A Warren Buffett Textile Lesson For The Rising AI Roll-Up Trend

"Once a few people in the parade decide to stand on their tiptoes, everyone has to stand on their tiptoes. No one can see any better, but they’re all slightly worse off."

Investors rushing to gain from AI through roll-ups of traditional firms may benefit from this business lesson by Warren Buffett. He shared it almost four decades ago in his 1985 annual letter:

    Over the years, we had the option of making large capital expenditures in the textile operation that would have allowed us to somewhat reduce variable costs. Each proposal to do so looked like an immediate winner. Measured by standard return-on-investment tests, in fact, these proposals usually promised greater economic benefits than would have resulted from comparable expenditures in our highly-profitable candy and newspaper businesses.

    But the promised benefits from these textile investments were illusory. Many of our competitors, both domestic and foreign, were stepping up to the same kind of expenditures and, once enough companies did so, their reduced costs became the baseline for reduced prices industrywide. Viewed individually, each company’s capital investment decision appeared cost-effective and rational; viewed collectively, the decisions neutralized each other and were irrational (just as happens when each person watching a parade decides he can see a little better if he stands on tiptoes). After each round of investment, all the players had more money in the game and returns remained anemic.

    Thus, we faced a miserable choice: huge capital investment would have helped to keep our textile business alive, but would have left us with terrible returns on ever-growing amounts of capital. After the investment, moreover, the foreign competition would still have retained a major, continuing advantage in labor costs. A refusal to invest, however, would make us increasingly non-competitive, even measured against domestic textile manufacturers. I always thought myself in the position described by Woody Allen in one of his movies: “More than any other time in history, mankind faces a crossroads. One path leads to despair and utter hopelessness, the other to total extinction. Let us pray we have the wisdom to choose correctly.”

The tippy-toe metaphor is very instructive: Once a few people in the parade decide to stand on their tiptoes, everyone has to stand on their tiptoes. No one can see any better, but they’re all slightly worse off.

What does it have to do with AI, you may ask. Well, it obviously presents a huge opportunity to introduce automation in accounting firms, homeowners associations, support centers, and a large variety of other industries. The New York Times recently reported:

Thrive Capital has bet big on artificial intelligence, including emerging giants of the field like OpenAI and Databricks.

Now the venture capital firm is taking a different approach: creating and buying companies that it believes can benefit from A.I. — including in industries that seem far more humdrum, such as accounting — and holding on to them for a long time.

Thrive Capital is far from being the only venture capitalist dabbling in this private-equity play, as per TechCrunch:

Venture capitalists have always focused on investing in companies that leverage technology to either disrupt established industries or create entirely new business categories.

But some VCs are starting to flip the script on their investing styles. Rather than funding startups, they are acquiring mature businesses — such as call centers, accounting firms, and other professional service firms —and optimizing them with artificial intelligence to serve more customers through automation.

This strategy, often likened to private equity roll-ups, is being employed by firms such as General Catalyst, Thrive Capital, and solo VC Elad Gil. General Catalyst, touting this as a new asset class, has already backed seven such companies, including Long Lake, a startup that scoops up homeowners associations in an effort to make the management of communities more streamlined. Since its founding less than two years ago, Long Lake has secured $670 million in funding, according to PitchBook data.

While the strategy is still new, a few other venture outfits have told TechCrunch that they are also considering trying out the investment model.

Among them is Khosla Ventures, a firm known for making early bets on risky, unproven technologies with long development timelines.

“I think we’ll look at a few of these types of opportunities,” Samir Kaul, general partner at Khosla Ventures, told TechCrunch.

The play seems obvious: AI is amazing, but some people still have a hard time figuring out how to use it. Especially the non-technical folks who typically tend to run homeowners associations and the like. Ben Evans recently expanded on this GenAI’s Adoption Puzzle. Therein lies the chance for the Silicon Valley crowd – the ultimate early adopters of new technologies – to get involved: they’ll scoop up traditional legacy firms, automate them with AI, and keep the fat margins to themselves.

