Episode 37: "Winners Emerge After the Five-Year Mark" | TCA Venture Group Chairman Emeritus John Harbison on Exit Timeline Expectations, Portfolio Diversification Strategies, and The Unexpected U-Curve of Returns

Insights from a 20-year angel investing veteran who created data-driven tools used by hundreds of angel groups

Today's episode explores three ideas that caught my attention:

1. The zombie portfolio problem - John created a simple "Lost Cause Fund" solution that lets angels harvest tax losses from walking dead companies. Genius. How many other innovations remain undershared across angel networks?
2. Expertise >> crowds - John's analysis revealed a U-shaped return curve where heavily-invested deals performed well, but surprisingly, some smaller deals with just a few deep-industry experts also outperformed. Fresh perspective on the “wisdom of the crowds.”
3. The first five years deceive us - Learning that early outcomes skew negative while big returns happen 5-15 years later explains why many angels quit too soon. Vital for inclusion in any angel education.

I explore these ideas and more with John Harbison, Chairman Emeritus of TCA Venture Group. With over 20 years of angel investing experience, John has led the ACA's data initiatives and helped develop the Angel Funders Report. His blend of management consulting and hands-on investing makes him a highly insightful, data-driven leader in the industry.

During our conversation, John shares:

• A practical approach to data collection that simplifies complex cap table analysis by focusing on the key ratio between investment amount and return amount, making portfolio tracking manageable for groups of any size.
• Detailed data analysis showing that early investment outcomes are misleading – the first five years are dominated by shutdowns while significant exits typically happen between years 5-15, fundamentally reshaping how angels should set expectations.
• A forward-looking vision for how AI can transform angel investing, from automating member expertise matching to guiding diligence questions, potentially improving both efficiency and decision quality. 

Connect with John 

LinkedIn | Blog

Stuff We Reference

• Seraf
• Alycia Doxon
• Ron Weissman
• CTAN
• Launchpad Ventures

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Transcript

[00:00:00] 

John Harbison: It either meant, you don't care or you care enough to do the analysis and you didn't like the answer and you don't wanna tell anybody about it.

It's a 0% return, it's a zero multiple I don't need to know what the cap table look like.

Of those two or three, at least two will be dead within five years and maybe the other one will still be alive, but it probably won't be an exit.

 10% of the exits make up 90% of the outcomes.

Nobody's smart enough to know which one is the 1 in 20 that's gonna be the big home run.

There was absolutely no correlation. It was a total shotgun blast.

Andrew Kazlow: Welcome to the Diligent Observer, the first podcast exclusively focused on helping angels see what others miss. I'm your host, Andrew, and every week we explore what works, what doesn't, and why through conversations with experienced startup investors and operators.

My guest today is John Harbison, Chairman Emeritus of TCA Venture Group, current Angel Capital Association Board Member, and the driving force behind two of my favorite resources for [00:01:00] angel investors, the annual Angel Funders Report and Data Insights Monthly. In this episode, John shares some extremely practical insights on angel investing returns, including how TCA's portfolio achieved a 5.8 x overall return, why the first five years of investments tend to favor negative outcomes, and the story of his group's biggest winner, a 368 x return that took 15 years to materialize.

I hope you enjoy learning from John as much as I did.

One quick note before we jump in. If you're an angel investor or thinking about becoming one, you need to know about the Angel Capital Association.

The A CA is an incredible community for connecting with experienced investors, tapping into tons of well-documented best practices and training resources, and just generally keeping up to speed with what's happening in the angel space.

Now I've really enjoyed getting connected over the last few years and that's why I'm so excited to partner with the a CA to bring you this [00:02:00] special series of episodes live from their annual summit in Denver. If you're serious about angel investing, you will definitely want to check them out. 

John, thank you for being with me today.

John Harbison: Pleasure to be here. Thanks for including me.

Andrew Kazlow: So I have to ask, what are you most excited about right 

now?

