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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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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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Two companies go head-to-head competing for market share in the digital streaming industry. Each has excellent management, brilliant content, and state-of-the-art facilities, but one company has something the other doesn’t—numbers.

Company A has 20 million subscribers and Company B has 100 million. If both companies spend $100 million on creating original content, it’ll cost Company A $5 per subscriber, but Company B only $1. Basic maths states Company A is going to have a hard time competing against Company B because it costs them five times more to make the same product. What’s Company A to do?

The obvious solution would be to cut the price of their subscription fee, ensuring it’s materially lower than Company B’s. However, Company B, being the astute strategists they are, know this play and drop their prices to match. This folly favours Company B — with lower fixed costs and higher margins protecting them from competitive onslaught. Company A, with higher fixed costs and lower margins, feels the squeeze and retreats gratefully back to the trench it came from.

This is Scale Economies at work.

Scale Economies create a moat not just through size, but through the prohibitive costs a challenger must pay to reach the incumbent’s efficiency.

This is the first deep-dive in the 7 Powers series. Hamilton Helmer’s landmark book on how businesses use strategy and value creation to create consistent differential returns — something he calls Power. In the introductory essay, I explained why value creation alone isn’t a moat. Now let’s examine the first Power that separates good businesses from great ones.

What Are Scale Economies?

“A business in which the per-unit cost declines as production volume increases.” — Hamilton Helmer

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Scale Economies is fundamentally about structure — not operational efficiency. When Netflix decided to move away from leasing film studio properties to creating originals, they solidified an element of their business model that had long had variable costs attached to it. If the film studios set a price for a property lease, there wasn’t a lot Netflix could do — but by creating originals, they now set the budget. If they wanted to spend $100 million on an original, that’s what they’d spend, and the more their subscriber base grew, the lower their costs were per original.

This is what Helmer means by “per-unit cost declines as production volume increases.”

The Different Types

Scale Economies can emerge through multiple mechanisms:

Fixed costs: High upfront capital expenditure (factories, equipment, R&D) spread over increasing volume. Netflix originals, semiconductor fabs, software platforms.

Volume/area relationships: Utilising production area to increase volume results in lower per-volume costs. Refineries and warehouses.

Distribution network density: As distribution networks grow denser with more customers per area, delivery costs decrease through more economical routes. Amazon Prime delivery.

Purchasing power: Large-scale buyers negotiate better pricing than smaller companies. Walmart, Costco, supermarkets.

Learning economies: Knowledge that reduces costs or improves quality, tied to production levels. Experience compounds over volume.

Benefits and Barriers

Benefits are more common in business: pricing power, cost reduction, lower operating costs. But barriers — those that prevent competitors from engaging in tit-for-tat tactics — are less so.

Benefit: The conditions that created the Power must materially grow cash flow through increased prices, reduced costs, or lower capital expenditure.

Barrier: As well as persistently increasing cash flow, there must be a barrier that prevents competitors from engaging in value-destroying arbitrage.

Barrier conditions deserve your utmost attention. Scale Economies can only exist when the cost advantage is material enough to change competitive behaviour — when competitors purposefully decide not to engage because it’s economically inefficient to do so.

Case Study: Taiwan Semiconductor Manufacturing Company (TSMC)

TSMC produces approximately 60% of the world’s semiconductor chips and over 90% of the most advanced chips. Their semiconductors can be found in modern cars, industrial sensors, and power management chips. Advanced chips — requiring more processing power — are found in iPhones, MacBooks, and AI processors.

TSMC isn’t a chip designer: Apple, Nvidia, AMD, et al. design their own chips, and depending on the complexity of manufacturing, that chip will almost certainly go to TSMC, where they’ve built an insurmountable moat. This is called a “foundry” business — they’re a fabrication plant for hire.

Their operating margins are consistently 40–45%, while their nearest competitor Samsung’s foundry business margins sit at 10–15%. Intel, who entered this market in 2021, has negative margins. Over two decades, these margins haven’t compressed. They haven’t been eaten away. TSMC is able to consistently create that determining factor of genuine Power: persistent differential returns.

The fixed cost base

TSMC’s fabrication plants cost between $20–30 billion to build. They’re filled with dozens of ultraviolet lithography machines costing in excess of $150 million each, run by thousands of people with PhDs, spending $3–4 billion annually on R&D developing the next generation of manufacturing processes.

That’s an eye-watering amount of capital expenditure. They have 12–13 operating fabs across Taiwan and Japan, with each fab having multiple phases, meaning the total number of operating fab phases is closer to 50.

