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The quest for “holy compounders” | EP101

January 26, 2022 Print

Our systematic assessment framework to narrow the probabilities in analysing fast-growing technology companies in an effort to improve our odds of identifying those elusive “holy compounders.”


  • What do we mean by “compounder,” and how is that different from a “steady company?”
  • Michael Mauboussin, M&A compounders, and the Mawer Lab—the origins
  • First framework element: our checklist for addressing the total addressable market (TAM) with some examples – Amazon, Alphabet, VMWare, Shopify, Uber, Microsoft, AWS, Adyen, Square
    • Incremental versus current market share
    • Scalability
    • Elasticity of demand
    • Value creation
  • Why trying to account for costs with tech companies gets muddled, and why reclassifying expenses is necessary when assessing both real returns and return potential – e.g., Amazon and Rob’s lemonade stand
  • How moat can help answer whether a compounder might sustain its growth and those high returns over time – e.g., Google, Elastic
    • Bonus: common types of moats in the tech industry; the classic platforms versus tools dichotomy; and why Justin gets a bit irked at the word, “intangible”


A transcript of this episode is available below, modified for a more enjoyable reading experience. For more posts exploring the ideas we talk about in the episode, check out our Related Reads links.

Your Host
Rob Campbell 113 Web 2022

Rob CampbellCFA

Institutional Portfolio Manager

Rob Campbell is an institutional portfolio manager at Mawer Investment Management Ltd., which he joined in 2016. He is responsible for the management and servicing of institutional clients and their portfolios.

Prior to joining Mawer, Mr. Campbell was an investment product specialist with MFS Investment Management, where he communicated investment policy, strategy and positioning; performed portfolio analysis; and led product development.

Mr. Campbell received a Bachelor of Arts in economics from Harvard University. He is a Chartered Financial Analyst (CFA) charterholder with investment experience since 2009.

He is a member of the CFA Institute and CFA Society Toronto. He is also a Canadian Ski Instructor’s’ Alliance (CSIA) Level 4 instructor.


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Rob Campbell:


Justin Anderson's back on the podcast this week to take us on a Monty Python themed quest—“The Quest for the Holy Compounders.”



And Justin, before we get started—we should note for those who are reading the transcript of this podcast, that we apologize for any faults; those who are responsible “have been sacked!” Let's jump in. What is this quest, what are holy compounders, and why are they important?

Justin Anderson:


Well, that's quite the introduction, Rob. So yeah, let me try with a straight face take on that question. So, what is the quest? We use this language of the holy compounder because the nature of the Holy Grail—which is obviously a play on Monty Python and the search for the Holy Grail—is that it's a very elusive target. It's a very difficult thing to find. And that's the way that we look at compounders.



Now, let's take a step back and just define what we mean by “compounder.” In investing, you're trying to put together a package of stocks into your portfolio. One of the sort of…most “sought after” let's say, components of that portfolio would be stocks, which are able to achieve high returns, and to achieve that over a long period of time and to continuously compound the value of the stock.



So, when we're talking about looking for these compounders, it's really hunting for these high return investments that are, due to the nature of the investment, able to maintain high returns over a long period of time, which translates into very high returns for investors.

Rob Campbell:


Elusive in the sense that it's hard to identify these ahead of time, is that right?

Justin Anderson:


I guess…because the nature of, let's say, capitalism and these kinds of stocks, is they're achieving a high return. And typically what happens when you're fetching a high return is you attract a lot of competition to chase after those returns. You're making a lot of money; and other people see that and they start companies and others move into your industry.

Justin Anderson:


And they start to bid down the pricing, for example, so that oftentimes the consumer will capture all the gains from the competition. Or, it'll turn out that they're not able to capture as much of the market as they grow it. Other players come in and take a piece of the market.



And so let's say 99 times out of 100 the base rate scenario is that competition moves in—even though a company at first had a high return—and fairly quickly over time, degrades the returns, degrades the amount of penetration into the market that that company can achieve, And therefore, it ceases to be a compounder and becomes more of a steady company.



It's the nature of capitalism and competition that makes them so elusive, defined as—you need to find that rare gem that has got a very strong moat and characteristics that are able to sustain its compounding and sustain its returns, despite competitors trying to move in on it.

Rob Campbell:


I presume it's pretty self-explanatory for why this quest is worthwhile. If you're able to identify these compounders and hold them, that's great stocks to hold in your portfolio. Do you have a sense for—however you're defining these compounders—do you have a sense for how important they've been either for market returns in general over the past few decades, or to maybe some of the portfolios that you work with at Mawer?

Justin Anderson:


This is actually one of the reasons we've been kind of talking about this trend is we run this process in our Lab. And just for the listeners, a reminder [that] The Lab is a technology group that's sort of appended to our Research team. And that group is specifically tasked to try to improve our processes using technology; make us be able to look at stocks better, faster than we would be able to without using technology. So, that's kind of the core function of The Lab.



