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This is part five of the 7 types of business Power series. To read the earlier articles click here.

In 1985, Coca-Cola began what is often described as one of the era’s biggest marketing blunders when they decided to replace the classic Coke formula, for New Coke. Not only did the company fail to foresee the anger and frustration this would cause—but the lengths people would go to get their old Coke back. One man in particular—Gay Mullins—was hell bent on achieving this goal. Mullins, a retired Seattle investor, created buttons, t-shirts, and established a society called Old Cola Drinkers of America, that would accrue tens of thousands of followers with the sole purpose of forcing Coca-Cola to make the original formulation public. There was even a hotline for people to vent their rage. In a sweet twist of irony, Mullins conducted two separate blind tests and preferred the taste of New Coke—both times. In light of his obvious new preference of soft drink, what do you think Mullins did?

He still demanded his old Coke back.

So, what’s going on here? How can somebody want—demand, even—something they’ve been proven to not prefer? Well, how many times have you purchased something for more money, when you could have purchased an exact, or near perfect similar product?

My bet is quite a few.

How many times have you purchased something to “show it off?”

Probably more times than you’d like to admit.

The reason you spend more money on a product when you could buy an objectively similar one, is the same reason you buy branded medicine over a supermarket alternative when your child is sick. To quote Ronseal, “it does exactly what it says on the tin.” This isn’t some global capitalist mind hacking you from their ivory tower to squeeze every last penny from you—it’s brand Power. One of the most confused, but powerful forces in markets.

Helmer’s Definition of Brand Power

For those new to the series, Hamilton Helmer’s 7 Powers is widely considered the best business book on strategy. What’s particularly interesting about this Power though, is I guess it’s not only business nerds who will find this interesting. If you’re a publisher here on Substack, you too will understand the need for strong brand image. But strong brand image, and what Helmer calls Branding Power are two very different things. Every company has a brand image. But, can every company achieve brand Power? Let’s first look at how Helmer defines this Power:

Helmer describes the definition of brand Power as:

“The durable attribution of higher value to an objectively identical offering that arises from historical information about the seller.”

Simplified:

The ability to charge higher prices for something that is objectively identical to its counterpart based on the name of the company.

Simply being aware of a brand, and a brand being able to charge a 10 X premium for a comparable product is the difference that separates brand recognition, from brand Power. Businesses with brand Power are able to charge customers more for an objectively identical product due to one, or both of the following two reasons: 1) the relationship with the brand elicits positive feelings towards their offering, which is distinct from it’s objective value—something Helmer calls affective valence, and, 2) the customer has “peace of mind” knowing that the product will be as expected—something he calls uncertainty reduction.

We’ve all felt affective valence towards something we’ve purchased. Just ask Apple MacBook users, or god forbid, Tesla owners. Both have competition that offer alternatives, but people do pay more to say they own a MacBook or they own a Tesla. There’s an argument that MacBooks are better laptops—an argument I agree with—but others wouldn’t. The same goes for Tesla. Regardless of them being the ugly duckling in the electric car family. Whatever it is that a business sells, there must be a benefit for the end user. If it does not make you feel a certain way once you are the owner, it becomes very difficult for the business to establish Power through affective valence alone.

Uncertainty reduction is a different beast. It thrives on your anxiety. As before, if you have a sick child you go to no ends of the Earth when they’re sick to make them feel better, and if that means paying £6.70 for a 10 pack of Lemsip Max Cold & Flu sachets when you could buy an identical SuperMarket-Own Brand for £3, you do it. Admittedly I don’t have kids, but I do have a dog with a penchant for visits to the vets. Often out of hours. Last year my wife and I wanted to change pet insurers after a 100% price increase, from £67.50 to £135 a month for no other reason than Roo, turning 9! We signed up to another vet and felt content we’d ‘saved’ £55 as our new bill was £80. But Roo started being sick after we changed insurer. He then started haemorrhaging blood from his backside. We quickly rushed to him to the vets that Friday evening and were told he had AHDS (Acute Hemorrhagic Diarrhoea Syndrome)—a condition that not only made his stool look like the leftovers from a gunshot wound to the head—but a condition that can be fatal.

My wife and I were petrified, followed by shock when we were told we weren’t insured. There was a two week window when taking out the new insurance where we weren’t covered. The estimated bill was somewhere between £3,000 and £5,000 to keep him in for just the weekend and carry out tests. We obviously instructed them to do what they needed to do, and that we will find the money. Money that we didn’t have at the time coming of a big holiday to the states.

I’ll save the emotional state of my wife and I for another story, but my wife rang up our previous insurers and begged them to help. And help they did. The clause in our previous contract with them gave us a 30 day grace period after we cancelled to go back if we wanted. They covered every single penny from our bill, and aside from holding our breath anxiously every time Roo has a poo, he made a full recovery.

This year our pet insurance bill is £227 a month, and it’s worth every single penny having the peace of mind that if something happens again our insurers are there to help us. We trust the insurance company. Not something you often hear people say.

In the book, Helmer uses the chirpier, but still anxious example of buying an engagement ring for a loved one:

“I bought Tiffany and I knew I was getting soaked. Didn’t matter—happy then and would do it again (in fact, I upgraded her wedding band to match channel diamonds years later). My priority was to buy the best without any doubt of quality/certification/etc. Size was not important. I wanted indisputable to match her. We’re not showy people and have never played up the fact the rings are from Tiffany’s. It was more appropriate to me to buy a reasonable size stone and know with quiet confidence that the thing is timeless—not a cheap knock-off or gaudy bauble.”

So how much more are people willing to pay for peace of mind?

In 2005, Good Morning America asked reputable gemologist Martin Fuller to appraise the Tiffany & Co. and Costco rings they had purchased. The Tiffany ring was bought for $16,600 and the Costco ring $6,600. What’s ironic is Fuller valued the Costco ring at $8,000—$2,000 higher than the retail price, and the Tiffany ring at $10,500. People are happy to pay nearly $10,000 extra to sleep easier at night? Fuller described why:

“You got exactly what they said you were getting. Anything that is brand-name and has developed a reputation that Tiffany has developed, they’ve earned it over the years for quality control. You can go there and you don’t have to think twice about your purchase. And you pay for that.”

That’s the benefit.

In case you haven’t yet figured it out, the barrier for this Power is time. It takes time to build a strong brand name, and positive reinforcing actions—something Helmer calls hysteresis—serve as the key obstacle. For a new-comer wanting to build their brand name, they are met with a lengthy and uncertain runway with no assurance that customers will feel any affective valence towards their offering. To make matters worse for them, no matter how good their offering is, it’s more than likely open to competitors copying them and eating away any small advantage they may have had.

Why Brand Recognition is Not Brand Power

What’s the difference then between brand recognition and brand Power —and more importantly how can you actually tell them apart?

Let’s look at one of America’s (former)
favourite beers.

Bud Light is one of the most well known beers in America and is advertised everywhere—including Super Bowls. Brands with strong recognition can afford such advertising through other Powers such as Scale Economies, but without making the goods distinguishable from others—customers cannot feel any affective valence towards it. In a 2023 blind test, Bud Light ranked 22nd out of 28 beers. This was on the back of ranking 6th out of 8 beers in 2022. It was impossible for drinkers to distinguish Bud Light from other light beers yet it was the most popular beer in the U.S. How? Marketing and consumer drinking habits. But, in 2023 a controversial marketing campaign, which somehow managed to alienate both political parties for different reasons, saw Bud Light’s US retail sales fall 17% for the year, cost them $1.4 billion dollars in lost revenue and resulted in them dropping down to third place, from first, in top-selling US beers. This fall from grace may have been triggered by the marketing campaign but it wasn’t because of it. The fact that Bud Light drinkers did not have an identifiable affective premium associated with the beer meant Switching Costs were near zero.

Again, brand recognition is not brand Power. The test: if you strip away the label—does the premium survive? If it does not, it’s likely consumer habit through better than average marketing.

Branding Challenges and Characteristics

Once Branding Power has been established it forever opens itself up to reputational scrutiny, copycats and changing consumer preferences, such as:

• Brand dilution: perhaps the easiest mistake to make. Careful stewardship of a brand is needed to ensure its reputation remains consistent with its historical image. Releasing products that deviate from what is typically associated can create confusion and dilute the brands reputation resulting in negative feelings towards the brand. Toyota, aware of their brand image as a reliable, cost effective car manufacturer decided to create Lexus when wanting to enter the luxury car market. They understood the difference between “reliable” and “luxury” cars. A high-end fashion brand trying their hat at “affordable” fashion is almost certainly going to ruin its reputation.

• Counterfeiting: people will always produce and buy counterfeit products. When a counterfeit product, such as a Louis Vuitton handbag, is produced and illegally sold to the masses it can damage the reputation of the brand. Tiffany would later go on to sue Costco in 2013 for ‘imitating’ to shoppers it sold Tiffany jewellery. They held no punches in their press release as they staunchly defended their brand: “Tiffany has never sold nor would it ever sell its fine jewellery through an off-price warehouse retailer like Costco.”

• Changing consumer preferences: over time customer preferences may change in ways that could negatively impact the brands image. Nintendo had developed a reputation for family-friendly video games, but when the direction of the industry changed to more adult orientated games Nintendo did not—or rather—could not through fear of diluting their brand.

• Geographic boundaries: the affective valence towards a brand may apply in one region but not another. Luxury brands have often struggled to infiltrate the Indian market because the Indians have their own luxury brands they prefer to Western alternatives.

• Narrowness: brands with strong recognition may actually be benefitting from scale economies. Bud Light can pay for Super Bowl ads because of their size, whereas a smaller business can’t.

• None-exclusivity: branding as a Power is non-exclusive. Multiple brands can, and do, have Power regardless of competition. Think of LVMH and Hermes. Both companies have Power in the same market. All brands with Power have returns superior to competitors who do not.

The Conditions for Power

Not all goods sold create the conditions for Power, but two conditions are needed to establish it.

The first is magnitude. A promise to justify the price tag has to be made. Business to business products typically fail to create the positive association needed in creating Power, as the main goal is that of objective deliverables. However, consumer goods that can be attached to a sense of identity clear this condition (again LVMH and Hermes), because they offer the individual an opportunity to flaunt. To let people know that they could have bought an objectively similar handbag —but wanted the luxury of peoples eyeballs on them as they tried to figure out why anybody would spend so much on branded bag when they could have bought a cheaper one that does the same job.

Brand Power derived from uncertainty reduction offers the buyer comfort by knowing exactly what they’re getting from a trusted brand. The money saved from the purchase of a similar product from a less reputable brand isn’t worth the anxiety. Goods that have bad tail events—such as a cheap weight loss alternative—can have significant consequences when they go wrong. Only last night somebody told me a story of a woman they knew who had stated having periods again in her late 50’s after taking a knock-off GLP1.

The second condition is duration. If enough time hasn’t passed to build brand Power, the goods will fall victim to normal competitive arbitrage.

Affective Valence is Non-Transferable

When writing this article I had what I thought was an interesting question: can a company have branding Power for one of its products but no Power for others?

It turns out, yes. The affective valence a consumer feels for one product will not necessarily transfer to another good from the same brand.

An example is needed to illustrate this. Coca-Cola also owns bottled water brand Dasani—a brand pulled from the U.K in 2004 after an ill-fated attempt to enter the market. In the U.S, the cost ranges from about $0.40 to $0.50 per litre. The same price range as other bottled water brands. The brand likely benefits from the Scale Economies, marketing, and budget Coca-Cola has at its disposal, but customers do not feel any positive association or uncertainty reduction towards bottled water. I mean, how could they? I find it odd that people buy bottled still water when it flows from our taps, but I suppose that’s because here in Manchester the tap water is actually quite nice to drink.

Surplus Leader Margin (How to Calculate a Brands Power)

At the end of each chapter in 7 Powers, Helmer using some overly complicated Math to calculate the Power in question. Here’s it taken directly from the book:

To help operationalise this, I’ll provide two examples. One for uncertainty reduction, and one for affective valence.

Example A: Tylenol vs Equate acetaminophen (uncertainty reduction mechanism)

Same products, same dosage, same quantity.

• Tylenol Extra Strength Caplets, 500mg, 100 count: $10

• Equate Extra Strength Acetaminophen, 500mg, 100 count: $2.08

B(t) = 10 / 2.08 = 4.81
SMargin = 1 / 4.81 = 0.207
1 - 0.207 = 0.79

Example B: Coca-Cola vs. Great Value Cola (affective valence mechanism)

• Coca-Cola, 2L bottle: $2.47

• Great Value Cola, 2L bottle: $1.74

B(t) = 2.47 / 1.74 = 1.42
SMargin = 1 / 1.42 = 0.704
1 - 0.704 = 0.30

Tylenol is able to charge a higher price multiple of nearly four times because of the uncertainty reduction mechanism. Coca-Cola charges customers a third more compared to alternative colas, built on the back of a century of positive association with the famous soft drink.

Final Thoughts

Helmer shows us two avenues for benefits that help establish Branding Power: affective valence and uncertainty reduction. Both elicit strong feelings towards the brand. The barrier is hysteresis: brand Power can only be created on the back of a lengthy period of reinforcing actions. A competitor with more cash, can’t simply compress the timeline. Duration itself is the moat.

The type of good matters too, and acts as a screen before you should even consider the benefit and barrier. Does the offering have magnitude—the promise of eventually justifying a significant price premium? Has enough time passed for the magnitude to be achieved? A three year old brand—no matter how good its marketing and products are, can have many things—but not brand Power.

