One of the core ideas of becoming an effective decision maker is to ensure that the future is easier than our present. We’ve previously explored how good decisions compound over time, to the point where you end up having to make fewer and fewer decisions compared to someone who stacked up lots of bad decisions in their past.
Every decision in your life is both a hypothesis and an experiment with regard to what will happen in the future. Unfortunately, we can never know with certainty the results of any experiment — otherwise, it wouldn’t be an experiment!
So while there is always a degree of risk in any decision we make, some decisions are riskier than others. We should not always judge decisions just by their outcomes; we should judge them by how we handled the information gathering and analysis process during the decision-making process.
Imagine that you have a decision where there is a likelihood of 90% that it will go in your favour. This is a bet that you should make all day long, every single day. And yet, the first time you make it, you may get that negative 1-in-10 result. That doesn’t mean it was a wrong decision, the odds were in your favour, and it just didn’t work out in this specific instance.
And so, we come to the question of balance in information gathering for decision making. How do we know when we should keep gathering more and more information, hoping to get further insights and certainty, and when we should just stop, make the decision, and act?
How can some people easily and confidently move forward with decisions even when they are missing what appears to be critical information? This is while others get completely stuck in overthinking and gathering ever larger amounts of information, that, instead of providing clarity to the decision-making process, hinders it even further.
How do we find the right balance between gathering information and taking action?
The critical thing is to understand the law of diminishing returns, which states that the level of marginal output decreases as the number of inputs increases.
This is true for all things in life, not just decision-making. For example, if you study for an exam for one hour, you’ll likely get a better grade than if you didn’t study at all. But if you study for two hours, you probably won’t get twice the grade — the law of diminishing returns applies.
In decision-making, there comes a point where gathering more information provides no real value and can even be detrimental to the decision-making process. When this happens, you need to be able to stop yourself from going down the rabbit hole of analysis paralysis and make a decision.
I touched on this point of diminishing returns in my essay on The Inverted U Curves of Life, which you may want to read for a further discussion on how this idea can be applied to our lives more broadly.
So, what’s the solve here?
Well, let’s break it down by the risks:
- Deciding too soon — This is what happens to people who are too risk-tolerant and optimistic. They don’t want for enough information, and then later on they wish they had paused and learned more before making a decision.
- Deciding too late — This is what happens to risk-averse people, and they end up missing on significant opportunities in life. They gather more information and build up anxiety, and sometimes just make an arbitrary decision because a specific deadline has to be met.
So, a good framework should help both types of these people to make better decision. One group has to slow down, the other has to learn to speed up.
In Part 1 of this series, we discussed the consequential/inconsequential and reversible/irreversible matrix, and this same tool carries across and works very well here. We can apply different techniques based on which quadrant of the matrix the decision falls into.
As a leader, this is important because you need to think about the pace of decision-making, and also which decisions you make vs which you let others make. Essentially, the more irreversible and consequential a decision, the more time you want to spend decision if all else is held equal.
If a decision is reversible and consequential, gather evidence and then decide.
If anything is below a certain point of consequentialism, let’s say 50%, I would suggest just making a snap decision. If you are in a leadership position, you don’t even bother to decide — delegate this to someone else.
One word of warning here, this does not mean that details do not count. I often make tiny product decisions regarding my software startup Blue, such as the language used in a pop-up message or the precise design of a component. While these are small decisions, and reversible, I believe that they are highly consequential, because our entire business model relies on the fact that we make an incredibly easy-to-use platform. If I don’t care about this — who will?
Let’s remember that bad decision-making is due to missing information that we wish we had at the time, or the lack of ability to process information in a coherent manner. Unfortunately, this second problem is one of those hard problems, where people often have a double ignorance of the subject: they don’t know that they don’t know how to process information correctly.
Putting that aside, it means that if we have the right information, we should be able to make better decisions when everything else is equal. However, information takes time and energy to gather, and so we need a simple heuristic to decide when to continue to gather more information, and when to simply act.
