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Every business decision carries a hidden weight. The choice to hire someone, launch a product, or invest in new software demands we calculate something we can never fully know: the future. So we build spreadsheets. We construct models with assumptions stacked on assumptions like a house of cards in a wind tunnel. We pretend certainty lives in our formulas.
But the most valuable decisions often happen on napkins.
Not because napkins are magic, but because they impose limits that spreadsheets don’t. You can’t fit thirty variables on a napkin. You can’t hide bad logic behind elaborate formatting. The napkin forces you to think clearly about what actually matters. It’s the opposite of most business analysis, which often resembles adding more ingredients to a soup that already tastes wrong.
This matters because complexity has become the default costume we wear when we want to appear serious. A simple analysis feels vulnerable, like showing up to a formal dinner in jeans. But that vulnerability is precisely what makes it powerful.
The Tyranny of Precision
Consider how most cost benefit analyses unfold. Someone builds a model projecting costs and benefits over five years. They calculate net present value. They assign probabilities to different scenarios. The final document has charts, sensitivity analyses, and enough decimal points to make you believe they’ve somehow conquered uncertainty.
The problem isn’t that these tools are useless. The problem is they seduce us into believing we know more than we do. That third decimal place doesn’t make your estimate about customer adoption rates three years from now any more accurate. It just makes it look more accurate, which might be worse than admitting you’re guessing.
The napkin approach flips this. Instead of building elaborate structures of pseudo certainty, you ask: what are the three things that actually determine if this works? Not fifteen things. Three. Maybe five if you’re feeling ambitious.
When Howard Schultz decided to expand Starbucks, he didn’t need a complex model to see that people would pay more for better coffee in a pleasant environment. The insight wasn’t complicated. The execution was hard, but the core logic fit on a napkin. If we create a place people want to be, and coffee they prefer to drink, and we don’t mess up too badly on the operational details, we’ll succeed.
That’s not laziness. That’s clarity.
The Three Questions That Matter
Real napkin analysis starts with identifying what actually drives the decision. Usually, it comes down to three fundamental questions, though they wear different disguises in different situations.
First: What’s the real cost? Not the number in the budget line, but the actual resource commitment. If you hire someone, the cost isn’t just salary. It’s the time spent managing them, the opportunities you can’t pursue because your attention is divided, the cultural impact of adding someone new. Sometimes these hidden costs dwarf the visible ones. Other times they barely register. But you have to name them.
Second: What’s the real benefit? Here’s where most analyses go sideways. They list every conceivable positive outcome, assign values to each, and sum them up. But benefits don’t add that way. If you’re considering new software that saves time, increases quality, and improves employee morale, you can’t just add those together. They interact. Sometimes they conflict. The key is identifying the primary benefit, the one thing that would justify the decision all by itself. Everything else is either supporting evidence or distraction.
Third: What has to be true for this to work? This question does more work than any spreadsheet. Every decision contains assumptions. Making them explicit transforms the analysis. If your new product launch requires reaching 10,000 customers in six months, that’s not a projection to model with probability distributions. It’s a hypothesis to test. Can you name ten potential customers right now? Have you talked to any of them? The math doesn’t matter if the underlying assumption is fantasy.
Why Simple Usually Wins
There’s a paradox hiding in complex analysis. The more variables you include, the more ways you can be wrong. Each assumption you add multiplies your error bars, even if the spreadsheet smooths everything into neat projections. It’s like building a tower from playing cards and calling it structurally sound because you used enough cards.
Simple analysis forces intellectual honesty. When you can only write three things on your napkin, you have to choose the three that actually matter. This is harder than building a model. Models let you include everything and pretend it all matters equally. Napkins make you decide.
This connects to something psychologists call the conjunction fallacy. The more detailed a story becomes, the more believable it feels, even though each additional detail actually makes it less likely to be true. A business plan that accounts for seventeen contingencies feels more robust than one that focuses on three critical factors. But probability doesn’t work that way. Every additional assumption is another thing that can go wrong.
The napkin protects you from your own storytelling instincts.
When Napkins Beat Models
Some decisions genuinely require complex analysis. If you’re valuing a pharmaceutical company with multiple drug candidates at different stages of FDA approval, you probably need more than a napkin. But even there, the napkin comes first. Before you build the model, can you explain in three sentences why this might be a good investment?
If you can’t, the model won’t save you. It will just give you more sophisticated ways to be wrong.
Where napkins really shine is in everyday business decisions. Should we attend this conference? Can we justify this expense? Is this partnership worth pursuing? These questions don’t need models. They need thought.
Take the conference decision. The cost is obvious: registration, travel, time away from work. The benefit is supposedly networking, learning, and exposure. But be honest. When was the last time a conference genuinely changed your business? Unless you’re speaking or you know specific people you need to meet will be there, conferences are usually expensive ways to feel busy.
The napkin makes this clear. The model obscures it with projections about “brand value” and “relationship building” that sound meaningful but signify nothing.
The Counterfeit Benefit
Here’s something most cost benefit analyses miss entirely: many benefits are counterfeit. They sound good in the analysis but don’t actually help you.
Information is the classic example. We treat information as inherently valuable. More data must be better than less data. But information only matters if it changes what you do. If you’re going to launch the product anyway, market research that confirms your bias isn’t a benefit. It’s an expense pretending to be prudence.