The biggest pitfall brands face is dilution. Chasing down-stream revenue at the expense of the affective valence that built the brand image in the first place. Imagine the disgust the proud Birkin bag owner would feel in the pit of their stomach if they saw Hermes offer an ‘affordable’ version of the bag they’d coughed up 25k to buy.

If you take nothing else away from this article, remember: brand recognition is often mistaken for brand Power, but there’s a rather simple calculation you can make to tell them apart.

Next week they’ll be a case study on Hermes and how they built one of the most iconic luxury brands of the last two centuries.

Until then, Karl.

If you’d love to hear more about Branding as a Power and the psychology people go through in justifying to themselves bloated price tags when other identical, or near identical alternatives are available hop into the 7 Powers thread i’ve just opened:

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You might have heard about the Boeing 737 that crashed a few weeks ago on a routine flight from New York to Seattle. From early investigations, a small component failed resulting in the death of all 197 passengers and crew onboard. Even worse, the component in question was swapped out a couple of months before for a cheaper alternative because the airline carrier was unhappy with the consistent uplift in price. The Federal Aviation Administration (FAA), and families of the deceased are rightfully demanding justice (and the head), of the greedy capitalist responsible for making such a shortsighted decision.

Thankfully, everything I’ve just said was a lie—but the scenario, could very well happen.

The Department of Defense (DOD) and commercial airlines must conduct regular maintenance on their aircrafts to avoid the exact scenario I’ve just fictionalised. For commercial airlines, the investigation and compensation would be damaging. For the U.S government to lose some of its warfighters this way: insurrection.

Switching Costs, one of Hamilton Helmers 7 Powers, form a powerful economic and psychological moat by making it painfully difficult for a customer to abandon a product or service once they’re embedded into that ecosystem. Think Apple users vs Android. This friction casts doubt in the end user’s mind—often summarised as “better the devil you know”—protecting the incumbent from challengers. In the SAAS industry, Switching Costs are sticky, annoying and time consuming. In the aerospace industry it can be matter of life and death.

No company understands this and has used it to their benefit more than TransDigm. Today, let’s look at how robust those Switching Costs really are.

Company Profile

TransDigm Inc is a leading global designer, producer and supplier of highly engineered aircraft components that are critical to the safe and effective operation of nearly all commercial and military aircraft worldwide. Approximately 90% of net sales for fiscal year 2025 was generated from proprietary products—components or products of which they are the exclusive owner of the intellectual property. Once their parts are designed into and sold on an aircraft, they generate net sales from aftermarket consumption (maintenance and repair schedules) over the life of that aircraft, and results in significant aftermarket revenue for approximately 25-30 years. A typical platform can be produced for 20-30 years, giving an estimated product lifecycle in excess of 50 years. Over 55% of net sales for fiscal year 2025 were generated from commercial and military aftermarkets.

TransDigm predominantly serve customers in the commercial, regional, business jet and general aviation aftermarket, which generally account for 30% to 35% of their annual net sales; the commercial aerospace OEM (Original Equipment Manufacturer) market, comprising large commercial transport manufacturers and regional and business jet manufacturers, which generally account for 25% to 30% of annual net sales; and the defence market (which includes defence OEMs and aftermarket sales to the U.S. and friendly foreign governments), which generally account for approximately 35% to 40% of annual net sales.

Their customers include: 1) distributors of aerospace components; 2) worldwide commercial airlines, including national and regional airlines; 3) large commercial transport and regional and business aircraft OEMs; 4) various armed forces of the United States and friendly foreign governments; 5) defence OEMs; 6) system suppliers; and 7) various other industrial customers.

Value-Driven Operating Strategy

Their business strategy is made up of two key strengths: 1) successful execution of their value-driven operating strategy, which is focused around three core value drivers and, 2) selective acquisition. The three value-drivers are; they look to acquire profitable companies, improve their cost structure and provide highly engineered value-added products to customers. Their selective acquisition strategy focuses on companies that manufacture proprietary components in the commercial aerospace and defense industry that have significant aftermarket content whereby they can implement their three core value drivers. They have successfully acquired over 100 businesses that operate as 55 independently run companies.

It’s this “value-driven” operating strategy that has brought TransDigm under some scrutiny. Former CEO Nick Howley insists that for customers, pricing is a “distant third or fourth” priority compared to safety, reliability, and on-time delivery. It’s hard to disagree. But other’s do disagree, including Charlie Munger, who believe TransDigm’s pricing strategy is predatory and “price gouging.” Take for example the Whippany Motor Rotor which increased from $654 to $5,474.

A 736% rise.

So why does TransDigm get away with pricing that would be called predatory in almost any other industry?

FAA Certification

The aerospace industry is governed by stringent safety regulations overseen by agencies such as the Federal Aviation Administration (FAA) and European Union Aviation Safety Agency (EASA). Once an aircraft manufacturer or airline integrates a TransDigm component into an aircraft, replacing it with a competitors part requires a lengthy, arduous and highly expensive process of reverse engineering, testing and securing certification. Over 80% of the products that TransDigm markets are sole source. TransDigm cleverly sells these initial components at moderate margins to then jack-up the price in the aftermarket. This is commonly known as a “Razor and Blade” pricing model. Razors are initially sold for a modest price compared to the price of replacement blades—which is enough to make your eyes bleed. Thankfully, I don’t shave.

If TransDigm’s Switching Costs rest primarily on regulatory re-certification friction, how durable is it if the FAA simplifies its procurement process?

Well, they already have.

PMA’s

A PMA (Parts Manufacturer Approval) allow for the approval of “generic”
components to be manufactured and sold by companies who do not own the intellectual property of that component. Wait, but didn’t I say before that nobody else can sell TransDigm’s products? I did, and that’s still true—sort of.

In practical terms, PMA’s function as “generic” or “OEM alternative” replacement parts. Once a manufacturer obtains PMA approval for a part, they are legally permitted to produce and sell that component to airlines and maintenance providers. So, while they do not own the IP to the comparable TransDigm component, what they have done is meticulously reverse engineer and proved by way of testing—that their product can offer a cheaper alternative to TransDigm’s component typically in the region of 40%to 80%/

However, acquiring a PMA certificate isn’t a walk in the park.

For starters, you have to try and reverse engineer a component. This could pay off, but it also could fail, and the resources and upfront capital would have been for nothing. Even then, the submission of what you deem a successful, or indeed improved alternative, requires detailed documentation including drawings and specifications. This is followed by proven manufacturing processes and quality control systems as-well as comprehensive test reports and computations proving its airworthiness. Lastly there’s extensive oversight and ongoing FAA inspections once approved.

The impact of this makes it economically unviable for most. Not only that, volumes for certain components are often low or cyclical, meaning significant on-going costs for keeping the product lines going to get what..a few orders worth thousands of pounds that took you 24 months and $1 million dollars to produce? And that’s just for one component. TransDigm has a catalog of over 400,000 SKUs.

The Barrier

TransDigm’s Switching Costs are durable primarily because they are regulatory rather than contractual. In fact, in their latest 10-K they explicitly list the lack of contracts as a business risk. But, once a component is FAA-certified and designed into an aircraft platform, the re-certification cost and timeline for a substitute makes displacement economically irrational for most.

As Nick Howley stated:

“These are little things going into big things. What matters is they don’t foul the big thing up. They work and you get them there on time. And if something goes wrong with that, you fix it fast”

Which of Helmers Broad Categories do TransDigm Have?

Financial: The cost of a replacement aircraft component is often insignificant compared to the financial loss commercial airlines would face for downtime, which typically results in them paying whatever price TransDigm sets. For military aircraft, the potential repercussions aren’t much better. If they decide not to replace or repair their serviceable aircrafts, it’s not only the service men and women who are in danger—but international policy. For a competitor to take OEM and aftermarket share away from TransDigm would take significant upfront—and risk-loaded capital. The growing PMA market (of which TransDigm has now fully entered by acquiring Jet Parts Engineering and Victor Sierra), does offer a financially cheaper option and will be interesting to see how it develops, but the typically insignificant cost of a component—relative to the potential loss of revenue from aircraft downtime—mean TransDigm will continue to have maximum pricing power.

Procedural: Approval to design, manufacturer and supply aircraft components comes under strict oversight from the FAA, EASA, and other global agencies. Through decades of quality management; from commodity resourcing, production manufacturing and the engineering of proprietary best-in-class components, TransDigm has consistently delivered and defended their reputation as being a reliable tier 1 supplier. For a competitor seeking to replicate TransDigm’s processes, intellectual property and catalog would not only take extensive time—but capital. Even then, reputation is a hell of a thing.

Relational: Through their decades of trading in the industry of aircraft components, TransDigm has built a trusted reputation for quality, safety and deliverability that makes it hard not only for competitors to match—but for the Department of Defense (DOD), and commercial airlines to want to completely shake up the industry’s procurement practices.

Final Thoughts

Switching Costs are most powerful when the customer is fully aware of them, but stays anyway. Conscious lock-in is a stronger moat than invisible lock-in because it signals the embeddedness is structural, not accidental. And while there have been investigations, hearings and short sellers all wanting to tear apart TransDigm’s value-driven pricing model—none have yet to be successful. They have previously swatted questions about the potential threat PMA companies pose, but their recent acquisitions of two significant players in that market show not necessarily a pivot in strategy—but situational awareness. TransDigm are awake.

Because TransDigm’s Switching Costs are regulatory in nature—they’re durable. For now at least. A crack down by the U.S government would certainly put pressure on their revenue and margins should they have to lower their prices when dealing with the DOD. Entry into the PMA market brings with it lower margins, yes—but improved volume. A counter argument TransDigm have used at hearings regarding price-gouging is the unpredictable orders and low volumes the DOD typically purchase. After all, who’s supposed to keep the product lines going when no one’s buying anything? But, conscious lock-in could also bring resentment and accelerate defection should the FAA or DOD decide to crack down on TransDigm.

Until next time, Karl.

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The School of Knowledge is the weekly newsletter for SME owners and investors who want frameworks they can actually use — frameworks, checklists, and operating manuals every weekend, built to read on Sunday and use on Monday.

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Sources:

• TransDigm 10-K 2025

• TransDigm earnings call Q2 2026

• TransDigm earnings call Q1 2026

• TransDigm earnings call Q4 2025

• FAA certification

• 50x podcast TransDigm research

• PMA vs OEM Aviation Parts

• Short selling report from Citron Research

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Netflix has long been championed for seeing in DVDs what Blockbuster didn’t—the future. Their DVD-by-mail business was akin to what Jeff Bezos did to retail book stores when he created Amazon. Bezos transformed a capital-intense business model, requiring high capital expenditures and physical stores capable of offering a few thousand books, into a distribution network capable of delivering nigh on every book ever published. Netflix also had the self-awareness to look towards the horizon, and where the future was heading—digital streaming. Reed Hasting say’s in the foreward to 7 Powers:

“The existential threat from Blockbuster was behind us, and we were on track to reach almost $1.7 billion in sales. These were hard-won advances, but even so our strategy challenges were no less daunting. The clock was ticking on our red envelope business, as DVDs by mail was clearly a transitional technology. And looming was the prospect of facing off against huge competitors with resources far beyond ours: Google, Amazon, Time Warner and Apple to name several.”

DVD-by-mail, and digital streaming are two separate industries with their own economics, and the prospects of entering the digital streaming industry didn’t look all that appealing: IT costs were getting cheaper by the year; cloud storage was expanding and with it costs plummeting. The barrier for entry seemed to be getting lower—not higher, and so too was the prospect of Power: that which creates durable differential returns.

But, Reed Hastings and his team at Netflix were strategists. They knew it was only a matter of time that digital streaming would do to them, what they did to Blockbuster. They decided that if they were going to be killed anyway—they’d do it on their terms.

“Any strategy framework, to be broadly useful to a business person, must address all key strategy issues within the organisation.”

In 2007 Netflix tentatively entered the digital streaming industry by partnering with a dizzying array of electronic hardware specialists. But they didn’t bet the house and go all-in. They did the leg-work, allowed themself exposure to this emerging market, and gained the much needed experience before making any big moves. While smart, these tactics aren’t a strategy and any potential for Netflix to gain Power in this industry was at the very best muddy.

The way streaming worked back then was streaming platforms like Netflix negotiated for streaming rights of content with film studios. But, the film studios were astute and strategic custodians of their properties, and would split them up by geography, regions, release dates, contract length and so on in ways that benefitted them, not Netflix. It’s the equivalent of wanting to get a new iPhone where the contract provider determines the amount of minutes, text and data you get as well as the price and duration of the contract.

Netflix fought for scraps for 4 years, until in 2011 where they finally made their move. Ted Sarandos, Netflix’s Chief Content Officer, believed it vital that Netflix secure exclusive streaming rights to certain properties. It was exactly this type of thinking that would allow Netflix the potential to finally gain Power over the film studios: they were going to start creating originals. This shift—from being controlled by the film studios—to creating their own content was not only expensive, but risky. However, this move was as bold as it was ingenious.

This was a brazen attempt at counter-positioning and upending the status quo. Reed Hasting:

“Throughout my business career I have often observed powerful incumbents, once lauded for their business acumen, failing to adjust to a new competitive reality. The result is always a stunning fall from grace. A superficial thinker might pin this on lack of vision and leadership. Not Hamilton. By inventing the concept of Counter-Positioning, he was able to peel back the layers to peer into the deeper reality of these situations. Rather than lacking vision, Hamilton established, these incumbents are in fact acting in an entirely predictable and economically rational way. Our earlier battle with Blockbuster bore out this notion.”