John Harbison: I've been coming to this since 2015 and I'd already been an angel investor for a dozen or so years at that time.

But I continue to learn from every one of them. This is the buzz at these summits is great. 

Andrew Kazlow: Mm-hmm. 

John Harbison: There are lots of people who have lots of experience. We learn from each other. I become a better investor every year because I'm learning from others and I like that kind of buzz. The presentations have insights that help me expand my knowledge.

Andrew Kazlow: Well, let me ask, what's one thing you've learned so far this year? We just wrapped up, I don't know, six hours of presentations. So, what's one kind of standout nugget that you'll go home with tonight?   

John Harbison: I think so [00:03:00] far the two highlights in me, there were two presentations, one yesterday and one today on, how venture capitalists think.

And, there were some common things that I knew there were some other things. I appreciated those nuances and had a better understanding for that. And I also liked that both of them, had some data behind it, not just in terms of their observations. So there's enough that we've done in our own analysis of data that I always kind of look for a confirmation in whatever somebody's saying.

And there were pieces, like the professor yesterday from Stanford, was talking about unicorns and he was saying that the incidence of unicorn and VCs is a

1 in a 101,

which is interesting because Tech Coast Angels has had about 300 outcomes and we've had four unicorns. So I said, oh, maybe he's right with the other things he's saying.

So you find little points where you can connect with or other things that come out as these are things that I hadn't really thought about it in that way. [00:04:00] And so it gives you a different perspective and you learn when you get better. 

Andrew Kazlow: Fantastic. Well, that is something that you seem to be very adept at.

You are behind in many ways, the annual Angel Funder Report that the ACA puts together as well as the ongoing Data Insights Monthly, I believe is what it's called, which I personally love and look forward to every month. So maybe for our listeners that are not as familiar, explain what is the Angel Funder Report and the Data Insights Monthly.

Uh, and then I'd love to ask you a few more follow-up questions. 

John Harbison: This goes back a ways. We started in, I think around 2016, 17. ACA started collecting data from their member groups on investments and exits and shutdowns, and we put that information together into the Angel Funders Report.

Each year we have 60 to 70 groups that are providing the information this year with 74 groups, which is a really good [00:05:00] turnout. They're about a thousand companies in the investment space. So, you know, we're up to 10,000 or so companies, that we accumulated over the years. You get the sense of the patterns of what are the investments, what types of securities are more prevalent, what kind of industries you're going in.

But then it also gets much more insightful and in terms of dealing with some of the causalities and other things like that, it's helpful to angel groups when they're trying to benchmark their own activities against the market. So this is sort of the market that they will compare themselves to. So if they say, well gee, you know, we're only doing 5% in that industry, and overall all this other angel groups are doing 25%.

They say maybe we got a blind spot there and we ought up looking more at that. So they try to understand that from a governance perspective, you can look at things like, what kind of investments are there per member? And how does that change by geography? And that's it helps angel groups understand where they fit in and it helps individual [00:06:00] angels to know whether the kind of investments they're doing, how they fit into the thing.

So Angel Funders Report is a snapshot once a year, gives a time series comparisons. The Angel Insights is something that I kind of was the godfather of about five years ago. The purpose of putting this initiative forward was so that we could learn from each other and each of us who had a passion for this, like I do in our own angel groups, had been doing analysis.

But even a large angel group, they're limited in the data set that you have. So what we're trying to do is to aggregate all those data sets to have more statistically valid observations and conclusions. So as we go in the insights, we make those kinds of observations, but we also go to some of the larger groups that do the analysis of their own thing and say, what have you learned looking at your own?

And so there are four or five or six groups that have a pretty robust data analysis of their own portfolio. 

Andrew Kazlow: [00:07:00] Can you share who those specifics are?

John Harbison: When I joined Tech Coast Angels, it was not one of those groups. And for the first decade it was not. When I joined in 2003, I asked the obvious question, so you guys are investing a lot.