And there’s more to come. TSMC is currently expanding to Arizona, where they plan to build 3–6 new fabs, two advanced packaging facilities, and an R&D centre totalling an estimated $165 billion. There are plans for 2–3 more in Japan, one in Germany, and one more back home.

Imagine trying to compete with that.

The volume advantage

TSMC can invest that kind of capital because they have the volume. TSMC produces 13x more wafers than Intel and 50x more than Samsung’s advanced foundry nodes. Intel and Samsung simply don’t have the volume that would enable them to invest in the kind of infrastructure and research needed to close the gap on TSMC.

What creates a barrier your competitors can’t cross?

You’ve seen how TSMC built their fortress. But here’s what separates genuine Power from temporary advantage: the barrier must be insurmountable. In the full essay, you’ll get:

• The complete TSMC breakdown: Why Intel can’t catch up despite 60 years of experience and unlimited capital

• Surplus Leader Margin explained: The simple calculation that reveals whether any business has genuine Power

• The diagnostic framework: Three questions to determine if a company has Scale Economies or just operational leverage

• When Scale is a trap: The red flags showing when chasing growth destroys value

• What separates TSMC from everyone else: Why most industries will never achieve this Power

This is the foundation for the entire 7 Powers series. Subscribe to get access to this essay plus the full breakdown of each Power, complete with frameworks for analysing any business.

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The barrier: Why Intel can’t catch up

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The quote comes from Amazon’s 2017 shareholder letter “Building a Culture of High Standards”, and demonstrates Bezos and Amazon’s perpetual drive in creating customer value. They obsessively sought to create value through a lens that put the customer front and centre of every decision they made. The company’s worst drawdown occurred from the dot-com bubble and saw them lose 94% of their stock value, but they continued steadfast in their mission. They would continue to provide customers of Amazon with as much value as possible through product differentiation and cheaper prices, weathering the storm through an unwavering commitment to customer experience over short-term profitability.

Every business provides some form of value in the products or services they sell, but value-creation alone isn’t a sufficient strategy in shielding a company from competitive onslaught. Every company needs a strategy for not only creating value—but creating structural barriers to shut their competition out. Something that places the company on a perch.

Amazon’s was optionality, cost and speed. Something Nick Sleep from Nomad Investments termed shared economies. Many companies don’t know their true value, others refuse to seek better value through fear of the sunk cost fallacy, and many don’t have any at all.

Let’s look at the story of two companies: an entertainment household name—infamous amongst boomers and millennials, and the other; a disrupter who looked at the same business model through a completely different lens.

People of a certain age will remember Blockbuster. The place you’d go to rent videos for the family to sit around and watch on a Saturday night when we didn’t have the world at our fingertips. It had a robust business model built around families, couples, friends or movie lovers sitting down and watching their favourite movies together for a reasonable price. The cinemas must have hated them.

But then came DVDs. A direct threat to VHS, and to Blockbuster themselves.

Blockbuster initially snubbed the new technology, and in 1997 even rejected a deal with Warner Bros to rent new releases before they went on sale to the public because they were asking for 40% of rental revenue in return. But in September 2001, Blockbuster finally made their move into DVDs, and announced a reduction of 25% of their VHS inventory to make way for them.

Too little, too late.

The entertainment household name adapted when they had a change of heart towards DVDs, but fatally, they continued with their brick-and-mortar business model. The disrupter—Netflix—saw it differently.

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—one requiring high and growing capital expenditures, with physical stores capable of offering only a few thousand books, into a distribution network capable of delivering nigh on every book ever published.

But crucially, Netflix saw past their own nose towards the horizon—digital streaming.

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 making it a viable business model. 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.

In 2007 Netflix tentatively entered the digital streaming industry by partnering with electronic hardware specialists. They didn’t bet the house and go all-in. They did the leg-work, allowed themselves 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 a clear competitive advantage in this industry was at the very best muddy.

The way streaming businesses worked back then was like this: streaming platforms like Netflix negotiated for streaming rights with film studios. But the film studios were astute and strategic custodians of their properties, and it was them that held power over the new kids on the block. They split their properties up by geography, region, release dates, contract length, and so on. 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 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. This move was as bold as it was ingenious.

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 film studios. If House of Cards cost Netflix $100m to make, 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 iron-clad barrier where none was 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. Value-creation wasn’t enough—it was the barrier that mattered.