This shows up everywhere. Training programs that don’t change behavior. Analytics dashboards nobody looks at. Strategic planning sessions that produce documents nobody reads. These things all pass standard cost benefit tests because we value the input rather than the outcome.
The napkin question cuts through this: If we do this, what will we do differently afterward? If the answer is nothing, the benefit is counterfeit.
The Opportunity Cost Nobody Calculates
Every decision has a ghost twin, the thing you didn’t do because you chose this instead. Economists call this opportunity cost. Everyone nods knowingly when it’s mentioned. Almost nobody actually calculates it.
That’s because opportunity cost is genuinely hard to measure. What would you have done with the money, time, or attention you’re spending on this decision? The answer is usually “I don’t know” or “something else valuable.” So we ignore it.
But on a napkin, you can’t ignore it. The space is too limited. When you write down the cost, you’re forced to think: what else could this buy? Not in abstract terms, but specifically. The $50,000 you’re spending on new furniture could hire a contractor for three months. The twenty hours a week you’re dedicating to this project means something else isn’t getting done.
Sometimes the opportunity cost is low. You have money sitting around and this is the best use you can find for it. Fine. But often, the opportunity cost is the real cost, dwarfing whatever number appears in the budget.
The Question Your Spreadsheet Can’t Answer
Here’s what really matters and what no amount of analysis can tell you: Does this decision make you more of what you want to be?
This sounds soft, maybe even frivolous. But it’s the most practical question you can ask. Every decision shapes your organization’s identity. Hire a certain type of person, you become a certain type of company. Enter a certain market, you become a certain type of business. The cumulative effect of these choices matters far more than any individual return on investment.
A company that takes on any client who can pay becomes a very different entity than one that’s selective. The difference doesn’t show up clearly in yearly revenue figures. It shows up in culture, reputation, and the opportunities that come your way a decade later.
You can’t model this. But you can ask it. On a napkin, you can write: If we do this, who do we become?
The Art of Good Assumptions
Every analysis rests on assumptions. The difference between useful analysis and elaborate fiction usually comes down to assumption quality.
Good assumptions have three properties. They’re explicit, testable, and few. Most business analysis fails on all three counts.
Explicit means written down and acknowledged. “We assume customers will pay more for quality” is explicit. Building a pricing model without ever stating that assumption is not. The assumption is still there, buried in your numbers, but now nobody can examine it.
Testable means you can check if they’re true without waiting five years. If your analysis assumes customers want a certain feature, you can test that by asking them. If it assumes a market exists, you can look for evidence. Untestable assumptions are just hopes wearing business casual.
Few means you’ve done the hard work of separating what matters from what doesn’t. Spreadsheet models let you hide behind complexity. Napkins force you to choose.
When Analysis Becomes Procrastination
There’s a reason people sometimes build elaborate analyses for straightforward decisions. Analysis feels like progress. It generates documents and meetings and the appearance of rigor. It’s also safer than deciding.
If you analyze something long enough, circumstances might change and make the decision for you. The opportunity might disappear. Someone else might solve the problem. Analysis becomes a sophisticated form of avoiding responsibility.
The napkin test catches this. If you’ve been analyzing something for weeks and still can’t articulate the basic logic on a napkin, you’re either dealing with something genuinely complex or you’re stalling. Usually it’s the latter.
This doesn’t mean you shouldn’t gather information or think carefully. It means the thinking should make things clearer, not more obscure. If your analysis is making the decision harder to explain, something’s wrong.
The Real Skill
Doing good napkin analysis isn’t about being casual or careless. It’s about developing the judgment to know what matters. That’s much harder than building a spreadsheet.
Spreadsheets are comforting because they’re mechanical. Follow the formulas and you get an answer. It might be wrong, but at least the process is clear. Judgment is messier. It requires understanding context, seeing patterns, and admitting uncertainty.
But here’s the irony: the people who build the best complex models are usually the ones who could explain their recommendation on a napkin first. The model doesn’t create their insight. It validates and stress tests it. The napkin comes first.
If you can’t explain why something makes sense simply, you probably don’t understand it well enough to be modeling it.
Making It Practical
So how do you actually do this? Start with three boxes on your napkin, real or metaphorical.
Box one: What does this really cost? Include money, time, attention, opportunity cost, and anything else that’s actually scarce and valuable.
Box two: What’s the primary benefit? Not every benefit. The one that justifies everything in box one by itself.
Box three: What has to be true? List the critical assumptions. The things that, if wrong, make the whole decision wrong.
If you can’t fill these boxes clearly, you don’t understand the decision well enough yet. That’s valuable information. It means you need more thinking, not more analysis.
If you can fill them clearly and the logic holds, you probably have your answer. You can build a fancy model afterward if you need to convince someone else or if you genuinely need to stress test the numbers. But you’ll know those are supporting tools, not the actual decision making.
The Napkin as Clarity Tool
The real power of napkin analysis isn’t that it’s fast or simple. It’s that it forces clarity. In a world that rewards appearing sophisticated, choosing clarity takes courage. But it’s also the only reliable path to good decisions.
Your napkin can’t lie to you the way a spreadsheet can. It can’t hide weak logic behind impressive formatting. It can’t make a bad idea look good through the magic of compounding assumptions. What you see is what you get.
And sometimes, what you see is that the decision is obvious and you’ve been overthinking it. Sometimes you see that it’s actually much riskier than you thought and you need to reconsider. Sometimes you see that the real question isn’t whether to do something but how.