The film studios could have copied Netflix into launching their own streaming platforms, but that would have meant cannibalising their already lucrative legacy business models (cinema releases, cable syndication, and DVD sales). The incumbents rational self-interest was Netflix’s moat. The collateral damage to their existing revenue stream made the net present value of copying Netflix at the time an unattractive prospect.

By taking this route, Netflix was now playing a different game. A game of one. Creating originals, such as the hit House of Cards (with that infamous Kevin Spacey look), and gaining exclusive rights to content, would mean that other streaming platforms would have to up their fixed-costs to compete with Netflix or remain beholden to the whims of the film studios. If House of Cards cost Netflix $100m and they had 30 million subscribers then the cost per customer was just over $3. If a competitor had only one million subscribers then the cost per customer to make the original would be $100. They created a 10m-high barrier where none was there before and told those who wanted to compete they’d have to pay up to do so. This radical shift in industry economics allowed Netflix to move away from the value-destroying commodity rat race they found themselves in, and created the path for another of Helmer’s Powers: Scale Economies.

The benefit for people using Netflix was clear: exclusive premium content, on demand, for a low subscription fee that can be cancelled at anytime. The more people that subscribed to Netflix, the more fixed costs they had to create original content.

If Netflix hadn’t made their move in 2011 who knows where they would be today, if anywhere at all. Disney, Amazon and Apple would all eventually all follow suit and create their own streaming platforms but it is Netflix who is still the clear market leader. They have over 325 million subscribers compared to their nearest competitor Amazon Prime Video’s 200m. Disney+ has 131m and Apple+ 45m.

Ultimately, Netflix’s transition from DVD-by-mail to digital streaming is a masterclass in structural strategy and the deliberate construction of Power. They recognised that simply participating in a market dictated by film studios was a tactical manoeuvre, not a strategy for enduring success. By boldly pivoting to original content, Netflix fundamentally altered the industry’s barrier conditions. They leveraged Counter-Positioning to paralyse incumbents—whose rational self-interest prevented them from cannibalising their own legacy models—buying Netflix the crucial runway needed to build insurmountable scale economies

Today’s subscriber numbers are more than just a testament to popular shows; they are the mathematical proof of a moat built on high fixed-costs and massive scale. Netflix proved that to escape a value-destroying commodity rat race, a company cannot just play the game better—it must possess the strategic foresight to rewrite the rules entirely.

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Sources

1. 7 Powers book

2. 7 Powers with Hamilton Helmer

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There’s a video doing the rounds at the minute of Steven Bartlett banging on about how a few glasses of wine wasted—no, ruined—three days of his life. I will refrain from passing judgement on how anybody can have such a sad view of reality, but the guy’s getting hammered for his (and others’) cultish pursuit of ‘optimisation.’ Optimisation, once a word that got you appreciative nods from your boss in company meetings, is now a dirty—no, boring—word. In fact, it’s so boring a story I knew I had to use it as an opener to the third instalment of the How to Design the Systems That Run Your Business series, because it’s not just podcasters that fall prey to this type of thinking—so do businesses.

For part 1 click here, and for part 2 click here.

When you optimise for something in your business, what you’re really doing is cutting, trimming, or tightening something. Firming it up. What can look like ‘waste’ though is often your lifeline in times of great stress. It’s like scraping lifeboats on a cruise ship so you can save on the fuel.

Efficiency taken to its extreme strangles the system it’s supposed to be optimising for.

Over-optimisation: the efficiency trap

Every cost-cutting programme, every consolidation of suppliers, and every operational optimisation tightens the system’s grip, leaving next to no margin for error. COVID-19 laid bare the ramifications of operational efficiency when taken to its extreme. Prior to COVID, most Western manufacturers practised just-in-time supply chains, and when the pandemic struck the impact was immediate and severe: Apple postponed product deliveries, Samsung and LG suspended production, Tesla closed factories, and US automotive inventory dropped from seventy-seven days of supply in January 2020 to fifty-five days by February 2021.

What Western commentary failed to grasp wasn’t that JIT supply chains are bad, but that their bastardised versions of it were. Toyota’s original conception of JIT, as practised within their Toyota Production System, relied on short, stable supply chains, production levelling, built-in quality control, and long-term thinking. It’s a learning system designed to make problems visible so that they can be solved. What Western companies were doing was offshoring work to low-cost suppliers, aggressively cutting inventory, increasing lead times, and removing any buffers for financial ‘optimisation.’ Such are the pressures of having quarterly earnings calls.

The difference between Toyota’s JIT model and Nissan’s was summed up by their COO, Ashwani Gupta: The just-in-time model is designed for supply-chain efficiencies and economies of scale. The repercussions of an unprecedented crisis like COVID highlight the fragility of our supply-chain model.

I know you can’t just sit there and plan for pandemics, but if you’re going to remove your company’s emergency lifelines—and therefore increase the tension on your company’s proverbial elastic band—you shouldn’t be surprised when it snaps.

Normal accidents and the governance paradox

The Governance Paradox explains why system accidents aren’t anomalies but inevitable properties of the system’s structure.

Charles Perrow, a Yale sociologist, provided a theoretical framework for why some systems are inherently resistant to resilience engineering. In his 1984 book Normal Accidents, Perrow argued that when a system exhibits both interactive complexity (components interact in hidden, non-linear ways to produce unexpected failures) and tight coupling (processes happen fast, cannot be easily stopped, and leave no room for improvisation), accidents are not anomalies but inevitable properties of the system’s structure. He called them “normal accidents”—normal not because they are frequent, but because they are inherent.

For systems builders, this paradox is of great importance. Tight coupling must be centrally managed, where quick decisions can be made by those in charge. But, interactive complexity benefits from decentralised, slower decision-making as a consequence of novelty and informational delay. This might sound contradictory, but Perrow’s framework predicted the Chernobyl disaster two years before it happened. When you add complex safety systems to already complex systems, interactive complexity grows, not shrinks.

When you have systems that are tightly coupled and interactively complex, it creates an impossible governance issue.

When designing business systems, you cannot simply bolt on resilience to an already tightly coupled and interactively complex system. It must be designed in from the beginning, through modularity and loose coupling, to allow failures to remain local. Amazon took this paradox seriously when they created their “two-pizza teams”: no more than eight people—the number of slices you typically get from a takeaway pizza—when they decomposed their monolithic codebase into microservices. If one team failed, it remained local and allowed the others to keep operating rather than bringing the whole house down with them.

So how can you build resilience into your systems?

The four structural features of resilient systems

Resilient systems have four structural features: they have excess capacity in the form of redundancy; there is no single point of failure in the business; they diversify away risk; and they have internal buffers capable of absorbing external variety.

• Redundancy means having more capacity than you would normally need in the event of unforeseen circumstances. In 2011, Japan was ravaged by an earthquake that damaged a nuclear reactor in Fukushima. Toyota’s supply chain was devastated and it took them six months to restore production outside of Japan. The reason it took so long was that Toyota couldn’t even name all of its sub-tier contractors, let alone contact them. Toyota conducted a comprehensive vulnerability assessment that identified up to 1,200 parts and materials that could potentially be affected by future disruptions. They drew up a list of 500 priority items to be secured with suppliers—including two to six months’ worth of semiconductors. When the global 2021 chip shortage hit, Toyota was the best-positioned automaker in the world, overtaking General Motors in sales for the first time.

• Modularity means designing systems that can absorb local points of failure without cascading. Haier, the Chinese appliance manufacturer, took this principle to its extreme under the leadership of Zhang Ruimin. From 2005 to 2012, Zhang eliminated over 12,000 middle management positions and reduced its hierarchical layers from twelve to three. The entire company was reorganised into some 4,000 micro-enterprises, each consisting of ten to fifteen people, with hiring, strategy, and compensation packages left for them to decide. Multiple micro-enterprises linked together to form ecosystems of micro-communities that share common goals but remain operationally independent. Zhang is quoted as describing his transformation as “changing a whole garden into a rainforest.” The resilience logic is straightforward: if one micro-enterprise fails, it doesn’t kill the rainforest.

• Diversity ensures that the system’s components are not all vulnerable to the same failure mode. A portfolio of different suppliers spread across different regions or geographies, a leadership team with different cognitive skills, a technology stack that does not rely on a single vendor—these are all expressions of diversity as a resilience strategy. This connects directly to Ashby’s Law: a system with greater internal variety is better able to withstand external variety when circumstances change.

• Buffers offer a cushion and a lifeline. Cash is the easiest tangible buffer there is. When companies don’t have cash—especially in downturns—they are headed to the company graveyard. When Toyota stockpiled six months’ worth of semiconductors, it might have looked like waste to some. But you don’t want to realise you need something, only to realise it’s too late.

The role of slack: apparent waste as structural insurance

Organisational slack might look like structural inefficiency to one person, but opportunity—or insurance—to another. It takes on many forms: redundant employees, unused capacity, unexploited opportunities, discretionary budgets, and unstructured time.

In 1948, 3M’s fifteen per cent policy allowed its employees to devote a portion of their paid working hours to self-directed, unfunded, and unmanaged projects. It directly led to Spencer Silver’s Post-it Note invention in 1968, which was then commercialised in 1980 by Art Fry. Google, inspired by 3M’s approach, not only adopted this policy but bettered it to twenty per cent. This reportedly led to Gmail, AdSense, and Google Earth.

The purpose of organisational slack isn’t to act as a buffer to take your foot off the pedal, but to allow employees to explore their curiosity in the hope of it producing something tangible for your organisation. You’re dedicating time and care to your future business. Nick Sleep famously had ‘thinking sessions’ on Friday afternoons, and he did alright.

Stress-testing before reality does it for you

If resilience must be designed in, it must also be tested before a real crisis does the testing for you. Three methods stand out for their practical effectiveness. They are particularly effective because, as Daniel Kahneman said, teams suffer from WYSIATI (What You See Is All There Is) and fall prey to groupthink once a decision is made. These methods go some way in actively hunting for blind spots.

• Red teaming designates an individual or team to purposefully attack a strategy to find its vulnerabilities, blind spots, or poorly constructed assumptions. The concept’s roots date back to the Vatican’s Advocatus Diaboli—meaning devil’s advocate. The history of red teaming is littered with examples of it in use: after intelligence failures during the 1973 Yom Kippur War, Israel developed the “Tenth Man Rule.” When all analysts agree, a designated person must disagree and explore alternatives. The US Army formalised the discipline in 2004 at the University of Foreign Military and Cultural Studies at Fort Leavenworth. Netflix’s Chaos Monkey, created in 2010, is an infrastructure version of red teaming in action. When the company was migrating to AWS in 2012, a script ran continuously that randomly terminated server instances during business hours. The philosophy was clear: the best way to avoid failure is to fail consistently.

• Scenario planning is a strategic framework for creating and analysing multiple possible futures to prepare for uncertainty. The concept was pioneered by Pierre Wack at Royal Dutch Shell in 1971 and does not attempt to predict the future, but rather to expand the range of futures an organisation can perceive and prepare for. This very concept prepared Royal Dutch Shell for the October 1973 oil crisis, after a three-hour presentation by Wack in September 1972 had outlined precisely such a scenario, turning the company from an ugly sister to a behemoth.

• The Premortem removes complacent thinking by forcing genuine quality analysis. When organisations and businesses make plans, they’re usually optimistic with risk analysis done as an afterthought: “we think this will work, but let’s consider some risks.” The problem with this type of thinking is that people stay overly optimistic, self-censor, and don’t want to seem negative—especially in group settings. The Premortem takes a page from Charlie Munger’s preference for inversion and starts at failure. When a plan is near being finalised, instead of identifying potential risks for the sake of it, Gary Klein proposes giving a short speech that goes something like this: “It’s a year from now and the plan has miserably failed. What happened?” It shifts the thinking exercise from theoretical to factual.

Final thoughts and the barbell strategy

Systems need room to expand and contract and over-optimising everything down to the tenth degree puts stress on a system. Stress that at some point, is bound to fail. If you need evidence that businesses can’t handle indefinitely growing stress, you need only look at biology for what stress can do to a human body and mind when overworked. Or just ask poor Steven.

Operationalising this framework relies on one last piece of the puzzle: Nassim Taleb’s Barbell Strategy. You build buffers into your system and use scenario planning, red teaming, and premortems to avoid ruin. But you also use organisational slack for small trial-and-error bets that won’t blow up the company if they fail—but can produce meaningful upside if they come off.

Until next time, Karl.

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The School of Knowledge is the weekly newsletter for SME owners and investors who want frameworks they can actually use — frameworks, checklists, and operating manuals every weekend, built to read on Sunday and use on Monday.

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I made some changes to the School of Knowledge in January, and while I love Substack, it doesn’t give me a perfect picture of what my audience wants. Sure, there’s click-through rates, audience growth and engagement metrics to measure, but Substack routinely likes to remind people that they might be having ‘issues’ with metrics, and what you see might not exactly be the truth.

I planned to check in with subscribers of the School of Knowledge every few months to make sure both our interests are aligned. I have a habit of being distracted. Unfortunately I got ill—quite ill actually—shortly after releasing my vision for the year that was also followed up by surgery on my hip after tearing my cartilage. My illness from January is still ever-present with regular hospital visits and potential procedures still not of the table. It’s left me exhausted—but writing offers me not only a distraction—but a way to gain clarity. It helps turn my incoherent scattered thoughts, into coherent understanding. That’s the idea anyway.

But I’m still not a mind reader.

I can see what gets opened, what gets shared, and what gets read to the end. What I can’t see is why. I can’t see which essays changed how you think about a decision you were making. I can’t see which ones you forwarded to a partner or a colleague. I can’t see what you wish I’d write more of—or, more usefully, less of.