They've always been in the top two or three groups in the country. I said, so how are you doing? The answer says, we don't know. I always thought there was a bad answer. It either meant, you don't care or you care enough to do the analysis and you didn't like the answer and you don't wanna tell anybody about it.

But I couldn't come up with a scenario. That was a good answer.

Andrew Kazlow: Yeah.

John Harbison: So after about a decade of that, I said, well, it's hard, but let me try to answer the question how we're doing. So I said, well, fortunately there was one guy before me who had tried to collect all this information it's very complicated

if you try to capture all the information you need to tell that, because all these companies go through a series of transactions and the cap table evolves, and when they have [00:08:00] different people in the cap table get different.

Andrew Kazlow: Yep.

John Harbison: It's very complicated.

Andrew Kazlow: And you don't get 

Updates and you can't find out.

John Harbison: And he was trying to capture all that and it was way too complicated. 

Andrew Kazlow: Yeah. 

John Harbison: So he got nowhere in answering the question, but he did collect information on which companies had shut down and which companies had exits, but that was where he stopped. So I picked it up there and I said, well, at that time we had about 50 exits and about the same number of shutdowns.

So I said, so for the shutdowns, we have been keeping track of how much money we collectively had put in these companies. And we knew when we had done that. And I figured out when the exit or the shutdown occurred. So for the shutdowns, I needed nothing else. It's a 0% return, it's a zero multiple. I don't need to know what the cap table look like.

You know, it's done.

Andrew Kazlow: Yep.

John Harbison: For the exits. I said, all I need to know is I need to find one investor that was in the deal. And know, asked them very specifically the question, how big was the check you wrote? And how big was the [00:09:00] check you got back? So if they said, I wrote a $25,000 check and I got $75,000 back, it was a 3x.

Andrew Kazlow: Yep. 

John Harbison: And if they wrote a $25,000 check and they got $12,500 back, it was a 0.5 x. So I got that and then I could run the new, so when I did that, at that time, it was pretty good. We had about a three or four times multiple. And the IRR was in the mid twenties. Since then, we've had other outcomes.

We're now up to about 300 outcomes on a portfolio of 560. Know it's not quite half of them being exits, but I think the number's 130, I forget the exact number, but the overall returns have actually gone up a little bit. We're up about five and a half. So if you'd invested in an equal amount in all 300 of those companies that had outcomes, you'd have 0.5 or 0.8 x back.

Andrew Kazlow: Wow. Which, which to be clear, no one investor has, but theoretically, if there was,

John Harbison: the industry 

tends to be around in the two to [00:10:00] three range. Right. 

Andrew Kazlow: Right. 

John Harbison: So that was a good number. 

Andrew Kazlow: Yeah. 

John Harbison: Uh, and, and an turnover rate of return, it was 24%, which is again, in the range of what people get as portfolios and this kind of thing.

And we, we, you know, we started to do that and then we kind of started advancing and we started to try to understand relationships and causality and other kinds of observations. So we started to make observations on things like, well, it's great to know that, but what else can I say with that? How about we look at the timing of the exits and the timing of the shutdowns?

Because it's very important to set the right kind of expectations when you go into this. And at the time when we started this kind of effort, there have been several studies be done by a guy named Rob Wiltbank who's a professor, and he was saying the, it was typically four to five years to just to have an outcome, which isn't, I think the right number.

The average is higher than that. But what's even more important than that is that in the first five years, the outcomes you do have [00:11:00] are biased towards negative outcomes because that's when you really find these companies we're not made for prime time. Yeah. And they've eventually hit walls. They can't overcome, they can't raise money, and they go out of business.

Yeah. When you get past that first five years, the majority of the outcomes tend to be exits. Whereas in the first five years, the majority tend to be the shutdowns. So that was an important message to send to people, because I was seeing people who were in, when they were joining us as a new angel investor, would say, this is different from what I'm used to.

I don't know if I'm gonna be good at this, so I'll just make two or three investments. I'll wait to see how they turn out. They don't turn out well, I'll stop. They turn out well, then I'll do some more. I said, well, if that's the philosophy, don't start. 'cause I'm gonna tell you what's gonna happen.

