Invest Like the Best with Patrick O'Shaughnessy - Tracy Graham - Investing in Overlooked Businesses – [Invest Like the Best, EP.206]

Episode Date: December 29, 2020

My guest today is Tracy Graham, founder and managing principal of Graham Allen Partners, a private equity firm that specializes in acquiring and building technology-enabled businesses. In our conversation we discuss how Tracy ended up playing football at Notre Dame, the key lessons he learned from famed coach Lou Holtz, why Graham Allen believes that businesses in secondary or tertiary US markets are undervalued, and why technology represents a great way to improve old businesses. I hope you enjoy my fun conversation with Tracy. For the full show notes, transcript, and links to mentioned content check out https://www.joincolossus.com/episodes/86798473/graham-investing-in-overlooked-businesses.   This episode of Invest like the Best is brought to you by Tegus. Tegus has built the most extensive primary information platform available for investors. With Tegus, you can learn everything you’d want to know about a company in an on-demand digital platform. Investors share their expert calls, allowing others to instantly access more than 10,000 calls on Square, Snowflake, or almost any company of interest. All you have to do is log in. Visit https://www.tegus.co/patrick to learn more.   This episode is brought to you by the MIT Investment Management Company (MITIMCO). MITIMCO is always on the looking for promising investment managers with the potential to compound our capital for a decade or more. If you think your firm is too small, too young, or too non-institutional, you might just be exactly what we are looking for. Check us out at https://mitimco.org/partner/ or e-mail us at  [e-mail]. Please also see our new page for emerging managers https://mitimco.org/emerging-managers/.   Invest like the Best is a property of Colossus Inc. For more episodes of Invest Like the Best go to https://www.joincolossus.com/episodes.  Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week.  Sign up here at https://www.joincolossus.com/newsletter. Follow Patrick on Twitter at @patrick_oshag Follow Colossus on Twitter at @JoinColossus   Show Notes [3:35] – [First question] – Tracy’s origin story [7:17] – Lessons from Lou Holtz [8:58] – Why Lou was so good as a leader [10:32] – His early experience as an entrepreneur [15:45] – Investing principle at Graham Allen and how it was shaped by his experience [18:41] – Types of companies they target for investment [23:09] – Defining a unique and interesting data set [27:14] – Mispricing data sets and the fools gold [29:19] – Overview of a Midwest manufacturing company [31:50] – How data is being generated in manufacturing businesses [36:57] – Data to improve marketing [41:13] – Using data to dissect distribution [45:59] – Valuation of the companies in terms of multiples they are looking at [47:31] – Business values he strongly believes in [50:54] – Significance of Kenneth Allen in the firm [52:23] – Kindest thing anyone has done for him      

This episode of Invest Like the Best is brought to you by Teegas. I started hearing about Teegas when several of my close professional investor friends sent me passages or ideas they'd found on the Teagas platform. Conducting effective primary research shouldn't take weeks. It should take hours. Searching for answers shouldn't be lengthy, cumbersome process. It should be easy and nearly immediate. Expert calls should not cost $1,000. Teaguez solves these problems and makes primary research faster and better for professional investors. Tecis has built the most extensive primary primary information platform available for all investors. With TIGIS, you can learn everything you'd want to know about a company in an on-demand digital platform. Investors share their expert calls, allowing others to

instantly access more than 10,000 calls on square, snowflake, or almost any company of interest. All you have to do is log in. Still want to do your own calls, TIGAS has a solution. Experts that are just as good or better than what you'd find on other networks for just $300 per call, not the $1,000 or more that others charge. If you're curious about Tegas, call the top performing investment manager you can think of. They're probably already a TIGA's customer, and they'll point you in the right direction because customers, myself included, love Tegas. Visit Tegas.co slash Patrick to learn more. Hey everyone, Patrick here to highlight a very unique sponsor. This week's episode is brought to you by the MIT Investment Management Company, also known as Matimco, the Endowment Office of MIT.

New and small investment funds, listen up. Matimco is looking to find investors starting funds today. Matimco is partnership-driven, long-term focused, and has an extensive history of backing investors early in their careers. These partners are key to delivering the outstanding investment returns required to support MIT's pursuit of world-class education, cutting-edge research, and groundbreaking innovation. Matimco is focused on finding and partnering with the best investors across the globe, no matter the market environment. No firm is too small, too young, or too non-institutional. If you or someone you know is currently in the process of starting a fund or recently launched, please email partner at matimco.org. Again, that's partner at MITimco.org or discover more on

their website, www.mptomco.org. Some of MIT's best partnerships have been initiated during challenging market environments. Matimco looks forward to hearing from you. Hello and welcome, everyone. I'm Patrick O'Shaughnessy and this is Invest like the Best. This show is an open-ended exploration of markets, ideas, methods, stories, and of strategies that will help you better invest both your time and your money. You can learn more and stay up to date at investorfield guide.com. Patrick O'Shaughnessy is the CEO of O'Shaughnessy asset management. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of O'Shaunacy asset management. This podcast is for informational purposes only and should not be

relied upon as a basis for investment decisions. Clients of Oshonnessy asset management may maintain positions and the securities discussed in this podcast. My guest today is Tracy Graham, founder and managing principle of Graham Allen Partners, a private equity firm that specializes in acquiring and building technology-enabled businesses. In our conversation, we discussed how Tracy ended up playing football at Notre Dame, the key lessons he learned from famed coach Lou Holtz, why Graham Allen believes that businesses in secondary or tertiary U.S. markets are undervalued, and why technology represents a great way to improve old businesses.