So I’m asking directly.

This poll takes about 10 minutes. All questions are optional, but I’d appreciate it if you could answer them all. Four questions are for paid members only, although the survey doesn’t differentiate between questions for free and paid subscribers, so again I’d appreciate it if free subscribers don’t answer them questions. The questions have (paid members only) in the question text so are easy to spot. There are no wrong answers and the most useful ones are usually the bluntest. If something I write isn’t landing, I’d rather know now than keep writing it.

A few things I’m trying to understand:

• Who’s actually reading this. Operators, investors, professionals, students, something else entirely.

• What you want more of, and what’s bouncing off you.

• For paid subscribers: whether the paid tier is earning its keep, and what would make it worth more.

• For free subscribers: what’s holding you back, and whether there’s a version of paid that would actually be worth it for you.

The results will ensure that our I keep our interests aligned. Don’t worry, i’m not going to start writing about topics that are un-TSOK, just dig a little deeper into what my audience is preferring. I’ll be sure to share a summary of what I learn in a follow-up post so you can stay informed of any changes.

If you’ve got 10 minutes, I’d be genuinely grateful.

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In the landmark book on cognitive science, Thinking Fast and Slow, Daniel Kahneman asked a simple question: can overconfident optimism be overcome by training? He didn’t think so. The main reason is that overconfidence in individuals is a feature of system 1 that can be tamed—but not gotten rid of. The main obstacle was that

subjective confidence is determined by the coherence of the story one has constructed, not by the quality and amount of the information that supports it.

Twenty-five very dangerous words.

Is he saying our brains, or rather—system 1—deliberately prefers quick, easy-to-digest, and familiar solutions over the quality of supporting information? If you take a second to think about that question before you answer (using your more deliberate and analytical system 2), you’ll likely come to the conclusion that you agree. To disagree would be to go against decades of cognitive science.

But Daniel Kahneman did acknowledge that where it is difficult for an individual to mitigate this lapse in judgement—Gary Klein‘s Premortem offered businesses and organisations an analytical framework that increased their ability to spot potential problems by up to 30%.

Premortem as risk diagnostic tool

When organisations and businesses make plans they’re usually optimistic, with risk analysis done as an afterthought: “we think this will work, but let’s consider some risks.” The problem with this type of thinking is that people stay overly optimistic, self-censor, and don’t want to seem negative—especially in group settings. The premortem takes a page from Charlie Munger‘s preference for inversion and starts at failure. When the plan is near being finalised, instead of identifying potential risks for the sake of it, Klein proposes to give a short speech that goes something like this: “It’s a year from now and the plan has miserably failed. What happened?” It shifts the thinking exercise from theoretical—to factual.

The premortem has two main advantages: 1) it goes some way to eliminating group think, and 2) it helps steer knowledgeable individuals in a much needed direction. Let’s go through the six-step process of how to conduct a premortem, including an example from my own business.

1. Brief the team just before commitment

Run the premortem when plans feel finished, but resources have not yet been allocated. Too soon and the plan won’t feel concrete enough. Too late and you’ll be battling with the Sunk Cost Fallacy. For my construction business, this could be at the end of finalising a tender—especially if the client is new, or if the tender sum is larger than our average bid. This shifts our thinking from “we need to start looking at our resources and capacity in the event that we win the tender” to “the job was a complete write-off and we need to desperately fix what’s happened.”

2. State the failure as fact

The statement of failure as a fact is critical. You’re not saying this might fail—you’re saying it has failed badly—and you want to know why. Ask each of the individuals to write down as many reasons they can think of for why it failed. It’s important that people know that nothing should be off the table in regards to why the failure has happened. It also shouldn’t feel, or be taken personally, with inflammatory language left out.

3. Everyone writes alone

No discussion. No group influence. Each person must generate their own opinions as to why the plan has failed. This is what separates the premortem from brainstorming and prevents the power of the first person’s words anchoring the group. If you need to, go in separate rooms. There’s always a cheater!

4. Round-robin: one reason per person per round

Each person takes it in turns to list one risk from their list. Have a facilitator note down all the risks and ensure nobody passes judgement as people are talking. This surfaces minority views that might not have had the opportunity in open discussion.

5. Group by failure type

Sort the reasons for failure into topics that best describe your situation. For example: execution failures (we didn’t do what we planned), assumption failures (our model of the world was wrong), external shocks (something happened we didn’t anticipate), and political failures (internal dynamics undermined the work). Pay attention to potential risks that have been flagged several times, cluster around a particular group type—such as execution—and especially reasons that leave the room in complete silence.

6. Amend the plan

For each high-priority failure reason, amend the plan, add a monitoring signal where possible, or explicitly accept the risk with your eyes wide open. Update, or create, your Risk Register for this plan, and add 3–5 concrete plan changes to mitigate those risks.

Why it works

Prospective hindsight lifts stated probability by 30%. I absolutely hate hindsight bias and it does something to my soul when people say “hindsight’s a wonderful thing.” Not least because it’s so obviously true, but because it doesn’t help you in any way at all. But Klein’s research found that imagining an event has already occurred makes people significantly better at identifying reasons it happened. Again, it’s important to reiterate: we’re not eliminating poor judgement, but limiting it. I’d take reducing poor decision-making by 30% any day—especially if all it took was a 10–20 minute exercise.

It gives permission to voice doubt without being disloyal. In most teams, raising concerns about a plan reads as opposition or negativity. The premortem reframes it as a contribution—you’re helping explain a failure that’s already happened, not undermining a decision being made. Risk management consultants get paid small fortunes from large corporations, organisations, and governments to remove risk—especially risk that comes with large financial implications.

It surfaces Unknown Knowns—tacit doubts that exist but aren’t spoken. The engineer who privately worries about a technical assumption, the salesperson who knows a client relationship is more fragile than the CRM shows—the premortem creates the structural conditions for those people to speak. It is specifically designed to surface quadrant III—unknown knowns. It can’t find quadrant IV (unknown unknowns, by definition), but it is extremely good at finding things the team collectively knows but hasn’t said aloud. Which is usually where the real risk lives.

How to run a Premortem in Claude

As part of my paid membership offering, where possible, I turn the mental models, concepts, and frameworks we learn into playbooks, article series, PDFs, worksheets, and other tools for practical people to deploy. For the premortem, I’ve created a generator whereby you plug in your project plan or decision and it conducts a premortem analysis for you—highlighting the six main risks in ranked order, proposals to mitigate them, and a revised plan you can print or download as a PDF.

Below, I used the premortem to better understand the risks of tendering for a project that is equal to 60% of last year’s revenue.

*Project or decision: tendering for a project that’s equivalent to 60% of last year’s revenue.

The Premortem as a risk mitigation framework excels because it draws on multiple knowledgeable people’s expertise—but for decisions you have to make alone, or if you want a quick analysis, the generator works great.

The concept and framework provided are free for all subscribers, but the tool is for paid members of the community which you can access below via the link.

How to access the Premortem generator

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We all have different ways of learning; some of us prefer text, some instruction, and others visually. I naturally prefer reading text at the start of learning a new topic or concept, prefer instruction when i’m trying to put that thing to action, and default to visuals when trying to understand something after getting stuck.

Claude is great for learning visually now that it can create interactive artifacts and has been helping me better understand some of the recent topics i’ve been writing about, such, as how to understand financial statements and Viable Systems Models (VSM), and i want to give you the prompt i’ve been using today. But first, lets see it in action by asking Claude to help me understand VSM, the Rumsfeld Matrix and produce an interactive compound growth calculator.

I then moved on to ask Claude to explain the Rumsfeld Matrix:

The ‘UNKNOWN’ category at the bottom was misplaced, but this time Claude produced a clickable quadrant where you could further explore one of the categories by clicking on it. I clicked ‘unknown unknown.’

Claude then produced another static visual. Again, there was a small error as Blockbuster went bankrupt in 2010 not 2009, but you can just let Claude know and it will fix it.

And finally i asked Claude to produce a compound growth calculator. I purposely left out the word ‘interactive’ to see if it produced a static image like above, but it produced an interactive version which is what was needed for this instruction. Here’s one screen grab:

And another after messing with the four interactive bars:

I hope this helps those of you who prefer learning visually or are looking for a prompt to help you create on brand interactive visuals.

Until next time, Karl.

Download the prompt by clicking the link. It will force you to download the document, so don’t worry, that’s normal.

Visual Explainer Prompt

The School of Knowledge was born as a placeholder for my thoughts and has turned into me distilling lessons i’ve learnt from being a nobody to a Royal Marine, to travelling the world, to getting paid thousands of dollars a day to cleaning ovens for minimum wage. I’ve built many lives in my 36 years and they’ve all taught me lessons—lessons that as a business owner-operator i want to share with people who are trying to build a life or career they want. If you just want the mental models, concepts and frameworks then stay for those alone. If you just want to learn about how to run or start your company and gain financial understanding you can do that too. But for those who want access to it all—warts and all—there’s an offer below waiting for you to just accept it.

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Incase you missed it

Yesterday i published the third deep-dive on the How to understand financial statements: Why cash is king. Essential reading for business owner operators:

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The School of Knowledge is the weekly newsletter for SME owners and investors who want frameworks they can actually use — frameworks, checklists, and operating manuals every weekend, built to read on Sunday and use on Monday.

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This is part three of my How to Understand Financial Statements series. A series for business owners and investors to finally get their heads around the three financial statements to improve their financial intelligence. Part one taught you How to Read an Income Statement and part two revealed Why Warren Buffett Reads the Balance Sheet Before Anything Else. Today’s piece is the third leg of the tripod: How to Read a Cash Flow Statement.

For decades Wall Street adored the income statement with measures such as EBITDA (famed by the cable cowboy John Malone) their preferred metric for determining how well a company was doing. EBITDA going up was good. EBITDA going down was bad.

But, if you’ve been following this series you should know by now that profit isn’t cash. You can’t pay for new equipment with profit, can’t pay your staff with profit—and you can’t pay your liabilities with profit either. You can only pay for things with cash.

If the income statement is a company’s report card, and the balance sheet is its photograph, then the cash flow statement is its bank statement.

It tells you one thing: where did the money actually go?

Why profit and cash are not the same thing

This is the part that trips most people up, so let’s deal with it first.

Two obvious reasons are that cash may be coming in by other means such as loans or from external investment. These won’t show up on the income statement, but will show up on the cash flow statement. But, there are also three not so obvious reasons for those who don’t yet fully understand the three financial statements:

• Revenue is booked at sale. When a company makes a sale or delivers a service, it records that sale as revenue. For example, my construction company takes on a months long timber window repair scheme for £15,000. We finish the job and invoice at the end of the month, but the customer (in construction) has 30 days to pay. No money will go into my bank account until that 30 days, but we record the project cost of £15,000 under revenue on our income statement. The profit is real; the cash is not yet there.

• Expenses are matched to revenue. The income statements main function is to tally up all costs and expenses associated with generating revenue during a given time period. Some expenses will have been prepaid already (a deposit on office rental), but most will be paid later. In my construction example, i have to pay merchants for materials, typically on account, and the subcontractors who carried out the work. If we’re doing our job right, both will typically be paid by us after we’ve been paid by the client.

• Capital expenditures don’t count against profit. I spend £60,000 on a new Ford Ranger, but that 60k doesn’t show up on the income statement as 60k. Remember...it shows up as depreciation. My accountant uses a straight-line method to depreciate the truck over three years. That’s £20,000 a year, or £1,666.66 a month of depreciation for 36 months—but the day i bought the truck i parted ways with £60,000 from my bank account.

In an ideal world cash should track net profit pretty closely, but for start-ups, or those businesses that are struggling—the discrepancy between profit and cash can be fatal.

Let’s continue to use Visa‘s financial statements as our walkthrough example for completeness.

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As a business co-owner I’m constantly spinning five plates at any one time. I want to focus more on the future of my business—capital allocation and identity—but i’m distracted by the now and day-to-day running of my business.

As an operator this is to be expected. After all, it’s unrealistic for 99% of people to expect for themselves the typical day that Warren Buffett has famed: read for 5-6 hours a day and make capital allocation decisions. The key distinction though; Berkshires businesses are run by their owner-operators, whereas for the rest of us—we’re left to run them and make capital allocation decisions.

That’s why for most of us the dream of reading 5-6 hours a day is just that—a dream.

A big part of how companies survive—and continue to thrive is because they deliver on what they’ve promised. But, the other side to that coin is financial intelligence. Once again owner-operators can look to investing concepts to better understand how their own business is running. The two are symbiotic. If you don’t understand why revenue isn’t cash, or know that your company gets paid on average 45 days when it should be 30, you’ll find yourself in hot water quicker than you can say ”how the hell has this happened?”

Because time is typically tight it deserves an appropriate solution. Once again we can draw from a legendary investor: Charlie Munger. Munger once told a story about the importance of using checklists to combat our built in biases and used a pilot as his example. To paraphrase, Munger said a pilot, regardless of how many flights they’ve flown will use the same checklist before each flight; and that if an intelligent professional like a pilot still uses a checklist, then there isn’t any good reason at all why you shouldn’t be using one as well.

With that in mind, I’ve produced a pdf with 45 financial metrics and examples I believe owner-operators must know to better understand their business.

45 Financial Metrics For Owner Operators

10.8KB ∙ PDF file

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I’ve also put these metrics in a .csv for those of us who use flashcard software such as Anki to learn.

45 Financial Metrics For Owner-Operators (Flashcards)

Until next time, Karl.

