Today, we talk about options. A few thoughts we consider: Are options always good? How often do we think about *all* of our options? Is there a way to trend towards having only good options? And, most importantly, how can we strike the right balance between time invested and optimal choice?
Today, we talk about options. The word "optionality" typically refers to the amount of flexible agency a person has in a given scenario; not necessarily a discrete number of options, but how much latitude there is in a given decision-making process.
A few thoughts we consider: Are options always good? How often do we think about *all* of our options? Is there a way to trend towards having only good options? And, most importantly, how can we strike the right balance between time invested and optimal choice?
And underappreciated and very important thing in our lives is our options. And very often we imagine that the choices that we have have different options than they actually do. Additionally, we often make choices without thinking about the resulting or the cascading options that we're either opening ourselves up to or we're closing ourselves off from. In today's episode, I want to talk about at least approaching this idea, thinking about options more clearly and trying to find a sweet spot. My name is Jonathan Cutrell, you're listening to Developer Tea. My goal in this show is to help driven developers like you find clarity, perspective and purpose in their careers. So when we talk about options, what exactly are we talking about? Well, a very simple example of this is going to the grocery store and looking at the options for, let's say, cereal. You're walking down the cereal aisle and you see hundreds of boxes, different varieties of cereal. And this is a really good metaphor because this encapsulates a lot of the way that we have to think about options. There are multiple variables in choosing cereal. There are, for example, the variable of price, the variable of quantity, the variable of taste, the variable of health or nutrition. These are all differing variables and they all kind of interplay with each other. You can get a very cheap but healthy cereal. Imagine a multiple matrices of ways of choosing what is the best possible cereal you could have, presumably a cheap cereal that also happens to be highly nutritional. And you can get a lot of it. Maybe that's a value. And interestingly, when we talk about options, we also have these things that are personal values are not necessarily good or bad. Even if we have cultural norms around them, for example, we may have a cultural norm around cereal being healthy. But let's say the healthy cereal that we've kind of culturally accepted to be healthy, maybe it has something in it that you are allergic to. And so for you, you kind of opt out of that kind of default good option. Similarly, we have a cultural norm around buying bulk, tending to be a better choice than buying smaller because you tend to get more for your money. But that's also not necessarily a good thing either. So options are a mix of these things that are kind of unequivocally or at least generally accepted to be good things, beneficial. It's a mix of beneficial things and or non-beneficial things. And then of course, a mix of things that are personal preference. Okay, so these are options. And so you're going down the cereal aisle and you find out that some of your options are very similar to each other. You can have honey nut Cheerios or you can have Cheerios, right? Hopefully I'm not infringing on a trademark here. You could have your frosted flakes or you could have corn flakes. These are similar options. And you can even have an off brand version versus an on brand version. Here's what's interesting about that particular, we're going to stress this metaphor as far as we can. That particular comparison is having off brand and on brand. They may have exactly the same fundamental structure, right? This is the same ingredients in both of those options. They may taste the same. The only difference is in your perception. Logically they're exactly the same except for the box, right? Something that matters to a trivial amount, the way that it's packaged. In every other way, they may be identical, but the way that it's packaged may change the way you perceive those options. Okay, so we're going to set aside the cereal metaphor and imagine that this has implications for all of our options, all of our choices. You can imagine that we have options that are very similar and then you can have options that are totally worlds apart. You can have fruity pebbles versus miniweights. These are two totally different cereals. I said we were going to set cereals aside, but of course we're going to stretch it once again as far as we can. So you have these variety of options in most scenarios. Very often we don't see all of the options that we have, first of all, right? This is one of the kind of cognitive issues that we have is we ignore the vast majority of options because it's difficult to make a decision when we have too many options. So in order to make a decision, we reduce the dimensionality in some way, one way to do that would be to remove a bunch of the options or to totally ignore a bunch of the options. Maybe we are going to totally remove all of the brands that we are unaware of or that we don't know anything about. Or maybe we're only, you know, we're going to sub-select. We're going to create a smaller selection of our options based on some arbitrary