The Lab also helps us to do scuttlebutt, which is sort of digging deeper and looking at alternative sources when trying to understand the competitive advantage of our technology investments. So that's just a little quick introduction into what The Lab is.



One of the processes that The Lab runs is an annual process, we call it “Project Moneyball,” which is a play on the Oakland A's and the statistical process that baseball team used to try to identify talent.

Justin Anderson:


We run this Moneyball process on our portfolios annually to really try to assess, okay, “Where did the returns come from? Which investments were the key investments made that year?” And that process really has uncovered this concept [of] the compounders—the compounding investments that we've made in the past. And some of the highlights would be companies like Constellation Software, which buys smaller software companies and puts them together into kind of a holdco structure; Paladin Labs; CCL [Industries]. A lot of these tech companies, we would classify them as compounders. And a lot of the value that we created in our portfolios for clients really was derived from these kind of compounding companies.



So the learning was, "Hey, this is a really important piece, these compounders." We know in hindsight that they're incredibly important for the value that we got in our portfolios, but is there a framework, is there a process that we can set up to try to more systematically root these out and discover them kind of going forward? That was kind of the genesis of why we thought that looking deeper into these compounders and trying to build a structure around that, why we got attracted to that.

Rob Campbell:


Before we dive into the framework, Peter Lynch has the concept of the tenbaggers. And is that the same thing? Tenbaggers and compounders? Am I thinking about those the same? I mean, a lot of the stocks that Peter Lynch would've identified as compounders were actually pretty straightforward businesses.

Justin Anderson:


I think you're playing around in the same neck of the woods. I mean, a lot of the words that we use are similar in concept. Why is the moat so critical? The moat sounds like an abstract concept. Okay, it keeps your competitors at bay, but you can start to articulate why exactly that's important because what it does is it lets you sustain those high returns and lets you penetrate deep into your market. It's tying a lot of concepts that we had out there into one.



I think another thinker that we've really leaned a lot on for this framework, is a gentleman named Michael Mauboussin. He publishes a lot of content on leveraging data similar to what The Lab does, but to try to figure out different themes and investment styles. And yeah, he also speaks a lot about some of the themes we talk about such as investing through the income statement, and the moats, and how to analyze those. So yeah, we definitely certainly haven't come up with this in a vacuum. It's been something that lots of different thinkers have a contribution to.

Rob Campbell:


Okay, great. And then just last one before the framework—are there different types of compounders? I know you mentioned Constellation [Software], Paladin Labs…I know just those are businesses that were built mainly through M&A. Is that mainly what you're speaking of when you talk about these “holy compounders?”

Justin Anderson:


Great point. So, one of the themes that we came with this framework is historically, Mawer our company, has found a lot of success in what we classify as, “M&A compounders.” So, as we talked about Constellation Software, Paladin, CCL, those would be companies that were very successful at compounding by finding a kind of a repeatable M&A investing style that they were able to repeat for many years and compound value that way.



And there's a new class. I guess it's been around for a while, but it's becoming a much more significant piece of the compounding pie if you will, which is [what we call] “organic compounders.” And so these would be businesses that Mawer has had less track record with because they're relatively new; they tend to be much more technology focused. But we definitely have made some investments in them, but [they] tend to be a little bit different.



Some of the example companies that we use in the organic compounding side of things—a classic example is Adyen, which is a payment processing company out of the Netherlands. And the reason we classify them as organic is they're achieving the very high growth rates on the order of 30% to 40% annually. But they're doing it without buying other companies, they're doing it organically. They're just doing it by growing their own business internally. So, that would be what makes them organic: they're fetching that similar kind of high growth that we would see on the M&A side, but they're doing it purely through internal investment and organic growth.

Rob Campbell:


Organic compounders may be being a little bit newer, more technology focused…we recognize that compounders historically speaking have been important with respect to driving portfolio returns, so would be great to be able to identify them early.



But of course, when we mention technology, we talk about high valuations as well. So, I gather that part of the framework is trying to identify what are businesses that have really strong potential to be compounders and separating them from technology companies where the longevity of that compounding is…you're just paying for way more than you're actually going to get. That's I guess the point of the framework.

Justin Anderson:


It's a really important problem that you're articulating there, because the trouble is these kinds of high growth technology companies are becoming a much, much bigger piece of the benchmarks and the investible universe that we look at.



So there's so much of this high growth technology. And how do you distinguish between them? They tend to fetch a very similar or comparable valuation. If you're high growth and if you're in tech, you're trading at a very high multiple. And it's our contention that a tiny subset of them, even though they might be trading at a similar multiple as the rest, are actually in that kind of organic compound or zone. Whereas a lot of them just don't have those features.