Of those two or three, at least two will be dead within five years and [00:12:00] maybe the other one will still be alive, but it probably won't be an exit. Yeah. And so you'll think you're really bad at this and you may not be bad at this because that one that's still alive may still become really big. So even if you'd invested in all 300 of those companies and eventually you got the 5.8 x return after five years, you just barely got above 1x.

Andrew Kazlow: Yeah. 

John Harbison: Even if you were destined to get a five or six multiple, you would think you're terrible because after five years it was only a one multiple and there's a time value and money, and my IRR is terrible and I might as well just put it in treasury bills, so part of the analysis is to do those kinds of things so we can start to communicate expectations so we get to know what people are doing.

The other part of that is the companies that exited in those first five years tend to exit at low multiples. Companies get to a certain point, some strategic acquire sees what they're doing that aren't really many revenues to [00:13:00] say, so they just buy them dirt cheap for 2 or 3x or 4x and you know, you'd never see the runup.

So the big multiples happen later on. And when I showed a chart which showed that take those exits by year from incursions and you go out into the future, you can see that the really big ones a lot of them were in the five to 10 years. Our biggest exit ever was after 15 years.

It was a 368 x. So nobody was crying about it. And the IRR was still very positive 'cause it was so big. But to get to those big multiples, it takes a long time to build a company that's a unicorn kind of a company that was a $12 billion IPO when it exited. 

Rick Timmons, who was my predecessor leading the data analytics, was doing the same things at Central Texas Angel Networks. So that's another group. And so when I would do an analysis, I'd say, Hey, Rick, can you do this with your portfolio? And we could compare, usually it was similar, so we got a [00:14:00] sense that the size of our groups was close enough to be statistically significant.

But when we pulled together, it's even more significant. The other groups that have done extensive knowledge of their growth, one is called Launchpad Ventures in Boston, and they probably have the best information because they track every single investor in a software package that they wrote and they now sell commercially on the market.

So if you're an angel and you wanna keep track of all these investments, their product's called Seraf, S-E-R-A-F, and it's not inexpensive, it's like $250 a year. But you can keep track of it. They do it for all of their members. So when you say,

Andrew Kazlow: So, just a comment on that next week we'll actually have, uh, Alicia Doxon, who runs Seraf Investor on the show.

John Harbison: Yep.

Andrew Kazlow: And she can tell us a little bit more about that. So, 

John Harbison: They're a great group of people there. They have a great track record returns, but they can answer questions down to not just at the group level, but at individual level. [00:15:00] There's one chart that they do, which we use in our presentations.

We're gonna use it again tomorrow, which looks at the diversification effect.  And like there's one chart that they do, which we use in our presentations.

We're gonna use it again tomorrow, which looks at the diversification effect. One of the things that's really important in angel investing is to understand that 10% of the exits make up 90% of the outcomes. So nobody's smart enough to know which one is the 1 in 20 that's gonna be the big home run.

So you gotta make 20 investments to have a chance at catching one of those. So typically you wanna have at least 20 or 30 in a portfolio, not necessarily for industry diversification, you just have more bets in the lottery, you know? Yeah. If you're gonna, if you think you're gonna win the lottery, buy one lottery ticket, that's probably not a good strategy.

You gotta buy a lot of 'em. Anyway, so they have a chart that says, look at every individual member, how many investments they have, and then they plot what the return on their portfolio was. And what it says is that if you are [00:16:00] doing 25 investments, you have five times the return and one fifth of the variability of returns.

Whereas if you're zero to five, it returns are all over the map. It's from losing everything to making, you know, a hundred percent return and everything in between. So as you get more, it gets more predictable what you're gonna do. So, they have done a lot of analysis that we use and we share, and we're increasingly doing other things about, exits and analysis and stuff like that.

