Spreadsheets are a great tool, but they tend to offer a level of certainty that’s often not justified.
We’re taught to believe that more data and more intricate calculations lead to better decisions, but that’s a myth rather convincingly debunked by researchers Green and Armstrong. In their paper, “Simple versus complex forecasting: The evidence,” they showed that when it comes to predicting the future, complexity doesn’t actually improve accuracy. In fact, it usually hampers it.
After looking at nearly a hundred comparisons, they found that highly complex models actually increased forecast error by an average of 27%.
They argue for a “simplicity principle,” suggesting that our elaborate models are often far less reliable than a good old-fashioned rule of thumb. Or even just basic extrapolation. Sure, multi-layered regressions involving hundreds of variables feel sophisticated, and in a way they are, but they frequently fall over because they can’t distinguish between a meaningful trend and random noise.
Psychologist Gerd Gigerenzer makes the same argument, noting that simple mental shortcuts usually outperform complex calculation. In most types of real-world environments, close enough is usually good enough. And, indeed, about the best you can hope for anyway.
It sounds overly simplistic, but a basic rule like “only invest in companies with positive sales growth, significant insider ownership, and solid unit economics” can be far more useful than a twenty-tab financial model. The complex analysis is perfectly tuned to a fictionalised future that may never eventuate, while the simple rule captures a fundamental truth about incentives and sound business logic.
The more you try to quantify every little thing, the more you lose sight of what actually matters. The fact is that many of the most important features of a business are qualitative and structural. The kinds of things you won’t find in the financial statements, such as the perceived value of a brand, or a founder’s obsession with their product. Which is why relying only on the quantitative is its own kind of risk; that of being precisely wrong instead of roughly right.
That’s not to say you should invest only on “vibes”. Or that’s there’s no value in running the numbers. Only that we shouldn’t be seduced by the false precision of fancy formulas and models, at least not without the broader context of all the messy stuff that isn’t so easily corralled.
Not everything that can be counted counts, and not everything that counts can be counted.
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