I hope you enjoy my fun conversation with Tracy Graham. So Tracy, it's so great to be spending this Friday talking to another Notre Dame person. I've been involved in the school lately in a bunch of different ways. And so it's been fun to see this pop up on my calendar as well. And I can't wait to talk to you about your entire background and the way that you think about business and investing. I thought it'd be neat just maybe selfishly because we share a bit of origin story in the school to hear your origin story and just hear sort of what you believe to be the major markers in your life and career that got you to where you are today. And then obviously we'll spend the majority of the conversation talking about what you see as

opportunities. Well, wonderful. Well, thanks, Patrick, for having me. First off, it is very likely that my origin story is not going to be the same as most. I'll start really early if that's okay with you. Please, yes, that's what I'm looking for. Okay, I'll start really early. So I was born and raised in the Inglewood District of Chicago. For those who are sort of seeing the current news in Chicago, you kind of get an idea of what the Englewood area of Chicago was like even 20 plus years ago when I was growing up there. So I grew up in the Inglewood District and pretty much attended a elementary school, attended this public school that in effect was, I'm going to say, 99.9% African American and there probably was one or two Hispanics that went to school with us.

So we grew up in this really hard core environment where walking to school was a bit of a challenge for us. I mean, you could sort of get into anything, just getting to school. And I was fortunate enough to have an opportunity to attend a private high school on a scholarship. You and I were talking a little bit about basketball, but I was actually a basketball player during that time. And I got a scholarship to St. Rita High School in Chicago, which is private school. That's important because it fundamentally changed my life and that really sort of became the catalyst that ultimately led to me getting involved in football, being president of my freshman class, really starting to see what I would consider to be the whole world and not sort of the part of the world that

I had grown up in as up to elementary school. So I played football and did pretty well in school, although I don't know that I had all the disciplines that I probably needed. I didn't established those in elementary school, but I did very well. Maybe it was just talent. I don't know. And I did well at St. Rita. And then very interesting part of that, Lou Holtz came to my house as a senior. I played football in Notre Dame all four years for Lou Holtz. And he came to my house on my senior year, walked through the door, put his feet up on my coffee table and basically said to my mom that he may never play football at the University of Notre Dame. But he'll get a degree and it'll be the best four-year that he makes for the next 40 years of his life. That upbringing and really the way we grew up

in the Englewood area really was a big catalyst to me sort of operating the way I operate today. And some of those things that people would not think about as assets or skills that you develop in those types of environments, intuition is an example of that. Creativity, figuring things out, Always, if you will, being aware is important. I talked about walking the school. You had to be aware. Those are things that I got a lot of reps on and in a sense have become innate. And I think they are very valuable as we evaluate companies and make decisions and figure out how to structure deals in a way that are win-wins for everyone.

I'm definitely going to come back to those points for sure. It's such an interesting take on how to think about businesses when you're evaluating them. but I can't help but ask a bit more about Coach Holtz. So in the four-year experience, I love that, four years for 40 years investment line. It's a good one. What do you remember most about, I guess, lessons taken away from the time under him as a coach?

What I remember most is what I bet if you asked, the probably thousands of players that he has coached over his lifetime, they're going to tell you, do right, do the best you can and treat other people the way you want to be treated. You're probably going to walk into their house, like you would walk into mine and see that on the walls of my children so that they understand it. There is no question that his ability to take 17-year-olds, 17 to 22-year-olds, let's say, a hundred of them, all from different walks of life, some from very low economic status.

And those, obviously, at the University of Notre Dame, you have all the way up to sort of the 1%, if you will, and get all of those people to be focused on something that's more important than themselves. Foundationalally, that's how I think about businesses. I think leaders do the same thing, and that's what I took away from Coach Holtz. And then the other thing I would say is never leaving your team. I think the University of Notre Dame, and specifically Coach Holtz continues to reach out to players, continues to be a very, very important part of our lives. And he has been for me over the last 25 years since I left Notre Dame.

In fact, as we get further into this, you'll find that my connection to Jay Jordan, who was a big catalyst in my life, my connection to Jay Jordan was a call that was made by Lou Holtz. After I graduated, he connected me with Jay Jordan. So very, very important part of my life, Coach Holtz was. What would you say is the reason he was so good at doing that? Was it just consistency of the message? Was it leading by example? This reputation he has of instilling this message is pervasive when you talk about people that played for him.

What was the secret sauce, if any, or was it just consistency of message? I think delivery is really important. The message itself was meaningful. In most cases, he simplified it. So it wasn't very complicated. I mean, obviously, you're talking to a 17-year-old. And again, a 17-year-old from Engelwood, or you could be talking to Jerome Bettis, who's an 18-year-old from the inner city of Detroit, who was one of my closest friends,

and an initial investor in my first business. But it doesn't matter where you do it. It has to be simple. and in a way that we can understand it. So I think Coach Hodes, not only the message itself is very simple, but his ability to deliver it with passion and feeling. And you really believed that he believed what he was telling you. So it was a lot easier to follow during that time.

And then on top of that, the message never changed. In fact, he once said to our team, I forget the game, but he said, you guys get to hear, I charge $40,000 or some number of that name, to hear this for 45 minutes and you guys get to hear it every day for free. So, yeah, I think that's it. It was the discipline, the consistency, and I do believe the simplification of the message so that the audience, at that time, group of players in college could understand and really internalize it. Well, you've given us the perfect segue into the next

stage of your story, which is starting a business sounds like soon out of college, where it sounds like Jerome Bettis was a part of that. I'm always saying, interested in people that straddle the operating and investing segments of the business world. So what was that early experience as an entrepreneur? Jerome Bettis, for those who do know him, and there may be some who don't, Hall of Fame running back, Pittsburgh Steelers, but he originally went to, as a rookie, went to the Los Angeles Rams. So he was one year older than I was, but we became very close friends at Notre Dame

and that friendship continued. So Jerome Bettis went to L.A., and he left Notre Dame early as a junior. and so he came back to finish up some of his degree, and I was still at Notre Dame through an enormous amount of communication, talking and staying up late at night, three in the morning, talking about things. I came up with an idea and I said, look, we got this great opportunity. I was looking at a phone book.