 We're getting better at it. I get excited because we're learning stuff all the time, and the data insights that we publish are ways to kind of say, this is the new thing that somebody's come up with and you can kind of consume it once a year. We put all that together in a report, so it's convenient if people don't want to consume it in their email.

We're actually working on now, a podcast version of it. 

Andrew Kazlow: Oh, sign me up.

John Harbison: And I experimented [00:17:00] with loading these insights one at a time into Google's Notebook LM.

Andrew Kazlow: Yeah.

John Harbison: And in 10 minutes it's a podcast like we're talking, two people talking, but it's really computers talking to one another, but they're talking about whatever's in the insight.

Andrew Kazlow: Yep.

John Harbison: And when you listen to this, you have no idea that it's not a real two people who are doing it. And it's very strange. That's an example of something an ACA's gonna put out, because not everybody has time to sit and read and consume these things. Some people want to consume things in the shower or they want to do it when they're at the gym or in their car or working out or hiking or whatever.

So, we'll make that kind of thing available. One of the other products we're developing is a feature that pools all the knowledge at ACA.

So, like all the presentations have ever been made in summits, all the webinars we've ever done, every data insight we ever published, every Angel Funder Report ever done, every publication we've ever done, all that [00:18:00] stuff is in a database that AI then queries and then you can ask your own question rather than a frequently asked question of that.

So you can pose a question like, tell me the pros and cons of preferred equity versus convertible notes. And it'll give you a very cogent response in two seconds just like you would use with ChatGPT or Gemini. But it's using that very curated expertise database of all these knowledgeable people who are the experts.

Andrew Kazlow: Well, very excited about all of that. I mean, wow, you have been thinking on this topic far more deeply than almost anyone else for a long period of time. I'm really curious to hear, as you've produced these monthly

updates. As you've produced all of this annualized data, worked with multiple communities, what are some of the things that you have found to be most surprising or unexpected that decade ago or beyond when you first got into this ecosystem, you thought totally differently. Like what are the things that you, okay,

John Harbison: that's a good [00:19:00] question.

Andrew Kazlow: Been surprised by, 

John Harbison: I was trained the first 20 years of my career as a management consultant. So the way we did consulting is we develop hypotheses, and it really didn't matter whether the hypotheses are right or wrong, but it focused in on getting the data and doing the analysis to test the hypothesis, just like a scientist does it.

So, we approach the same thing here. We develop hypotheses and then we say, where can I go get the data to do that? So for instance, early on, one of my hypotheses was that there must be a wisdom of crowds effect. In this space because it's just like when you see a jellybean jar and you have 200 people guessing how many jelly beans, it's better than one person.

Andrew Kazlow: Yep. 

John Harbison: Or if you have how many people at the county fair guessing the weight of the cow, the crowd does a better job than even some expert cattle guy. And so I figured that must be true in investment. So when, I made it analysis. I looked at how much TCA put into deal. The Y axis was the [00:20:00] multiple coming out.

Mm. Expecting there would some scatter, but it would be this line that kind of went up. Yeah. Yeah. 

Andrew Kazlow: There'd be a correlation between those two. 

John Harbison: There was absolutely no correlation. It was a total shotgun blast.

Andrew Kazlow: Wow.

John Harbison: And so I said, well, you know, that's discouraging, but it's insightful. don't necessarily run off the cliff with everybody else.

And I said, but maybe there's ways of asking the question a little bit differently and getting insights out. So then I asked a little differently and I said, what if I take all those same data points and I group 'em into buckets by how many people invest, not the whole thing, but let me put 'em in five buckets.

So the ones that we invested more than a million in a deal, there were 54 of those, of the 560 that we've done. And then how many were in the 50 to 200 and how many were in the 200 to 400? And the 400? 600 so forth. Then it started to be really insightful because the category that was over a [00:21:00] million was about what our average was.

It was about five and a half. So if you get enough people in there that it's truly, wisdom of crowds that worked. If you went to the other extreme, the highest was actually 200 to 400. That was 12 x.