So there's this interesting situation we find ourselves in the market today of, just a wide space of stocks that fit this… sort of high growth tech. And asset allocators are asking themselves, "What the heck do we do with this?" A lot of them are just throwing their hands up and saying, "This is just too crazy, these valuations. How are we going to make sense of this?"



And so one of the things that I hope listeners can get out of this is just I think there is a way to try to make sense of it, there's a kind of a systematic framework that you can use to go through this huge space and try to find the much more compelling investments.

Rob Campbell:


Awesome. Well, let's get into it. What's the first element in the framework?

Justin Anderson:


The first piece of it is we call it, “total addressable market” or TAM for short. If you drop the word TAM inside of Mawer, or with many money managers, you might start a fight. And the reason for that is TAM is—

Rob Campbell:


Dirty word in some quarters?

Justin Anderson:


It's a completely un-auditable number, it can be a made up number. There's really no way to make it credible in the eyes of an investor ("Okay, well what is the actual TAM?") So, that's very different than say, a growth rate, which you can actually look back and say, "Okay, the company grew at 30%. It is what it is."

Justin Anderson:


Whereas TAM is very forward looking. I think that's traditionally why a lot of folks kind of get a little defensive when they hear that word.



I think the reason why we decided to go with that in the framework, as opposed to say, growth, is that it does have this element of forward-looking-ness to it, which is obviously a weakness, but it's also a strength. Because when you're looking at growth, you really are trying to think of sustainable growth. What's the company that's going to be able to continue to grow for many years? And that, whether you call it sustainable growth or TAM—I mean it's all just semantics at the end of the day. You're just looking for a business that can grow for many years. That's different than just saying, "Okay, they've grown a lot in the past."



A good example we might use is say, Alphabet and Amazon. Contrast that to VMware. Which… [these] are three companies that, after when they were earning about $150 million each in revenue at different time periods, if you kind of stacked them all up at $150 million revenue but then you did a TAM analysis, you'd get a very different answer for Alphabet and Amazon than you would for VMware, which had a well-defined market of virtualizing servers.



And you could actually say, "Okay, this is how much that market can really grow. And it's a tiny fraction of what, say, the search industry or the global retail could grow." So that would give you a very different opportunity set or TAM, which would be much more attractive in the case of, say, Alphabet and Amazon in the early days.

Rob Campbell:


Just so I understand that right—basically you're saying that those three companies when they were deriving similar amounts of revenue, they were all growing at the same rate, just the ability for Amazon and Alphabet to continue growing for many, many years at that rate was much longer than the TAM or the total addressable market that VMware had?

Justin Anderson:


Exactly. If you asked yourself at that point when they were earning the similar number and they were growing at a similar historical rate, you could say, "Okay, well what's the industry that they're penetrating into?" That kind of analysis would lead you to conclude that Alphabet and Amazon should theoretically be able to grow sustainably for longer than VMware.

Justin Anderson:


You had asked [for] the first point in the framework, so, what I'll do is I'll just go through and kind of lay out some of the things we look for in TAM. So, let's say you were back in that time, you were looking at Amazon, Alphabet, versus, what are some of the characteristics that you'd be looking for to try to identify bigger TAMs versus smaller TAMs?



And we kind of have four steps to the checklist here. The first one is around incremental versus current market share. This is the concept that one of the companies that we invested in back in 2017—a company called Shopify was a business that was very small in the online retail market; they had maybe sub 1% market share. So very small. But growing very quickly. So, kind of in that early stage of the TAM curve, if you will.



But one thing [we noticed ]when we did some scuttlebutt, we learned that Shopify was winning over 90% of new business; incremental market share of people signing up when they were first opening their web stores. And so that really high incremental share versus current market share all things equal is a very good indicator for a strong TAM. That's kind of one piece.



A second piece is on scalability. So scalability—I call that the 10X question. This is a relatively simple concept to understand. If I increase my revenues or I grew my business by 10 times, how much business complexity, how much cost would that entail to get there? And if the answer is actually, you wouldn't have to do much, then [laughs] you've got a very scalable business.



Number three in the framework within TAM is elasticity of demand. The classic story here is with Uber. When Uber was first going into San Francisco trying to displace the taxi market, a lot of analysts looked at it and said, "Well, the taxi market's only this big." Let's call it a billion. “And you're not really going to find this kind of big market there for Uber, and the numbers don't make any sense.” But what Uber found is by offering a much better product at a much lower price point, they actually 10Xed the demand response. So people started to want to drive a lot more, to take taxis a lot more. So the market exploded in size when you brought a bit of a better product at a much lower price point. We call that the elasticity of demand effect. So that would be the third piece that you were really looking for when we're looking for these strong TAMs.

