Getting Comfortable With 'Good Enough' in Investing
When you first start analyzing companies, it's easy to get bogged down in the details and feel a need for absolute certainty. To break free from that mindset, it helps to look at how Warren Buffett handles uncertainty—he’s a master at it. He often repeats the idea that it’s better to be “approximately right than precisely wrong.” This is a core lesson for anyone interested in .
Even though Buffett is more familiar with financial statements than almost anyone, he understands the danger of getting lost in the numbers and losing sight of what truly drives a business: its competitive advantage, or moat. This is why he calls himself a business analyst, not a financial or securities analyst. The distinction seems small, but it’s massive. A financial analyst might believe the numbers are what drive a company's performance. A business analyst, however, knows that the numbers, ratios, and stock price are all just outcomes of the business's underlying quality. This is a fundamental concept in understanding at its core.
The Power of Approximation
This is where the concept of “earnings power” comes in. It’s important to be reasonably accurate when figuring out a company’s potential earnings, but we have to keep the exercise in perspective. The real goal is to find incredible businesses with durable competitive advantages. Once you've found one, you can then make some reasonable approximations about its earning potential. Properly used, earnings power is a valuable tool, but it’s not meant to be calculated down to the last decimal. It’s about being “directionally accurate.”
Let’s look at an example using my past analysis of Amazon’s earnings power to see how this works in practice. Suppose you felt my estimate of a 10% margin for Amazon’s online segment was too optimistic. That’s fine. We can cut it in half to 5%, which is even lower than Walmart's margins. While this is a huge change in our assumptions, the actual effect on the company’s valuation is pretty minimal. This adjustment lowers the company’s earnings power by about 15% and raises the multiple from fifteen times to eighteen times.
Why Precision Doesn't Matter as Much as You Think
Now, let's look at it from the other direction. What if you believe my estimates were actually too low? Maybe you used a different framework, like Bennett Stewart’s EVA, and after adjusting for things like sales, marketing, and R&D costs, you calculated that Amazon’s earnings-power multiple was closer to twelve times. The thing is, it doesn't really change the final verdict much. Whether the multiple is twelve or eighteen, the conclusion remains the same: Amazon is a table-pounding buy. This is the kind of insight that can turn from a gamble into a calculated strategy, making it an excellent .
Looking back, my initial projections were indeed on the conservative side, especially regarding 2020. Cloud computing growth was right on track at 30%, but e-commerce, supercharged by the pandemic, grew by nearly 40%—double what I had projected annually. This just goes to show that the real value comes from identifying a high-quality business, not from nailing a precise forecast. When you’re , focusing on the big picture is far more important than getting lost in the weeds of a spreadsheet.
