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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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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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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.

If you know somebody who this would help, be a pal and pass it onto them:

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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 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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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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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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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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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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Charlie Munger said that to get ahead in life you need to understand the basic concepts of the hard sciences: physics, chemistry, engineering and maths. And while accountancy is more art than science, it should go without saying that every investor—whether you buy stocks, real estate or commodities—and every current or aspiring business owner, should be able to understand and interpret financial statements.

Why?… because your capital depends on it.

Regardless of how much money you do or don’t have—nobody likes to lose it. Especially not to ignorance.

Financial statements are broken down into three main documents: the income statement, balance sheet and cash flow statement. Today we’ll be going through the income statement and breaking down what each line means. This document lets you know if the company you own or stock you want to buy is profitable.

But don’t take my word for it. Here’s an excerpt from the brilliant book Financial Intelligence:

“Learn to decipher this document, and you will be able to understand and evaluate your company’s profitability. Learn to manage the lines on the income statement that you can affect, and you will know how to contribute to that profitability. Learn the art involved in determining profit, and you will definitely increase your financial intelligence. You might even get where you are going.”

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To help put the scary and confusing definitions into context, we’ll be using Amazon and Visa as example companies. One of them (Amazon) produces products and services and the other (Visa) is a service-based company that collects fees on transactions. Both are well known for what they do, and you should always start with companies you already know a lot about.

This is an in-depth one, so you might want to bookmark this in case you want to come back to it. If you’re reading this in email and the email is truncated click on "View entire message" and you’ll be able to view the entire post in your email app.

A Few Tips Before You Start

Where to Find Them

When you want to read a company’s financial report, you have some options on where you can find them:

1. Investor Relations Pages: Most large corporations will have dedicated “investors” or “investor relations” sections on their website where an archive of their reports will live in PDF for you to read/download.

2. Third-Party Aggregators (free & paid): AnnualReports.com: A free directory of annual reports for listed companies across the UK, US, Canada, and Australia. Financial News & Portals: Sites like Yahoo Finance and the Financial Times (FT) Markets Data often provide links to annual reports on their company “tearsheet” pages. Specialised Databases: For deep research, subscription services like FAME (for UK/Ireland), S&P Capital IQ, and LSEG Data & Analytics provide consolidated financial data and original filing images. I personally use a paid service called Fiscal.ai, who also offer a free version (no affiliation).

3. Official Government & Regulatory Portals (free): Companies House (UK), EDGAR / SEC (USA), SEDAR+ (Canada), for example.

Or, just type in “COMPANY NAME annual report” into your favourite search browser.

Nomenclature

When reading financial statements, you’d have thought that there would be concrete wording for each definition but alas, there isn’t—there are multiple names for the same thing. Sales, top line, turnover and revenue aren’t different things—they’re the same. Net profit is also known as bottom line, net income, net earnings and net income after taxes (NIAT). At first this can be confusing, especially when looking at income statements from different companies, but I’ve tried to make it as easy as possible to understand by breaking down the income statement into six key components which I list before reviewing Amazon and Visa’s income statements.

Standardised vs Reported

Probably a bit beyond this article, but you should know that companies have to follow certain rules when it comes to financial statements. Depending on where you live, these might be called GAAP, US GAAP, IFRS or something else. The basis for these complicated accounting rules is to “standardise” how companies report their numbers so that the average Joe (and investor) can understand them as there is continuity across reports and companies. Most companies also report non-GAAP figures in their reports, as they may believe it represents a better picture of the company’s actual financials.

What Currency Is It In?

This might sound obvious but shouldn’t be overlooked. Be sure to check whether the numbers are in pounds, American/Canadian dollars, euros or something else. If you want to convert that currency back to your own, remember that the currency conversion rates might be different today from the reported numbers. This is where online websites excel over print or static copies because many allow you to select the company’s local currency, USD, or the currency of your country and convert the numbers for you.

Thousands, Millions or Billions?

Are the numbers you’re reading in thousands, millions or billions? At the top of each statement, the company should state what the numbers are “rounded” to. Here’s a screenshot from Visa’s 2025 Annual Report that tells you the numbers are in “millions.”

Before we begin, have a quick look at Amazon and Visa’s “statements of operations” which is just their way of saying... income statement, and have a go at guessing what you think the definitions mean, how both companies differ slightly, and why.

Visa

Amazon

To better understand the income statement, you can break it down into six key sections: 1. revenue, 2. operating expenses, 3. operating profit, 4. non-operating income, 5. taxes, and 6. net profit. That’s it.

Beyond that, you can introduce ratios, margins and percentage changes to the numbers to help assist you with your analysis of a company. A word of warning though: up isn’t always good and down isn’t always bad. Remember when I said it’s more art than science?

Let’s get into it.

1. Revenue

Visa calls it net revenue and Amazon calls it net sales (broken down into products and services) but they’re the same thing. It’s the total amount of money the company has charged its customers from selling its products or services over a given period and before costs are deducted. Revenue can certainly make you gleeful when first looking at it but revenue certainly isn’t profit. At least not yet.

Visa

Amazon

* You’ve probably noticed that Visa’s latest year is on the left hand side and Amazon’s is on the right. Don’t ask me why but be aware—there are little traps everywhere trying to trip you up if you’re not paying attention.

Revenue should only be recognised when a product or service is delivered. Here are some differences between when Amazon and Visa recognise revenue:

1. Amazon (Direct Sale): When you buy a $100 Echo from Amazon’s own inventory, they record the full $100 as revenue. They are the “Principal” in this transaction.

2. Visa (The Fee): When you use a Visa card for that same $100 purchase, Visa doesn’t count the $100. They only record their small transaction fee (often just cents) as revenue. They are a “Service Provider.”

3. Amazon (Third Party): When third-party sellers make a sale on Amazon, Amazon does not recognise the full amount of the sale as revenue. Instead, they only record their net share plus commissions and fulfilment fees.

But when something’s delivered can mean different things for different people. In the book Financial Intelligence, the author asks what you would do in these situations:

- Your company does systems integration for large customers. A typical project requires six months to design and be approved by the customer, then another twelve months to implement. The customer gets no real value from the project until the whole thing is complete. When have you earned the revenue that the project generates?