We can think of these as two possible modes to be in:
- ASAP — I think everyone is familiar with this acronym, which means “as soon as possible”. It means that we want to move quickly, and we’re looking for the type of information that will give us a clear-cut positive or negative indicator that we want to move forwards or stop.
- ALAP — This is not in the common lexicon, but it means “as late as possible”.
You want to use ALAP only when decisions are irreversible and inconsequential because more of the right information = better decision making. But, this can also be taken to extremes in itself. At the maximum, you will eventually die, so you probably want to make the decision before then.
In all seriousness, if you keep waiting, eventually, you will get to the point where you start to pay the opportunity cost for waiting and not making a decision: you start to lose opportunities. It is just before this point when you want to asses the information at hand, and then make the decision. This ensures that you are working with the best information possible, but you have not paid the price for it.
On the other end of the spectrum, you may have inconsequential decisions, and those you want to take asap — the biggest risk here is that these decisions hang around for a long time and clog up your mental space and distract you from the far more consequential decisions in life.
This is where delegation can also come into its own. As a leader, you should always be trying to delegate as much as possible because this helps to build the confidence, judgement, and experience of the team around you, and it makes these people feel like valued team members. If a leader slows down reversible and inconsequential decisions, it can be highly demotivating to those in the team because it makes them feel that their judgement cannot be trusted. In these cases, it is better to let team members make a decision and then correct later if required instead of not giving trust in the first place.
Turning back to the big decisions, those are highly consequential and irreversible, the key question we should be asking ourselves is: When do we know when to finally act?
The simple answer is when you believe you are at the top of the inverted U curve: any more data and time spent on this decision will not help, and it will actually hurt. Signs that this is the case can include :
- You have multiple experts who have given you their best estimate, and they all say it is time to act.
- All the people who are going to be affected by this decision have had a chance to give their input, and you have synthesized that information as best as you can.
- You are trying to find new information, but you are now going to low-quality sources of information.
- Conversely, you have already found the key piece of information that makes the decision very clear — then just stop and make the obvious decision.
- You have considered all the risks and rewards, and you believe that the potential upside outweighs the potential downside.
- Your team is getting restless, and they are starting to lose faith in your ability to make a decision.
These are just some of the signs that indicate that you may be at the top of the inverted U curve, and that it is time to act on a decision finally. The key is not to wait too long, as this can lead to sub-optimal decision making, but also to not act too soon, as you want to ensure you have all the information necessary to make the best possible decision.
The other key thing to consider is when you are waiting so long that you start to lose opportunities . As I said before, this is the opportunity cost of waiting, and it is something you need to be aware of. If you wait too long, you may find that the window of opportunity has passed, and you have missed your chance.
This is a good excerpt from Tribe of Mentors by Adam Robinson:
Virtually all investors have been told when they were younger — or implicitly believe, or have been tacitly encouraged to do so by the cookie-cutter curriculums of the business schools they all attend — that the more they understand the world, the better their investment results. It makes sense, doesn’t it? The more information we acquire and evaluate, the “better informed” we become, the better our decisions. Accumulating information, becoming “better informed,” is certainly an advantage in numerous, if not most, fields.
But not in the eld of counterintuitive world of investing, where accumulating information can hurt your investment results.
In 1974, Paul Slovic — a world-class psychologist, and a peer of Nobel laureate Daniel Kahneman — decided to evaluate the effect of information on decision-making. This study should be taught at every business school in the country. Slovic gathered eight professional horse handicappers and announced, “I want to see how well you predict the winners of horse races.” Now, these handicappers were all seasoned professionals who made their livings solely on their gambling skills.
Slovic told them the test would consist of predicting 40 horse races in four consecutive rounds. In the first round, each gambler would be given the five pieces of information he wanted on each horse, which would vary from handicapper to handicapper. One handicapper might want the years of experience the jockey had as one of his top five variables, while another might not care about that at all but want the fastest speed any given horse had achieved in the past year, or whatever.
