it's happening, especially with

774
00:41:22,680 --> 00:41:26,240
Speaker 4: the current administration, we're liberalizing a lot of the rules

775
00:41:26,239 --> 00:41:28,000
Speaker 4: for private market access. You know, there's a lot of

776
00:41:28,040 --> 00:41:33,320
Speaker 4: work being done around can retail investors access private equity firms,

777
00:41:33,320 --> 00:41:36,600
Speaker 4: private credit firms. I think that will continue to happen,

778
00:41:36,600 --> 00:41:40,120
Speaker 4: and I think that's a big tailwind for KARTA and

779
00:41:40,200 --> 00:41:45,040
Speaker 4: I think the US economy and GDP because so much

780
00:41:45,080 --> 00:41:48,560
Speaker 4: of this capital is being now deployed in useful ways.

781
00:41:49,040 --> 00:41:51,360
Speaker 4: I think that will continue to be true in the

782
00:41:51,400 --> 00:41:56,400
Speaker 4: next administration. Hopefully they will continue that legislative policy. I

783
00:41:56,440 --> 00:42:00,879
Speaker 4: think it will be weird and twenty or thirty years

784
00:42:00,880 --> 00:42:04,080
Speaker 4: it will be weird that we locked out ninety nine

785
00:42:04,080 --> 00:42:06,000
Speaker 4: percent of Americans out of private capital.

786
00:42:06,160 --> 00:42:09,240
Speaker 2: So when I look at who's being aggressive in terms

787
00:42:09,280 --> 00:42:12,319
Speaker 2: of moving from how do we get more people onto

788
00:42:12,360 --> 00:42:16,560
Speaker 2: the old turnatives and private side, it's everyone from Blackstone

789
00:42:16,640 --> 00:42:21,120
Speaker 2: to Blackrock, Carlisle, Apollo, Goldman sets go down the list.

790
00:42:21,440 --> 00:42:25,000
Speaker 2: I'm assuming you're working with some or most of these companies.

791
00:42:25,760 --> 00:42:30,640
Speaker 4: We know them all, We're huge fans. I was lucky

792
00:42:30,719 --> 00:42:36,560
Speaker 4: enough to spend an hour with Rob Goldstein, the COO

793
00:42:36,640 --> 00:42:39,719
Speaker 4: over at Blackrock, and he was telling me kind of

794
00:42:39,760 --> 00:42:43,320
Speaker 4: the vision of Blackrock and their perspective on private markets,

795
00:42:43,320 --> 00:42:46,520
Speaker 4: and you know, he made this very salient point, which was,

796
00:42:46,960 --> 00:42:48,839
Speaker 4: you know, when they talk to their customers, they might

797
00:42:48,880 --> 00:42:52,240
Speaker 4: look at a customer and they spend you know, twenty

798
00:42:52,280 --> 00:42:57,160
Speaker 4: five million dollars a year on public market infrastructure and

799
00:42:57,200 --> 00:43:01,520
Speaker 4: technology for their public market allocation software, and they might

800
00:43:01,560 --> 00:43:04,279
Speaker 4: spend you know, three hundred you know, three hundred and

801
00:43:04,280 --> 00:43:09,640
Speaker 4: fifty thousand dollars on their private frash fraction right with Blackrock,

802
00:43:09,680 --> 00:43:11,640
Speaker 4: but they might spend a million dollars total. So three

803
00:43:11,719 --> 00:43:14,600
Speaker 4: hundred fifty k is with Blackrock and seven hundred k

804
00:43:14,719 --> 00:43:17,879
Speaker 4: is with a bunch of other vendors. And his team

805
00:43:17,960 --> 00:43:19,799
Speaker 4: is like, oh, we should go after that seven hundred

806
00:43:19,880 --> 00:43:22,480
Speaker 4: k and we'll win the whole you know, million dollars

807
00:43:22,480 --> 00:43:24,640
Speaker 4: that they send an ALTS, And he goes, no, no, no, no,

808
00:43:24,880 --> 00:43:26,759
Speaker 4: Well we need to do is figure out how to

809
00:43:26,800 --> 00:43:29,040
Speaker 4: get that million dollars a year they spend an ALTS

810
00:43:29,440 --> 00:43:32,200
Speaker 4: to be twenty five million dollars a year, and then

811
00:43:32,239 --> 00:43:36,200
Speaker 4: we'll capture half of that. And that was the mental

812
00:43:36,239 --> 00:43:38,359
Speaker 4: mind shift that I think Blackrock is so smart at

813
00:43:38,400 --> 00:43:41,319
Speaker 4: which is we're trying to grow the market, not our

814
00:43:41,360 --> 00:43:42,880
Speaker 4: percentage of the market, right.