How companies create value, and how they ensure they leave their competitors in the rear view mirror, is laid out by Hamilton Helmer in his landmark book on analysing businesses: 7 Powers. Helmer has spent decades trying to work out what separates a bad business from a good one, and a good one from a great one. He starts with two definitions of strategy that answer two distinct questions—one about the nature of value, the other about how to capture it persistently.

Strategy

The study of the fundamental factors that drive potential business value.

The diagnostic lens: what are the foundations of value in this business?

Strategy has two objectives: to reveal the foundations of business value—and attempts to guide businesspeople towards value-creation. It can be split into two topics:

1. Statics: “Being There”: What makes Netflix’s content so durably valuable?

2. Dynamics: “Getting There”: What elements helped produce such favourable results?

Looking back at our Netflix case study, we can see that Netflix’s decision to depart from conventional norms and create originals was what set them apart from other streaming platforms, but also what made their business model so durable and valuable. This is the difference between static value—the structural advantage they hold—and the dynamic quality that allowed them to build it in the first place.

strategy

The set of conditions creating the potential for persistent differential returns.

The competitive lens: what conditions allow a company to hold that value against rivals?

Persistence is a non-negotiable element in creating long-term differential returns. 10% growth—per year—for three years, would only constitute 15% of a company’s value. Having stellar returns for three years, and then poor returns the next three, is unlikely to create durable long-term differential returns. How could it? Value is what gives rise to persistent and above average returns. It’s all about establishing and maintaining an unassailable perch.

These differential returns give rise to Power: the underlying conditions that give a company a consistent and unfair advantage over its competitors. This is as difficult to achieve as it is important, but can be attained through two means:

1. Benefit: The conditions that created the Power must materially grow cash flow through a combination of increased/decreased prices, reduced costs, or less capital expenditure.

2. Barrier: As well as persistently increasing cash flow, there must be a barrier that prevents competitors from engaging in value-destroying arbitrage.

The astute business strategist knows to look for the barrier conditions first—not the benefit.

Benefits are more common in business: competitive pricing, cost reduction, operational efficiency. But barriers—those which prevent competitors from engaging in tit-for-tat tactics—are less so. Companies that know what a competitor is doing, but won’t engage in trying to replicate them through fear of destroying their own value proposition, do not have Power—at least not yet. Therefore it is barrier conditions that first deserve the strategist’s attention.

An industry’s underlying economics and a business’ specific competitive advantage must interact in ways that are favourable for Power to exist.

You can measure strength, but the concept of Power is relative. When comparing a company’s Power over a competitor, you’re looking for what is measurable—their strengths—those which have the potential to translate into Power.

Good strategy not only requires you to seek out Power (and potential Power) between direct competitors, but indirect ones as well. After all, Power changes hands like a clock face changes time. Value-destroying actions are linked to poor execution of strategy and following conventional wisdom. No business is immune from a fall from grace.

Value gets you to the final. Power is having your name written in the history books.

Through value-creation and impenetrable barriers, Bezos propelled Amazon towards trillions in market cap. Netflix established itself as the number one streaming platform. Helmer didn’t invent these principles. He found them—in companies like Amazon and Netflix—and codified them into a framework any operator can apply.

Here’s what most business owners miss: they can articulate the value they create, but they can’t name the structural barrier protecting it. They know their strengths but confuse them with Power. They work harder, improve operations, cut costs—all necessary, none sufficient.

The question for your business isn’t whether you create value. It’s whether you’ve built barriers that prevent competitors from taking it from you.

Helmer identified seven specific types of Power. Seven structural advantages that, when present, create persistent differential returns. Some you can engineer deliberately. Others emerge only under certain conditions. Knowing which is which is the difference between wasted effort and compounding returns.

But here’s the problem with Helmer’s book: it’s written for investors analysing public companies, not operators running them. The frameworks are sound, the case studies compelling, but they don’t answer the question every business owner needs answered: How do I know if I have this? And if I don’t, can I build it?

That’s what the 7 Powers series does.

Over the next seven essays in this series, I’ll break down each Power—not as an academic exercise, but as a diagnostic framework you can apply to your own business. Each essay will include:

• The anatomy of the Power: what it is, how it works, and why it creates barriers

• Recognition criteria: the specific conditions that signal its presence or absence

• Application for SME operators: how construction firms, professional services, and capital-intense businesses can identify opportunities to build each Power

• Diagnostic tools: checklists, frameworks, and questions that move you from theory to action

The first Power we’ll examine is Scale Economies—the same advantage Netflix used to turn content creation from a liability into an unassailable moat. We’ll look at how fixed costs spread over volume create barriers, when scale becomes a trap instead of an advantage, and how to identify whether your business has the potential to build this Power.