And on the back cover of this phone book was a lawyer, which was sort of this malpractice type of lawyer. So he had a big picture on that phone book. I called up the company and I said, how much does that cost to put a picture on the back of the phone book? They said something like $5,000 a month. Now, this is South Bend, Indiana, so I'm taking $5,000 a month. I'm 21 years old at the time. I'm thinking, man, that's highway robbery.

I can do that a lot cheaper. Right about that time, the Internet was coming out. And so I came up with an idea to start a company. And at the time, we called it Cybercom Business Directory. It was CBD Networks. And our big idea was, we're going to put the whole phone book on the internet. And we're going to build this search engine and we're going to do all of these things. But you got to understand, that was 1996.

So we quickly realized that people didn't have internet access yet. So there was no way they were going to do any searching on the internet. And those that did was accessing a 28-8 modem. So there was no way they were going to do it. But Jerome Bettis, he sort of loaned me the first $80,000 to start that business. And that was my first entry into entrepreneurship, which quickly led to me running out of money because I thought 80,000 was the world at the time. I thought I had enough money to do everything.

So six months later, the company is doing fairly well because we are now building this thing. Actually, we had pivoted already to providing internet access. So we're doing well, and that's what led me to the next phase, which was I went into Lou Holtz, who was the only other person that I knew who had money. and I asked him to invest in our company. I remember sitting in his office. He's smoking this pipe. I'm setting the time for myself that you could smoke indoors then.

I went to the back in his office and gave him my pitch. He had one year left at Notre Dame. He didn't know at the time, but we had this conversation. And he said, I absolutely thought he was going to say, yep, I'm all in. And he said, nope, Tracy, I don't invest in businesses. I'm a football coach. I do what I do and gave me the story. And he didn't beat around the bush.

So it was a pretty hard no. No way. Don't do it. But he did the next best thing. In fact, I think that one of the most important things he did was he introduced me to Jay Jordan. And Jay and I had a meeting at 6am in the Morissan, which is a hotel on campus. And Jay and I just really connected very well. About a year later, through sort of a just a courting period, getting to know one another, Jay invested. That was my first deal. It was exciting for me. I made what I thought was a lot of money, a couple of million or so selling 60% of my business to Jordan. And that was a great time for me. And obviously, again, now you've got to go back and say, you're talking about a kid from Englewood who never had anything. Mother didn't graduate from high school kind of deal, single parent, three older sisters.

It was a fundamental change in my life. And my relationship with Jay Jordan and then Chris Murphy, who's another individual who really mentored me in a way that you just don't see from people generally with kids that they don't know and sort of didn't grow up like them. We went on to do 23 or so acquisitions, build up the company, exited in 99, and that was sort of the success story of my first entrepreneurial endeavor. There were a ton of bumps and bruises and all the things I learned in that. I got a lot wrong. I had no clue what I was doing. And through all of that, Jay still stuck by me. And I would say, I got my MBA for sure during that three-year period. There are some very, very interesting stories. And part of those stories were about sellers.

And having this young kid come in and say, hey, I want to buy your business. And some of these people were obviously, most of them could have been my parents. I can't even imagine the type of things I was saying at that time, but I was learning the business and I got a deep understanding of the mid-sized businesses or lower middle market companies, how to build companies, how to integrate companies, sort of all the things you need to have today if you're going to make investments in companies that are operating in that lower middle market space. You came to market at such an interesting time, as you say, right as the internet is coming out into the world. And I'm always interested talking to people of your graduating class just because the timing is so interesting. And

the way your investing career has progressed, I think has always included technology, data, connectivity, you know, some of the things that were really exploding right as you got out of school. And so I'd love to fast forward all the way to Graham Allen and just here at a high level to begin and then we'll dig into lots of particulars. What the sort of differentiated thesis or idea is, the kind of founding principle of what you're doing at Graham Allen and how it's impacted by those early experiences. I'd say that the core thing is that, that we believe that lower middle market companies, and specifically those in secondary and tertiary markets, are generally undervalued in many cases simply because of their location or their geography.

People sort of give less of a value to those companies. And then from a technology perspective, we believe that you can get the most lift by helping those companies really start to use technology and now data. Early on, it was just technology. and today it's more data and AI and analytics, which we can talk about, that you get the most lift initially in those companies. You get the most margin expansion, the ability to grow those companies well for a lot of reasons. But generally speaking, because in those secondary markets, they don't tend to have the talent. And most are run by individuals who have been doing it for 30 years.

And so the transition or shift for them generally is pretty hard. In my early days of going out and having literally hundreds of conversations with owners of businesses because they were also our customers. So I was in a sense working and acquiring technology companies, but all those technology companies were serving lower middle market companies generally in these secondary markets. And so I got to know sort of the culture, the feeling, how they operated and how they thought about the world, why they did or didn't invest in technology. I really got to know them and feel really like connected with those businesses. So, When I finished up, so I sold my second company with Jay. So I had done two exits. All of my experience

had been a technology lens, but focused on lower middle market companies and sort of build up strategies around that. And so it was a natural for me. I had come of age, if you will, and I had made enough money. And I thought, you know what, I'm going to start my own firm. And I'm going to focus in this market that I think is sort of off the beaten path, doesn't have a lot of competition from other private equity firms. And I think there's a huge opportunity here, especially with our intimate knowledge of data and technology, having done that over the last 12 years, we thought we could make a big difference. And we've been able to do that over that time frame by focusing on this very specific geographic segment of companies.