- Your company sells to retailers. Using a practice known as bill-and-hold, you allow your customers to buy product (say, a popular Christmas item) well in advance of the time they will actually need it. You warehouse it for them and ship it out later. When have you earned the revenue?

- You work for an architectural firm. The firm provides clients with plans for buildings, deals with the local building authorities, and supervises the construction or reconstruction. All these services are included in the firm’s fee, which is generally figured as a percentage of construction costs. How do you determine when the firm has earned its revenue?

The first example I’m not too sure, the second I would say once the product is shipped, and the third I have direct experience in as I co-run a construction company and deal with architects all the time. They’ll take 90% of it up front and do f-ck all after that.

Relax, architects—i’m joking. I know you work in milestones.

2. Operating Expenses

Operating expenses are the costs the company incurs from making a product, delivering a service or running the company’s day-to-day operations. Some directly contribute to growing the business such as (COGS/COS), some keep it afloat (SG&A) and others look to bring work in or develop products (marketing, R&D). Take a look at some of the differences between the two companies.

Visa

Amazon

Both companies have different types of operating expenses because they’re two very different companies but, on most statements you’ll find the following:

Cost of Goods Sold / Cost of Services (COGS/COS)

Cost of Goods Sold or Cost of Services represent the direct costs to the company for producing a product or service—the materials, labour and delivery.

For companies that sell products like Amazon, it’s easier to attribute a cost to a physical product plus work out the inbound shipping costs. For companies like Visa, who offer a service, it’s harder to tie a specific cost to a specific unit of service.

Selling, General & Administrative (SG&A)

A catch-all for costs that fall outside of COGS/COS and don’t directly contribute to growing revenue but keep the lights on and the company ticking over. Think of things such as:

• Salaries

• Office rent

• Marketing

• Advertising

• Legal or HR fees

Depreciation & Amortisation (D&A)

This is a “non-cash” expense. Accountants spread tangible assets like equipment, vans and buildings, or intangible assets like software and patents out over their useful life for accounting purposes and record this on the income statement. If my company buys a van for £36,000, the accountant, if using a straight-line method of depreciation, might determine that the useful life of the van is 3 years and would allocate a £1,000 cost of the van per month to the income statement.

My company is not paying out £1,000 per month as the van was bought in a previous accounting period using cash, debt or a mix of both but, it’s still expensed and thus comes off the company’s gross profit.

Research & Development (R&D)

R&D is money a company is spending on researching and developing future products, services or processes. For Amazon, think Amazon Echo, Firestick, Prime, etc. Visa doesn’t explicitly have an R&D section, but does have a “Network and Processing” line which, if Visa is making improvements to their systems, you could argue this is R&D.

Total Operating Expenses

This represents the total costs of all operating expenses and is subtracted from revenue. You can see how Visa—a service provider, has significantly less operating costs than Amazon that has physical infrastructure and inventory.

If you have money left over after all costs are subtracted, well done—you’ve made an operating profit. But you still can’t get too excited yet. You’re closer to making a profit, but it’s no home run.

3. Operating Profit

Once all operating expenses are subtracted from revenue, you arrive at operating profit. Operating profit is a useful metric when assessing the health of a company because it gives you an indication of how profitable the company is before you start to add or deduct tax, interest, and other investment income. Things that don’t really have any bearing on how well the company is operating from the products or services it sells.

Visa

Amazon

4. Non-Operating Income

Companies can also make money from activities that do not directly contribute to their operations.

Visa

Amazon

Non-operating income can include:

Interest Income

• Interest earned from cash in a savings account

• Interest from government or corporate bonds the company holds

• Interest received from notes receivable or loans to third parties

Investment Income

• Dividends they receive from shares held in other companies

• Realised gains from selling physical assets such as property, plant, equipment

• Stock they sell (if they sold it for more than they bought it)

• Rental income from investment properties that may not be related to the primary business

They could also owe money.

Interest (Expense)

Interest expense is the cost of borrowing funds the company may have used to grow the business, make an acquisition or pay down bad debt (swapping high-interest debt for low).

Total Non-Operating Income

Total non-operating income is what the company earned from interest and investment income minus any interest paid (expensed). If it’s a plus, the number is added to operating profit, and if it’s negative, deducted.

5. Tax Provisions

When companies make profits, they have to pay taxes, and what the company’s liability for that tax will show up here before the bottom line—net profit.

Visa

Amazon

As these companies are global powerhouses you’ll have to do some digging as where they paid they tax if that’s you’re thing. Is it all in the states or is it spread over regions?

6. Net Profit/Income

Net Profit is the bottom line of the income statement. If you’ve made a profit it’s what’s distributable to shareholders of publicly listed companies, or the owners of private companies, after all costs, interest and investments, taxes, and any one-time charges are removed from revenue.

Visa

Amazon

Considering Amazon’s revenue was almost 16x Visa’s they’re not too far apart when it gets to the bottom line. Being the beast they are, Amazon needs to keep spending money on new warehouses, fleet and product development to keep growing. On the other hand, people are increasingly paying less with cash and more with their cards. Visa, and Mastercard own a duopoly in this space and have done for decades.

If you only understand those six sections, you’ll already be ahead of buckets of people when it comes to understanding the income statement. For those that want to analyse the statement in a little more depth, you can look at the following.

This article is from “The Nuts & Bolts” section where I provide business operators and investors the mechanisms and manuals to make better decisions. To continue viewing articles like this please consider upgrading to The School of Knowledge+.

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Margins, Percentages and Ratios

Gross Profit Margin

Gross profit is what’s left after Cost of Goods Sold (COGS) and Cost of Service (COS) is subtracted from Revenue. Gross Profit can also be expressed as a percentage to monitor profitability of a company’s products and services at a rudimentary level.

Visa’s revenue for September 2025 was $40 billion and its cost of sales was $7.9 billion. Therefore, its gross profit was $32.1 billion.