If you’re serious about building a business that compounds value rather than just creating it, this series is where theory meets application.

Until next time, Karl.

The 7 Powers series is part of The School of Knowledge, where I translate sophisticated investment frameworks into actionable tools for business owners. £15/month gets you access to the full series, The Case Library, The Toolkit, and The Reading Room which i’m offering to you today, plus access to everything else, for a 20% discount.

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OpenAI have recently released ChatGPT 'Agent Mode,' an autonomous operator with deep research capabilities that can 'do things for you.' Depending on which side of the fence you sit on—grossed out and tired by the increasing awareness of machine-produced content—or excited by the prospect of being more efficient, ChatGPT's Agent Mode (and its current limitations) should offer solace for those concerned about acquiring what the £20 pro plan can offer—gained time.

Currently, at least in the UK, I have 40 uses of Agent Mode per month. At first this appeared to be a limitation, but it's made me realise something profound: you can't sit there and use it all day, every day. When you have infinite opportunities, mediocre results lose their appeal. Warren Buffett knew better. If investors are limited to only 20 investment decisions in their lifetime, suddenly every decision demands excellence. The same can be said about Agent Mode.

People are confusing AI with 'doing the thinking' on the part of the human, but it should be considered a representation of how well you are at communicating. If you're getting lousy outcomes, is it because AI is slop, or is it because you haven't been able to communicate your desired properly? AI exposes bad thinking.

The same logic applies to ChatGPT's Agent Mode. It can't all of a sudden make you 10X more efficient if it doesn't understand what you mean to begin with. Prompting is clarity of thought translated into text.

Over the last week I've tested various ways to use Agent Mode as a business owner and writer on Substack. Some saved hours. Some were flops—but they all reminded me that I needed to better my thinking to achieve the outcome I desired.

Here are 6 personal case studies from using Agent Mode this week:

Limitations, Frustrations and When Not to Use Agent Mode

Booking Simple Reservations

I severely procrastinate at mundane jobs I have no interest in doing, no matter how easy they are. A symptom of ADHD, which I have. So, the thought of having a little helper do all the things I don't like doing sounded like music to my ears. Here's the prompt I used:

Find me a reservation for 2 people at the restaurant 'Sparrows' in Manchester, UK between 18:00 and 20:00 on a Friday or Saturday. Search for August and September.

It failed spectacularly. Sparrows is undergoing work in August, which Agent Mode recognised, but it also claimed it was closed for all of September, which it wasn't. I also wanted to see how fast Agent Mode was, so decided to manually reserve a table myself. It took about three times longer than me to not find me a table.

Emphatically, Humans 1 - 0 Agent Mode.

E-commerce Shopping

Next I needed to buy some work jeans. Here's my prompt:

I need a pair of work jeans and prefer the colour blue. They need to be hard wearing because of my job in construction, and I currently wear Levi's which I find comfortable and fit well. I'm a size 32/34 and prefer tapered jeans. Please search the web, including Amazon for a sturdy pair of jeans I can use for work under £50. They must be well reviewed.

I chose Amazon because I'd seen Agent Mode autonomously buy things for people, but I ran into significant problems. Amazon blocked Agent Mode. Whether this is due to privacy restraints in the UK or something on my end I haven't yet worked out, but it did provide a report with links to jeans within the scope of what I asked for. I'm giving it the nod here for being intuitive.

Humans 1 - 1 Agent Mode.

Booking Flights, Hotels and Tickets

Next up I asked Agent Mode to organise a day trip to Dublin for me and the two other company owners. Here's the prompt:

Find me flights from Manchester to Dublin, Ireland on the 22nd November this year for 3 people. The flight should be in the morning. Also, find us accommodation and make sure the hotel states 3 separate beds. Use booking.com or Airbnb to find a room or apartment. Keep flights and hotel/apartment under £350. Also try to find 3 tickets for the Ireland vs South Africa rugby game.

The flights it found were £14.99 and were great times. To our dismay we realised they were for a date in August! This was easy enough to change, but a massive red flag that you should always have the human sign off before purchasing anything. It did however find a suitable apartment and tickets to the game, although they were sold out when we tried to purchase them. A great effort but I wouldn't trust Agent Mode with my wallet just yet.

Humans 2 - 1 Agent Mode.

The rest of this essay is for members only. You’ve seen where Agent Mode falls down. Here’s where it shines — with the exact prompts, templates, and QA checklists I used to save a full day this week. Copy them, run them, and keep the human in the loop where it matters.

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