rule, right? Maybe even a rule that we don't know, maybe just the things that are in our eyesight. We aren't necessarily explicitly creating this rule, but we're implicitly only choosing the things that are in our eyesight, in our eye line, you know, level with our heads, right? We're creating this implicit system, this implicit filtering system, and this happens in real life too, right? The things that we see, the things that are most apparent to us might be the things that we choose as our option set, okay? Additionally, when you choose an option, right? So we've already done this dimensionality reduction gymnastics where we take all of these options that we otherwise would have, theoretically we have, you know, hundreds of options or potentially an endless number or close to endless number of options, and we reduce it down. Our brains would love to have it down to two options. And we've chosen that we're only going to go with either Cheerios or Honeynut Cheerios and no other cereals exist in our little cereal option universe. So once we have this choice on the table between options, the interesting thing that we very often don't think about when we make decisions, when we make choices between options is what do we leave ourselves with? What options do we leave ourselves with? And I'll explain a little bit more here about what that means. So let's back up. The set of options that you have for the cereals in front of you is based on another choice that had options, which is which of the stores are you going to visit? If you go to a grocery store, you're going to have a totally different set of options than if you were to go to a convenience store. They may have 10 options at a convenience store, a hundred at a grocery store. Similarly, if you were to go to, let's say something like Whole Foods, you're going to have a totally different set of options from the options that you had either of the other two places, right? So you have optionality that begets optionality. In other words, the options that you face now are likely the reason or the result of options that you've previously filtered through. All of our lives are these cascading sets of options. And choosing our option sets based on our resulting option sets is one of the most important levers we have in our lives. Pay attention to this very closely. If we choose option sets that leave us with better options and we do that continuously. If we continuously choose options that provide us better options in the future, by default, we're making, we're kind of biasing ourselves towards better choices. So in other words, if we only have good choices in the future, only good options to choose from if option A, B, or C are all good for us or they are all helping us meet our goals. If we choose an option that gives us A, B, or C rather than say C, D, or E, D, or E, not as good as A, B, and C are, if we choose options that buy us towards A, B, and C, then we're more likely to make good choices in the future because our option set has gotten better. All right? So this is meta thinking, right? We have to think about the options that we have in terms of the options that they are going to provide us as we move forward. So let's take it back to serial because everybody understands serial and everybody has to love serial, right? If you choose, let's say you choose Cheerios ever, Honey Not Cheerios, well now you don't necessarily have to choose between Honey Not Cheerios and Cheerios because it's not that hard to add Honey to Cheerios, right? It's kind of a convoluted example, but if you were to choose something that already has a lot of decisions made for you, then your optionality in the future is reduced. Okay? If you choose something that has reducing optionality in the future, then those choices are cascaded further forward. And here's why that matters. As you begin to limit your data set or your option set, as you begin to reduce that dimensionality where you have fewer and fewer options or you have fewer and fewer kind of characteristics that filter those options out, right? Then your options become easier to pick from. So the goal isn't necessarily to increase the total number of options to a theoretical maximum, right? We shouldn't have to try to evaluate every possible option ever available. Think about that. There's no way that you're going to read every single label on every single cereal box. Instead, you're filtering mechanisms, the choices that you make about how you filter, the choices that you make about what store you pick to shop from, right? That is going to have a greater effect because your decision making power is never going to be able to evaluate everything. And when we kind of give up on that evaluation side, which is the slow thinking, when we resort to fast thinking, when we resort to kind of intuitive thinking, when we say, oh, that label makes that cereal look healthy and therefore it probably is, this is intuitive thinking. We see green and we imagine that it's healthy. Well, that's going to lead us down a potentially bad path because, you know, we're going to have a lot of that evaluation that we've done would be very useful, but it's impossible to do it across a full option set. So what we should be focusing on is a sweet spot. How can we avoid the maximum, right? We don't want all of the options on the table to try to evaluate because that's impossible and we're going to end up reverting to intuitive gut base decision making, which is likely to end poorly eventually. But we also