Justin Anderson:


And then the fourth component is value creation. This one is really this question of okay, how much value are you creating for your customers and giving to your customers?



A good example of this is Microsoft and AWS, Azure—these public cloud companies that are coming in. And they're offering their clients much bigger infrastructure foundations at a much lower cost point. So when these companies adopt these cloud infrastructures, they're able to deliver the same product at a much lower price. So that's creating a lot of value. And that's another thing that you want to look for when you're looking for TAM.



It's a bit of a laundry list there of items, but I wanted to give the listeners kind of the full framework of, okay, here are four of the things that we really look for when we're trying to identify these robust TAMs.

Rob Campbell:


I'm trying to compare it to—if we open a lemonade stand at the bottom of the driveway…like we might think that the total addressed market was the neighbourhood. But I'm not so sure that incrementally, we would be getting like Shopify did—90% of every glass of lemonade bought in my neighbourhood. We try to scale that business up 10 times…we'd have to buy way more lemons, and cups, and probably do a lot of advertising to try and get people to come down to our dead end on our street. Doesn't strike me as a business that would meet a lot of those characteristics.



What I am curious though is the first two that you mentioned—how much incremental share is the company winning, how scalable is it—that seems a little bit more easily measured than say, for example the third one, the elasticity of demand, which seems more like a hypothetical thought exercise. And I'm just curious how you weigh that and how you evaluate? You mentioned Uber. Like you said, nobody really predicted the size of the market. So, how do you get comfort around that element of this TAM framework?

Justin Anderson:


It's a great question. I think one of the arguments for, I guess, active management in the first case is this sort of analysis gets very much out of the realm of pure science and into the realm of human judgment and fine art, if you will. Because there's no way you're going to tell a computer to go through and really be able to assess a lot of these features. You might be able to identify high growth.

Justin Anderson:


But is it really going to be able to go into the nuances of elasticity of demand, and scalability, and value creation? These are much more difficult to suss out.



So, despite me being very kind of pro-tech, and a lover of computers, and dreaming that they can do ever more for us as investors, this is a really good example of where you really do need that kind of human element to make the assessment.



I think each of the components of the four have different degrees of “assessibility” if you will, of how much you're able to really do a proper analysis. I mentioned Adyen before, and Adyen is a pretty clean example because you can look at that business, which is in the payments business.



So, when you take a taxi or an Uber and you swipe your credit card to make the payment, Adyen is the company that is going to verify that indeed we should approve this payment, it's not a fraudulent payment; then to wire the funds between the merchant bank, which is the bank behind Uber, and your bank, the issuing bank that is the bank behind your credit card, and make sure those two talk to each other and wire the funds. So that's basically what Adyen does.



But what they did quite unique[ly] in the payment industry is they built a global platform. Because most of these payment platforms were spinoffs from regional banks, and therefore their setups were very regional in nature. They couldn't cross regions very seamlessly. So Adyen built this global platform which made it so that when they were scaling, when they were growing the business a lot, they didn't have to add new regional platforms and business complexity to the business. They would just leverage their existing platform. So it became an extremely cleanly scalable kind of business model.



In the terms of scalability and incremental market share—those are relatively simple to get your head around. I think I agree with you that elasticity of demand can be very difficult. One term we often use for those types of businesses are kind of…“real options.” So, the idea being that you can't really put a dollar value because you don't know what the demand response is going to be.

Justin Anderson:


A really good current example is actually Square, which is a small component in our Global Equity Fund. It's a business that's really going after consumer banking in a major way, and they're very much at the start of that journey.

Justin Anderson:


And for many years people [were] kind of unhappy with the quality of consumer banking. Imagine you go to your MasterCard credit card statement and after three months you can't even link it back to previous statements and it's kind of a disastrous consumer experience. And Square is coming in and saying, "Hey, can we really just make consumer banking a way better experience?" So how successful are they going to be at that is very uncertain. What's the demand response going to be like is very uncertain. But we would definitely put that more in that bucket of look, they're playing around in a highly valuable zone that is a low quality response today. Can they really improve it? Maybe. There could be a lot of value there.

Rob Campbell:


And could certainly appreciate the size of their TAM or totally addressable market if they are successful there.



Okay, so TAM, the first component: they may have some aspects that may have some drawbacks, but we'll classify those merely as “scratches” or “flesh wounds” for the purposes of this framework. What's next? What's the second element?

Justin Anderson:


Well, I was going to retort, “your arm’s off” but I guess we'll continue with returns here. But it is a bit of “your arms off” situation because oftentimes with these stocks, once you move to the second component which is returns, the story starts to seemingly degrade a little bit. Let's say you found a stock that you think has a great TAM—it's got the scalability, it's got the incremental market share, elasticity demand, value creation. But then you run into the returns, and almost all the time, the returns are going to look very poor [laugh], And you're going to get pretty disappointed. And that actually happens a lot where you find a big bucket of high growth stocks, but it doesn't look very attractive on a returns basis.