To see that as a percentage (or margin), just do the following calculation:

$32.1 / $40 = 0.8025

0.8025 x 100% = 80.25%

*I’ve rounded the numbers.

Operating Margin

Like gross profit margin, investors and business owners want to keep an eye on the operating margin of a business and understand why it’s moving in one direction or another. Is the corporate office bloated and dragging down margins? Is the company embroiled in a legal dispute with fees adding up? What about the other way—why has your operating margin jumped 10% this year? Maybe you’ve cut back on marketing or used internal employees instead of consultants who’ll likely charge higher fees.

Either way you need to ask: Is what you’re seeing sustainable or is it smoke and mirrors?

To get to this figure, the calculation is as follows:

$68.6 / $638 = 0.108

0.108 x 100% = 10.75%

Net Profit Margin

Net profit margin is expressed as a percentage once all operating costs, non-operating costs and tax provisions are subtracted from revenue. It tells you what the company earned as a percentage in relation to revenues. Low margins are vulnerable to sudden price changes or one-off charges. Think Trump and his tariff war the last 6 months.

$20 billion (net profit) / $40 billion (revenue) x 100%

$20 / $40 = 0.5

0.5 x 100% = 50%

Percentage Change of a Metric

If you want to track a metric change of a company, such as revenue to see if it’s improving or declining, use the following calculation:

Current year - prior year

/

prior year =

x 100%

Example:

If this year’s revenue is £550,000 and last year’s revenue was £500,000, the calculation would be as follows:

£550,000−£500,000 = £50,000

/

£500,000

= 0.1

0.1 x 100 = 10%

Earnings Per Share

Earnings per share (EPS) is a company’s net profit divided by the number of shares outstanding. EPS is a number that investors, particularly Wall Street keep an eye on. An EPS miss will almost certainly drag the stock price down but weirdly enough it rising can sometimes do the same. Who’d be an investor.

Final Thoughts

The income statement answers one question: Is this company profitable? A company showing a loss this year might have been profitable eight of the last ten years. Is it a good company or a bad company then? When analysing a company—you’re own included, you want to look for trends overtime. Has revenue grown at a healthy rate over the last 5-10 years? Has D&A rocketed suddenly (think AI/tech stocks)? If so, why? Why is this companies gross profit 15% higher/lower than it’s industry peers?

If you like solving puzzles or murder mystery games you might do well at investing. If you can smell bullshit a mile away, even better.

You should now, at least on a basic level, be able to answer that primary question, understand what each definition means, and how to get to net profit. Understanding the nuances though is just a little more difficult and will require reading many income statements form different companies and industries.

Here’s a quick checklist of everything we’ve gone through:

Before diving in, tick off these basics:

• Check the currency: pounds, dollars, euros?

• Check the scale: thousands, millions, or billions?

• Identify the reporting period: quarterly or annual?

• Note the accounting standard: GAAP, US GAAP, or IFRS?

Then work through the six key sections:

1. Revenue: the top line; what the company charged customers

2. Operating Expenses: COGS, SG&A, D&A, R&D

3. Operating Profit: revenue minus operating expenses

4. Non-Operating Income: interest, investments, and other gains/losses

5. Tax Provisions: what’s owed to the taxman

6. Net Profit: the bottom line; what’s left for shareholders

Key calculations:

Gross Profit Margin = (Revenue − COGS) ÷ Revenue × 100

Operating Margin = Operating Profit ÷ Revenue × 100

Net Profit Margin = Net Profit ÷ Revenue × 100

Percentage Change = (Current Year − Prior Year) ÷ Prior Year × 100

And, remember:

• Revenue isn’t profit

• Up isn’t always good; down isn’t always bad. Understand why it’s so.

• The same thing has multiple names (revenue = sales = top line = turnover)

• It’s more art than science.

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

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This article is from “The Nuts & Bolts” Section where I provide business operators and investors the mechanisms and manuals to make better decisions. To continue viewing articles like this please consider upgrading to The School of Knowledge+.

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References:

1. Financial Intelligence by Karen Berman & Joe Knight

2. Amazon 10-K - Feb 2025

3. Visa 10-K - June 2025

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You can predict with near-certainty that an industry with 25% returns on capital today will earn far less in five years. You can also predict with near-certainty that an industry earning 5% returns today will improve. You cannot predict which specific companies will succeed or fail, when exactly the turn will come, or how management will respond. This distinction—between what’s predictable and what isn’t—is the essence of the Capital Cycle Framework, and it changes everything about how you should invest and run a business.

The Ebb and Flow of Capital

Companies that generate high returns tend to attract capital (think AI at the minute), whereas companies that generate low returns repel it. This simple statement is the core idea behind the Capital Cycle Framework, coined by Marathon Asset Management.1 Not only is this sequence of events predictable—it can also be capitalised on by the contrarian investor and business owner.

When companies start to make above-average returns, capital floods in. Banks, VCs and hedge funds want this train to continue past its designated stop and offer to fund the companies through debt or equity. The companies use this injection of capital to invest in growing their market dominance.

But what goes up must come down, and growing profits don’t just attract greedy investors—they attract competition. More players want to join the game and get their sliver of pie. When a company, industry or sector has had excess capital pumped into it and competition is fierce, it begins to develop overcapacity, margins start to get squeezed and profits start to decline.

When the cost of capital exceeds returns, worried investors start to panic and begin selling off their shares. Once this starts, and nothing interrupts it, it snowballs. They take their money and begin to look (and promote) the next best thing.2

But what happens when excess capital has left? The industry should start to consolidate as the debt-laden companies merge or get bought out. Once this has happened, and excess capital has moved over to the next best shiny thing, profits should start to climb up again and the cycle starts afresh.

The framework is laid out in Capital Returns, and the book’s editor, Edward Chancellor, argues that this ebb and flow of profits, capital and competition helps contribute to market bubbles and busts. Once you realise this, you can’t unsee it.

But if this is so obvious and so predictable, why does it continue to happen? The answer lies in how we think—or fail to think—when money is involved.

Let me introduce you to the behavioural traps.

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Understanding Mean Reversion’s Role in the Capital Cycle

Capital cycle analysis is fundamentally about mean reversion—the idea that extreme things tend to move back towards average over time.