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This is the second instalment of my How to Design the Systems That Run Your Business series. A series dedicated to helping business owners and operators run their businesses more efficiently, including how I run mine. To read the first article on designing and monitoring feedback loops please click here.

Every system has a boundary, and the first act of the system builder is to draw it. This sounds like an analytical exercise—study the problem, identify the relevant variables, include them—but it’s not. Boundary decisions are strategic choices, often the most consequential ones an organisation makes, because they determine what you can control, what you can accumulate, and what you must take as given.

Draw the boundary too narrowly, and you will be blindsided by forces you assumed were someone else’s problem. Draw it too broadly, and you will drown in coordination costs. The history of corporate strategy is littered with examples of both errors, and the theoretical and practical tools for thinking about boundaries—from Coase and Williamson to Ashby—remain among the most powerful and underused frameworks in organisational design.

Why firms exist: Coase, Williamson, and the logic of boundaries

Negotiating terms, writing contracts, monitoring performance, and finding the right counterparty all have a price attached to them—directly or indirectly. Ronald Coase’s 1937 paper “The Nature of the Firm” asked a deceptively simple question to his economic counterparts: if markets are efficient, why do firms exist at all? His answer was transaction costs. Using the market isn’t free. When costs are high enough, it makes sense to bring them in-house, where management can direct their resources through authority rather than by price. Hence the need for companies.

This presents a boundary question: how big should a company be? When the cost of organising one more transaction internally equals or exceeds going to the market, then going to the market is the most efficient thing to do. The company has expanded past its boundary and it is no longer cost-efficient to keep it internal.

The implications are significant:

• Firms are not just production functions—they are governance structures that exist because markets are imperfect

• The boundary of the firm is an economic decision, not an organisational one

• Vertical integration, outsourcing, and make-vs-buy decisions all flow from this logic

The business operator should constantly be asking: where is my boundary? and what makes sense to keep in-house versus outsource? This applies not only to finances, but to all resources: time, energy, and capabilities. At the micro level, the operator should be checking that what sits within their boundary is making them more resourceful—not less.

There are no hard and fast rules when it comes to boundaries. They contract and expand as markets change, meaning you must adapt to them as well.

Oliver Williamson, joint 2009 Nobel Prize winner in Economics, operationalised Coase’s insight through the concept of asset specificity—the degree to which an investment loses value when redeployed to a different use or relationship. Williamson identified four types: site specificity (an oil refinery cannot be moved), physical asset specificity (specialised tooling designed for a single product), human asset specificity (knowledge and skills tied to a particular relationship), and dedicated asset specificity (general-purpose investments made for a specific buyer that would create excess capacity if the contract ended).

When asset specificity is low, market transactions work well. Buyers and sellers are interchangeable, contracts are straightforward, and competition disciplines behaviour. When asset specificity is high, bilateral dependencies emerge. A factory line built to a single customer’s requirements, a skilled worker trained in proprietary systems, or a contractor who has built up years of accumulated client knowledge cannot easily walk away. This creates hold-up risk: the other party can renegotiate better terms after you’ve committed, knowing you can’t easily leave. You have that sunk cost feeling.

Williamson states that when asset specificity is high, transactions should be internalised, where managerial authority replaces contractual negotiation. The company’s boundary, then, is a governance decision: it sits where the risk of opportunism in the market exceeds the cost of bureaucratic coordination within the hierarchy.

Boundary decisions done well

Apple’s approach to integration is a masterclass in selective boundary-drawing.

Apple designs its own silicon, operating systems, and retail experience, but outsources final assembly to Foxconn and chip manufacturing to TSMC. Why don’t they just do everything? The reason they don’t is a masterclass in selective boundary-drawing: Apple integrates where tight coupling between hardware and software creates differentiation that cannot be achieved through arms-length contracts, and outsources where the bottleneck is commodity-scale manufacturing.

Apple’s decision to design its own processors is the Transaction Cost Economies framework in action. In 2008, Apple acquired PA Semi, a small processor design house, for $278 million. In 2010, Apple launched the iPad with the Apple-designed A4 chip—the first Apple system-on-chip. By 2020, Apple had introduced the M1 chip, which ended their reliance on Intel for Mac processors. Steve Jobs captured the strategic logic by quoting Alan Kay: “People who are really serious about software should make their own hardware.” It’s not that Apple could make better chips than Qualcomm or Intel in some abstract sense—but that a chip designed for a single entity can optimise for things a general-purpose chip cannot: power consumption, security architecture, and hardware-software co-design.

Amazon’s boundary was drawn not from selective integration—but sequential expansion.

In his 2023 shareholder letter, Andy Jassy described building something called “primitives“—core capabilities like warehousing, picking, packing, and shipping that can be turned into new products. Internal logistic primitives turned into Amazon Prime, an online store selling books turned into an everything store, and internal infrastructure needs turned into AWS. This boundary strategy wasn’t selective, but sequential. Each internal need was externalised into a product that fed into the Amazon flywheel.

The pattern at Amazon is consistent: solve an internal problem, build the infrastructure, then externalise it as a platform—expanding the firm’s boundary and feeding the flywheel simultaneously.

It’s easy to look for companies that have demonstrated a masterclass in not only designing their boundaries but executing them. Let’s now look at two that got it terribly wrong.

Boundary decisions gone wrong

Boeing’s “efficiency” boundary design ends up being a plane crash.

The Boeing 787 Dreamliner programme is an example of catastrophic boundary failure. Boeing outsourced up to 70% of the aircraft’s design, engineering, and manufacturing to more than fifty tier-one suppliers across the globe. The budget ran to an estimated $40 billion, dwarfing their original estimate of $5 billion. As well as being 40 months late, Boeing’s final assembly line was held together with temporary bolts purchased from Home Depot after supplier Alcoa could not ramp up fastener production fast enough.

How could a company like Boeing—known for engineering excellence—get it so wrong? UCLA Anderson Professor Christopher Tang had an answer:

“You only know what’s going on with your tier 1 supplier. You have no visibility, no coordination, no real understanding of how all the pieces fit together.”

I would say it’s pretty critical that you have a deep understanding of how the parts of an aircraft should fit together.

Boeing’s mistake was expecting to receive complete, flight-ready assemblies, but instead receiving sub-assemblies requiring extensive rework. They had fallen into a classic systems trap: information delay. They had modelled their system on Toyota’s supplier-development approach, but failed to build the relational infrastructure that makes Toyota’s system work. Toyota shares information, conducts joint improvement activities, and treats key suppliers as extensions of itself—relationships built over decades of investment in human asset specificity. Boeing handed off complete design control to suppliers based on price, not relationships. These are exactly the high-specificity transactions that Williamson predicted would fail under market governance. In his Nobel lecture, Williamson used the outsourcing of Boeing’s highly specialised fuselage to Vought Aircraft Industries as a perfect example of something requiring significant investment in specific assets that should have been kept in-house.

Boeing’s 787 Dreamliner is a case study in misaligned organisational boundaries—a prime example of how prioritising cost structure over quality control can massively backfire.

How Kodak had the future of photography in its hands and let it slip.

In 1975, a twenty-four-year-old Kodak engineer named Steven Sasson built the world’s first portable digital camera—a 3.6-kilogram device capturing 100×100 pixel black-and-white images onto a cassette tape. Management’s reaction, as Sasson later told the New York Times, was: “That’s cute — but don’t tell anyone about it.” It’s not that Kodak was ignorant of the new technology; they filed a patent in 1977 and earned billions of dollars in licensing revenue from it. The problem was the fence line Kodak had drawn around the company—their boundary. Kodak’s business was film, paper, chemicals, and processing. Digital photography didn’t fit their model or their identity. They treated it as exogenous—something to be curious about, rather than an endogenous capability to be developed from within.

When Kodak’s leadership did diversify, they moved into adjacent markets by acquiring Sterling Drug for $5.1 billion in 1988. Their logic seemed sound: “we know chemistry, drugs involve chemistry, therefore this is adjacent.”

The problem wasn’t their logic—it was that they weren’t following where their customers were going: digital. The Sterling Drug investment was sold off in pieces by 1994, and in 2012 Kodak filed for bankruptcy, thirty-seven years after one of their own engineers had built the future.

Kodak restricted the expansion of their boundary by actively deciding not to meaningfully pursue digital photography. This illustrates how inside-view thinking (we’re good at chemistry) can crowd out outside-view thinking (the market is moving somewhere we aren’t).

These four examples—two good, two bad—lead us into the theoretical framework that explains why Apple and Amazon succeeded, and why Boeing and Kodak didn’t. Variety.

Ashby’s Law and the question of variety

W. Ross Ashby’s Law of Requisite Variety, published in An Introduction to Cybernetics in 1956, provides the theoretical foundation for understanding why boundary decisions matter so much. The law states, in Ashby’s own words, that “only variety can destroy variety”—meaning that for a system to remain stable, its control mechanism must be capable of generating at least as many states as the disturbances it faces. A thermostat with only on/off settings cannot regulate temperature precisely; a manager with a single response to every problem cannot govern a complex organisation.

The implications for boundary-setting are direct. If you draw your system boundary too narrowly, your system will lack the requisite variety to handle disturbances from the environment. If you draw it too broadly, you waste resources managing internal complexity that does not contribute to matching external variety.

Organisations must be able to adapt to variety. Kodak’s boundary was drawn too narrowly by not assigning resources to digital—which was not only a clear market trend but a signpost from the future that chemical would be obsoleted by digital. The conglomerate’s boundary is often drawn too broadly, its variety impinged by size and coordination costs that offer little flexibility.

So, for you—the business operator or systems designer—how do you move from understanding Ashby’s Law to putting it into practice?

Stafford Beer’s Viable System Model (VSM) is essentially Ashby’s Law operationalised into an organisational architecture. Ashby says a viable system must match the variety of its environment. Beer asked a follow-up question: how do you actually design an organisation to do that?

The Viable Systems Model Framework

The Viable System Model (VSM) answers this by splitting the variety-handling problem across five subsystems:

• System 1: the operational units absorbing frontline variety

• System 2: the coordination needed between units to prevent confliction

• System 3: internal control and resource allocation (the “inside and now”)

• System 4: external intelligence gathering (the “outside and future”)

• System 5: identity and policy, which sets the purpose and balance of the organisation

Through this framework, Beer recognises that you can’t centralise all variety-handling at the top. The environment moves too fast and is too complex, with informational delays inevitably distorting what’s happening in real time. A viable system should absorb local variety. System 1 units handle the complexity of what’s happening on the ground. System 4 is focused on information gathering—not just to plan for the future, but to protect it. Each system offers a buffer.

Learning about the VSM, you begin to see why Warren Buffett and Charlie Munger preferred to run Berkshire Hathaway the way they did. Their decentralised model continued to allow exceptional management to run and absorb the complexity of day-to-day operations—something both Warren and Charlie would gleefully admit was outside their Circle of Competence. Warren and Charlie’s role was clearly Systems 4 and 5: looking for external opportunities by reading the market and focusing on increasing shareholder value.

If you've found value in this essay so far, what follows is where the theory meets the ground. I walk through how I've applied Beer's five systems to my own construction business and the tools I've invested in, what they cost, what they saved, and the questions I'd now ask of any business before drawing its boundary. If that's useful to you, consider upgrading to TSOK+.

How I used the VSM framework to build my business’s systems

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18 months ago, my co-business owners and I turned down the opportunity to refurbish a beautiful four-storey Georgian building in Manchester city centre. Not because we couldn’t do the work — we’d already completed a smaller, similar scheme two years before. Not because the margin was wrong — it would have been our largest ever contract. We turned it down because the client had a particular kind of energy. The sort that tells you the relationship will cost you, and your reputation.

All it took was eight words in a pre-start meeting: “I don’t want to hear about price increases.”

Thinking about making decisions is additive. Frameworks for evaluating options, scoring criteria, weighing upside. The whole apparatus of good decision-making, as it’s usually taught, is about getting better at choosing what you want.

The more durable skill is the opposite. It’s subtraction. Building a clear picture of what you won’t do — and trusting your gut when the moment arrives.

This isn’t exactly a new idea. It shows up across disciplines under different names.

The Stoics called it via negativa — the idea that you understand something more reliably by what it isn’t than by what it is. Taleb borrowed it for investing: remove the fragile, and what survives tends to be worth keeping. Munger called it inversion — “tell me where I’m going to die, so I’ll never go there.” Buffett built the too hard pile as a literal mechanism: a category of decisions not refused individually but pre-refused as a class. The pile doesn’t require fresh analysis every time. The work was done once.

What these frameworks share is the same underlying logic: subtraction as decision technology. You’re not picking from a menu. You’re shrinking the menu until only the obvious things remain.

Most operators have a wish list for the work they want. Very few have an exclusion list. The ones who do tend to move faster — not because they’re smarter in the moment, but because the moment requires less of them.

The exclusion list does the cognitive work in advance. This client profile was just a hard no. It wasn’t that we tried to squeeze more money from clients — it was that he’d already delayed the job by two years (construction materials and labour invariably go up at least once a year), hadn’t paid a penny to the design team who’d designed his project, and very much thought of himself as some sort of private equity geezer. He even turned up to a meeting with a Great Dane in tow. I can only assume he was trying to intimidate us. His problem was he thought that bringing a dog to a meeting with prospective contractors would do that.

Examples like this also sharpen your circle of competence — not as an abstract boundary, but as a working document. Knowing what you won’t touch tells you more about what you actually are than any mission statement.

The hard part isn’t making the list. It’s trusting it when something sits just inside the line and the upside looks attractive. That’s when the list earns its keep.