One of the ideas I'm most interested in for the next couple of decades is what my friend Jerry Newman calls the deployment era of technology, meaning that we're going to see tons of what I'll call very traditional businesses catch up in the technology and data spheres, apply sort of best practices, if you will, just to modernize their businesses. And in doing so, significantly improve the nature or economic model of their businesses. I'd love to hear your reaction to that about sort of how big this opportunity is. And I'm interested in every aspect of this. So first and foremost, I guess I would be curious to know what kinds of companies you tend to look at that make for interesting investment targets where running this sort of modernizing playbook

is most attractive? I'll start by saying is I think it's huge. I think what you just outlined is exactly what we're going to see over the next 10 to 20 years. I really do. I think there'll be one of two things that happen. One is an opportunity. The other one is I think a big challenge for small companies in these secondary markets. The opportunity is they modernize and they leverage data and AI to improve gross margins and then spur additional investment in sales, which ultimately drives faster growth from a revenue perspective. So that's one way to do it. And then obviously, they're able to compete with some of their larger competitors. The other part of it is that their larger competitors find ways to use AI and technology that allows them to reach into the

secondary markets and compete better with some of these smaller or lower middle market companies, and they are slow to adopt or transform or too slow at transforming their businesses. So one is a challenge, and the other one is a big opportunity. So obviously, we focus our time on the big opportunity. And we think at Graham and my partners, we think we're uniquely able to help companies make that transition and improve margins, grow faster. And through that, we believe that's the alpha generation engine, which is our ability to use data and AI to help companies do that. One of the vehicles we've done extremely well on is the

back office of healthcare providers. When you look at that, it's still being done the way it was done 30 years ago, literally, except there's more regulation, more compliance, more of everything, and they haven't changed the model. So the workflow still operates the same. The opportunity there is it's highly labor-intensive, the back office part of it, is labor-intensive, and it's inefficient as well. So one of the things we've done is we acquired a company in that space, specifically focused on oncology. It was the back office of an oncology group. We have, in effect, modernized that entire process. Margins up significantly, growth up significantly, and then there's two things we're looking to do at Graham-outland partners.

The first is to use AI internally to improve the margins of the business. The second thing is figure out how we monetize some of the proprietary data that we talk about. When we get into sort of how we diligence companies and how we come up with ideas, you'll find that we talk about exclusive access to proprietary data. And I know you have a lot of people who want to talk about datasets and go into one of our ideation sessions. One of the things you'll hear is what's the real value? Is it the model or the data? Someone will say, well, if you have exclusive access to property,

proprietary data about a region, then you have a better chance of building a good model. And some people will say, well, other people can kind of recreate that. So the model is more important. So we go back and forth over what the real value is. But we really like the healthcare industry today. We love where we are in the Midwest. We like manufacturing. But specifically, the manufacturing part of it is the service and maintenance of plants and equipment within those plants. There are a lot of good, interesting companies in our area related to that. We really like the insurance brokerage business. You'll find a common theme about those companies is that in their cost of revenue, it is highly labor intensive. What they're selling is a lot of intelligence and ideas. And we think it is

those types of businesses that are going to be ripe for using better technology. Not unlike a hedge fund, right? I mean, you use technology to augment really, really smart people. I think we'll see some of the same types of things that really start to apply to your more traditional operating companies. I happen to think all of that is both true and represents a huge opportunity, but it's also quite abstract. And I would love to make it as tangible as possible for people listening. And so I'll ask a series of questions about this process. So the first would be maybe an example or two of and sort of the features of what an interesting proprietary data set looks like. how do you know when you've come across one? What are the features of that data set? How do you

underwrite a company that might have one of these things? I'd love just to hear more detail on that piece of evaluation of companies. I'll use as an example, sort of our oncology business, which is great. So the first thing we're looking for when we look at a data set is we say, look, can we get exclusive access to it? Is it proprietary in any way? And is it perishable? is the way I would think about it. When we're looking to value it, we're also saying, and if we get this data set, can we run a model or can we get insights from the data set that are that are in some ways proprietary and valuable to others? So as you can imagine in the oncology space, it's very, very expensive drugs that are being used to take care of patients, chemotherapy drugs and

other types of drugs. The use of these very expensive drugs, we were able to see what the choices that physicians were making. We have the schedule. So when you think about all the dimensions of things that we have in that data set, so we know every patient, not the names and all of that, but we know what stage of cancer, what they have, how they use it, what the effects of it have been for them, what it costs to service them, what insurance carrier they have, what their schedule is. So we use that to do forecasting. So if you have a company like Pfizer or Eli Lilly and all of those guys, what they want to know is what's the forecast of our drugs, because we know that because we have all the physician schedules that go along with that.

So we know every patient that's going to receive chemotherapy for the next, let's call it, eight weeks or so. So we use all of that information to really try to provide insight to the pharma industry, if you will, on a number of different issues. One very simple one is they just want to forecast their sales for the region. how much of their drug is going to be used in that region. So we have access to that and we have exclusive access to it because we basically have, as either clients or ownership, all of the oncology groups in the region that are there.