This is a major problem in the industry today. Because coming back to you your lemonade stand idea, if you looked at your lemonade stand, there's two very different types of expenses. There's the expense of building the lemonade stand, the capital cost if you will. And then there's the cost of the lemonade itself, maybe your employee wages. And those are two very different expenses. Building the lemonade, you have to do that once (the lemonade stand). And theoretically you can continue to derive cash flow from that. Whereas the ongoing costs—the salaries and buying the lemonade—those are associated with the sales, so you can't really get away from those.

Justin Anderson:


In the world of technology, that distinction is getting very much muddled. And a lot of the major investments that are being made—say the lemonade stands—and [in] the case of technology that would be the code. Investing in the code base, hiring developers to write the code. That's creating the foundation. Nine times out of 10, that gets treated as an expense for the purposes of the income statement. So, what that does is it leads to a situation where these technology companies often have very thin balance sheets; because they're expensing everything, they don't really have much of a balance sheet; they're growing at this crazy rate. The return metrics look all over the place because of the thin balance sheet. So, you have a very small denominator, and it tends to go through a low profitability period and then at negative returns. And all of a sudden it goes to like 80% returns. And it's like, “something's not right here with the accounting!”



And our contention—and I mentioned Michael Mauboussin before, he's really written some great stuff on this as well recently—is that what's really happening is people are overly relying on the accounting numbers to assess these technology companies. They're not really understand[ing] the underlying economic power and returns that they have in some cases. Our contention is that every single stock you have to individually analyze to try to understand what component of their spending is really that kind of, capital-lemonade-stand-type spending, and what component of the spending is really an expense associated with the revenue that year, a cost of goods sold sort of spending. And when you do that sort of analysis, sort of recast the accounting statements, you get very different stories on which companies look profitable from a return perspective.



So, that is really foundational to what we do in The Lab—is we try to apply this process of systematically looking at every stock and trying to understand how they're spending their money, classifying that money spending as either an investment or not. And it leads to a very different kind of story on the return side of things.

Rob Campbell:


I guess there are a couple different dimensions to that. One is just…how much should you reclassify? So I think that makes sense. If I'm building code that's going to last for the next 20 years, but the investment that I make in that is by paying salaries to developers, well, that's treated as an expense on an income statement—that's not being capitalized. I can understand how that would need to be reclassified.

Rob Campbell


How do you decide how much of that to do? And I don't know if you have an example of just how to go through that—how much of a company's expenses you decide to treat as capital or capital expenditures.

Justin Anderson:


When we were going through TAM, we talked about how hard it is for a computer to do all of this work. I think when we go into this, it's even harder [laughs]. It's like this is really where you need that human judgment to come in and to make the assessment. Let's use an example.



So, Amazon back in 2019, before we made major investments in that we did a lot of looking at this sort of…” income statement investing,” as we call it. And what we found was in their 2019 report, they spent a billion dollars that was all expensed on trying to get SMBs (small and medium-sized businesses) in India online. Trying to get them to have an online platform. They spent about $4 billion expanding their one-day delivery. They had mastered two-day delivery in North America and they were moving towards offering one-day delivery.



We estimated that they spent $4 billion. (That was really an investment in a set of processes and whatnot.) We estimated, they reported in their statements that they had 10,000 employees working on Alexa. Alexa is if you know, that little machine that's in your house that you can talk to, and tell it to get you groceries, and whatnot. It's not generating much revenue for Amazon right now, but they're hoping to make an investment in the long term to make it more seamless. It's sort of clearly a long-term investment—a lemonade stand if you will. And it's getting expensed, those employees' salaries are getting expensed as if you're buying the lemonade. So that piece we estimated was roughly $2 billion that they were spending on that.

Justin Anderson:


So that's the kind of little, boring, nitty gritty research that you're doing—you're kind of going line by line. You're trying to figure out okay, what are these guys actually spending on investment? What are they actually spending on COGS? And in the case of Amazon, we estimated they'd spent about $60 billion in tech and marketing in 2019 on their income statement. And we believed that about $15 billion of that was actually spending on investment, at a minimum. We felt like that was a pretty conservative number. And then when you recast that through the income statement over time, it told a very different story on the returns.

Justin Anderson


So that's a very specific example of a company where we did all that analysis. And that was the conclusion that we came to.

Rob Campbell:


How helpful is management with you in this regard? So, I mean, they've got their accounting statements, which it sounds like aren't a lot of help, although it's kind of the starting point. There may be some notes that go along with the annual report that might give you some indication. But I guess the question is—you referenced Mauboussin—just like if this is such a problem in the industry, particularly within technology, does management kind of help you out in this regard? Or do you have to do all that digging yourself?

