Audio available in app
Evaluate decisions based on process, not outcome from "summary" of Thinking in Bets by Annie Duke
When we make decisions, we often judge their quality based on the outcome they produce. If things turn out well, we tend to view the decision as good, while if they turn out poorly, we see the decision as bad. This is known as resulting, where we evaluate the decision-making process based on the outcome that occurred. However, this approach can be misleading because it ignores the role that luck plays in determining outcomes. Just because a decision led to a good outcome doesn't necessarily mean it was a good decision, and vice versa. Instead of focusing solely on outcomes, we should evaluate decisions based on the process that led to them. By examining the steps we took, the information we had at the time, and the reasoning behind our choices, we can better understand the quality of our decision-making. This process-oriented approach allows us to learn from both successful and unsuccessful outcomes, as we can identify what aspects of our decision-making were within our control and which were influenced by luck. When we shift our focus from outcomes to process, we can develop a more accurate understanding of our decision-making abilities. We can recognize that even good decisions can lead to bad outcomes due to factors beyond our control, and that bad decisions can sometimes result in positive outcomes through luck. By separating the quality of a decision from the outcome it produces, we can make more informed choices in the future.- Evaluating decisions based on process rather than outcome helps us become more effective decision-makers. It allows us to assess our reasoning, judgment, and information-gathering skills without being swayed by the randomness of luck. By honing our decision-making process, we can increase our chances of making sound choices that lead to favorable outcomes more consistently. Ultimately, focusing on process enables us to make better decisions in a world where uncertainty and randomness are constant factors.