So we have probably about, I would say, 80% of the region's chemotherapy is sort of running through our database. So that's a proprietary data set. Valuing that data set, really it's hard. I mean, at the end of the day, I can tell you there's no secret sauce to valuing it. what you're trying to figure out is how much margin expansion you think you can get as a result of having access to the data. And you're really running some very complicated models to try to determine that. Now, generally speaking, in the lower middle market space, there's very little value by the seller that's put on data because they don't use it. We're just at that stage. Now, Patrick, that'll change

over the next five years. People will start to understand the value. of data. I generally think, in fact, I've never walked into a lower middle market company and said, can we talk to your data scientists and that company say to me, yeah, he's in this office over here or there. Generally, they don't have data scientists. So they haven't really explored data and how you might use that data. The first use case I gave you really focused on how a third party might use that data. That's one of the things we did. Another use case for them is they really want to benchmark their sales. So you give them the forecast, but they also want to know when they don't choose their drug, what drug they did choose. And they want to know that. And they want to get that

information in almost real time so that they can go out and talk to doctors and really educate them more on the efficacy of their drugs. So that's an external use of the data set that we use. There's a lot of pieces of this that are interesting. Maybe the first is the opportunity is to miss pricing because the data sets are valuable in general but aren't valued by the sellers of the businesses. So it's almost like you're getting a free option or something inside the business that you're buying that you can then go control the outcome around. What are like examples of what I'll call fools gold, which is something that it looks like might have this feature, some internal data set that you look at and for whatever reasons figure out is not as attractive

as you thought it might be at first glance? I would say anything that we see on the clinical side of health care has been either, I don't know that I would classify it as fools goal, but what I will say is that it's so damn hard to do that we haven't been able to crack that. And on top of it being hard, the level of accuracy that the model has to have is so high that even if you're on the administrative side of health care, sort of the back office cost side, if we're at 90%, we're competing with 60%. The clinical side of it, if you're at 90%, it's worthless.

When we think of that, our original thoughts were, man, this would be great if we could sort of help make some of the decisions around care using AI and algorithms, that has been, in a sense, fool's goal. That is not something that has been, certainly in the current state, reachable. That's what comes to mind for me. right away as you think about parts of the data set that we thought were really, really valuable and has turned out to be too big of a lift for us to get at. Others in manufacturing also exists where you think, man, I have all this data and I have a lot of this really, really valuable thing because I have it. But if you don't have creativity and a business model to

wrap around it and you haven't found anything very interesting in the data, it's really difficult, very different between having data and insights. As you, you know, you're not. You're you know, real insights are hard to come by. I don't know a whole lot about the manufacturing world. What does a secondary or tertiary Midwestern manufacturing company look like? And I'm interested in like crazy specific. Are they producing X units of some widget? What is the, it could be a real example or sort of like a blended one. What does one of these businesses look like? There are really a tale of two types of manufacturing companies in the Midwest. There are now some very large manufacturing organizations in that space in the RV recreational vehicle space,

which we are literally 20 minutes away from. So in that scenario, there are, in many cases, 100 plants that they are operating and they are building various types of things from levelers and jacks and to bike racks. Literally everything is being manufactured in those. And those are typically very large. But what I would say, the majority of them are going to be someone who's making one or two products or really one core product and then a few variations off of that product. They are two plants maximum, one to two plants. They're going to be somewhere between $50 million and $100 million in revenue, somewhere between you're probably $5 and $15 million and EBITDA. We have a very interesting example that we would use and they make a, I won't say

their name because they're a good prospect for us. But they make a very unique product. They've been making it for 15 years. They sell to U-Haul and a number of different companies. They do about 25 percent, EBITA margins. One plant, in this case, about $35 million a year in revenue. Very, very good, strong company, been running for a long, long time, family-owned, and passed down to the children who are now running it and doing a phenomenal job of doing it, but they want to grow. So that's a great opportunity. They see opportunity out there to grow, and they need support and help in doing that. And so we see a huge opportunity at working with those types of companies. But that's the typical company. That is the typical company, a traditional manufacturing,

one, two products, one or two plants, again, $50 million in revenue, a lot of opportunity to scale, but haven't had the scale mindset. Those are opportunities for us, obviously, to come in and help them grow and use technology to make their businesses better. And I can give you a little bit more detail, but that's the general profile of a manufacturing company in the Midwest. The additional detail that I think would be really interesting is the data piece now. So it's funny, like manufacturing businesses are almost like the scaled up lemonade

stand that we all use to describe businesses. Like, they're pretty easy to understand. They produce something and sell it. versus some more complicated stuff. So I'm curious for something like that, how is data being generated, produced, or captured in a manufacturing business where I would assume part of their improvement over the years has been like process efficiency. Like they do a pretty good job in the actual physical manufacturing process of building the thing.

How then is data, you know, a byproduct of that process that you guys can then sink your teeth into? And how might you use data in a plant like that to make either the process or the business model better? This goes a little bit to what we've done, but also how I think the world will change for manufacturing in general. I think the customer experience, the use of their product is a big part of how you use data to improve in a manufacturing space. Engineers use a lot of data. One of our big customers at one of our portfolio companies is Whirlpool. A lot of learning, I mean, that's been five, almost six years now that we've been working with them. Some of those same disciplines that apply or sort of use cases for,

for analytics that they would use in improving the engineering of their product, really putting sensors on products and things of that nature, collecting data about their product as is out in the field. Those are the types of things. That's the kind of data that they are now collecting, but then have trouble in some case making useful and unlocking the value of that data. But those that do it well, I don't put the lower middle market manufacturers in this category because they don't do it well today. But some of the use cases that we look at around that is collecting data on the use of a product in the field and having that data, analyzing that data in a way that engineers would have the ability to improve that product.