815
00:43:42,719 --> 00:43:44,759
Speaker 2: That makes that makes a whole lot of sense. So

816
00:43:44,880 --> 00:43:49,280
Speaker 2: they're looking at an adjacent market to their public market

817
00:43:49,320 --> 00:43:51,920
Speaker 2: dominance of the biggest investment firm in the world at

818
00:43:51,960 --> 00:43:56,440
Speaker 2: around twelve trillion dollars. How do you decide what adjacent

819
00:43:56,560 --> 00:44:00,400
Speaker 2: markets are attractive and you might want to into them?

820
00:44:00,440 --> 00:44:03,879
Speaker 2: If you started with cap tables, you're doing all sorts

821
00:44:03,880 --> 00:44:05,080
Speaker 2: of other data analytics.

822
00:44:05,320 --> 00:44:06,920
Speaker 3: How do you figure out what's adjacent?

823
00:44:07,280 --> 00:44:09,880
Speaker 4: We have a really strict framework on it because we

824
00:44:09,920 --> 00:44:11,759
Speaker 4: spend a lot of our time thinking about where we

825
00:44:11,800 --> 00:44:16,279
Speaker 4: can expand and we have really two criteria. So one

826
00:44:16,320 --> 00:44:19,920
Speaker 4: is do we have a right to win? So what

827
00:44:20,000 --> 00:44:22,040
Speaker 4: gives us competitive edge that we can do that nobody

828
00:44:22,080 --> 00:44:25,239
Speaker 4: else can do? And second is can we win that

829
00:44:25,280 --> 00:44:28,200
Speaker 4: market quickly? Because we're very much of software business, like

830
00:44:29,440 --> 00:44:30,960
Speaker 4: if you can win a market, but it takes a

831
00:44:30,960 --> 00:44:33,719
Speaker 4: long time. We're a growth, growth company, so it's got

832
00:44:33,760 --> 00:44:35,600
Speaker 4: to be fast. So you have to have a very

833
00:44:36,640 --> 00:44:40,160
Speaker 4: aggressive customer acquisition model that creates a flywheel that the

834
00:44:40,200 --> 00:44:43,000
Speaker 4: more customers you get, the more customers you get. And

835
00:44:43,040 --> 00:44:45,359
Speaker 4: so if those two things are true, we'll go after it.

836
00:44:45,600 --> 00:44:48,160
Speaker 4: And it leads you to really funny things where you

837
00:44:48,160 --> 00:44:52,920
Speaker 4: wouldn't actually attack adjacent markets that are obvious adjacents, that

838
00:44:52,960 --> 00:44:56,160
Speaker 4: have obvious adjacencies. So the example I love is cap tables.

839
00:44:56,160 --> 00:44:58,800
Speaker 4: In four nine A. Cap tables was a legal service

840
00:44:58,880 --> 00:45:01,719
Speaker 4: when we entered it by lawyers. Four nine A valuations

841
00:45:01,760 --> 00:45:05,360
Speaker 4: was evaluation service done by valuation providers. Nobody thought of

842
00:45:05,360 --> 00:45:07,640
Speaker 4: them as similar. What we realized is by having the

843
00:45:07,680 --> 00:45:11,160
Speaker 4: cap table, we could do valuations faster, cheaper, smarter, and

844
00:45:11,200 --> 00:45:13,560
Speaker 4: so we just started doing valuations.

845
00:45:12,960 --> 00:45:15,520
Speaker 2: Well, you know the total number of shareholders, you know

846
00:45:15,560 --> 00:45:19,000
Speaker 2: what the last transaction or funding was. It sounds pretty

847
00:45:19,040 --> 00:45:19,960
Speaker 2: basic math.

