In life, our decision-making capability is often judged by the outcomes of our decisions. When we achieve good results, it means we made good decisions, and when we achieve bad results, it means we made bad decisions.
At first glance, this makes perfect sense and why would it not? A good decision is expected to lead to good results and a bad decision is expected to lead to bad results. That's the way we're taught.
However, this type of thinking has some significant limitations, and the reason for that can be explained by statistics.
The way I see things, a good decision is one that is statistically more likely to result in a positive outcome. Likewise, a bad decision is one that is statistically more likely to result in a negative outcome.
This separation may sound simple, but it makes all the difference.
Let me illustrate this point by sharing a very common example:
Imagine I'm browsing X (Twitter) as I often do and I stumble upon one of the hundreds of crypto-influencers shilling a memecoin. I read some of their tweets or maybe join a Space that they are hosting, and after a few minutes, I'm very much convinced that this memecoin is about to explode.
I immediately fire up my go-to exchange, I throw a few hundred bucks at this promising memecoin and, deciding that I had enough fun for the day, I go to bed.
The next morning, I woke up to a dozen different alerts on my phone saying my shiny meme coin jumped 1000% overnight. I made it! Thanks, Twitter influencer, you are the best!
I rush to my exchange once again and swap my very valuable back into a reliable stablecoin, pocketing a huge profit.
Now, looking back, was following this influencer into investing in this meme coin a good decision? According to the mindset mentioned at the start of this article, yes, it was a very good decision. I made a lot of money in a short period of time! What can be better than that?
But let's take a minute to look at the alternative definition that I proposed before: a good decision is a good decision is one that is statistically more likely to result in a positive outcome. Another way to put it would be "a decision that should be repeated over and over again."
Under these new optics, the situation changes drastically. I no longer consider this investment a good idea because data shows that 76% of Twitter influencers promote dead memecoins, meaning that should I repeat this decision, I would lose money more often than not.
Suddenly, that didn't seem like such a good decision anymore, despite the fact that I had made a lot of money with it.
The key takeaway of this article is that the quality of a decision does not depend on the quality of the resulting outcome. In the example above, I showcased a scenario where a bad decision resulted in a good outcome, but the contrary is also perfectly possible. A good decision can and sometimes will lead to a bad outcome, but that doesn't change the fact that it was a good decision to begin with.
It all comes down to statistics and risk management. It's easy to look at a decision in hindsight and use this failed concept to evaluate it based on the outcome, but we only had so much information at the moment we had to make such a decision.
It's very tempting to judge a decision based on its outcome but that way of thinking is fundamentally limited.
A better way to evaluate a decision is based on its "repeatability." A good decision is one that should be repeated over time.
Moreover, it's entirely possible that a good decision will result in a bad outcome and that alone doesn't make it a bad decision. Sometimes, a bad outcome is just a bad outcome.