There's a lot of opportunity around the supply chain management of that. It's really not something that's done very well in your lower middle market or smaller manufacturing plants. It'd be scary to you if you saw how it actually works today. Very little data, highly manual. A lot of people in backroom. In many cases, not so many people, which is actually worse, because they have a receptionist who might be doing all the billing and then also turn it around and getting all the invoice in and negotiating pricing and all of that kind of thing. So where we look at data in that perspective is, and I got to be clear here, in most cases, in the smaller manufacturing world, it's a heavy lift in the sense of getting the capability to bring all the data in. So whether you got to put sensors on

products, whether you're connecting to all their suppliers and getting access to those data sources, those are the types of things that you have to do to get the data and then bring it all together. And obviously, you know the process of cleaning and labeling and doing all the things you need to do that data. So in manufacturing, the primary use cases, and this is still being developed, I don't think anybody has the answer here. So I'll start with that. No one has the answer.

But where we think the opportunities are for manufacturing specifically is improving, the quality of the product, improving the customer experience or customer service. Many of them have call centers that they are supporting. They're collecting a ton of data there. Those are the types of use cases that we are looking at as it relates to manufacturing. But that's one where we see opportunity in the future. My vision of the manufacturing space is that when I see a plant, what I see is a big data center with a bunch of machines in it. And today, you need a lot of people in that data center in that plant to do a lot of the work. Ultimately, we will have sensors and things on that, on each of those machines,

and a lot of that will be obviously automated, in my view. There are a number of companies today that are really interesting to us that are not direct manufacturers, but they support the manufacturing industry. And those are your maintenance companies, the people who make, it's a pretty good business where they go in. The manufacturer has outsourced the servicing of all of their machines. The data play there, of course, is that, today, it's a high cost of people cost to do that. And ultimately, as those machines are outfitted with connectivity to Wi-Fi and obviously given us the ability to collect all the data off of those machines, we can be far more efficient in servicing those machines and understanding which

machines need something as simple as oil, as an example during the maintenance period, how often those machines can be used. So that today is highly inefficient. It shouldn't be that way. But you need data to be able to answer those questions. And when you start talking about, especially on the larger manufacturer side, when you start talking about hundreds of plants, you're talking about thousands of machines and they have to support those machines. So the maintenance companies are out there doing that. That's one we're looking at. I would say we haven't done a deal in that area yet, but we really think there's some opportunity. The financial sort of profile of those companies looks really, really promising. Pretty much everything we've talked about so far is related to, I'll call it

product, process or product, using data to improve those things, the experience, the product itself, how it fits. We haven't talked much about marketing or distribution. Can you say a bit about your experience using data there for these sorts of these lower middle market, tier two, tier three businesses or tertiary businesses? So there's two very interesting things. And one I've been playing with. So I run it by you. And it's an interesting conversation that many of the listeners might look at. And it gets directly at this software. question and sort of the distribution and sort of the future of how software will work and how it'll change. And the other one now asks your question directly, which is sort of how we've

used it in marketing to help sort of expand these companies. Generally speaking today, I think where technology is, where the AI and sort of all this is related to marketing, it's basically everybody's doing the same thing, it's trying to help you target customers better. I think that's been a big win for us that we've been able to improve sort of our marketing efficiency. or the marketing efficiency of some of these companies. But really, that's just been at the level of really having access to clean data and having a better understanding of your customer. And that's been important.

The biggest lift, I think, we've gotten from that related to customers directly is really being able to determine where we were making our net income. We think about customers. Most people operate at a gross, when they're evaluating this company, they operated a gross margin level or gross profit level, and not a net income level by customer. We get aggregated data with that. And so what we've been able to do in many cases

is really get a better understanding of the profitability of each one of our customers at the net income level. And the only way to do that is to really break out this aggregated data and get what we call transaction level, a transaction level understanding of the profitability of each of your customers.

So one example is, when we go into a process, company. We own a fairly large part of our company as a managed services company that does sort of IT for a number of different companies in the area. And one of the things we found is if you just look at a list of products or service or what you're selling to that company, what you'll find is two or three companies, 10 companies, all with the same service. So we all have the exact same thing. They're all paying the same price, except one of those companies calls your call center 50 times. And the other one calls two times. You're spending.

a significant amount of money to support that customer, and generally, in small businesses, now in larger companies, maybe they have this capability, but if you're not looking at your data by call at the transaction level by customer, really looking at it that way, you might not understand. Your gross margin is going to be the same, because the service itself, you're providing, let's say, some managed security service, or it's going to be the same. But your cost related to just your billing, support, all of those things, they've very drastically by customer. That typically doesn't go into a pricing model or have any kind of pricing strategy for companies of the size that we're discussing. And so really getting access to

transaction level data is an example of how we would use data around customers and how we either market better to those customers, how we structure our client's success organization around those customers because we have your profit drivers, which are the ones you want to spend the most of your time with, you have your profit drains and then your profit drags. And so in each one of those areas, there's a large group of your customers that are likely dragging your margin, your overall net income down, that you're treating the same as all the other customers. So I think the way AI plays a role as it relates to customers is allowing you to look at each customer individually, and that's virtually impossible if you're going to have human doing all the

analysis. Building that kind of capability into your data platform is a far better way, far more efficient, and actually far more effective way to get at customers from a direct perspective around customers. From a distribution perspective, that's a very interesting question, and I have a lot of thoughts on that today, because I've kind of tried to dissect the distribution network of software today and with Snowflake coming out and doing so well, it's another opportunity for me to look closer at how software is delivered today. And is that the right model and how it works? So as you think about distribution, it is sort of my understanding and research that says that today your traditional Silicon Valley company building software

would say, we build great software in the valley and you probably need to be here. That's where all the talent is. Or there are a few other hubs that you can sort of build. from, but that's the primary hub and we built, and I would equate them to sort of being the OEM, if you will, if this were the manufacturing world, it'd be the OEM or maybe the automakers of Detroit is another great example of that. The go-to-market strategy or distribution strategy is generally that for our largest customers, we are going to have a direct sales force. And then for every other customers, we're going to build a channel partner program, and we're going to go out and effectively, we're going to sell software through.