848
00:45:19,760 --> 00:45:21,680
Speaker 4: Right totally, It's just math on the cap table. But

849
00:45:21,719 --> 00:45:23,839
Speaker 4: they are completely different industries. So if you think about

850
00:45:23,880 --> 00:45:26,319
Speaker 4: from a market perspective, they're different, but you think about

851
00:45:26,360 --> 00:45:29,239
Speaker 4: it from where we have competitive edge, they're the same

852
00:45:29,280 --> 00:45:32,920
Speaker 4: and the same with fund accounting, fund administration, fund accounting software,

853
00:45:33,200 --> 00:45:36,240
Speaker 4: very different industry than cap table management. But we're able

854
00:45:36,280 --> 00:45:38,759
Speaker 4: to connect the cap tables to the funds and that

855
00:45:38,800 --> 00:45:41,480
Speaker 4: gave us unique competitive advantage that nobody else could do.

856
00:45:41,760 --> 00:45:43,799
Speaker 4: And so now we're in the fund admin business, and

857
00:45:43,840 --> 00:45:46,239
Speaker 4: that's our second biggest business line.

858
00:45:46,360 --> 00:45:49,480
Speaker 2: You guys also do compensation analytics. How did you find

859
00:45:49,480 --> 00:45:50,440
Speaker 2: you into that space?

860
00:45:50,560 --> 00:45:53,000
Speaker 4: We realized we're the only ones that could do benchmarking

861
00:45:53,080 --> 00:45:56,080
Speaker 4: for both salary and equity for startups.

862
00:45:56,120 --> 00:45:58,160
Speaker 2: Oh of course, nobody else can do it, and so

863
00:45:58,280 --> 00:46:01,200
Speaker 2: without the equity, the salary be that significant.

864
00:46:01,239 --> 00:46:04,440
Speaker 4: That's right. But to start at a priority ago we're

865
00:46:04,440 --> 00:46:06,359
Speaker 4: gonna do cap tables and that's gonna lead us into

866
00:46:06,400 --> 00:46:09,800
Speaker 4: compensation didn't make a ton of sense. And that's that

867
00:46:09,960 --> 00:46:12,919
Speaker 4: we have a flywheel of This is how we entered

868
00:46:12,920 --> 00:46:13,600
Speaker 4: these industries.

869
00:46:14,120 --> 00:46:16,400
Speaker 2: You're the perfect person to ask this question. I'm going

870
00:46:16,480 --> 00:46:17,280
Speaker 2: to go off script.

871
00:46:18,160 --> 00:46:19,120
Speaker 3: So I spoke at.

872
00:46:19,080 --> 00:46:22,560
Speaker 2: An event in June and Silicon Valley. It was a

873
00:46:22,640 --> 00:46:26,160
Speaker 2: kind of funky hotel that was turned into this really

874
00:46:26,320 --> 00:46:31,640
Speaker 2: interesting space right on the edge of trying to remember

875
00:46:31,680 --> 00:46:34,279
Speaker 2: exactly where it was, about forty five minutes outside of

876
00:46:34,320 --> 00:46:40,360
Speaker 2: San Francisco, but anyway, it was an employee benefits conference

877
00:46:40,400 --> 00:46:42,480
Speaker 2: with all sorts of people, and I was there to

878
00:46:42,520 --> 00:46:46,239
Speaker 2: talk about my book at the time, and I heard

879
00:46:46,360 --> 00:46:49,640
Speaker 2: over and over again from all these people who therefore

880
00:46:49,640 --> 00:46:54,600
Speaker 2: a one k people their employee compensation consultants, their health

881
00:46:54,719 --> 00:46:58,719
Speaker 2: benefit consultants, all these people who were telling me that

882
00:46:58,880 --> 00:47:06,040
Speaker 2: there's this sort of misalignment amongst Silicon Valley employees who

883
00:47:06,080 --> 00:47:09,200
Speaker 2: are more interested in the dollars than they are in

884
00:47:09,239 --> 00:47:13,640
Speaker 2: the equity, which just completely sounds upside down to me.