Understanding this should help investors not overreact when companies make above-average returns. Except it often doesn’t. People buy stocks they’ve never heard of based on a viral tweet. Businesses invest in building up their capacity at exactly the worst time—when everybody else has the same information and idea.

The Capital Cycle Framework shows that people spend too much time focusing on the supply side of the equation, and not the more predictable side—demand. Often in business, there are winner-take-all, or winners-take-most scenarios at play, so when something comes along that brings higher than normal profitability, the rest of the companies in the industry adopt what brought them the returns, or else they get left behind.

Demand for construction projects doesn’t triple overnight just because three new firms opened. But supply—the number of firms bidding—can double in 18 months when returns look attractive. You can’t predict which firms will win, but you can predict the overcapacity will crater margins.

So what do you do if you find yourself in an industry that’s either overhyped or bottomed out? Well, correct capital allocation principles still apply. And that starts with working out what return you expect to get from your investment (your internal rate of return, or IRR). If the investment falls below your desired rate of return, you should pass. If you remember back to my post on the Outsiders, Bill Anders did this. He sold the companies where General Dynamics wasn’t the number 1 or 2 player.

Divesting made financial sense.

So why don’t more people make decisions that are best for their situation? How do they consistently get burned by bad investments and poor capital allocation decisions for their business?

The answer has something to do with how you view your circumstances.

The Inside vs Outside View

The Inside vs. Outside View is about how you make predictions and judgements. The inside view focuses on the unique details of your specific situation—your plan, resources and circumstances. The outside view looks at what typically happens in similar situations by using statistical data and historical patterns from comparable cases.

Reading case studies is the easiest and cheapest way to learn about the Capital Cycle Framework.

Wall Street investors and the banks don’t care about the long-term prospects of a company, sector or industry, because they understand one simple fact: a dollar today is worth more to them than a dollar in the future, and Wall Street continues to play a blinder. We think that they’re the idiots with their short-sightedness, but they’re the ones who know that there’ll always be start-ups, IPOs and new fads that need funding. Even better, when the bubbles burst they offer their helping hand through debt.

Much like the prostitute who doesn’t care if the man who wants to pay her for sex has had a bath this week—Wall Street will continue to get into bed with anybody willing to pay them fees.

How to Avoid the Inside View

The inside view makes you overly optimistic because you focus on what makes your situation special whilst ignoring base rates. Most people naturally default to the inside view (”our project is different”), which is why projects run over budget and start-ups fail at predictable rates (90%). Using the outside view helps you make more accurate predictions by grounding your estimates in reality rather than hope. And no, prayers don’t help.

So how do you become somebody that takes the outside view? You study. You study because you don’t have the luxury of making the mistakes that the companies and investors make in real booms and busts. Not many companies survive being blown up. When you take the outside view, you’re opting to be a rational, contrarian, and independent thinker. They say: “it’s different this time,” but you ask: “why is it?”

It’s great if you can ride the 30ft wave and safely stay on board all the way back down to the applause of others, but if you can’t surf, or worse, swim—don’t bother getting in the water.

The Prisoner’s Dilemma

The prisoner’s dilemma is a situation where two people can either cooperate with each other or betray each other, and the best outcome for both happens when they cooperate—but each person is also tempted to betray because it could give them an even better individual result.

The classic example: two prisoners are questioned separately. If both stay silent (cooperate), they each get 1 year in jail. If both betray each other, they each get 3 years. But if one betrays whilst the other stays silent, the betrayer goes free whilst the silent one gets 5 years.

Here’s how it plays out: Industry returns hit 25%. Company A invests in expansion. Company B sees this and thinks if I don’t match them, I’ll lose market share. Company C sees both expanding and thinks I can’t be the only one sitting still. Within 18 months, the industry has overcapacity, margins compress, and everyone’s worse off than if they’d all shown restraint.

How to Know if You’re in a Prisoner’s Dilemma

You’re in it when your main justification for investing is “everyone else is doing it” rather than your specific competitive advantage. If industry returns are above historical average and you feel pressure to invest or be left behind, the trap is already sprung.

You have four options:

Don’t play (if you’re strong). If you have a healthy balance sheet, sit out the expansion phase. Let competitors overcapitalise, wait for consolidation, then acquire the weak players.

Play defensively (if you’re medium). Match investments but use operating leverage, not debt. Maintain flexibility so you’re not locked into high fixed costs when margins compress.

Change the game (if you’re smart). Compete on specialisation, relationships, or quality instead of capacity and price. Find a niche where you’re not playing the same game.

Exit (if you’re realistic). Weakly positioned? Sell while returns are high and buyers are optimistic. Ego prevents most people from taking this option, but it’s often the right one.

Capital allocation rules:

• Never take on significant debt to fund expansion when the entire industry is expanding

• Build cash reserves when returns are high, not when they’re low

• Question any investment justified primarily by “competitive defence”

• Prioritise balance sheet strength over market share during booms—underperforming temporarily is fine if you survive to consolidate later

The brutal truth is most companies can’t escape because they’re not strong enough to sit it out and not smart enough to change the game. If that’s you, recognise it early and exit before the defection phase destroys your equity value.

Competition Neglect

Competition neglect is when people, or businesses, underestimate just how many others are thinking the same way they are, leading them to ignore how much competition they might face. This is exacerbated when the barrier to entry is low.

Social media companies don’t care if the viral piece of content was from an account with 40 or 400,000 followers, and neither do advertisers care about who’s willing to pay them the highest bid. Amazon has even made this an essential part of their business model with their Pay Per Click (PPC) advertising. A haunting example of competition neglect I’ve fallen victim to.

How to Avoid Competition Neglect

Remembering this mental model helps explain why people enter overly crowded markets, apply for long-shot opportunities without backup plans, and overestimate their chances in competitive situations. Recognising this helps you make more realistic plans by remembering: if something looks like a great opportunity to you, it probably looks that way to many others too.