What’s the fallacy in this thesis? It does not consider the second-order effects. Yes, the first firm in an industry to introduce AI automation would likely become more profitable. For a short while. The chasm, however, provides but a fleeting moat; eventually AI would hit the mainstream market. The other firms would figure out how to integrate it.

What would the new industry equilibrium look like? The fallacy is to assume everyone would keep the same revenues, only with more profit dollars flowing to the bottom line. That not how things work in commodity businesses, which homeowners associations very much are; Charlie Munger explained in his famous talk, The Art Of Stock Picking:

The great lesson in microeconomics is to discriminate between when technology is going to help you and when it's going to kill you. And most people do not get this straight in their heads. But a fellow like Buffett does. For example, when we were in the textile business, which is a terrible commodity business, we were making low-end textiles which are a real commodity product. And one day, the people came to Warren and said, "They've invented a

new loom that we think will do twice as much work as our old ones." And Warren said, "Gee, I hope this doesn't work because if it does, I'm going to close the mill."

And he meant it. What was he thinking? He was thinking, "It's a lousy business. We're earning substandard returns and keeping it open just to be nice to the elderly workers. But we're not going to put huge amounts of new capital into a lousy business."

And he knew that the huge productivity increases that would come from a better machine introduced into the production of a commodity product would all go to the benefit of the buyers of the textiles. Nothing was going to stick to our ribs as owners.

That's such an obvious concept ‑ that there are all kinds of wonderful new inventions that give you nothing as owners except the opportunity to spend a lot more money in a business that's still going to be lousy. The money still won't come to you. All of the advantages from great improvements are going to flow through to the customers.

Exactly! Once AI automation kicks in, the steady-state is, well, no longer steady. Our tech-forward homeowners association would be tempted to leverage its improved cost structure, and lower its prices in an attempt to gain market share. Just like the first person to stand on their toes in the parade. They get to see a little better. Until the person in front of them also stands on their toes. Other homeowners associations are pressured to join the party. They are forced to use AI and lower their prices as well. Eventually, everybody stands on their tiptoes. They all go back to making the same profits, unable to recoup their investments in introducing AI. They missed the second-order effects of AI.

What’s required for business owners to benefit from investing in efficiencies? Munger goes on to explain:

Conversely, if you own the only newspaper in Oshkosh and they were to invent more efficient ways of composing the whole newspaper, then when you got rid of the old technology and got new fancy computers and so forth, all of the savings would come right through to the bottom line.

In all cases, the people who sell the machinery ‑ and, by and large, even the internal bureaucrats urging you to buy the equipment show you projections with the amount you'll save at current prices with the new technology. However, they don't do the second step of the analysis which is to determine how much is going to stay home and how much is just going

to flow through to the customer. I've never seen a single projection incorporating that second step in my life. And I see them all the time.

Rather, they always read: "This capital outlay will save you so much money that it will pay for itself in three years." So you keep buying things that will pay for themselves in three years. And after 20 years of doing it, somehow you've earned a return of only about 4% per annum. That's the textile business.

And it isn't that the machines weren't better. It's just that the savings didn't go to you. The cost reductions came through all right. But the benefit of the cost reductions didn't go to the guy who bought the equipment.

It's such a simple idea.

It's so basic.

And yet it's so often forgotten.

With this lesson from Charlie Munger, it’s not hard to predict who stands to benefit from the rising wave of AI-rollups: society, hopefully, since all of us would be paying less for our accountants, support services, homeowners fees, and so forth. The venture-capitalists-turned-PE would probably make money: both from management fees on their roll-up funds, as well as from making those legacy firms into customers of their portfolio AI startups — the ones building AI tools for accounting firms and HOAs to incorporate.

It’s the investors in the roll-up funds that should probably be more concerned, as they might experience the same lessons that Buffett and Munger painfully learned in the textile business: the technology may work just fine, and the cost reduction would materialize; it’s just that the savings would flow to someone else.

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