885
00:47:15,160 --> 00:47:18,280
Speaker 2: Am I just looking at a weird corner of the world.

886
00:47:18,520 --> 00:47:21,839
Speaker 2: Or is that a thing that hey, you can't pay

887
00:47:21,880 --> 00:47:24,080
Speaker 2: you rent with equity, I have to at least make X.

888
00:47:24,560 --> 00:47:26,839
Speaker 2: What do you see out there in terms of how

889
00:47:26,880 --> 00:47:32,360
Speaker 2: startup employees are thinking about equity versus cash payments for comp.

890
00:47:32,080 --> 00:47:34,359
Speaker 4: Yeah, We've spent a lot of time thinking about this,

891
00:47:34,800 --> 00:47:39,640
Speaker 4: and I'll frame it as you know, wealth management. Financial

892
00:47:39,680 --> 00:47:43,200
Speaker 4: advice is a well established industry in the public world,

893
00:47:43,200 --> 00:47:45,399
Speaker 4: and I'll call it the liquid world. Right, you pay

894
00:47:45,520 --> 00:47:48,600
Speaker 4: you know, one percent or half a percent of aum

895
00:47:49,560 --> 00:47:52,200
Speaker 4: to your financial advisor and they help you manage your assets.

896
00:47:54,160 --> 00:47:56,600
Speaker 4: There is no equivalent in the private world. Like if

897
00:47:56,640 --> 00:47:59,200
Speaker 4: I'm an employee and I make you know, one hundred

898
00:47:59,200 --> 00:48:01,040
Speaker 4: fifty thousand dollars year and cash, but I'm sitting on

899
00:48:01,080 --> 00:48:04,440
Speaker 4: a million or two million dollars of equity ill liquid equity?

900
00:48:04,760 --> 00:48:06,960
Speaker 4: How do I think about that? How do I work

901
00:48:07,000 --> 00:48:09,279
Speaker 4: on it, and there is no industry for that. The

902
00:48:09,360 --> 00:48:11,640
Speaker 4: financial advisors don't know how to work with that, in

903
00:48:11,640 --> 00:48:14,520
Speaker 4: part because they don't understand the private market, you know,

904
00:48:14,880 --> 00:48:18,239
Speaker 4: ill liquid asset piece, but also they don't have they

905
00:48:18,239 --> 00:48:20,759
Speaker 4: don't have any way to monetize two million dollars with

906
00:48:20,880 --> 00:48:23,360
Speaker 4: the private stock. You can't you know, you can't charge

907
00:48:23,360 --> 00:48:26,200
Speaker 4: one basis point or a percent of AUM on it.

908
00:48:26,640 --> 00:48:31,200
Speaker 4: And so we've wrestled with this question of if an

909
00:48:31,280 --> 00:48:35,440
Speaker 4: industry were to be created, not wealth managed, but but

910
00:48:35,600 --> 00:48:39,879
Speaker 4: wealth management for ill liquid people, for high net worth

911
00:48:39,920 --> 00:48:43,239
Speaker 4: but ill liquid asset holders, what would that industry look like.

912
00:48:44,040 --> 00:48:45,800
Speaker 4: And so we've been thinking a lot about that problem,

913
00:48:45,840 --> 00:48:51,640
Speaker 4: and we recently launched a partnership with Morgan Stanley where

914
00:48:51,960 --> 00:48:55,120
Speaker 4: last year we posed this problem to them and we said, hey,

915
00:48:55,560 --> 00:48:59,160
Speaker 4: we think it's worth solving wealth management for ill liquid holders.

916
00:48:59,360 --> 00:49:00,960
Speaker 4: How would we do that? And they're, you know, the

917
00:49:01,040 --> 00:49:04,120
Speaker 4: largest wealth management for the country. They do this extremely well.

918
00:49:04,160 --> 00:49:07,040
Speaker 4: And now we're creating Emotion to basically help these employees

919
00:49:07,200 --> 00:49:08,719
Speaker 4: who are like I would just want the cash because

920
00:49:08,719 --> 00:49:10,000
Speaker 4: I don't know what to do with this equity. I

921
00:49:10,040 --> 00:49:12,839
Speaker 4: don't know, I don't understand it. I don't know when

922
00:49:12,880 --> 00:49:15,000
Speaker 4: it's going to be liquid, and can you create a

923
00:49:15,040 --> 00:49:17,640
Speaker 4: financial advisory industry to help those people?