managed service providers. A great example of that is Salesforce would do that in some respects. And typically what happens is you sell software and if it's certainly enterprise software, it needs to be customized in some way. You hire this managed service provider. And so the customer gets a bill from, let's say, Salesforce and then they also get a bill from the managed service provider for doing the installation, implementation, and all of that. The question really is for us, and we've started to buy really interesting sector we love is the managed service provider groups that really control the distribution of software into secondary markets. I mean, I will tell you, in our region, we have never seen anyone from Amazon come to sell

technology, Salesforce, or any of those companies. There's always a middle person, middleman, who is in that business. We're exploring this, but we really like this industry. Do we control distribution of software specifically into this very targeted customer segment? Do you control the distribution of some of the more common, software, security applications, data warehousing applications, the analytics type applications, do we control that by controlling some of the distribution through the managed service providers? The mobile phone market, where most people typically decided to sell it through Best Buy years

ago, and Apple decided, look, we're going to build our own Apple stores, we're going to sell it direct. Another one, I think, I still need to do a little homework on this one, but Tesla, where they said, look, we're not going to have a bunch of dealers out there that are really selling it. we want to control the customer experience from end to end. It's a different model. The question really becomes, is tooling what customers really want? Or is it the service that they want? Do they really want another tool, another software tool, that they have to now go out and try to hire a team of people, which are really scarce in these secondary markets, or pay a managed service provider, which is very hard to do when you're talking analytics, is that the delivery or

distribution model that will win out in the long run. We tend to believe, and we're still confirming a lot of this, that there is a real opportunity if you are able to develop really strong products, but focus those products, not just on selling them sort of as tools for other people to use, because they don't have data sciences, they don't have data engineers, and those level of talent that you need to do it, or is it better to just sell those full service? They're still paying for the software, but to sell it full service and not have a managed service person in the middle, really, that's increasing the cost to the customer. It's those types of things that I'm really thinking about.

And we just asked a simple question, is that the way it ought to be? Should it be delivered that way? Is it really in the best interest of the customer that you sell them another tool? I often question people, again, would love to hear your thoughts on it about, I think software is one of the most underutilized assets on the balance sheet. You buy software. with all these tools, you pay for all these tools. And typically, what we find is companies use 10, 20% of the capabilities of the software, but they pay for 100% of it. Is that really the model that is ultimately the model that's going to win out? Anyway, when we talk about distribution, that's some of the things we're thinking about. And when we think about distribution for

software and technology in general, I think it's a different model than selling to your Fortune 500 or your fortune, really your Fortune 5,000 who are going to have technical capabilities and people on staff who can really get the best out of this software. I just couldn't agree more that it represents a big opportunity. Part of that too is, I think price, which we haven't talked about yet. With software companies in public markets, you mentioned Snowflake, which by any measure is an unbelievable business, but also by any measure trading at an astronomical price in terms of, you know, multiple of its revenue. I cannot help but ask the question about median valuation or whatever metric you want to use of the sorts of businesses that you're talking about. We could use that

canonical manufacturing business that you mentioned earlier. What are the sorts of multiples sales or EBITDA or whatever that these things tend to transact at today? I would say generally we pay somewhere in the eight times LTM and then it's going to be six and a half times forward. And that's a general statement, but I can tell you that we typically don't pay greater than eight times. It can creep up a little bit. Obviously, each deal is looked at independent. And so I'm giving sort of rule of thumb that we like to be somewhere in the eight times EBITDA and then, and having that really pro forma out to about six and a half, maybe seven times. And that's of EBITDA, of course. So some reasonable multiple of sales. What is so interesting here is just that you're talking about a lot of the same things that

will drive value outcomes using technology, et cetera. Sometimes building technology, it sounds like building models, building data models, but with an entry price that just provides more air cover because you've got something already producing cash. And you've had so much wide variety of interesting experience that sort of straddles these two, the very modern world and the very traditional business world. I would love to just hear any riffs or thoughts on major business or professional conduct principles that you've gleaned from all this variety of experience, the things that you believe

most strongly about doing business in the right way? I would have to go back to the foundation of just doing right, doing the best you can and treating other people the way you want to be treated. Because of what people might consider having some success in business world and certainly from my upbringing, there's a lot of sort of praise, if you will, that has come my way. But nothing's more important to me than to say that the people who did business with me, years ago when I started, Shannon Raleigh still do business with me today. Notre Dame was a customer of mine in my very, very first business.