don't want the opposite end of the spectrum where we only have two options or even worse, we only have one option or we have to choose no option, right? That's a really bad scenario. We want to increase our optionality. We have to have the right number of options to be able to choose something that we've evaluated thoroughly without having to evaluate every possible option, right? So this is where satisfying, if you've ever heard the term satisfying, I encourage you to go and Google it. Satisficing is basically choosing a limited option set, right? Based on some predetermined criteria, really good filtering mechanisms, good heuristics, well thought out heuristics to filter out some things. And instead of getting everything perfect, we just bias it towards the good. In other words, we're probably going to get it right or close to right most of the time, but sometimes we have to sacrifice getting it perfect, right? There's a big gap between good enough and perfect and we need to be shooting for good enough most of the time with our optionality. What that means is we don't need to evaluate every single cereal box. We need to look for the ones that have the right things. For example, maybe you're going to use price and calories as your two filtering mechanisms and then you can choose from that subset and those filters are going to provide you with the right number, right? That's one example that you can think about. Other examples of filtering to the right number and using these heuristics, we can find in our everyday lives, we can find choosing a software development platform, a language, for example. Well, does this language have a lot of people who use it? Very simple example, right? Does this language have a really good documentation? I'm only going to choose a language that has good documentation. That's going to cut out a lot of languages. So now you're not having to evaluate every single metric on every single language. You're reducing your options to a known good set, right? And here's why it's called satisfying because it's a supportment of sacrificing and satisfying. So you're making a satisfying decision based on some level of sacrifice. You're sacrificing some things that you don't know. Maybe there's a language out there that would be incredible, even though it doesn't necessarily have good documentation. So you might be filtering out false negatives. There may be a serial on the shelf that is worth the extra calories just because it has some stellar, nutritious value in it. But you filtered it out because you're choosing a particular metric to filter on. This is how optionality should work. We should look for a specific level of optionality that hits a sweet spot where we can actually evaluate our options, right? And where we're biasing ourselves towards good options that we're opening up into the future. And we're not going all the way down to, oh, we're only going to pick the perfect serial. And if the perfect serial doesn't exist, we don't have any serial at all. We've chosen none of these match our criteria, right? And we also don't want it to be so broad that trying to determine which one of these is the perfect serial takes the rest of our lives. That's a nearly impossible feat. So to wrap this up, because we've talked a lot about different options and we've done more than our fair share of talking about serial today, we want to wrap this up by understanding how do we search for that sweet spot? The first thing to do is to stop looking at the options and start thinking about the result. What is it that you're trying to do here? Don't try to use your intuition to decide between your options. What is it that you're trying to do? So think about the result. But I also want you to think about the result as a transformation function, right? What does that mean? Well, instead of thinking about the result as, oh, once I make this decision, this is the final thing that will happen. That this is the end of the line for this decision-making process. I want you to think about the result as a option maker. When you make this decision, whatever your next important decision is, what will that decision provide you in the future? What kind of options does that decision open up for you? What we want to do is think about our options that are coming out as a result of our decisions, not just our options, during a decision. So all of our decisions are these chains of choosing between options. And as we refine ourselves into better options sets, then necessarily our decisions are going to ultimately be better. If all you have on the shelf is healthy cereal, your decisions are kind of made for you in a way. You can only eat healthy cereal. Thanks so much for listening to this episode of Developer Tea. I hope you enjoyed this episode. I hope you like cereal as much as I do and are as intrigued about decision science and all of these kinds of psychological but practically important kind of crevices of thought that we explore on the show. I hope you enjoy this episode as well as other episodes of this show. And if you haven't listened to this to this podcast before, then I encourage you to subscribe if you enjoyed this episode because we do a lot of episodes like this one. You can subscribe in whatever podcasting app you're currently using. Developer Tea is exploring new options this year. We're likely to start releasing videos on YouTube at some point, hopefully early this quarter. Watch out for that. 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