Like many people, you may be thinking some version of “But I can’t answer my key uncertainties! It would take years to know for sure!”
Well, yes, as a matter of fact. You probably can’t eliminate all of your uncertainties. But that isn't the point. You’re not trying to achieve certainty. You’re trying to reduce your uncertainty so that you can make better decisions.
I took a class with an unusually eccentric professor during my undergrad. This professor claimed that every possible outcome is equally probable, and hence we can’t make inferences about what is more likely to happen based on what happened in the past. Now, I don’t know if this women literally believed that the sun was equally likely to rise in the east or west tomorrow, but that is the literal interpretation of her stated beliefs.
This stance probably seems ludicrous to you. It certainly did to me. But I think a weaker version of this belief is actually fairly common. The weaker belief is that we can’t be certain, so it isn’t worth trying to get more information.
Not at all! The picture isn’t black and white, but there are still darker and lighter shades of gray. We have a lot of data that we can use to narrow our guesses about what the outcome of different decision would be - in other words, the probabilities of those outcomes. Even given our uncertainty, it can matter a lot to go from 50% certainty to 80% certainty. So don’t toss up your hands yet.
It might help to think in probabilities. For example, is it 50% or 90% certain that you’ll get that promotion? Or what is the range of options that you’re 90% confident contains the real answer? You can say something is “medium” vs “very” likely to happen, but it’s easier to get confused. How often do “medium” likely things happen? How often do “very” likely things happen? What is the difference, and is it consistent? By the time you get to the end of that train of thought, you’ve already put rough numbers to the words, and those numbers may be easier to check and track.
Relatedly, spending a bit of time improving the accuracy and calibration of your guesses is low hanging fruit for making better decisions. The book How to Measure Anything has a great chapter on calibration training, and the Open Philanthropy project commissioned a calibration training tool you can try out here.
Uncertainty reduction is always proportional to how much you already know. If you know very little, then it is very easy to reduce your uncertainty at least a little bit. For those of you familiar with Bayesian reasoning, reducing your uncertainty is equivalent to updating your prior probabilities.
Similarly, it’s extremely common to find uncertainty aversive. Not knowing exactly what to do may be the single most common cause of procrastination. When you have a big or important decision in front of you, it can feel overwhelming even choosing what exactly you need to decide on.
So start by decomposing your decision. What do you already understand? What smaller steps do you know how to do? Who can you ask about the parts you’re confused by? You already have a lot of information - start there! And it’s not cheating to start with small steps like asking for help if you’re really confused.
Finally, you’ll often have to accept that you’re never going to be entirely sure. Once you’ve removed what uncertainty is worth removing, you need to make a decision despite the remaining uncertainty. You can always gather more or better information. Ultimately decision-making is based on judgment calls. Let’s just make them well-informed judgement calls.