Justin Anderson:


This is a real problem that you're hitting on in the industry, because the accounting systems have been kind of built for let's say the 19th, 20th century when people were building large hotels or they were building bridges. The nature of accounting has been kind of tuned to that sort of physical investing, physical equipment investing. And today, the huge capital investments are really in code and software. And those aren't getting treated the same way as those historical investments. So it's leading to this bit of a problem where the accounting is diverging so far from the actual economic reality that leads to a problem.



And then to your point about management being open about it—one of the graphs I often encourage management to put out is where they show the vintages of their customer revenues. They show by year how much customers that they acquired in a certain year, how much revenue are they generating from that vintage. And very few do that. But the ones that do do that, it definitely helps you down this pathway of understanding how much they're investing versus how much they're spending.



But in general, they'll write these 300-page annual report and you might get two pages that are actually kind of relevant on these specific issues. It's a very difficult problem. I think it's a big problem for the industry overall that hopefully over time, people start to shift on. But yeah, it just takes a lot of… “roll up your sleeves” as an analyst to try to get to the bottom of it.

Rob Campbell:


There are things that we can do. It takes effort to be able to reclassify some of these things between the income statement and the balance sheet. But I guess the next question is, okay you've determined with Amazon for instance, there's $15 billion that you've reclassified as actual investment.

Rob Campbell:


How are you judging whether that's a good investment or not, or it's a wasted investment?

Justin Anderson:


The beauty of that is once you reclassify, the accounting does the rest. In this case, what you would effectively be doing is increasing their balance sheet relative to what they report as their balance sheet, because you're assuming that $15 billion is really an expense. But you're also improving their profitability because you're assuming $15 billion was an investment, not a COGS. The numbers still flow through, and all you're going to see is a different picture on what you think the actual long-term margin is of the business, what you think the actual return of the business is. Those are the things that are going to get adjusted. But there's no getting away from the numbers that have been reported.



I want to emphasize strongly—we run this through hundreds of companies and a ton of the companies come out with, "No, they're not creating wealth. They're not making wealth-creating returns." So, this isn't just a tool to get you to adjust something into a wealth-creating return. It's quite common that you don't get that when you try to do this.



And sometimes you get companies that are doing kind of the opposite, where they're capitalizing spending, which we consider to be “no, you're not actually building a lemonade stand. You're actually paying for the lemonades.” So it goes the other direction. And that's not uncommon. It's less common in the tech industry, but a good example would be in the oil and gas industry where businesses—they'll book huge amounts of capital, they'll spend a huge amount of capital just to keep the production flat, because oil naturally declines. And we say, "No no—that's not actually an investment of capital, that's maintenance capital,” which we really think is operating expense to keep your business flat. So we'll actually reclassify that and degrade their margin materially.



So there's no sort of one direction to this. It's every company's unique. And all we're trying to do with each company is move the spending in a way that achieves the sort of answer to the question of, “if you were to just keep your business flat, what do you have to spend on that?” And that's your COGS, and the rest is probably investment. And the way you know if it's good investment or not is you look at the returns on the investment after you've reclassified it.

Rob Campbell:


So trying to do what accounting was meant to do, which is reflect the economics of the business?

Justin Anderson:


Yeah, exactly [laughs].

Rob Campbell:


Despite the fact that there may be a record number of companies today that “lose money.” I guess you're saying that yeah, a lot of them are, even when you make these adjustments. But there are also a few of these “holy compounders” that are really not. And yeah, it's kind of the irrelevance of the accounting standards today.



Okay. So we've figured out total addressable markets, we've tried to make adjustments to figure out the returns that a company's actually generating. What's the third part of the framework?

Justin Anderson:


The third and bringing it all together, is the moat. And we kind of talked about this at the start of the discussion. But this is so critical, because now that I think that the listeners kind of understand okay, we're looking for these big TAMS, and we're looking for these high returns, well, the ultimate question is to become a compounder is you need to be able to sustain that growth and those returns over time. And that's where the moat comes in. If you have a very strong moat, then that means that there's a higher probability that you're going to be the sole or one of the only major penetrators into the TAM. So, if the TAM is a $45 billion TAM, you might get $30 billion of it after 10 years. You're going to penetrate far. Whereas if your moat is weak, the TAM might be $45 billion, and you'll only get a billion [dollars] because a whole bunch of competition moved in to chase the TAM.



So that's one piece of the moat. The other piece of the moat is the returns. Let's say we've sorted out that, "Hey, your returns are 40%." Wonderful. Very wealth-creating—especially in a market where the cost of capital's probably on the order of 6% to 7%. It's wonderful. But, after year two, all of a sudden the there's two new competitors popping into your industry, and they're offering the same services at half the price to their customers. Well, what does that do to returns? It starts to degrade returns.