Finally, in addition to asking the handicappers to predict the winner of each race, he asked each one also to state how confident he was in his prediction. Now, as it turns out, there were an average of ten horses in each race, so we would expect by blind chance — random guessing — each handicapper would be right 10 percent of the time, and that their confidence with a blind guess to be 10 percent.
So in round one, with just five pieces of information, the handicappers were 17 percent accurate, which is pretty good, 70 percent better than the 10 percent chance they started with when given zero pieces of information. And interestingly, their confidence was 19 percent — almost exactly as confident as they should have been. They were 17 percent accurate and 19 percent confident in their predictions.
In round two, they were given ten pieces of information. In round three, 20 pieces of information. And in the fourth and final round, 40 pieces of information. That’s a whole lot more than the five pieces of information they started with. Surprisingly, their accuracy had flatlined at 17 percent; they were no more accurate with the additional 35 pieces of information. Unfortunately, their confidence nearly doubled — to 34 percent! So the additional information made them no more accurate but a whole lot more confident. Which would have led them to increase the size of their bets and lose money as a result.
Beyond a certain minimum amount, additional information only feeds — leaving aside the considerable cost of and delay occasioned in acquiring it — what psychologists call “confirmation bias.” The information we gain that conflicts with our original assessment or conclusion, we conveniently ignore or dismiss, while the information that confirms our original decision makes us increasingly certain that our conclusion was correct.
So, to return to investing, the second problem with trying to understand the world is that it is simply far too complex to grasp, and the more dogged our at- tempts to understand the world, the more we earnestly want to “explain” events and trends in it, the more we become attached to our resulting beliefs — which are always more or less mistaken — blinding us to the financial trends that are actually unfolding. Worse, we think we understand the world, giving investors a false sense of confidence, when in fact we always more or less misunderstand it.
You hear it all the time from even the most seasoned investors and financial “experts” that this trend or that “doesn’t make sense.” “It doesn’t make sense that the dollar keeps going lower” or “it makes no sense that stocks keep going higher.” But what’s really going on when investors say that something makes no sense is that they have a dozen or whatever reasons why the trend should be moving in the opposite direction.. yet it keeps moving in the current direction. So they believe the trend makes no sense. But what makes no sense is their model of the world. That’s what doesn’t make sense. The world always makes sense.
In fact, because financial trends involve human behavior and human beliefs on a global scale, the most powerful trends won’t make sense until it becomes too late to profit from them. By the time investors formulate an understanding that gives them the confidence to invest, the investment opportunity has already passed.
So when I hear sophisticated investors or financial commentators say, for example, that it makes no sense how energy stocks keep going lower, I know that energy stocks have a lot lower to go. Because all those investors are on the wrong side of the trade, in denial, probably doubling down on their original decision to buy energy stocks. Eventually they will throw in the towel and have to sell those energy stocks, driving prices lower still.
And this is something that I often had to explain to clients in Mäd that wanted to spend far too much budget on research for User Experience and User Interface Design.
You need a surprisingly small sample size — sometimes as few as five individuals — when trying to figure out usability problems. Each additional interview will indeed yield new findings, but the core findings will be in those first five or seven interviews. Each person you interview after that will tell you more and more of what you already know and less and less about what you don’t.
I believe a lot of clients can’t quite believe this because they are used to the type of market studies that do broad canvassing and speak to hundreds or thousands of people to understand trends and sentiments.
So a few things to recap from today:
- Slow down when making irreversible and consequential decisions.
- Speed up when making reversible and inconsequential decisions.
- Understand how the rule of diminishing returns applies to gathering information for decision-making purpouses.
- The time is right to make critical decisions when you’re about to start losing opportunities or you’ve stopped gathering any further useful information.