Before entering a market or making a major investment, ask: What can we do that competitors can’t easily replicate? If your advantages are all things others could copy in 12 months—better marketing, more capital, harder work—you’re underestimating competition. Real advantages are structural: proprietary relationships, regulatory moats, network effects, or genuine technical superiority. If you don’t have one, reconsider the investment or business model.

Creative Destruction

The great reset.

Creative destruction is when new innovations destroy old industries and jobs whilst creating new, better ones to replace them. Netflix destroyed Blockbuster, but created new jobs in streaming technology and content production. Cars destroyed the horse-and-buggy industry, but created the massive automobile industry. EVs are now creating more change, not just in the cars we drive, but in the infrastructure we build around them.

Too much of a good thing doesn’t last forever, and disruptive technology arrives when you least expect it. You can’t avoid it, but you can learn to live with it.

How to Survive Creative Destruction

Step inside the mind of your competitors or a new, hungry and ambitious founder. How would they take your market share? Play devil’s advocate and ask yourself questions such as:

• What emerging technology could make our core offering obsolete in 5 years?

• Which competitor is operating on a completely different cost structure?

• If I was building the business today, would I build it the same way?

When the landscape changes, you want to be on the necessary, not painful, side. Old jobs disappear, which hurts people in those industries, but new opportunities emerge that often make society better off overall. Understanding this helps you adapt to change rather than resist inevitable progress.

Now What? A Diagnostic Framework for Your Business

Understanding the behavioural traps of the capital cycle is one thing. Knowing where you are in it and what to do about it is another entirely.

Most business owners and investors can recognise a boom when they’re in one—but only in hindsight, and if you’re like me you fucking HATE hindsight. The challenge is identifying your position in real-time and making decisions that protect capital when everyone around you is expanding.

Below is a comprehensive diagnostic framework designed to answer three questions:

1. Where is your industry in the capital cycle?

2. How strong is your competitive position?

3. What should you do about it?

The framework consists of five interconnected tools for both business owners and investors:

1. Industry Position Assessment: A 12-question diagnostic that scores where your industry sits in the cycle (Trough, Downturn, Growth, or Peak). Uses observable market signals rather than guesswork.

2. Competitive Strength Assessment: A 5-question scorecard that evaluates whether you’re strong, medium, or weak relative to competitors. Your cycle position matters less if you’re positioned to survive.

3. Red Flag Checklist: 23 behavioural warning signs that you’re making capital cycle mistakes in real-time. The circuit-breaker when you’re caught up in momentum.

4. Balance Sheet Strength Scorecard: A detailed financial health assessment. Tells you whether you can survive a downturn, acquire competitors, or need to exit.

5. Quarterly Tracking Template: Track your scores over time to spot inflection points early. The cycle doesn’t announce itself—you have to watch for the signals.

These aren’t theoretical frameworks. They’re operational tools tested against real historical bubbles. When we scored the 2006 US housing bubble using the Red Flag Checklist, 22 out of 23 warning signs were present at the peak—validating that the thresholds work.

For each of the tools there is also a business owner and investor version.

Not ready to upgrade yet? Fair enough. But here’s what separates this from other business newsletters: it’s written by an operator for operators—people who need to make actual decisions on Monday morning.

The models, concepts and frameworks are free. The tools that let you use them aren’t.

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This is the first essay of my second mini-series: An Introduction to Capital Allocation & Why It’s the Most Important Job for Any CEO. Over the coming months, I plan to dive deep into the foundations, principles and frameworks that some of the best capital allocators over the last 100 years have deployed to create excellent businesses for their shareholders and communities—so that you, the CEO or business owner, can make the most informed decisions about how best to use your company’s capital.

Rest assured that I too am a business co-owner of a construction company in the UK, and I will not put pen to paper practices that I wouldn’t use in my own business. After all, this is fundamentally a newsletter for people with skin in the game—those concerned with putting theory into practice.

A note on language: Throughout the series, I will use the terms “CEO” and “business owner” interchangeably. Why? Because the principles of capital allocation apply equally whether you’re running a Fortune 500 company or a private construction business. The main difference is scale and scrutiny—CEOs of public companies must justify their decisions to Wall Street, while private business owners answer to partners or themselves. But the fundamental question remains the same: how do you deploy your company’s cash to create the most value over the long term? You’ll notice most of my examples come from public companies. That’s not because these principles don’t apply to private businesses—it’s simply because public companies must disclose their decisions, giving us a wealth of case studies to learn from. The beauty of studying these CEOs is that their mistakes and successes are documented in detail, allowing us to extract lessons without paying the tuition ourselves.

Let’s get into it.

The Americano you pick up every morning, the car you drive to work, and the clothes on your back are all products of businesses. Now, it doesn’t take a genius to figure that out, but when you stop to think about it, almost everything we interact with is the product of somebody else’s business. They consume our world and give us everything we want, need or desire.

Some people have many businesses, some one, and many none—choosing to work for one instead. They can be run by a single person from their bedroom, or have hundreds of thousands of employees spanning multiple continents. To have a business, you need to have something to sell—like coffee, a Prius or jeans. But it can also be a service such as laundry washing, leasing software or personal training. If you can think of something to sell, and somebody pays you for it—it’s a business.

But how do companies grow—and how is it that some are worth trillions of dollars, and others barely get by? You could argue it’s luck, timing or once-in-a-lifetime ingenuity, and those factors certainly play a role, but I think the real differentiator is something more systematic. Let’s first look at an important distinction between the two types of business owners.

The Two Types of Business Owners

In order to have a successful business, you first need to be confident in three things:

1. The products or services you sell today will still be the products or services people will pay for tomorrow,

2. They are of a certain quality, and

3. That quality is reflected in the price at which you sell the product.

Buying something consumable for pennies and it breaking is not the same as spending thousands of pounds on an Hermès bag and it falling to pieces within three months. Rest assured, the next time the customer wants to overspend on a bag—they’ll be walking over the road to Louis Vuitton.

Good business owners know that they need to run their operations efficiently in order to generate free cash flow. After all, if you don’t have money—you can’t invest it. With that said, you focus exhaustively on this mantra and have your day-to-day operations nailed down to a T and tuned like a 1965 Shelby GT500. The company is generating healthy amounts of cash, and you sleep easy at night knowing you’ve played your part.