That's actually the normal way that these things typically play out—is where there are high returns, capitalism will attract all sorts of other players to try to capture those returns.

Justin Anderson:


So that's why, again, you go back to the moat and you say, "What is that about your business that protects you from that competition and that lets you continue to kind of claim that high return situation?"



So I'll spell out just like we did with TAM, I'll spell out a framework of some of the things we look for in these companies to try to identify the companies that have the strong moats, which therefore might translate into sustainable returns and a high penetration of TAM.

Rob Campbell:


This kind of feels like a discussion of Porter's Five Forces and competitive advantages. Are these kind of more specific to tech companies, these organic compounders?

Justin Anderson:


It's a little more specific to tech companies. And it's also specific to very high growth companies. You still might be an incumbent business that's growing at 0%, and moat and Porter's Five Forces are still very relevant to you because you're worried about getting disrupted and you don't want your revenues to fall off a cliff.



So I think different types of industries where you're an incumbent trying to maintain yourself versus, say, [an] organic compounder where you're trying to grow. They might have a different sort of set of moat features that are more or less relevant. So, the ones that we're talking about here at least for me have been the ones that have been the most useful in assessing moats inside this kind of…organic compounding tech world.



So, continuing on that—the first one is kind of the traditional moat in technology, [which] is inertia. Inertia is this concept that once you start using something, you're more likely just to continue using it because habit, and it just takes time to switch to something else. And the converse of that is what we call the “cost of ownership moat.” We talked a little bit about that. It's also a TAM feature. But the cost of ownership is sort of like if you adopt this technology, you can actually reduce your costs overall for your business. And a good example of that, we kind of talked about it a few times, is Adyen, the payments company. Where they are able to deliver, they can actually show the numbers. They can actually deliver a lower cost product than the competition because they have this global single platform that allows them to make these decisions on whether to approve transactions more efficiently and more effectively.

Justin Anderson:


So, that leads to a cost of ownership moat. And we think that moat, the ability to offer the same product at a lower cost that your competitors can't match, is something that gives you that sustainable advantage over time.



The second example I wanted to describe was this “sticky” software example. So, probably the most common moat feature you hear about when people talk about software is it's sticky. “It's great because it's sticky.” And what does that mean? It means that once you install the software, like right now we're using a certain software for this podcast. And once you install that software and get familiar with it, it's very hard to move to some other software that might even be better. But it's like no, I'm used to this, it does the job, whatever. So that's sticky. That's a great moat.

Rob Campbell:


You get trained on it, it speaks to all your other systems, it's totally embedded in what you’re doing…

Justin Anderson:


That's right. It's totally embedded. And to rip it out and to go with something else, that something else better be a whole lot better to justify all that time and expense. That's all fine and good, but there's a lot of examples of companies that are like that. Like one of the poster child examples is Oracle, which is a business that is extremely sticky; it's like a database, it also is kind of consuming a lot of your ERP systems (enterprise resource planning systems). And that system very sticky. But Oracle today isn't growing very quickly, despite digital industry growing very fast.



So what happens is sometimes these sticky businesses—which in the short term can be very good moats—in the long term, they can actually encourage tech debt and the accumulation of the company's technology getting weaker over time because they're not making the key investments to keep it up to date. And I contrast that with what we call, “the learning flywheel.” And learning flywheel—the poster child example of this is Google, which everyone's familiar with.



So, Google is a business that isn't sticky at all. Google's not embedded into any of your systems. If you wanted to switch tomorrow from Google to say DuckDuckGo or another search provider, it would take you nothing to do that. So it's not sticky.




Justin Anderson


But Google still has a very powerful moat. And it's the learning flywheel moat, because what happens is because they command so much of the market, they get all of the queries going into their servers, into their databases. And they're able to learn much more effectively at what people are really looking for, what they're not looking for, and then update their algorithms and kind of stay on the edge of their industry. And that learning flywheel I think is more powerful in some ways than a sticky business model, because it constantly forces you, encourages you, to stay up to date with your technology.

Rob Campbell:


So, the cost of ownership is more related to offering something that is at a lower cost than anybody else can do. And that's the competitive advantage. The learning flywheel seems to be just better product oriented. Almost like a network effect, effectively.

Justin Anderson:


That's right, yeah. It's often a network effect. You often find this in businesses where they have some big component of the market for some reason. Like another example we use is Elastic, which is a search provider. They offer basically…it's like an enterprise search provider, so, a lot of the apps you use like Uber (coming back to Uber), if you search for a car on Uber, you're using Elastic’s technology to find the driver/which drivers are nearby to you and connect you kind of properly with them. What makes them have a learning flywheel is that 90ish percent or 80% to 90% of developers when they need to put a search product into their app, they choose Elastic. That's such a command over the industry that they're constantly learning from those developers what features they need, what features they don't need, how do they improve the product? So it kind of lets them keep the product on the edge, which is a really powerful moat because you can't really see it ever degrading. Versus tech debt, which often the problem is it can great over time, and then as new disruptors start to build new technologies, you might lose your moat. So this learning flywheel moat is quite powerful.

