Whenever something is not working as well as expected, we seek to understand why and improve it. This is usually pretty straightforward: we figure out its current flaws by observing and interacting with it, fix them, and it should work better. But when this is naively applied to more complex things, such as large systems, it may not work effectively, while giving the impression that we did everything right. This is because we have a tendency to think that the obvious flaws are the most critical ones, which is not always the case. Sometimes, the most discernible issues are not the main cause of problems, and addressing them will only yield superficial improvements, while the true root cause remains inconspicuous and unsolved.

To an observer, any sufficiently complex system, such as large corporations, will be full of obvious flaws, regardless of how well or badly it’s working. Even the most successful companies in the world have their own share of organizational dysfunctions, and they are successful despite them. The exact reasons for the success of a company are not so easy to articulate, but their flaws are glaring and easy to spot. For example, people have been talking about Apple’s internal team dysfunctions quite a lot for a while, and any number of these very obvious flaws can be seen as a company-killing problem. Yet they continue to grow and be one of the richest companies in the world. Of course, they might do even better had some of these flaws been addressed, but it’s clear that these obvious dysfunctions are not stopping them from being wildly successful. Conversely, for a company that is not doing so well, the obvious flaws may not be the reason, and fixing them is not guaranteed to bring huge success to the company.

One reason for the mismatch between what is obvious and what is actually important is our own biases. Our analysis is heavily biased towards things that we can categorize and quantify with structures, numbers, and processes. These are are very specific types of things, ones that we understand well, and that are fairly deterministic. Things like organization structure, communication cadence, and operational efficiency. As a result, these types of flaws are disproportionately over-represented in all the flaws that become exposed to us. But what about the other types of issues, the ones not so well understood because of their nebulosity and not so easily explained because of their nuanced complexity? They may be massive contributors to the big problems we have, yet are rarely surfaced. It’s easy to say that we’ll be successful if we just worked more smoothly and produced more features per week. It’s much harder to justify the claim that we are not successful because of the vertical we are in and that we need to re-think our position in the market.

So we should always look deeper at issues, and never settle for the obvious. Don’t take anything for granted, and ask why is something really important, how will it actually help us. Sometimes the obvious flaws are actually the most critical ones, but that conclusion should be reached only after a thorough analysis from first principles.