What’s on your exclusion list — and have you ever written it down?

Until next time, Karl.

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The second instalment of my How to Understand Financial Statements series explains how to master the balance sheet. Warren Buffetts first statement he picks up. The first instalment on understanding the income statement can be found by clicking here.

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Out of the three financial statements, the balance sheet is more than likely to be the most confusing to you. After all — profit derives from revenue, and cash is — well, cash. But the balance sheet is the first financial statement that Warren Buffett picks up. Why?

Simply put, the balance sheet is harder to manipulate than the income statement. For business operators and self-taught investors, it’s not that you should understand it — you absolutely need to.

This is part two of the How to Understand Financial Statements series. Part one, is free and taught you How to Read an Income Statement. Today, you’ll be learning why the balance sheet always reveals the most about a company.

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Not all problems are the same types of problem.

The biggest mistake you can make as an operator is to treat a complex situation as if it were merely a complicated one. Every problem lives somewhere — and where it lives determines how you should respond to it. The Cynefin Framework is a decision-making tool developed by David Snowden at IBM in the late 1990s. Its name comes from the Welsh word “habitat” or “place of belonging,” and there are five domains which help you categorise what type of problem you’re facing.

Domain 1: Clear

These are the problems where cause and effect are obvious to anyone paying attention. The rules are known, best practices exist, and you just need to follow them. The approach is: sense → categorise → respond.

For my construction business, this can be anything covered by a standard, code, or regulation. We have risk assessments and method statements to help mitigate and control risks and hazards. We follow building regulations set by the UK government or the HSE for safety and quality control. Fire door specifications or concrete mix ratios are pre-determined against rigorous testing. There’s no debate about the right answer — you just have to apply the known procedure. When dealing with novelty, if you reach for a solution that won’t fit, it simply won’t work.

The risk here for operators is complacency: you cannot treat all problems like they’re Clear problems.

Domain 2: Complicated

Cause and effect still exist, but you need expert analysis to identify them. The answer isn’t obvious, but it is knowable — given the right expertise. The approach is: sense → analyse → respond.

Just this week one of my site managers came across a complicated problem but didn’t know how to respond, because she determined she lacked the knowledge to answer it. She thought this was a Clear domain problem. The question came from a specialist subcontractor about the design of their bolts for anchoring down the steel to the new foundation. It isn’t a question we’re qualified to answer — hence structural engineers being part of the design team. The only solution was to tell her to remove the stress of having to deal with this and get confirmation from the expert — which in this case was the structural engineer.

Complicated domains need experts. The data and logic are there — but somebody who knows how to sieve through it and correctly analyse it is needed. It’s the territory of experts and professionals, where there could be more than one good answer — but both come from rigorous analysis.

Domain 3: Complex

Here’s where most interesting business and investment decisions actually live, and where most leaders get into trouble. In Complex systems, cause and effect can only be understood in retrospect. You can’t analyse your way to the answer in advance because the system itself changes in response to what you do. The approach shifts: probe → sense → respond.

Capital cycles aren’t predictable by modelling. I can observe signals of where I believe the UK construction industry is within that cycle, but I can never be 100% sure we’re at the bottom or the top. I can only plan for such eventualities and remain adaptive. The danger in Complex terrain is demanding certainty before acting — or, equally bad, using one successful probe as evidence of a repeatable formula. The system keeps moving. Treating the current shortage of raw materials because of the Iran/Israel/America conflict as a Clear or Complicated domain problem means I am either trying to analyse a moving target and will act too slowly, or treating the issue as having a standardised process and making erroneous decisions.

Domain 4: Chaotic

Cause and effect have no relationship at all — there’s no time to analyse. You need to act immediately to establish some kind of order, then move into sense-making. The approach is: act → sense → respond.

Here, you act to contain, stabilise, and prevent further harm or problems. My Royal Marines background is instructive here: the ability to act under pressure without complete information, establish some order, and then begin to understand what happened. Operators who freeze because they want more data in Chaotic situations make things worse. What’s the absolute worst thing that could happen within your business — a complete shit show where the consequences are extreme? That’s this domain.

Domain 5: Disorder

This is the most dangerous domain, and the least discussed. It’s not a type of problem — it’s the state of not knowing which domain you’re in. When people are in Disorder, they default to their comfort zone. The expert reaches for analysis. The instinct-driven operator acts before sensing. The process-follower looks for a procedure. Most bad decisions happen here — not because people are stupid, but from misdiagnosis.

The Central Lesson

The framework’s real value comes from having a clear understanding of the boundaries. Clear problems can become Chaotic if you become complacent. Seeking certainty before action confuses Complex problems with Complicated. And the instinct to treat everything as Complicated — to keep hiring more consultants, to run more analysis — is a particular trap for intelligent, analytical people.

The diagnostic question worth keeping in your back pocket: “Am I analysing this, or am I experimenting with it?” If you need to experiment to find out, you’re in Complex terrain — and your job is to design good probes, not better analysis.

If you found this useful, the paid tier of The School of Knowledge+ goes deeper into the frameworks that actually change how you operate and invest. Recent issues have covered Hamilton Helmer's 7 Powers — the competitive strategy framework used by some of the world's best investors — with worked examples, diagnostics, and case studies you won't find summarised anywhere else. If you want to think more clearly about business and capital, it's worth the upgrade.

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This week i’ve been digging back into systems thinking; mainly understanding how to diagnose and alter feedback loops. Essential reading for those wanting to understand the drivers behind their business behaviours.

Until next time, Karl.

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In the big picture, one store’s inventory problem may seem trivial and fixable. But imagine that the inventory is that of all the unsold automobiles in America. Orders for more or fewer cars affect production not only at assembly plants and parts factories, but also at steel mills, rubber and glass plants, textile producers, and energy producers. Everywhere in this system are perception delays, production delays, delivery delays, and construction delays. Now consider the link between car production and jobs—increased production increases the number of jobs allowing more people to buy cars. That’s a reinforcing loop, which also works in the opposite direction: less production, fewer jobs, fewer car sales, less production. Put in another reinforcing loop, as speculators buy and sell shares in the auto and auto-supply companies based on their recent performance, so that an upsurge in production produces an upsurge in stock price, and vice versa. That very large system, with interconnected industries responding to each other through delays, entraining each other in their oscillations, and being amplified by multipliers and speculators, is the primary cause of business cycles.

The difference between a systems thinker and a system builder lies in a single verb: design. To read Meadows is to learn how to see feedback loops in existing systems—to trace reinforcing spirals and identify balancing mechanisms. But the operator’s question is harder: how do you engineer feedback into a system that does not yet have it? How do you decide what signal to amplify, what delay to shorten, what correction to automate? The shift from observation to architecture is the shift from analysis to craft, and it is the foundational skill of anyone who builds organisations, products, or supply chains.

A well-designed feedback loop compounds because every major decision is evaluated against the loop’s logic, not against isolated metrics.

Zara’s customers shop at their stores 250% more than other fashion retailers—not because their clothes are inherently better than everybody else’s—but because they understood how to design effective feedback loops.

The flagship brand of Inditex, Zara’s feedback loop was built on speed and efficiency. Traditional fashion retailers typically take six to nine months to go from design to shops, with most of production done pre-season. Zara has compressed this down to fifteen days. Under a quarter is designed before the season begins, with over half designed, manufactured, and shipped mid-season in direct response to customer demand. Store managers across more than six thousand shops in over eighty countries transmit sales data and qualitative observations—”this colour shirt isn’t selling,” “we can’t ever have enough stock of this winter coat”—to a centralised data-processing centre that operates around the clock. Small initial batches, sometimes just a few items, are sent out to test demand and feed data back into the system.

The logic behind the loop runs as follows: fast response to demand generates higher sell-through rates (roughly 85 per cent of items sell at full price, against an industry average of around 60 per cent), which generates better margins, which funds the proximity manufacturing infrastructure. There was also a deliberate choice to house roughly 50 per cent of production hubs in Spain, Portugal, Morocco and Turkey in lieu of Asia to make this kind of speed possible in the first place. The average Zara customer visits seventeen times per year, compared with three or four for a typical retailer, because the product mix changes constantly.

The feedback loop is not merely observed; it is architecturally embedded in every operational choice—from the location of factories, to the design of the RFID-tagged supply chain, to the twice-weekly ordering cadence.

But not every feedback loop requires speed to be effective—and not every successful feedback loop has to be reinforcing.

Between 1948 and 1975, Taiichi Ohno and Eiji Toyoda created Toyota’s Andon system—one of the most elegant balancing feedback loops ever designed for a production environment. When a worker on the assembly line spots a fault, defect, shortage, or safety hazard, they pull a cord (or press a button in modern versions). A coloured light displays above the assembly line—green for normal, yellow for help requested, and red for line stopped. The word “Andon” means “paper lantern” in Japanese, hence the colours. Once initiated, a team leader goes over to thank the worker who pulled the cord. If the problem can be fixed within the cycle time, the line continues; if not, the affected station is stopped until the problem is resolved. The frequency and nature of every stop is logged and fed into Toyota’s continuous improvement process, Kaizen.

Problems on a Western production line are thought of as poor performance, whereas at Toyota—they are seen as the highest form of quality control. At one Toyota plant, when the average number of Andon pulls per shift dropped from a thousand to seven hundred, the CEO called an all-hands meeting—not to celebrate but to investigate. Either problems were being hidden or standards were too low. For Toyota, the absence of correction is itself a danger signal because it implies the balancing feedback loop has gone quiet.

The NUMMI joint venture between Toyota and GM in the 1980s proved the system was transferable: the Fremont, California workforce, previously considered GM’s worst, became its best within a year of adopting the Andon system and its cultural infrastructure.

Toyota embedded in their production lines a system that rewarded patience over speed, quality over output metrics. They demonstrated another clear understanding of feedback design when they also created a negative feedback loop—with the purpose of mitigating material waste.

Toyota’s pull-based system ensures materials are only moved down the production line as and when they are needed, resulting in maximum efficiency. This is the inverse of a push-based system that forecasts when certain materials are expected to be needed.

At Toyota, Kanban cards are physical tokens of demand, visible to all. The card-based production control system operates as a balancing feedback loop: downstream workstations signal to upstream workstations when they need more material. This pull-based system creates a negative feedback loop that regulates production by actual consumption rather than by forecast, preventing the overproduction that bedevils push-based systems.

The Zara and Toyota cases are instructive, but they're the easy half of this essay. The harder question is what happens when feedback loops go wrong — and more usefully, what you actually do about it. Below i've covered three failure modes (with the case studies to match), the single highest-leverage intervention for each, and a practical audit framework you can apply to your own business. If you've ever explained a bad quarter with "the market shifted" or "we didn't see it coming," that section is probably worth your time. There's also a downloadable worksheet for paid subscribers.

When feedback loops fail: too slow, too fast, or miscalibrated

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What’s the difference between being stuck in a job you despise for 40 years and a 12 x 8ft cell? Nothing. The sad fact is—most people get up and go to work for somebody else’s version of what it means to live life. You feel paralysed, trapped in a body betraying your own free will. You don’t want to be here—you swore you weren’t going to be—but here you are anyway.

There’s something lifeless about following another person’s dreams. When you’re a kid, your dreams are of being a rockstar, an athlete, an artist. I was always the footballer scoring the winning goal in the World Cup final. Nobody wanted to be a cog in a massive wheel.

You say dreams are for kids, but i disagree. They just look different as an adult.

A dream as an adult is working on something you value—not despise. A dream is having enough money to share experiences with the people you love—not dislike. You waste 40 hours of your week, or more bluntly—86.6 days of your year on a job you couldn’t care less for. A dream as an adult is waking up in the morning and looking forward to the day—not in a whimsical way, but because you’re ready for whatever the day throws at you.

A dream as an adult is doing something with purpose.

I never once imagined as a kid, or even in early adulthood, that i would enjoy writing. Even worse—enjoy writing about stuff like capital allocation, mental models or how to be a systems thinker. But you can’t choose who or what you fall in love with. 15-year-old Karl would probably be taking the piss out of 36-year-old Karl. Perhaps because i’m approaching 40, i’ve been thinking about midlife crises a lot more. I don’t think i’m the susceptible type, but i also didn’t see my future love for financial ratios either. But, why do people have midlife crises? I think people have them for many reasons, but i think many come back to one thing: purpose. Or more specifically—a lack of.

Us humans are a stubborn bunch. We’d rather be an insider suffering with the many, than an outsider. To go against the grain is to choose isolation. Writing about business couldn’t sound any more boring if i tried; it also sounds counterintuitive to what i’ve spoken about, but let me explain: The shoes on your feet, the coffee in your cup, and the eggs you ate for breakfast all come from businesses. People are businesses—plain and simple. Without people there can’t be any businesses.

So let me ask you again: What’s the difference between being stuck in a job you despise for 40 years and a 12 x 8ft cell? Nothing. But, let me ask it differently: What’s the similarity between being stuck in a job you despise for 40 years and a 12 x 8ft cell? A lack of purpose. Direction.

The School of Knowledge was born as a placeholder for my thoughts and has turned into me distilling lessons i’ve learnt from being a nobody to a Royal Marine, to travelling the world, to getting paid thousands of dollars a day to cleaning ovens for minimum wage. I’ve built many lives in my 36 years and they’ve all taught me lessons—lessons that as a business owner-operator i want to share with people who are trying to build a life or career they want. If you just want the mental models, concepts and frameworks then stay for those alone. If you just want to learn about how to run or start your company and gain financial understanding you can do that too. But for those who want access to it all—warts and all—there’s an offer below waiting for you to just accept it.