Rob Campbell:


Yeah. It's such an interesting concept that something that's sticky might actually longer term be a problem. And what is it? Is it just…do companies get lazy, or is it just too difficult sometimes to keep up when something's that embedded?

Justin Anderson:


Well, I think the extreme example of this is, let's say a government or otherwise monopoly. Where, if you don't have to do anything to keep your business alive, then it can breed complacency.

Justin Anderson


It can make the product deteriorate, because there's no incentive for you to kind of stay on the edge. I think sticky business don't necessarily fall directly into that kind of monopoly risk problem, but it's kind of a similar problem of resting on your laurels so to speak, and just enjoying the powerful business that you have. But over time, it's like no—if you don't invest, eventually someone is going to come around with a better product.

Rob Campbell:


Yeah. And thinking about the sustainability of growth, this seems like a pretty important one. What else are you looking at with respect to moat?

Justin Anderson:


The last one we kind of highlight here is just the classic platforms versus tools dichotomy. So, the example that should be familiar for everybody is if you contrast the iOS platform on your or iPhone or the Android platform on your Samsung phone. Those are platform businesses, those operating systems, because you can install different things on top of them. They're not going away anytime soon. We see those as quite powerful. You want to be a platform. You want to be enabling third parties; [it’s] a much more attractive business than, say, the apps that you directly install all on your phone, which would be more like a tool. So you might install an app that helps you find something, or some retail thing, or whatever the case may be. That app has a much weaker moat than the underlying platform that is holding the app.



That kind of operating system versus app—we use that all across different industries when we're looking at companies to try to say okay, is this really a platform kind of business more like an operating system? Or is this more like a tool that is solving some specific need that is therefore more easy to disrupt?

Rob Campbell:


Can I ask you…these businesses that are largely built on intangibles—does that not imply that the risk is higher as well? Given the fact that while something goes wrong, you don't have much capital that's left. Does that make sense? Is the risk not inherently higher these businesses, given that they're more intangible in nature?

Justin Anderson:


The kind of question there is the switching costs could be lower. I think it would depend on the business. I don't know if the business is inherently—if you can put them into one bucket like that. I think if they have weaker moat characteristics, the switching costs are going to be lower for them.

Justin Anderson


And yeah, anytime the switching costs are low, then it's going to be a lower quality business. But some of these businesses…I would take Azure Cloud platform, which is also intangible in many cases, has very high switching costs. I think it's really case by case in my opinion on whether or not—even the word intangibles kind of triggers me a little bit [laughs] because I sort of think of it like, “what's an intangible?” At the end of the day, I just see two things. I see you're spending money on capital that is something that's going to last for a long time, or you're spending money on cost or goods sold. And if we call it PP&E, if we call it intangibles, I'm less interested in that distinction than I am in the actual economic reality of the nature of the spending.

Rob Campbell:


Interesting. I guess I'm coming at it from an old school perspective. If you spend a whole bunch of money and invest in code and then somebody else comes along and has got a better product, we don't really have anything left with that code I don't think. Whereas if I built my lemonade stand, I'd had an actual physical stand well there might be some value to that, even if somebody down the street came along with a better marketing engine.

Justin Anderson:


I think that's fair. And I think physical capital is probably less volatile, all things equal than sort of…code investments. But I guess I would just go back to the nature of what it is that you're spending on. Because there are physical assets that do get written off. You start to think about a lot of these oil sands investments and in industries that people are moving away from. And it's like yeah, maybe a lot of this stuff does actually get written off or is less valuable than the balance sheet would suggest.

Rob Campbell:


That's been really interesting. It sounds like despite the high valuations in tech lands, there's lots to be interested in. I think it is important to highlight what we're talking about today is not companies like Rivian, which just IPO-ed, [and where] there's just not a lot of revenue. It's not how much you're going to adjust in terms of capitalizing and expensing that's going to make that look like a more profitable business. You're speaking mostly about businesses that are really fully formed, that have got lots of potential runways, do generate high returns, and have moats that can protect those returns. And it's about parsing those out versus the rest of the universe that this framework can help.

Justin Anderson:


That's well said.

Rob Campbell:


Great. Well Justin, thank you for taking us on this quest. As always, it's just great to have you on the podcast.

Justin Anderson:


It's been a pleasure! I can't think of anyone I'd rather be on the quest with Rob than with you.

Rob Campbell:


Awesome. Thanks Justin.

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