924
00:49:18,440 --> 00:49:23,360
Speaker 2: That's really fascinating. I was genuinely shocked, maybe because I'm

925
00:49:23,440 --> 00:49:26,440
Speaker 2: more risk seeking than risk averse, and the thought of

926
00:49:26,440 --> 00:49:29,759
Speaker 2: equity is so, you know, attractive to me. But I

927
00:49:29,800 --> 00:49:31,680
Speaker 2: guess when you're in the thick of it and you're

928
00:49:31,719 --> 00:49:35,439
Speaker 2: grinding one hundred hour weeks, hey, I'm working my butt

929
00:49:35,480 --> 00:49:37,760
Speaker 2: off and I still have to worry about paying my rent.

930
00:49:38,000 --> 00:49:39,080
Speaker 3: I don't want to go that way.

931
00:49:39,360 --> 00:49:41,920
Speaker 2: That was the only explanation I could come up with,

932
00:49:42,000 --> 00:49:44,759
Speaker 2: but it was It was really quite fascinating.

933
00:49:45,680 --> 00:49:47,800
Speaker 3: I only have you for a limited amount of time.

934
00:49:47,880 --> 00:49:50,520
Speaker 2: Why don't we jump to some of our favorite questions

935
00:49:50,520 --> 00:49:53,640
Speaker 2: that we ask all of our guests, starting with and

936
00:49:53,680 --> 00:49:56,000
Speaker 2: you're a good person to ask this. Tell us about

937
00:49:56,000 --> 00:49:58,840
Speaker 2: your mentors who helped shape your career.

938
00:50:00,120 --> 00:50:03,080
Speaker 4: You know, I don't think I've had just one. I

939
00:50:03,400 --> 00:50:06,719
Speaker 4: think I pulled together a lot of people that have

940
00:50:07,400 --> 00:50:09,600
Speaker 4: that helped me with little different things. And so you

941
00:50:09,640 --> 00:50:12,400
Speaker 4: know everything from my boxing coach in high school and

942
00:50:12,440 --> 00:50:15,439
Speaker 4: college that that you know, boxing is an interesting sport

943
00:50:15,480 --> 00:50:19,200
Speaker 4: because it's one of the very few sports that if

944
00:50:19,239 --> 00:50:21,400
Speaker 4: you're tired and you're in pain and you have to

945
00:50:21,480 --> 00:50:23,160
Speaker 4: let off the gas a little bit, it hurts more,

946
00:50:23,239 --> 00:50:23,719
Speaker 4: not less.

947
00:50:25,080 --> 00:50:25,879
Speaker 3: You got a dig DP.

948
00:50:25,960 --> 00:50:29,680
Speaker 4: That's right. And you know there's it's literally in the corner.

949
00:50:30,239 --> 00:50:34,440
Speaker 4: And you know from from perseverance, from him, from the Marines,

950
00:50:35,080 --> 00:50:39,480
Speaker 4: from you know, Mark Andresen who helped me figure out

951
00:50:39,640 --> 00:50:42,239
Speaker 4: you know, uh nut suite what we call EERP for

952
00:50:42,280 --> 00:50:46,439
Speaker 4: private capital out of breakfast uh to you know John

953
00:50:46,480 --> 00:50:48,440
Speaker 4: Waldron who I had got to have a lunch with

954
00:50:48,520 --> 00:50:52,080
Speaker 4: him as president at Goldman, who explained to me why

955
00:50:52,239 --> 00:50:54,719
Speaker 4: bankers make more money than I do, and it's because

956
00:50:54,719 --> 00:50:58,120
Speaker 4: of the regulatory defensibility. And so you just pick up

957
00:50:58,160 --> 00:51:00,600
Speaker 4: these nuggets from these very smart people and and you

958
00:51:00,640 --> 00:51:01,759
Speaker 4: hold him as a treasure trove.

959
00:51:02,960 --> 00:51:05,160
Speaker 2: Let's talk about books. What are some of your favorites?