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For those that want to keep on reading about uncertainty and changing your beliefs (or lack of) start here:

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Yesterday i published the third deep-dive on the 7 Powers series: Counter-Positioning. Essential reading for business owner operators:

Until next time, Karl.

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There are few occurrences in business as complex as the emergence and eventual success of a new business model. — Hamilton Helmer

After the First World War, the French built a line of concrete fortifications, obstacles, and weaponry along their border to protect themselves against the Germans, famously known as the Maginot Line. Up until the Second World War, war was almost predictable, slow, and recently fought in filthy trenches just metres from your enemy. You couldn’t blame André Maginot’s rationale for building the line — after all, it was the Germans who had been defeated the last time out.

But the Germans — bankrupt, embarrassed, and sent to the world’s metaphorical naughty corner — developed something so extraordinarily novel it birthed its own name: Blitzkrieg. And it was something else. The Maginot Line never stood a chance as the Germans ravaged their way through Europe to Paris, unfortunately developing its own signature branding: “For expensive things that offer a false sense of security.”

However, this isn’t a lesson on military ignorance: it’s about the most consequential Power in Hamilton Helmer’s 7 Powers. A Power whereby the incumbent can know of the novel business model, but declines to alter their strategy until it’s too late and they’ve been steamrolled. This Power is called Counter-Positioning.

This is the third deep-dive in the 7 Powers series — Hamilton Helmer’s landmark book on how businesses use strategy and value to create consistent differential returns—something he calls Power. In the introductory article, I explained why value creation alone isn’t a moat; in the first deep-dive, I covered Scale Economies; in the second, we examined Network Economies. Let’s now get into the third Power: Counter-Positioning.

What is Counter-Positioning?

A newcomer adopts a new, superior business model which the incumbent does not mimic due to anticipated damage to their existing business. — Hamilton Helmer

Jack C. Bogle had a radical new idea: an equity fund that simply tracked the market. On May 1st, 1975, he managed to persuade a reluctant Wellington Management board to back his company, Vanguard. Up until then, funds had been run by managers who collected fees and commissions — but Bogle’s Vanguard would operate at cost, return all profits to fundholders, and eventually abolish sale commissions.

The idea didn’t go down well — initial subscriptions reached just $11 million by 1976. The sticking point was that Bogle needed brokers to help distribute the fund, but the fund’s premise was centred around not needing their input. It’s hard to get people to do things for you when they have no self-interest.

And just like the French were thinking rationally when they built the Maginot Line, it’s easy to see why the active management firm Fidelity weren’t interested in this new business model. No star fund managers, no research department, and an unwillingness to attempt to beat the market — it went against everything that made Fidelity what it was.

Fidelity were awake to the threat alright — they just fancied their model more than Vanguard’s. That’s what Counter-Positioning actually is: the incumbent knowingly decides against adopting the new business model. And it’s far more unsettling for investors than a story about incumbent blindness.

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The Mechanisms of Counter-Positioning

Compared to Vanguard, Fidelity Investments possessed a structural disadvantage: they had to consistently beat the market before deducting their fees to arrive at the same place Vanguard was aiming for — to track the index. That’s no small task, and Fidelity was fighting against three forms of collateral damage:

Revenue cannibalisation: Vanguard directly ate into Fidelity’s active management fees by offering customers a way to circumvent them entirely — opting for Vanguard’s fund instead. This is similar to how Blockbuster relied on late fees (50% of revenue) and Netflix came along with a superior model: digital rental and no late fees.

Distribution destruction: The new model undermined Fidelity’s reliance on brokers, who collected their fees regardless of how well the fund performed.

Identity destruction: The most powerful of the three. Fidelity’s whole mythology was built on the premise that people needed their expertise — their star managers, their research, their brokers. Admitting that Vanguard had a superior model wasn’t just breaking a historical promise to customers: it was questioning the very identity of the company. Some businesses just can’t look themselves in the mirror.

Benefits and Barriers

The benefit

The new business model is superior to the existing one by offering considerably lower costs, or the ability to charge higher prices. For Vanguard, they completely negated portfolio manager fees, broker fees, and trading costs simply by not needing their ‘expertise’. Along with returning profits to fund-holders, this allowed Vanguard to take market share from Fidelity.

The barrier

Compared to the other Powers, the barrier for Counter-Positioning is a tad more mysterious. The barrier is formed from the incumbent’s own willingness to deliberately not engage with the newer business model, believing the potential returns are inferior to their legacy model and won’t make up the collateral damage from switching. Their existing model acts as a prison. It wasn’t that Fidelity were caught on their toes, or lacked foresight — it was determined through a thoughtful, calculated process that ultimately concluded they just couldn’t switch financially. A rational decision by any means.

“Why would anyone settle for average returns?” — Ned Johnson, Fidelity

Case Study: Vanguard

So how did Bogle’s bold move in 1976 pan out? Let’s look at Vanguard’s assets under management (AUM):

• August 1976: $11M at launch

• Mid-1977: $17M (Helmer’s figure, from the book)

• End of 2015: $3T (Helmer’s figure, from the book)

• December 2025: $12 trillion total, of which $10.1 trillion is index assets and $1.9 trillion is active1

That progression — from $11 million to $12 trillion over nearly 50 years — is one of the most dramatic compounding stories in financial history. If we calculate the CAGR:

CAGR = (12,000,000 / 11)^(1/49) − 1 = approximately 32.8% per year

(Both figures expressed in $M: $12 trillion = $12,000,000M; starting AUM = $11M)

But it’s important to note a caveat: this isn’t an investment return. It’s a measure of business growth — AUM expansion driven by two compounding forces simultaneously: market appreciation on existing assets, and net new inflows as investors moved from active to passive. What the CAGR captures is the combined effect of a superior product attracting capital while the incumbent was rationally paralysed. Every year Fidelity decided not to fully replicate Vanguard’s model, more assets migrated. The CAGR isn’t measuring Vanguard’s investment skill — it’s measuring the rate at which the Counter-Position compounded against Fidelity.

Fidelity’s rational decision not to engage with the new model may have been smart in the short term, but catastrophic long term.

The fee cliff

It wasn’t until 2018 that Fidelity launched their Zero funds2, introducing a 0% expense ratio to compete with low-cost index providers. Just 42 years later.

Interestingly, average expense ratios increased through the 80s and 90s, rising to an average of 1.04% in 1996. The incumbent active funds weren’t even cutting fees in response — they were raising them. Eventually, passive investing became impossible to ignore, and by 2021 expense ratios had fallen to approximately 0.46% compared to 0.06% for index funds — a gap of roughly 7.5x.

Fidelity manages roughly $5.4 trillion in discretionary AUM today. At a blended active fee of even 0.50%, that’s $27 billion in annual fee revenue. Vanguard’s average expense ratio across its $12 trillion AUM is approximately 0.05–0.06%, producing around $6 billion in revenue despite managing more than twice the assets. That gap — $27B vs $6B on comparable AUM — is the collateral damage number made concrete. You could argue that Fidelity would have been foolish to move into passive indexing any sooner than they did.

That’s what makes Counter-Positioning as a Power so interesting. The incumbent can survive — thrive even — but they are rationally unwilling to copy the new entrant because the numbers don’t math the way they want them to math. Fidelity survived. Blockbuster did not.

The distribution network problem

Not only did the numbers not stack up, but Fidelity was built on incentives. Active fund managers were paid well for beating the market, advisors earned a commission for getting customers to move money into Fidelity’s funds, and brokers collected fees for sorting out the admin. It was a win-win-win for all involved. And besides, most people who invest in funds look at total fees of, say, 2–3% per year and think: that’s not a bad deal, is it? It’s only when you do the maths and see the compound effect of those fees over 30 years that you start to have a heart attack.

Better to do that maths in your healthier years, i’d say.

For Fidelity to have entered this market in the mid-seventies would have meant a complete reconstruction of their foundations, and from being in the construction industry i can tell you one thing: if you need to change your foundations, whatever’s sitting on top of them — a building, a business model — has to come down.

The identity trap

Most interesting, i think, is how it would have looked if Fidelity had changed course. A prestigious firm with ‘world-class’ portfolio managers suddenly tells customers: “we actually think we’ve found something better — and guess what, it’s practically free.” Maybe great for those just signing up, but a potential headache for those already heavily invested. Having a reputation to uphold is costly.

So, Fidelity saw exactly what Vanguard was doing. They had the capital, the distribution, the brand, and the talent to respond. They understood the new model completely. So why did it take them over forty years to copy them?

In the paid section, i look to answer this question, along with:

• The precise calculation Fidelity made — and why it was rational, not lazy

• Helmer’s decision tree for evaluating any Counter-Position — and what it reveals about durability

• The three ways incumbents fail to respond: Milk, History’s Slave, and Job Security — and why only one of them is investable

• How to calculate whether a Counter-Position will hold or collapse

• Six red flags to watch out for that tell you if Counter-Positioning will fail

• Where weak versions of this Power appear — and what they’re actually worth

Helmer’s Decision Tree: The Taxonomy of Incumbent Failure

Stand-alone attractive?

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Every capital allocation decision you make means foregoing other options available to you—and getting those decisions right is the difference between good investments and great ones.

Between a 12% return or 20%.

Great investors such as Charlie Munger and Nick Sleep thought about capital allocation a lot, and i leaned on their way of thinking when i had to make a capital allocation decision for my business this week.

The construction industry is cyclical. We’re usually one of the first industries impacted by recessions and usually the last out of one. The last couple of years i’ve seen clients delay more projects, material and labour prices double and national insurance rates shoot up, all contributing to a difficult period for the industry.

But, a declining industry offers opportunities for businesses that operate well, have healthy margins and, more importantly—have cash on their balance sheet ready to deploy.

Being a Principal Contractor in the UK, you are heavily reliant on being competitive enough to win jobs through the public or private sector, which in general is just a race to the bottom with margins amongst the lowest in any industry. A big part of this is the layers upon layers of bureaucracy in the industry—all taking their fees whilst passing on the risk to the contractors. Fair enough—but i want more reward for my risk.

A couple of weeks ago i was presented with software that cut right through those layers of bureaucracy and went straight to the source of what we wanted to do as a company: buy land, build commercial buildings on it, and then sell or rent them. No estate agents to deal with, no developers, no consultants—no waiting around for people to do things for you. No tendering. A direct link to the landowner, with a service that even sent them letters with your offer.

It was great, but the problem was that the software was expensive and i declined their service. But, a few days later i sat and thought about the decision i’d made. With this software i could do everything remotely. i didn’t even need to leave my desk. By rejecting their service i was accepting that i was willing to carry on searching for land the old way; scrolling websites, communicating with estate agents, taking time out of my day to go and view the land, and relying on them to get back to me whenever they pleased. Not to mention the synthesised bidding wars they create.

i added up the time it would take for myself or my business partners to do all of this, and conservatively estimated that the minimum would be two days a week if we were limiting our search to the North West of England, and were taking it half-seriously. We are also unquestionably up against other companies who have whole departments dedicated to doing something similar, with better resources and more capital.

Once i looked at the maths—the cost of one of us doing this manually for two days a week, or 104 days a year (not accounting for holidays)—it dwarfed the annual cost of the software. That’s before any savings from going direct to the vendor and developing and building ourselves.

The opportunity cost of not purchasing the software was too high, so i made a call with my tail between my legs and changed course (not before getting two months free).

i don’t have a crystal ball and time will tell if the investment pays off, but by understanding the concept of opportunity cost—by being able to work out the present value of future cash flows—i’ve given myself a reasonable edge and sought to take back more control over my company’s future prospects.

And that’s what The School of Knowledge hopes to assist you with. Making better business and investment decisions. There are no rose-tinted glasses here—i call a spade a spade and look to share everything i’ve found useful in getting to where i am today.

If you’re an operator—someone who does things—and would like to read more about capital allocation, opportunity cost and net present value, click through to the following posts:

For paid subscribers, next Saturday i produce a deep dive into the most paralysing form of business strategy: Counter-Positioning. To read the first two articles in this series click below.

Until next time,

Karl.

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Jeff Bezos built a $2.9 trillion company on principles that are almost two thousand years old. He just didn’t explicitly say so. Nobody reads Amazon’s Leadership Principles and thinks: this is a philosophy of how to live. But they should.

Bezos built Amazon because he understood The Lindy Effect: if something has been around for 2,000 years, it’s likely to be around for another 2,000. Unlike Western nations, where state and religion are separate—Bezos didn’t believe in severance. He built into Amazon a culture where business principles and personal principles weren’t two different worlds, but one.

Have backbone; disagree and commit is the courage to go against the grain. Before starting Amazon, Bezos had a well-paid job on Wall Street. When Bezos told his boss he was leaving, his boss gave him two weeks to think it over, but Bezos quit anyway. Deciding what to do in life—your purpose—is inherently hard, but perhaps Bezos listened to what Seneca had to say:

“Each time you want to know what to pursue or what to avoid, look to your highest good, the aim of your life as a whole. Everything we do ought to be in accordance with that aim. Only one who has the entirety of his life in view is in a position to arrange life’s particulars. Even with paints all at the ready, no one can render a likeness until he has decided what he wants to paint. That’s our mistake: everyone deliberates over the parts of life; no one over life as a whole.”

Bezos wasn’t looking at creating Amazon as a side project. He was looking to create his life’s work. If you align your work principles with your personal principles, you create consistency in everything you do.

Frugality is another example of that consistency—and perhaps the most counterintuitive one.