Andrew Kazlow: Wow.

John Harbison: And the 50 to 100 was like 7 or 8x. So those smaller ones were getting higher returns than the ones with the big ones.

The ones in the middle, we were getting like 1x. So it was like a big U when you looked at it. So then we say, okay, well why is that? We come up with hypothesis and then we go and test those. So my hypothesis right now on that is that a lot of those deals that don't end up getting a lot of investors in it are deals that inherently have more risk.

There's more uncertainty around it. There's more reasons for investors to say, that's too risky for me, I'm just gonna pass. But there are a few people that are deep [00:22:00] in an industry and understand it, and they go ahead and do it, and they do just fine but the stuff in the middle is, it's not enough to catch the true crowd effect, but you start getting people who aren't thinking that much and are getting into it that maybe they shouldn't be getting into it.

Andrew Kazlow: Yeah.

John Harbison: And so it starts being averaged up by a lot of people who don't know as much about the thing. Our most recent large exit was a 58 x and there were only two investors in it. And one, it was his very first investment. 

Andrew Kazlow: Take that one home.

John Harbison: So I talked to him, I said, so what happened?

He says, well, it was my first investment, but I came from that industry. I knew that whole thing called. I knew exactly what this company's doing. I knew what the risks were. I could talk to the entrepreneur about how are you gonna mitigate the risk? I could give him advice and counsel and mentoring to do that.

And is it a surprise that that was a success? No. So the other correlation I take just on that. So we look at a [00:23:00] problem one, wisdom of crowds. So then I take and saying, okay, I've got a new hypothesis. How about if we test whether the teams that did the due diligence had a deep expert on it, or whether a bunch of smart generalists.

I haven't tested that yet, but anecdotally, I think the answer is, that when the deep ex experts are on it and they put thumbs down, there's a reason to avoid that. And when the, the deep ex stemmed up, there's a reason to think about that versus the rest of us who may not be deeply in the industry, just saying, geez, a good presentation.

Like the entrepreneur, you know, sounds good. Let's run for it. 

Andrew Kazlow: Yeah. 

John Harbison: Those are the ones in the middle and they don't tend to go so well. So it's always peeling back the onion every time you come up with analysis and answer raises other questions, but we're getting closer to an understanding.

And what I find really exciting about it is I've been doing now this for, you know, over twenty, my first angel investment was in 1998, [00:24:00] and I'm a better investor now than I was before, but without learning from everybody else and all this analysis, I'd have to wait till I'm 180 before I actually know what I'm doing and I'm not gonna live that long.

So it's really important to learn as you go along, and it's really important to impart these learnings on the really brand new angel invest. I wish somebody's around to tell me some of these things when I was getting started. All the teams I've led in my business career, I have this thing about every time we do a deal, whether it works out or doesn't work out, we do a debrief, figure out what went right, what went wrong.

And I want the whole team to learn from that. I want the whole angel environment to learn from whatever we individually are learning and it'll just move our game up in order of magnitude. 

Andrew Kazlow: Yeah. 

John Harbison: And so I think we're never gonna get to the point where half of the investments are gonna be home runs.

Mm-hmm. But if you're the kind of VC that has one intense success, or two in 10 excess versus one intense, you're so far ahead of everybody else. So I think [00:25:00] we can improve those outcomes. I think we can have more that are not necessarily the spectacular outcome, but still good outcomes. And so I think we'll all get better and we'll do a better job.

Yeah. 

Andrew Kazlow: So John, let me ask you this, because I think there's a lot of angel groups out there that are really struggling with how do we organize our data? How do we track this stuff? It's a lot of work. It's messy, right? You talked about it. And there's a reason that there's only a few groups that are kind of leading the charge when it comes to this analysis.

And then that seems to be driven by a few key individuals like yourself, who really care and are willing to go that extra mile. Assume you're sitting down to a small angel group that is maybe made 10 investments and they are trying to organize and track and structure their data in a consistent, you know, logical way.