But if you barely even have time to sit down and eat your dinner, when are you able to seek out those capital allocation opportunities?

Great business owners know that effectively deploying cash generated from operations is more important to the company’s longevity than solely focusing on day-to-day activities. If you had two identical companies with one focused exclusively on operations, and the other on maximising shareholder value via effective capital allocation, the companies’ performance wouldn’t be marginal—but worlds apart. The examples and case studies we’ll use in this series will show how CEOs deployed capital to generate staggering long-term results—we’re talking about companies that outperformed the S&P 500 by 10x, 20x, even 30x, simply because the CEO mastered this skill.

Understanding how to create free cash flow and how to produce a return from it are two very different skills. Some people aren’t equipped with either skill, but a rare few have both. As business owners, it pays to understand where you lie on that spectrum.

Having cash in the bank ensures the company always has money at hand. How much is different from company to company. If you’re capital-light, then a couple of months’ operating expenses might suffice. If you’re capital-heavy, you’ll want more. Now, accumulating cash can be a strategic play—Buffett famously held billions waiting for the right opportunity. But there’s a difference between patient capital allocation and paralysis. If you’re keeping cash in the bank because you don’t know what else to do with it, that’s not strategy—that’s indecision. And indecision has a cost.

If you want to solidify the longevity of your company, you need to be thinking about capital allocation.

What Is Capital Allocation?

Capital allocation is how you—the business owner or CEO—deploy the company’s leftover cash after operating expenses, taxes and liabilities are taken care of.

The term “capital allocation” is typically used by investors to judge how well a CEO is utilising the company’s cash. The difference between a CEO who runs a Fortune 500 company and a regional construction business is that CEOs of publicly listed companies have to justify the decisions they’ve made to investors, their board and Wall Street. Private business owners are left alone with their decisions, unless there are other partners or external investors.

Now that we know capital allocation is how a CEO invests the company’s cash, the natural question is: what can they invest in? When you invest in something, you expect something in return, which is usually more than what you put in. But what can a CEO invest in—and what are these options that separate good capital allocators from great ones?

CEOs have five options to invest the company’s capital:

1. Invest in current operations,

2. Stock repurchases,

3. Pay down debt,

4. Acquire other businesses (M&As), and

5. Pay dividends.

There is a sixth option of doing nothing, which we’ve already covered above.

They also have three ways to finance capital: company cash, take on debt or issue equity.

Good capital allocation skills mean having the understanding of how to finance capital and knowing which of the above five options will generate the highest returns over the long term.

Let’s look at each of the five options.

1. Invest in Current Operations

Investing in current operations is typically the default option for when a company wants to use some of its excess cash. If you’re a construction company, you could decide to use the company’s cash to invest in new plant, tools and equipment, upgrade your company workflows to maximise productivity, or buy a company office instead of renting one. The chief goal here is to put your company’s cash to work so that the company is more efficient and productive, with the expectation that by doing so the company can generate a better return.

2. Acquire Other Businesses (M&A)

Acquisitions can offer a strategic competitive advantage that internal investment simply cannot achieve, and should be used when the expected rate of return from the other options is less favourable.

Acquiring another company can instantly give you access to new geographical locations, customers and product lines, and there are many different philosophies that companies deploy to achieve this. LVMH, the luxury conglomerate, owns 75 brands across six different sectors. This diversification can act as an economic moat, but for others such as Constellation Software, they only acquire other companies who specialise in VMS (Vertical Market Software).

When an attractive company appears undervalued, acquiring said company can instantly eliminate competitors and open up their customer base to you faster than building internal products themselves could. But just like share repurchases, when a company overpays for an acquisition, this comes at a massive cost to shareholders for publicly traded companies, or to you and your partners in a private company.

In summary, an acquisition should be favoured when it’s deemed the fastest and most effective way to gain market share, roll out new technologies or enter new markets.

3. Pay Dividends

Another option at the capital allocator’s disposal is to issue a dividend. If the company is publicly traded, then shareholders invested in the company will receive dividends in line with the company’s dividend policy, weighted by share count and class. Some companies issue multiple or single dividends per year—known as dividend stocks—others sporadically, and some not at all.

If you are a private company and are also a shareholder of said company, when a dividend is paid, you receive an amount that is based on the percentage of the company you own. If you own 50% of the company and the company votes a £50,000 dividend, you will receive £25,000 before tax.

Whether you’re a company that’s traded on the NYSE or provide laundry services in a small English town, once a dividend is issued, you pay tax on it. Depending on your current tax bracket and the dividend amount, you could end up departing with an unhealthy amount to the taxman.

Let’s go through three examples to illustrate. In all examples, you and your partner decide that after a successful year you will issue a dividend to the tune of £50,000, or £25,000 each.

Taking the highest tax rate into account, you’ll pay nearly 40% out in tax. As a CEO or business owner, you have to ask yourself if this is the best use of capital allocation for the company.

I’m not saying don’t pay your taxes—just don’t pay more tax than you need to unless you need the money for something private, say a house purchase or side project.

4. Stock Repurchases

CEOs have two options when buying back stock:

1. They can either use cash on the balance sheet, or

2. They can use debt to finance the repurchasing.

The first option is more cautious, with shares typically being bought over a longer period of time when the stock is deemed cheap. The second option is usually done in the form of a tender, with a much larger purchase made in a single hit. The former is the equivalent of draining a reservoir via a straw—the latter a suction hose.

Both options can create long-term value for shareholders, and both options rely on the company’s stock being undervalued—but there is fundamentally a difference in conviction between both approaches.

However, it’s simply not enough for a CEO to buy back shares and think they’re doing a good job. Indeed, buying back shares that are overpriced is just about the worst thing you can do with the company’s money aside from burning it.

Private companies, of course, cannot buy back their own stock on the exchanges, but they can retire shares or buy out partners in part or in full.