In the early days at Amazon, Bezos had employees use old doors as desks rather than buy new furniture, and reportedly still gives out a “Door Desk Award” to employees who find innovative ways to save money. This wasn’t about being cheap for accountancy reasons: it was to breed a culture of frugality into Amazon. Constraint breeds resourcefulness and self-sufficiency, and leads to invention: overconsumption leads to softness, bloat, and excess, which corrupt judgement.

“It is in times of security that the spirit should be preparing itself to deal with difficult times; while fortune is bestowing favours on it then is the time for it to be strengthened against her rebuffs.”

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That’s the Stoic parallel.

It’s easy for companies to get fat when food is aplenty, but Bezos was distilling in the Amazon culture what Seneca prescribed in the individual: use the good times to prepare for the hard ones.

The same logic runs through Amazon’s approach to trust (justice).

Bezos was famously willing to forgo profits for years to earn customer trust at scale because he valued their loyalty more than his bottom line. By obsessively focusing on customers in the form of low prices and maximum choice, he earned their trust. This discharging your duty to others, even when it’s costly to you in the short term, reminds me of what Seneca said:

“All his thoughts should be as distant as possible from personal advantages.”

It’s easy to scowl now (with the benefit of hindsight) that Bezos is a billionaire, but he wasn’t when he wrote these principles. What Bezos had to do, to instil in the Amazon culture, was to be right—and be right a lot.

At first this leadership principle looks a bit self-promotional, but to have any chance at doing anything well in life you have to be more right than wrong. It sounds overly simplistic, but aside from helping one’s ego, being right also builds something else—judgement. Or as Seneca would say: wisdom.

Judgement isn’t something you can read your way to. It’s built through decisions made, mistakes owned, and patterns recognised over time. That’s what Bezos was encoding—not a principle about being clever, but about developing the kind of wisdom that only comes from being in the arena.

“Besides, what grounds could I possibly have for supposing that a person who has no acquaintance with books will never be a wise man? For wisdom does not lie in books. Wisdom publishes not words but truths—and I’m not sure that the memory isn’t more reliable when it has no external aids to fall back on.”

Amazon’s 14 leadership principles are corporate speak, but I knew there was more to it than that. They were a philosophy: a set of beliefs and guiding principles that worked just as well professionally as they did personally.

The reason Bezos, or anyone interested in building something lasting, reaches for 2,000-year-old principles is because time distinguishes principles that work—from those that don’t.

Are your professional principles different from your personal principles? If yes, asking yourself why might just be the best decision you’ll ever make.

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Until next time, Karl (The School of Knowledge).

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When a product launches it attracts initial users. If the product is popular, more people flood to use it, making it even more popular. As it grows in popularity and user numbers, more people begin to use the product until it reaches a tipping point of no return. This self-reinforcing feedback loop is the power of Network Economies.

This phenomenon is behind the explosion of companies like Meta (Facebook), Uber, LinkedIn and TikTok. Meta and TikTok become more valuable as people use the apps to communicate and share their lives with friends and family. LinkedIn becomes more valuable as more professionals join the network, meaning you no longer have to physically go out to network. As more people use Uber, more drivers join, and the days of queuing up in the rain at a taxi rank are over.

Not only do they create more value as they become ever more popular, but they also become increasingly difficult to move away from as user count increases.

If Scale Economies is math: Network Economies is psychology.

This is the third piece in the 7 Powers series — a deep-dive into Hamilton Helmer's framework for understanding how businesses build durable competitive advantage. If you're new to the series, the introductory piece explains why value creation alone isn't a moat, and the second piece on Scale Economies uses TSMC and Intel to show how cost structures become competitive weapons. This piece covers the second Power: Network Economies.

What Are Network Economies?

Let’s first define what Network Economies are:

A business in which the value realised by a customer increases as the installed base increases. — Hamilton Helmer

I was listening to an Acquired1 episode on Meta this week in preparation for this article and was blown away by a fact. Meta has 4 billion users (of which 3.5 billion are active daily users) across Facebook, Instagram, Messenger and WhatsApp. That’s nearly half of the world’s population. TikTok has an estimated 1.5–2 billion active daily users and LinkedIn roughly 1 billion. These apps have become part of people’s routines, and to a certain extent—their lives.

I remember when WhatsApp first came out. I had some friends who used iMessage to communicate and others through BlackBerry. WhatsApp came along and created an ecosystem where it didn’t matter what type of phone you had, because you all used the same messaging platform. It became very sticky. And that was the point. WhatsApp with some friends using it was mehh, but WhatsApp with all of your friends was everything. Especially as a teen.

Now think about professional networking. There’s nothing wrong with meeting up for a coffee, or going for a few social drinks (i’m quite partial myself), but professionals are busy people. LinkedIn looked to solve the problem of people wanting to network more, but struggling to balance their professional and personal lives, by creating a professional networking platform available 24 hours a day, 365 days of the year. Of course, there’s nothing they can do about some of the utter cringe people put on there. Perhaps it adds to its appeal.

The key difference between Network Economies and Scale Economies is this: unlike Scale Economies, where your costs come down from having volume—in Network Economies the value of your product increases from having volume. By volume I don’t just mean having lots of customers—that’s market share. The volume of people using a product must materially increase its perceived value to existing users.

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Types of Network Effects

Direct Network Effects

Social media has direct Network Effects: more users = increased value for existing users. Skype had this too. Just like WhatsApp, it was useless unless the person you wanted to reach had it. Going analogue, when Alexander Bell’s telephone patent expired in 1894, hundreds of independent companies launched as the craze for telephones was booming. AT&T’s response was to refuse the independent companies interconnection—if you weren’t on their network, you couldn’t call their customers. Their network was more valuable because they could reach more customers.

Currency and language are two of the oldest Network Effects you can think of. The dollar (or Bitcoin) has zero utility as a standalone item unless people adopt it and actively trade with it. Remember—before currency, people traded silver, gold, bread, camels and daughters! Much to my dismay (as i’d love to learn a new language), the world has adopted the English language as its preferred second language. The more people speak English, the more people from non-English speaking countries want to learn it. It doesn’t matter that there are more Indian and Chinese speakers than there are English.

Indirect Network Effects

Black cabs used to rule the roost in the UK. If you wanted a taxi in central Manchester or London, you’d do well to find a cab that wasn’t a black cab. Enter Uber. The more drivers Uber put on the road, the more people used their app. The more people used their app, the more drivers signed up to taxi for Uber. This is indirect Network Effects, or two-sided platforms. It works the same way with eBay. eBay on its own wouldn’t be much use to anyone, but the more people that list stuff on eBay, the more people buy. Once eBay becomes more popular, even more people want to sell stuff on eBay, encouraging even more people to buy.

Amazon created this feedback loop through FBA (Fulfilled by Amazon), except it has a triple benefit: the seller, the buyer and Amazon. Win-win-win.

Value comes from at least two different groups benefitting each other.

Data Network Effects

Tesla states on their website that their Full Self-Driving2 cars have been trained on “over 100 years of anonymous real-world driving scenarios” from a fleet of over six million vehicles, and that the fleet “collectively experiences a lifetime of driving scenarios in 10 minutes.”. By mid-2025, Tesla’s fleet was reportedly adding around 15 million miles a day. Although Google is currently leading the way on fully autonomous cars, this amount of data collection from Tesla is staggering. Musk said himself that this data had increased AI training compute by 400% in 2024 alone. This data is used to produce better products for Tesla and train their AI.

Platform Network Effects

Through the iPhone, Apple created one of the best examples of Platform Network Effects: iOS. Apple’s apps alone are powerful—having an iPhone is like having a little computer that fits in your pocket—but throw in Apple’s App Store, which opens it up to third-party developers, and you have the world at your fingertips. The value isn’t created from individually having an iPhone, but from third-party developers offering the user roughly 2 million apps.

Other examples include: Obsidian allowing third-party developers to create community plug-ins, Shopify’s app store, Amazon AWS, and Visa by connecting cardholders with merchants.

Hybrid

The truth is many companies have multiple types of Network Effects: Apple, Amazon, Uber. The apps or products they create serve more than one person or group, their perceived value increases as more people use them, and they all collect swathes of data that they use to create even better products.

Benefits & Barriers

The Benefit

The benefit of Network Effects is clear: the value of a product increases as more people adopt it. The sheer scale of audience capture can lead to rapid growth, increased popularity (further increasing audience), and outside investment. Companies that are in a leadership position with Network Economies can charge higher prices than those whose products are perceived to offer less value, because audience volume is substantially less.

The Barrier

Competing with a company that has genuine Network Effects can be costly. The cost of gaining market share (customers) can have a substantial negative impact on the opponent’s P&L as they battle to incentivise people to defect to their product. But nobody likes to arrive at an empty party. For developers, this means they need to create a space that will attract the most people in the quickest amount of time—but reputable socialites always arrive late, when the house is full. The platform you’re reading this on has done a pretty good job at convincing big household names to move onto the platform in the last 12 months. This makes Substack even more appealing, which in turn will bring in even more household names. Most companies create benefits—but barriers are what create long-term differential returns.

Companies that have true Network Effects often exhibit winner-take-all scenarios, and competition has two options: 1) fight (and probably lose), or 2) create something novel.

Some barriers may look like genuine Network Effects, but features aren’t a barrier. At least not a durable one. When Snapchat came along with their novel feature “stories”, people loved it. Who’d have thought it, aye. But creating timed disposable videos isn’t a sustainable moat, and for Snapchat the water dried out—when Facebook had enough data to validate the idea, they copied them. So did Instagram (owned by Meta). People still use Snapchat (just Snap now), but their novel idea wasn’t structural—it was too easy for a competitor to rob their idea for their superior network to benefit from. Companies can also match your pricing, but if they don’t have the volume those profits will take a battering unless they have a substantial cost-saving benefit—or scale advantage.

The astute business strategist knows to look for the barrier conditions first—why can’t customers leave this network, not why did they join in the first place.

Case Study: Meta’s Dominance

Network Effects are perhaps the most potent of Helmer’s 7 Powers, but many strategists miss one critical distinction: Network Effects do not automatically constitute Power. For there to be genuine Power there must be durable differential returns and immunity from competitive onslaught. Meta Platforms unconditionally demonstrates Helmer’s conditions for Power.

Mark Zuckerberg launched “TheFacebook” from a Harvard dorm room on 4th February 2004, and within 24 hours, 1,200 people had joined. Initially limited to .edu emails, Zuckerberg paired exclusivity with intoxicating FOMO effects, and within a month over half of Harvard’s undergrads were on the platform. Facebook reached 1 million users by the end of 2004, 100 million by 2008, and crossed 1 billion monthly active users in October 2012—making it the first social media platform to do so. Meta’s sheer reach defies comprehension: 43% of the world’s population use Facebook, Instagram, WhatsApp, Messenger or Threads daily, and 48% monthly. Facebook alone has 2.1 billion active daily users, with a 60% daily retention rate. These numbers mean that nearly every other human being you see on Earth uses one of their products each month.

The company’s market cap has grown from $81.7 billion at its 2012 IPO to $1.66 trillion as of writing, representing a compound annual growth rate of roughly 24%. This includes a 76% peak-to-trough decline in 2021–2022, driven by metaverse spending concerns, Apple’s App Tracking Transparency hit, and TikTok competition. Let’s not forget the Cambridge Analytica scandal in 2019 either. Zuckerberg trimmed the company by cutting 21,000 jobs to refocus on AI, and from the trough in October 2022 the stock would rebound over 500% (it would later come down again due to capital expenditure fears).

A £10,000 investment in Facebook on the day of its IPO would be worth roughly £170,000 today.

The Failed Challengers

Facebook has boxed many a round with challengers including: Google+, Snapchat, MySpace, Ello, Peach, Vero, Diaspora, Path and Friendster. How was Facebook able to fight off these companies—especially Google, with its billions of capital and users already integrated into its ecosystem? Because Facebook had genuine Network Effects. These companies may have had a product that users would benefit from if they switched—but they never figured out why users would want to leave: the barrier.

TikTok represents the most sincere competitive threat to Facebook, as they pivoted to a different network: teenagers—who weren’t yet embedded in Facebook.

People regularly complain about the Meta ecosystem saying they want to leave, but the numbers don’t show that. User numbers are increasing year on year. Facebook has had numerous scandals: Cambridge Analytica, data breaches, privacy violations, content moderation failures, mental health concerns, antitrust investigations. Any one of these would sink most companies. Yet last year advertising revenue increased 22.1% to $196.2 billion, accounting for nearly 98% of total revenue.

Saying you want to leave is one thing, but not being able to because you’ll lose access to your network is textbook Network Economies.

Meta has compounded its revenue at 27% a year for the last 10 years. They consistently carry gross margins of 80%+ and have left a graveyard of competitors in their wake. You’ve seen how Facebook built the world’s largest social network. But here’s what separates Network Economies from every other Power: your customers become each other’s switching costs.

In the complete essay, you’ll discover:

• Why Google couldn’t beat Facebook: Despite superior technology, unlimited capital, and Google’s distribution power, Google+ failed catastrophically. The barrier wasn’t technical—it was structural.

• The Three-Question Diagnostic: Determine if network effects are strengthening or weakening—critical for investment analysis

• When networks collapse: The specific conditions under which network effects reverse and platforms die (MySpace, and what nearly killed Facebook)

• Five Red Flags: Red flags to watch out for when analysing companies that might show structurally weak Network Effects

Subscribe to The School of Knowledge+ to get the complete framework for identifying and analysing Network Economies—the Power where growth itself becomes the barrier. For this series I am offering a lifetime 20% discount for those who join:

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