Like how would you coach them to take the next step? What would that step be? How would you encourage them to think about it? 

John Harbison: So there are some tools that already are made available that make that [00:26:00] easy, or relatively easy, rather than just not knowing what to do or what to capture. So, for instance, a lot of people gave thought into what are the things that ought to be captured each year?

and ACA puts that into a spreadsheet with input forms and pull down forms. So you can just use the spreadsheet, collect that information as you get it, you fill in the things, that's one way to do it. And then once a year you send it off to a CA and it gets added into the database. It's all protected proprietary and all that kind of stuff.

But that's one way. We also are just rolling out this year a software tool, an online tool that you can, again, under your own password, add that information as you go through and you can download it in Excel so you have that information. You can basically in collecting it and quite frankly, what we do at TCA and any startup group, this is what I would say to do a lot of them don't have any paid staff. They're just doing it with a bunch of volunteers, and so they don't have time [00:27:00] to do this. So for the minimum allow thing is, we have a version of this that's in Surveymonkey. Or you can use this online tool, and all you have to do is send the link to the tool or send a link to the SurveyMonkey, to your CEO and say, fill it out.

It takes you about eight minutes and usually there's enough goodwill from an entrepreneur that just got a bunch of money. They'll spend eight minutes. and that gets you going in terms of capturing. So from that, you'll start to build a base of how much we invested, as well as a lot of other criteria for those investments.

And you'll come back to that later on. The second thing you need to do is you need to track the outcomes. Now, if it's a fund, you usually figure that out, but if you're a kind of group where everybody's writing individual checks, it's a little harder to know what the outcomes are. You can obviously tell your members, if you're aware of an outcome, let me know and I'll record it.

My simple way of doing it, 'cause they're 400 members, I'm not gonna call 400 members and ask them what happened. So I have just simple spreadsheet use that, consolidate one of the fields in there [00:28:00] is the URL. So I just go down the field once a year and I click all the URLs. I see how many of the websites are dead.

If I get a 404 error, it's moves from an active into pending. And then I go and send in our communication app, it's like Slack. I say, okay, here are the ones that their URLs don't work anymore. Can somebody just tell me, did they change their name and have a different URL? Did they go out of business or did they get acquired?

And if they got acquired, let me know. So I'm gonna ask you a couple questions, like how much you got out of it. 

Andrew Kazlow: Hmm. 

John Harbison: And so I use that and sometimes there are a few that changed the name. Some said, yeah, they were closed, and sometimes nobody answers. And then I sort of assume they're all shut down. For the ones that, Then I'll just do a Google search or I ask ChatGPT, Gemini is X, Y, Z company still alive. And usually you can get the answers. So basically that's how I find the outcomes. And then when I have the outcomes, all I have to do is for the exits, fill in [00:29:00] what the multiple is, have a little spreadsheet that just, calculates the IRR and suddenly I can start reporting on my group. So it's not a tremendous amount of work to do it, but it's intimidating to get started. 

Andrew Kazlow: Yeah. I love so much about your approach to all of this is the way that you have taken what is very overwhelming and black box to a lot of investors and made it quite simple.

I mean, even back to earlier in our conversation, you talked about how your predecessor was trying but couldn't get to a finished product and you were like, let's just find out what the size of the check was that came back and then we could do the math and that's our return, simple solution in this case,

you've created a very simple solution. Track the URLs, click, click, click, click, click, and then you double click on the ones that can come back. Weird like that's so simple.

John Harbison: Yes, and there are other, you can use a tool like Seraf to do it at a group level.

Andrew Kazlow: Yeah.

John Harbison: For your fund, if you have a fund or for your individual members, you can set up some groups, um, have a group [00:30:00] license and they can include their individual members.

And so they do that and capture it that way. The downside of what I'm doing is by necessity, since I don't have visibility into the actual returns, other than the ones I've invested in, I have to make simplifying assumptions. So for instance, if the company goes public, and we've had it, 15 or so that have gone public, I don't know when they sold them.