5. Pay Down Debt

A CEO can decide to pay down company debt with excess cash. There could be a number of reasons why they would want to do this:

1. High cost of debt: Paying down high-interest debt provides a guaranteed, risk-free return on capital that is equal to the interest rate they are eliminating. If you have a company credit card that is paying 25% interest, then paying off this debt is more than likely better than the other options available to them.

2. Risk and financial flexibility: If the company’s leverage (debt-to-equity ratio) is too high or the company is worried about an economic downturn, then the CEO might play defensively and pay down debt. High debt also increases financial risk and the chance of defaults, and by reducing debt, the CEO improves the company’s credit rating, which in turn lowers the cost of future borrowing. If there is a recession, legal or regulatory disputes, then having low amounts of debt makes the company more resilient, which can mean taking advantage of opportunities (like cheap acquisitions) that financially strained competitors cannot.

3. Lack of high-return opportunities: The company has exhausted all other internal and external investment opportunities that would offer a return greater than the cost of debt. If the cost of debt is X and the expected return from all other options is less than X, paying down debt is the economically rational choice.

Final Thoughts

A well-run company is a cash-generating machine, and by now, it should be clear that being a good capital allocator requires the understanding of the multitude of options available to the business, and you, the CEO.

There isn’t one option from the five that’s consistently the best. Being a good capital allocator means understanding when to choose one over the other. Personally, for publicly listed companies, I think a dividend should be last on the list or not used at all so that the company can save up the excess cash for acquisitions. Many great capital allocators have done this, as alluded to before with Warren Buffett, who used Berkshire Hathaway’s subsidiaries to generate billions of dollars, which in turn bought more companies, which returned more billions to Berkshire.

In today’s essay, we’ve covered what a good business looks like, the two different types of CEOs, what capital allocation is, and the five options available to CEOs and business owners when it comes to investing the company’s leftover cash.

The next essay will explore the remarkable capital allocators featured in The Outsiders by William N. Thorndike. But here’s a snapshot: they didn’t follow the playbook. While their peers paid dividends because “that’s what shareholders expect” or made acquisitions to appear on magazine covers, these CEOs deployed capital with surgical precision—often doing the exact opposite of what Wall Street demanded. We’ll examine how they knew when to use each of the five strategies, and more importantly, when to ignore conventional wisdom entirely. The goal isn’t to memorise their moves, but to understand the thinking that let them recognise

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

Whenever you’re ready

The School of Knowledge helps you understand the world through practitioners. Those who try, fail and do (skin in the game). 📚💡

Join our growing community of like-minded lifelong learners here:

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This focus has allowed me to spend my time researching and writing about just one topic, but more importantly—practicing it.

Doing is the foundation of knowledge. Simply reading excess material and writing about it (although writing brings clarity) can often lead to biases such as the Dunning-Kruger effect or overconfidence. Simply knowing what something is and knowing how to do it is not the same thing. I wouldn't dare dream of getting in an F1 car!

The Journey So Far

The mini-series has taken readers through a progressive understanding of AI capabilities:

1. How to Use AI Effectively: We dug into the three systems models and assigned them best-case roles.

2. ChatCPT Agent Mode: A semi-autonomous virtual assistant that can execute complex, multi-step workflows or online tasks for you.

3. AI Isn’t Making You Stupid—You’re Just Learning Wrong: We through the latest research in the science of learning, and compared how AI was utilising the knowledge of world-class cognitive scientists, educators and pedagogy experts to help make you smart.

4. My Secret Productivity System: Practical workflows that helped me grow this newsletter to nearly 10,000 subscribers. Including how I use AI.

   ---

Quality Over Quantity

There have been two inflection points since I started The School of Knowledge: after reading Robert Pirsig's Zen and The Art of Motorcycle Maintenance and Lila, and upon writing my 100th piece here on Substack. At both times I was reminded that this isn't a race, quality matters and that the original thesis behind starting a Substack was to help me cope with my ADHD symptoms through writing. I didn't fare great in school, and it was only as an adult in my mid-twenties that the curiosity bug finally worked its way into my body and helped me realise that there's lots I wanted to learn about.

Different strokes for different folks.

Quality is an important subject to me. It always has been—I just didn't realise it before reading Zen. It was important, necessary even, when I was a 19-year-old Royal Marine, important when I returned to college at 29, when other people around me were stuck in careers they hated, important as a business co-owner leading projects and very much important as a writer now. The words I put to paper (digital) are a direct reflection of the many small decisions I have made prior to typing them.

In keeping with that theme I've created:

The AI Advantage: A Comprehensive Guide to ChatGPT, Claude and Gemini.

What You’re Getting

The AI Advantage is:

• 38 pages of consolidated learning

• 13,000 words of practical insights

• 23 core concepts organised into Foundational, Intermediate, and Advanced sections

• A reference guide that transforms you from novice user to operator

The Value Proposition

For paid subscribers, this comprehensive guide is included as part of your membership benefits. For others, it's available as a standalone purchase—an investment in understanding tools that are rapidly becoming essential for knowledge work.

If you’re somebody who wants to start seeing the benefit from using AI and are asking yourself “How do I go from someone who uses AI occasionally, to someone who wields it as a natural extension of their thinking?” This guide answers the critical question.

Looking Forward

The next series will be on Capital Allocation. For those that don't know what capital allocation is, it's how CEOs of publicly listed companies invest their companies' cash, and looking into if they're doing a good job for both the company and its shareholders. Now, you might say "Going from AI to capital allocation is a bit flip-floppy, isn't it?" but I don't think it is, and here's why.

You can replace capital with words such as people, resources, time, energy, commitment etc., and the principles are mostly the same. To allocate something is to distribute it—and the good thing about publicly listed businesses is the treasure chest of information we have available to us as well as books upon books on the people who created them.

They are of course all integrating AI in interesting and novel ways too.

Final Thoughts

In a world where AI capabilities are expanding monthly, having a solid foundation isn't optional—it's essential. This guide provides that foundation, built not on speculation but on seven weeks of dedicated practice and experimentation.

For those ready to move beyond basic prompting and discover what these platforms can really do, The AI Advantage offers a practical roadmap from someone who's already walked the path. If you don’t believe me, maybe take Charlie Munger’s Advice instead:

For paying members of The School of Knowledge, the guide is below the paywall.

