The Unified Theory of Value & Tech Investing (or, How Cantos Invests) | by Ian | Medium

On more pensive days, which have been abundant of late, I feel a sort of odd camaraderie with the late Stephen Hawking in his quixotic striving for a unified theory of gravity and quantum mechanics. Mine being a far lesser mind, the pursuit that has dogged me in ten years of investing has been a model that unifies the so-called value investing framework solidified by Benjamin Graham and tech truisms epitomized in “growth” stocks, namely FANMAG. While there are many differences between the two apparently disparate schools of thought, there are two equations they largely agree on. Let’s start with the first:

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My Enterprise Value Equation

In a venture capital context it’s more about assessing potential enterprise value (EV sub P) so that equation gets simplified to:

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Potential Enterprise Value

This equation is why VCs love to talk about total addressable market (TAM), or market size (I prefer “revenue opportunity”), but they air the term more than moat, or defensibility, because it’s more readily knowable. Enlightened VCs concern themselves with potential TAM rather than current market size, but predicting future demand from people like them is another favorite topic so TAM continues to receive disproportionate attention. In investing terms, such widely discussed variables are typically priced in––i.e. consensus––and thus offer less opportunity to yield above-market returns. Which brings us to the second common equation between “value” and “tech”:

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Opportunity for Investment Returns

Let’s use our prior equation to modify this for venture capital opportunity:

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Opportunity for Venture Capital Returns

A venture capitalist’s job is essentially to maximize this equation across each fund’s portfolio. TAM, as we’ve discussed, is at least perceived as being easier to assess or project. Perception can be discerned fairly reliably by valuation––though a nuance of venture capital is that the illiquid market-making, lack of transparency, and ability for management to select among investors means that pricing is often inefficient. The remaining variable, moat, receives more attention from classic value investors such as Seth Klarman than it does from popular venture capitalists, so I poured over Michael Mauboussin’s seminal paper hoping to glean some gems. Those gems are abundant in the value frameworks discussed in “Measuring The Moat”, The Intelligent Investor, and Porter’s Five Forces, but technology as a driver of defensibility was only paid lip service. (The word “software” is mentioned only once in Berkshire Hathaway’s 144-page 2019 annual report.) As far as I could tell these prolific investors categorically missed or were at best late to the largest, most entrenched (even monopolistic) enterprises of all time. So what were they missing?

Well, here’s a moat as depicted on the cover of Mauboussin’s iconic “Measuring The Moat” report:

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A Buffett moat

And here’s how I think of Amazon’s:

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A Bezos moat

I’ve come to believe the categorization of businesses and investors between “value” and “growth” is a misnomer, and that the difference is simply in the multiple each is willing to pay for staying power––which is a function of their understanding of moats and how they evolve over time. By his own admission the “Oracle of Omaha” doesn’t understand technology businesses––by which I take it he means software businesses––but my highly educated mother who ran in-classroom technology initiatives doesn’t understand the appeal of video games and even as a VC in my early 30's I don’t get TikTok so let’s cut the old guard some slack. (The investors mentioned have been wildly successful by any measure so don’t feel sorry for them either.) I knew I needed to understand moat creation as it hinted at opportunity per our equations but I had to look elsewhere, specifically to more contemporary literature.

Certain aspects or types of technology-driven moats are widely understood, most notably network effects, or network economies––which, to his credit, Mauboussin and other value investors address as demand-side economies of scale though they largely failed to imagine how dramatically these could come into play in the absence of geographic constraints. An original eBay investor, Benchmark Capital holds perhaps the deepest institutional knowledge around marketplace network effects and I am deeply thankful to Bill Gurley for generously sharing that wisdom. While network economies are arguably the strongest long-term defensibility driver, and Cantos-backed companies such as Knowde, Legit, and Clara Health take advantage of them, there are clearly others––e.g. intellectual property, supply-side economies of scale, switching cost, brand––but they had not been summarily categorized through a unified and technology-familiar framework. I was ready to put my inconsiderable mind to the task but had been putting it off for the same reasons I’m a VC and not an operator.

I’m thankful I did, because a couple years back my pal Ramtin Naimi at Abstract Ventures recommended Hamilton Helmer’s 7 Powers, a framework that Keith Rabois and others have referred to as “Silicon Valley’s best kept secret”, and holy gigaflop I feel like I found the cheat codes. Helmer kicks off the book with the same potential enterprise value equation I’d come to––though his looks like this:

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Helmer’s Potential Value Equation

(Execution––that is management or in venture capital’s case the founding team––are arguably a third variable though Helmer and I both consider this is a necessary-but-not-sufficient component so I will not discuss it here.)