Andrew Kazlow: Yeah. 

John Harbison: They sell it at the IPO. Did they hold it for five years, 10 years later? So you can come up with a different number. Some companies have optional exits along the way and some companies have different points of entry at different valuations. The best way is to track it for each individual investors, but I don't have the luxury of the data.

So I've had to make a simplifying assumption. And my simplifying assumption is, if I have two different returns from two people invested at different times, I just used the number that has the highest return. 

Andrew Kazlow: Oh. 

John Harbison: So that puts a positive bias, but then I offset it by all those write downs and shutdowns generate a [00:31:00] tax benefit, which I assume is zero.

'Cause again, I don't know what their tax return looks like, but it's probably they're 30% or 40% if they live in California of whatever they lost, they got back in taxes. So there's some offsets, and I think overall it's a reasonable conclusion. But the right way to really manage it is to factor all that stuff in.

Then that'll get you a truer sense of what the return is. 

Andrew Kazlow: Well, John, any final thoughts as we wrap that you would leave our listeners with as we head into the end of day two and the start of day three.

John Harbison: You know, there's a lot of groups that won't ever do the analysis, but there you can still learn from those that do. And really important to learn, and we all can continue to learn. You know, for instance, a few years ago, ACA started putting courses out and we started out with about six or eight courses.

We now have 12 courses. And they're taught by the world's expert in whatever the topic is. You know, board representation, somebody like, Ron Weissman, that you just interviewed here, [00:32:00] he teaches that course. So they're really good, strong experts. And I took all the courses after I've been doing it for 20 years, and I learn stuff in every one of those courses.

So whether you're new to it and you wanna accelerate the learning, whether you just wanna kind of refine your game, there's lots here at ACA to improve your game. And while you're doing it, you're meeting a lots of interesting people and having a lot of fun along the process.

Andrew Kazlow: Fantastic.

John Harbison: And helping the world grow. We've been talking about returns. That's part of why I do this. But a big part of what I'm doing is I wanna give back. I wanna teach these entrepreneurs my mistakes. I've been an entrepreneur, so I want them to make no mistakes. So there's the give back there.

And then the other part is in my own, in philosophy is I like companies, not just that are gonna make money, but are gonna put a dent in the world somewhere in a meaningful way. Whether they solve some medical problem or some climate change or energy use or something like that. Most of my investments in that.

So I feel good about saving lives and [00:33:00] improving lives in meaningful ways. And all of this activity, if you didn't have this activity, the main reason our economy is what it is because of all this startup activity. That's really the reason the US is ahead of other countries. 'Cause we have a more robust ecosystem.

Europe is catching up, they've got a great system and they're catching up on that, but a lot of other countries don't and they just don't have the benefit of that. And I did analysis once and I looked at the top 50 companies. At any point in time and where the growth of employment is.

And it's all from the companies that have been formed through this kind of act. And I went back to 1970 and looked at what percent of employment now is driven by the companies that have been formed for this. And it's the vast majority and all of the growth, it's all coming from those kinds of companies.

So if suddenly you don't have this stuff, we're gonna be a lot smaller country. The economy's gonna be a lot smaller. It's gonna get ugly, because the big guys [00:34:00] go through a life cycle and die. They just kinda wither away. And it's these new companies that come in and fill in and take up the slack. So all this activity really helps local economies, it helps the national economy, improves their quality of life.

All those things are good. It doesn't happen if you don't get people motivated to write the checks and get the thing going. 

Andrew Kazlow: Well, John, this has been fantastic. Thank you for joining us today and I look forward to our next conversation.

John Harbison: Well, thanks 

some good luck as you go forward to this, and thanks for doing what you do. Thanks for listening to this episode of The Diligent Observer. I'm your host, Andrew, and if you're an angel investor looking for essential angel intel in five minutes every week, I think you'd enjoy my newsletter. I send my best stuff, interesting deals, and more straight to your inbox so you never miss a thing.

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