For those interested in a one-time payment click here.

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

Whenever you’re ready

The School of Knowledge helps you understand the world through practitioners. Those who try, fail and do (skin in the game). 📚💡

If you’re not ready for commitment just yet, join our growing community of like-minded lifelong learners here:

Subscribe now

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Here's what nobody tells you about productivity tools: most people use them wrong. They collect apps like trading cards—Notion for this, Obsidian for that, seventeen different AI assistants for everything else. Then they wonder why they feel more scattered than before.

The last 4 weeks, I've been exploring how to integrate AI more productively, but the lightning pace at which things can change has left me numb in the brain and feeling, well, unproductive.

I have had a lot of fun exploring the basic functionalities of Claude, ChatGPT and Gemini. I understand them better as tools now, but that's what they'll remain—tools. Not total solutions.

Through learning about AI, I've come to see the value in the tools I was using before. Slower, yes, but steady!

I can't deny AI has opened up ways of working that wouldn't have been possible just a few years ago. The key I've come to learn, though, is in understanding when to use the right tool for the right job—and that includes AI.

My system, if that's what you can call it, isn't perfect, but when I deter from using it, I can feel the ship taking on water. The tools I use can help bale water out, or drag the ship down further.

I've been writing The School of Knowledge part-time for a little over two years now. That's as well as co-running a construction business, which I greatly enjoy. The pair have formed this symbiotic relationship where I can use writing to help me at work, and work to help me write. If I'm calling a spade a spade, I'm not an expert in writing, content creation or pretty much anything, but I have built this Substack to nearly 12,000 people, and I want to share with anyone willing to listen my favourite tips, tricks and tools that got me there.

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Readwise

I've been using Readwise for a few years as a way of capturing highlights from my physical books. It does this by opening up my camera within the app and taking a picture of my highlight. Readwise then converts that passage into text where I can edit, tag and add notes. All of my highlights are in one place, so I can quickly read the highlights of one book or digital file if I wanted to. On top of this, I also have a "Highlights Feed" which can be thought of as a better social media, where instead of reading politically charged rhetoric all day, I can instead read Munger, Pirsig and Seneca—or whoever your favourite writers are.

The app is clean, easy to use, and even has some features that aid actual learning, such as spaced repetition. Readwise has also introduced an AI agent that can scan through my highlights and pull conceptually similar highlights for us to chat about. Great for resource gathering.

Reader

Reader is Readwise's sibling. What makes Reader brilliant is its unified reading experience. Instead of jumping between browser tabs, newsletters in Gmail, and PDFs scattered across my desktop, everything lives in one clean interface. I've set it up to automatically import my Substack subscriptions, so when I sit down for my reading session, I'm not hunting through emails or bookmarks. I just open Reader, and there's my curated queue of quality content. The highlighting syncs instantly to Readwise, meaning I never lose a good quote or insight again.

Kindle

Readwise's ability to capture highlights from a physical book is a game changer, but it's laborious. I had 199 highlights from Poor Charlie's Almanack and it took me hours to upload them all from that book alone. I've tried to upload them immediately after highlighting, but that ruins the flow of reading, and I've tried uploading the previous day's highlights before beginning to read, but whichever way I did it, it was a chore.

So, I decided to buy a book from the Kindle store and give it a go. It worked so much better than my old way. I highlight a passage, take notes and within a few minutes it's uploaded to Readwise and synced to my Obsidian vault upon opening. I still prefer reading a physical book, but having the ability to sync my Kindle, Readwise and Reader highlights directly to my note-taking app Obsidian saves me hours a week, days a month and weeks a year.

For those who are familiar with the book "How to Take Smart Notes," I take notes underneath my highlights, which are called literature notes. These are rough, and most of the time won't make sense to other people; however, these are important as they form the basis of my permanent notes.

Google Keep

The newest addition to my system, I've been using Google Keep to record on-the-move notes. Something Obsidian isn't great at. I can create lists, upload images, audio, set reminders and scribble over anything. Visually appealing and with easy exporting and integration capabilities, it's a great little note-taking app for when i’m on the move.

Capturing information is only half the battle. The other half is organising it before it buries you.

Eisenhower Matrix

I've tried many task management systems, including Thiago Forte's "Second Brain," but I've found most to be too complex—and when things are too complex—they rely a lot on motivation to keep going. I've found that the Eisenhower Matrix is simple, but works for me. Remember what Charlie Munger said:

Every week, I write out what needs doing and then organise it according to its importance and urgency, and just like dark clouds pass after a thunderstorm, so does my brain fog after completing this simple but effective exercise.

Notes Scheduler

Short-form content is hard to keep up with, even if you want to post just once a day. Substack Notes is great for discoverability, but it doesn't let you schedule posting which sucks. It sucks because you can sense when people haven't thought things through and gained the clarity that only writing, editing and time can provide.

How often do the words that come out of your mouth make sense? How often do you wish you would have said things differently?

To combat this, I created a "Substack Notes Scheduler" in Notion. Because Substack has limited API capabilities, I still have to copy and paste the text into Substack when I want to publish. Slightly annoying but it works great. No more opening Substack, clicking the + button and staring at a blank page.

Something I haven't been doing much of recently but need to get back into is sitting down every Sunday and making 7 days' worth of short-form content. Again, this simple system that takes an hour each week helps keep my Substack consistent and is often used as a guide to what long-form content I should write.

Here's where the real magic happens though: turning all that captured information into actual knowledge.

Obsidian

Obsidian is my note-taking app where all of my captured highlights live. From there, I elaborate on them and turn them into short notes. This forms the basis of my permanent collection and from which I write most of my long-form content. One of the key features of Obsidian is the graph view. Because Obsidian uses back links, the graph view represents a brain-like image showing the connections between all of my notes. It's like having somebody else's eyes to see a different world.

Obsidian offers community plug-ins, and this is where it goes from a really good note-taking app to a great one. Even the best knowledge system needs enhancement, and in the next section I show you how AI transforms my workflow from a 7/10 into a 9.5.

Smart Connections

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