960
00:51:05,160 --> 00:51:06,560
Speaker 2: So are you reading anything currently?

961
00:51:07,400 --> 00:51:11,719
Speaker 4: We just read amp it up as a leadership team.

962
00:51:11,800 --> 00:51:15,240
Speaker 4: So last month we took sixty of our top leaders

963
00:51:15,239 --> 00:51:18,319
Speaker 4: at KARDA on an off site. And every time we

964
00:51:18,360 --> 00:51:20,000
Speaker 4: do an offsite at KRDA, we pick a book to

965
00:51:20,040 --> 00:51:21,480
Speaker 4: read and everybody has to read it and we do

966
00:51:21,520 --> 00:51:24,239
Speaker 4: a discussion group. And it was very timely for us.

967
00:51:24,280 --> 00:51:29,960
Speaker 4: We're in very much an acceleration motion, and so everybody

968
00:51:30,160 --> 00:51:32,440
Speaker 4: at Carda right now is reading amp it up and

969
00:51:32,480 --> 00:51:34,360
Speaker 4: talking about it really interesting.

970
00:51:35,000 --> 00:51:37,120
Speaker 2: What about streaming, what are you listening to in terms

971
00:51:37,200 --> 00:51:40,040
Speaker 2: of podcasts or watching on Netflix or Amazon. I kind

972
00:51:40,040 --> 00:51:42,560
Speaker 2: of get the sense you're not a big couch potato

973
00:51:42,640 --> 00:51:43,080
Speaker 2: kind of guy.

974
00:51:43,440 --> 00:51:46,320
Speaker 4: I'm not. I don't really watch TV except I have

975
00:51:46,360 --> 00:51:49,400
Speaker 4: an eleven year old boy, and I recently got him

976
00:51:49,400 --> 00:51:53,719
Speaker 4: into Arrested Development, which is a classic, absolutely some of

977
00:51:53,719 --> 00:51:57,240
Speaker 4: the best comedy ever done. And we're watching it together

978
00:51:57,440 --> 00:52:00,520
Speaker 4: and we're loving it. And now he he hits me

979
00:52:00,560 --> 00:52:03,239
Speaker 4: with the lines and you know that I've made a

980
00:52:03,320 --> 00:52:05,480
Speaker 4: huge mistake and we're having a great time with it.

981
00:52:06,200 --> 00:52:09,640
Speaker 2: Narrator, it wasn't yeah right. I mean that's where that

982
00:52:09,680 --> 00:52:11,799
Speaker 2: comes from. People use it all the time, but it all.

983
00:52:11,719 --> 00:52:12,680
Speaker 4: Goes right back to.

984
00:52:14,280 --> 00:52:18,000
Speaker 3: I like his podcast SmartLess. Yeah, it's kind of fun.

985
00:52:20,480 --> 00:52:23,759
Speaker 2: Our final two questions, what sort of advice would you

986
00:52:23,800 --> 00:52:26,600
Speaker 2: give to a recent college grad who is interested in

987
00:52:26,640 --> 00:52:33,239
Speaker 2: the career in filling the blank entrepreneurship, startups, private companies.

988
00:52:33,880 --> 00:52:36,240
Speaker 4: You know, I just did a talk at Waterloo yesterday

989
00:52:36,760 --> 00:52:39,520
Speaker 4: to a bunch of soon to be grads there, and

990
00:52:40,040 --> 00:52:42,400
Speaker 4: I said, you know they were computer science grads and

991
00:52:42,719 --> 00:52:45,360
Speaker 4: I said, you know there's you know they know of

992
00:52:45,400 --> 00:52:49,800
Speaker 4: this algorithm called the hill climbing algorithm, which is basically,

993
00:52:49,800 --> 00:52:51,799
Speaker 4: if you're trying to find a global maximum versus a

994
00:52:51,800 --> 00:52:53,560
Speaker 4: local maximum. What I mean by that. The analogy I

995
00:52:53,640 --> 00:52:56,279
Speaker 4: use is, let's say you're a French you know, you're

996
00:52:56,280 --> 00:52:58,279
Speaker 4: climbing in the French Alps as a mountain climber, and

997
00:52:58,320 --> 00:53:00,400
Speaker 4: you're trying to find the tallest mountain in the French helps.