And Notre Dame is an investor, a partner today in some of our businesses. And many of the other customers, some of our really closest people, have continued to do, and continued to work with us over a long period of time. When you think about doing business the right way and really what determines that, everybody can talk about it, I think. But ultimately, if you don't do business the right way, even if you talk a good game, people stop doing business with you. So I've been around long enough for people to really get to know who I am. So some of those business principles, I talk, maybe my team would probably say, I don't want to hear him say it anymore. I often say,

it's easy to do business with someone when things are going your way or to make the easy decision. It's easy when it's going your way. So if you have a huge profit, everything's working out the way you want it to work out, then it's easy to make decisions. But the business lesson for me is you really know what people are all about when decisions get tough, already going to do the right thing. So some of the lessons we talk about is you never have to call me or ask me what to do because I just want you to do the right thing. And 95% of the time, I think people know what the right thing is to do. When you think about those lessons of business, it's weird because my, most important business lessons I didn't get from business at all. I got from Lou Holtz and I got from

Notre Dame and some of those very basic things that do right, do the best you can, treat other people the way you want to be treated. And if we do those things in our company, then in every way, governance, conflict of interest, any of the things that all of those things arise, all of them. They come up and if you're in business long enough, they will come up. And how you deal with them is the most important thing. And so you have to be foundationally sound, in my view, in order to get it right most of the time. And I think we've been able to get it right most of the time. Again, I'll talk about it where I started. Lou Holtz was able to make it simple. Don't complicate it. It doesn't have to be something that sounds profound. It has to be digestible by a lot of people who all have various backgrounds

and understandings. So you have to simplify it so that you all can rally. around a set of core principles. That's what we've been able to do. If you think about what I learned from business in the area of in that way, again, as I say, I didn't actually learn it from business. Would you be willing to discuss who Allen is in the Graham Allen partners? Absolutely. Absolutely. Kenneth Allen is a childhood friend of mine that I named the company after because after a sort of growing up knowing him since I was five or six years old, being in class together all through elementary school. And then when we, in Chicago, I don't know if everybody does,

but you graduate, if you will, from elementary school. And we graduated from eighth grade. Very interesting story. You had to take an interest exam to go to St. Rita High School. And the interest exam was $20 or something. That $20, Kenneth Allen and I both go back to our moms. And none of our families were wealthy, of course. And my mother gave me the $20.

I'd go take the exam. His mother said, look, there's all these public schools. is here. We're not paying for you to go to school. She did not give him the money to do it. He did not go to St. Rita. Over the next four years, our lives started to drift apart and turned very, very different. At the end of the day, he was killed right before when I was coming to Notre Dame in April of 1991. I reported to camp in August. He was killed in April of 1991. And it was very tough time for me, given the intense relationship that we had had. And when I got out and I said, I'm going to start my own company, I wanted to really

never forget him. There is no living Alan. It's Kenneth Allen, who was a childhood friend in mind. It's an incredible story. And it's an interesting bookend to our discussion of your own story, which is just so fascinating in so many different ways. And I'm excited to ask my traditional closing question to you, specifically, which is to ask what the kindest thing that anyone's ever done for you is.

Man, that's a great one. So as I've talked to you about since we started talking, I've been very fortunate. I'm not going to say my mom because I will tell you that in my view, she's a saint, but I won't say anything about my mom, which literally she is top of the list. But I talk to you about Chris Murphy and J. Jordan. Both of those two have done things that are so kind to me and really change the trajectory of my thinking, which then ultimately has led to career and life and has changed my family. I got a meeting with Chris Murphy very early in my career. It was the first time we would ever meet. He is the chairman of First Source Bank, which is a regional publicly traded bank here in South Bend. He agreed to a meeting. It was a Friday, and the meeting was scheduled at two.

Again, I knew nothing. I knew nothing about business. I was really just pretty green. I was that earliest stage. I'm probably 22, 23 years old. And I go into his office and immediately he says, hey, I can't do this meeting right now. I got to go. I have waited for a long time to get this meeting. He said, what are you doing right now? And I said, I'm doing nothing. I had this meeting schedule. We got on his plane and we flew to Naples, Florida. And I spent seven days with him and his family. Now, we had never met before this meeting. During that seven days, I also met another guy, Basil Sellers from Australia, who's a very successful guy. And I got seven days of what I think, was the best lessons that I could ever get.

It was so kind. He was so kind. His family was so kind. And that relationship has lasted now for nearly 25 years we're going on. That was the kindest thing. And then Jay Jordan did a very similar thing. We went to the Hamptons. I will tell you that it changed my life in ways that I never thought about at the time.

And I think it's a metaphor for just giving a kid access and letting them see the world differently than they've ever seen the world and the impact that it could make on a kid just being able to see it, being able to see Naples floors. For me, that was a big deal. Today, I've been in Naples many times, but back then, I had never been to a place like that, and certainly not the Hamptons, and just giving me that exposure. I think my family would say was one of the nicest things that they've ever did because I think it changed generations of my family, just having that. That's the nicest thing. That's a long story. But it's near and dear to me and both those people continue to be very important people in my life.

And they might say, I've done 50 of those nice things for you, Tracy. Just me, I could hear Jay answering that question. It would be fun to hear them answer the question. Well, this has been so fun. I think what you're doing is unique and very much of the times. And I think it represents how many opportunities there can be in little corners of the world. So I've really enjoyed learning about the process and the firm. It's been great meeting you personally today.

really appreciate your time, Tracy. Absolutely. And I'm involved in Notre Dame quite a bit as well. If you come down, I'd love to take you out to one of our fascinating restaurants here in South Bend. That, you know, I will take you up on. As long as there's a basketball game or something like that on the other side of it, I'm in. All right. Absolutely.

We'll make it happen. Take care, Tracy. Have a great weekend. Hey, thank you. If you enjoyed this episode, you can sign up for a new email newsletter sent out each week called Inside the episode. Each week, I condensed that week's episode to my favorite big ideas, quotations, and more. I've been recommending books to members of this email list for years, and we'll keep doing so in this weekly email. You can sign up at investorfieldguide.com forward slash book club.