He then describes in detail the seven “powers”, or defensibility drivers, he has categorized over his career. I can’t recommend this book strongly enough (the audiobook is great too though misses some of the key graphics) but I’ll do my best summarize them here:

1.) Scale Economies: This is the widely understood notion of supply-side economies of scale, where making more of a thing reduces its unit cost, purchasing more of it improves purchasing power––or, and this is Helmer’s contribution, it increases the amount a company can spend per customer relative to its fixed costs such that it delivers more consumer surplus vs. the competition

Examples: Intel, most manufacturers, Netflix, Walmart, Robinhood

2.) Network Economies: The product improves the more customers use it, accruing nearly insurmountable barriers to competition at a certain scale. In many cases network economy businesses exhibit winner-take-all dynamics, which puts such an onus on expansion that it may be logical to operate unprofitably for a portion of time. (This explains two venture truisms––winner-take-all, growth-over-profitability––and why they are only true in certain cases.)

Examples: LinkedIn, Facebook, Airbnb, Y Combinator, Knowde, Clara Health

3.) Counter-Positioning: Where a new and superior business model would actively destroy value if pursued by an incumbent, or would at least do so for the incumbent’s executives. Counter-positioning is often made possible by new technology. Helmer calls this power his favorite as it is the one he originated.

Examples: Vanguard, Netflix, SpaceX, many Google products, Solugen, Mission Barns

4.) Switching Costs: Self-explanatory; what I like to call “enterprise stickiness” though it applies to consumer businesses as well.

Examples: Operating systems, most enterprise software (esp. systems of record), Spotify, Helium Health, Symbio, ALICE

5.) Branding: When the signaling or search cost of a product is reduced by the target market’s perception of the brand.

Examples: Many apparel, jewelry, and alcohol brands; Apple

6.) Cornered Resources: Intellectual property and trade secrets, uniquely qualified people/teams, government licenses or other regulatory favor, and other proprietary assets.

Examples: Most biotechs, specialty chemicals, Pixar in the ‘90’s & ‘00’s, most “deep tech” startups––Skyryse, Prellis, Eridan, Chameleon, XGenomes, CurieCo

7.) Process Power: When a company through its experience has aggregated such institutional knowledge that it exhibits discernibly higher efficiency vs. its competitive set. (I view this power as a technicality and largely write it off as it is idiosyncratic, difficult to identify, and accumulates so late in companies’ lives as to be irrelevant to startups.)

Example: Toyota in the ‘90’s & ‘00’s, Bridgewater Associates

You might rightly observe, and Helmer goes on to discuss, that different powers emerge at different stages in a company’s life––which he categorizes as the origination, takeoff, and stability phases:

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Hamilton Helmer’s Power Progression (“7 Powers”)

Helmer’s Power Progression answers an existential question for Cantos that previously I could only speak to with loose Clay Christiansen quotes: Why technology is necessarily a driver of new enterprise value. Going back to our potential value equation, technology has the power to drive deeper moats and expand market scale––even sometimes creating entirely new markets. It is highly unusual––though not impossible––to engineer such power by sheer ingenuity rather than in the wake of newly commercialized technology, but entrepreneurs and venture capitalists rightly search for opportunity in that wake.

Let’s view the 7 Powers in a venture context. The stability phase being of virtually no consequence to venture investing I mostly ignore branding and process power. In my experience, scale economies tend to aggregate too late in the takeoff phase to be highly relevant to startups either so I note them but don’t underwrite investments to them. Switching costs surface earlier but are relatively common and often go hand in hand with costly sales teams so enter my diligence but sit below the three powers I consider most relevant to seed investing (in ascending order): Cornered resources, counter-positioning, and network economies. There are three reasons I focus on these powers above the others:

1.) They are relatively capital efficient to produce,

2.) They are virtually insurmountable barriers to entry (each with exceptions: other startups could also pursue the counter-positioned business model, network economies are only insurmountable at a certain scale, and cornered resources are time-limited)

3.) Their presence or potential are easily discernible at the earliest stages.

Armed with this new framework (Helmer published 7 Powers in 2016) I’ve been judging Cantos’ investments in new light, notably with greater confidence intervals around upside potential which in turn allow me to flex my valuation standards when multiple powers are present and/or their magnitude is sufficiently high. The holy grail for me, especially given my dispositional focus on frontier tech, is when a cornered resource produces network economies, counter-positioning, and/or high switching costs. If you’re thinking of starting a company or are raising seed capital and that’s you, email me at ian at cantos dot vc and together we’ll see if what I’ve come to think of as the Unified Theory of Enterprise Value & Tech Investing does for us what it’s done for Helmer and the companies he’s backed (e.g. Netflix, Shopify, Amazon, Atlassian, Zoom, 10x Genomics)…

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Hamilton Helmer (Strategy Capital) Gross Returns 1994–2015, averaging 41% annually