998
00:53:00,400 --> 00:53:03,040
Speaker 4: But there's cloud cover, you can't see, you can't see

999
00:53:03,080 --> 00:53:05,960
Speaker 4: the tops of these How would you find the highest mountain?

1000
00:53:06,040 --> 00:53:09,080
Speaker 4: And you would do it by picking a mountain, climbing

1001
00:53:09,120 --> 00:53:11,279
Speaker 4: to the top, recording how high you are, and then

1002
00:53:11,440 --> 00:53:14,160
Speaker 4: randomly jumping to another mountain and climbing and recording that.

1003
00:53:14,200 --> 00:53:16,640
Speaker 4: And there's all this math around. You know, how many

1004
00:53:16,920 --> 00:53:18,799
Speaker 4: random jumps to mountains do you have to have to

1005
00:53:18,800 --> 00:53:21,560
Speaker 4: have a ninety percent probability of finding the global the

1006
00:53:21,600 --> 00:53:26,080
Speaker 4: global maximum? And I say it's a great analogy for

1007
00:53:26,160 --> 00:53:31,839
Speaker 4: a metaphor for early careers, which is most of us, unfortunately,

1008
00:53:31,920 --> 00:53:35,440
Speaker 4: are taught. You go through kindergarten to high school to college,

1009
00:53:35,440 --> 00:53:38,319
Speaker 4: you pick a career at nineteen or a specialty. You

1010
00:53:38,360 --> 00:53:41,319
Speaker 4: then become a finance analyst and associate, then you become

1011
00:53:41,320 --> 00:53:43,080
Speaker 4: a senior associate, then you become a man, and you

1012
00:53:43,160 --> 00:53:46,080
Speaker 4: just you kind of walk this track and you never

1013
00:53:46,400 --> 00:53:49,880
Speaker 4: ask the question, am I on a local hill or

1014
00:53:49,920 --> 00:53:53,680
Speaker 4: a global optimal hill? And I encourage people early to

1015
00:53:54,160 --> 00:53:57,600
Speaker 4: jump mountains to figure out which which mountain they want

1016
00:53:57,600 --> 00:53:59,120
Speaker 4: to be on. And I think one of the reasons

1017
00:53:59,160 --> 00:54:02,640
Speaker 4: many people my age are very unhappy in their careers

1018
00:54:02,719 --> 00:54:05,000
Speaker 4: is they look back and they realize, Oh, I got

1019
00:54:05,040 --> 00:54:06,360
Speaker 4: to the top of the mountain, but it was the

1020
00:54:06,360 --> 00:54:09,560
Speaker 4: wrong mountain. And I encourage young people to mountain jump.

1021
00:54:10,200 --> 00:54:13,080
Speaker 2: I love that metaphor mountain jump is a great great line.

1022
00:54:13,640 --> 00:54:17,279
Speaker 2: What do you know about the world of entrepreneurship, startups, etc.

1023
00:54:17,680 --> 00:54:20,680
Speaker 2: Today Might have been useful twenty or so years ago

1024
00:54:20,680 --> 00:54:21,919
Speaker 2: when you were first starting out.

1025
00:54:23,239 --> 00:54:26,600
Speaker 4: Idea matters. It matters a lot because I've had a

1026
00:54:26,640 --> 00:54:28,839
Speaker 4: lot of great ideas that did not work, and I

1027
00:54:28,960 --> 00:54:35,200
Speaker 4: worked hard at it. I also think there's this counterintuitive,

1028
00:54:37,719 --> 00:54:40,840
Speaker 4: I guess thesis that's happening right now, which is the

1029
00:54:40,880 --> 00:54:45,160
Speaker 4: more entrepreneurs there are, the harder entrepreneurship guts, but people

1030
00:54:45,239 --> 00:54:47,439
Speaker 4: think the opposite, right, Oh, so many, so many people

1031
00:54:47,480 --> 00:54:48,799
Speaker 4: are doing it. I can do too.

1032
00:54:49,840 --> 00:54:53,680
Speaker 2: That. Michael Mobisont calls that the paradox of skill. The

1033
00:54:53,760 --> 00:54:57,760
Speaker 2: more skillful players there are in sports, the more luck matters,

1034
00:54:58,000 --> 00:55:00,880
Speaker 2: because everybody's playing at such a high level one hundred percent.

1035
00:55:01,080 --> 00:55:04,680
Speaker 4: And I think it's one of these funny things where

1036
00:55:04,840 --> 00:55:07,799
Speaker 4: like not many people, you know, dream or move to

1037
00:55:08,440 --> 00:55:12,200
Speaker 4: Atlanta to be one hundred meter you know, sprinter, because

1038
00:55:12,320 --> 00:55:14,160
Speaker 4: you know, I think I can be the greatest hundred

1039
00:55:14,160 --> 00:55:17,600
Speaker 4: meter sprinter in the world. And it's because there's not

1040
00:55:17,640 --> 00:55:19,239
Speaker 4: a lot of luck. I mean, there's luck around. You

1041
00:55:19,239 --> 00:55:20,960
Speaker 4: don't get injured and all of those things. But like

1042
00:55:21,000 --> 00:55:22,759
Speaker 4: we pretty quickly can tell.

1043
00:55:22,680 --> 00:55:25,120
Speaker 3: That is good and who's your skill out?

1044
00:55:25,320 --> 00:55:28,400
Speaker 4: Yes, And it's a little bit like acting like so

1045
00:55:28,520 --> 00:55:31,200
Speaker 4: much of it is luck that because so much of

1046
00:55:31,200 --> 00:55:33,960
Speaker 4: it is luck, people think anybody can do it, and

1047
00:55:34,440 --> 00:55:38,560
Speaker 4: it's actually worse. You actually have to be a super skilled,

1048
00:55:38,920 --> 00:55:41,120
Speaker 4: you know, one hundred meters sprinter and you have to

1049
00:55:41,120 --> 00:55:43,719
Speaker 4: be lucky to do one of these startups. And I

1050
00:55:43,719 --> 00:55:45,160
Speaker 4: think a lot of people are like, oh, you know,

1051
00:55:45,360 --> 00:55:47,240
Speaker 4: a lot of it's luck. So if it's luck, anybody

1052
00:55:47,320 --> 00:55:49,080
Speaker 4: can do it. It's it's you got to have both

1053
00:55:49,120 --> 00:55:50,720
Speaker 4: that makes it actually hard or not easier.

1054
00:55:50,760 --> 00:55:54,239
Speaker 2: I love the expression table stakes, smart, hard working, that's

1055
00:55:54,400 --> 00:55:55,560
Speaker 2: just to enter the arena.

1056
00:55:55,960 --> 00:55:57,799
Speaker 3: Then you got to get lucky on top of us.

1057
00:55:57,880 --> 00:56:03,520
Speaker 2: Right. Unbelievable. This has been absolutely fascinating. We have been

1058
00:56:03,600 --> 00:56:06,560
Speaker 2: speaking with Henry Ward. He is the CEO and co

1059
00:56:06,640 --> 00:56:11,080
Speaker 2: founder of Karta, helping to manage much more than just

1060
00:56:11,120 --> 00:56:17,680
Speaker 2: the cap table for tens of thousands of companies, investment funds,

1061
00:56:17,719 --> 00:56:22,000
Speaker 2: and investors. If you enjoy this conversation, well check out

1062
00:56:22,000 --> 00:56:24,480
Speaker 2: any of the five hundred and sixty five we've done

1063
00:56:24,920 --> 00:56:30,840
Speaker 2: over the past eleven years. You can find those at Bloomberg, iTunes, Spotify, YouTube,

1064
00:56:31,200 --> 00:56:34,560
Speaker 2: wherever you get your favorite podcast. And be sure to

1065
00:56:34,640 --> 00:56:39,440
Speaker 2: check out my new book How Not to Invest The ideas, numbers,

1066
00:56:39,480 --> 00:56:43,200
Speaker 2: and behaviors that destroy wealth and how to avoid them

1067
00:56:43,400 --> 00:56:55,200
Speaker 2: How Not to Invest at your favorite bookstore