By Kevin DeLuca
We are constantly faced with optimization problems throughout the day: What will be the fastest way to get to work today? Do I go through the drive-through or park and go inside? Should I commit to reading this ThoughtBurner post or do something else in my free time? We want to be as happy as possible, which means that for each of these choices we try to choose the best or optimal decision. Luckily, we’re usually pretty good at figuring out the best course of action and live pretty efficient lives.
Suppose, however, that at every little decision you made during the day, you chose a less-than-optimal choice. You would have been happier doing something else, but for some reason you didn’t take the time to think hard enough about your decision. You made a mistake – you took the busier route to work today. A single optimization error may not make much of a difference, maybe only a few wasted minutes of your life. But imagine that out of the estimated thousands of decisions we make every day, 10 or 100 or even 1000 mistakes are made. The effect starts to add up until you realized you wasted a ton of your time or gotten yourself stuck in a bad mood.
I believe there is a huge loss in efficiency and happiness due to our natural inability to optimize every single little decision-making problem we face during a typical day. While a wasted minute here and an inconvenience there may not seem like a big deal, the effects start to add up over time and across people.
Why do we make these mistakes? The most obvious barrier is that, often, the potential benefit of ‘solving the optimization problem’ for these little, everyday decisions is less than the mental cost of that calculation – that’s why you skip it in the first place. We are efficient and instead of solving each problem individually we use heuristics to answer them, usually by making assumptions or acting out of habit. But our assumptions aren’t always right, and our habitual actions aren’t always optimal. In fact, a lot of work in applied economics involves testing whether or not assumptions are true or not. In many of our daily optimization problems, the tools of economics could help us make better choices. We could learn, for example, under what conditions it would be better to take the drive-through rather than park and go inside.
Professional economists don’t worry about helping people solve the little decisions – usually they have their sights set on bigger fish, and rightly so. But the questions that are interesting to non-economists are about the little problems they face all the time, and I think that by framing and solving these problems with economics we could make a lot of people’s lives more efficient and happy. Using economic methods, we can test the validity of certain assumptions and, from there, dispel inefficient or unsupported behavioral prescriptions.
The cost to figure out many of these assumptions – the cost of performing research, collecting and analyzing data, along with disseminating the information – is too high for any one person to do. The extra minute or two saved by a more efficient decision isn’t very useful if it takes days or months of your time to figure it out. But if someone else provided you with the information, then you could costlessly incorporate it into your decision making and better optimize. And if enough people used the information, we might see a net overall benefit – the months of research might save, in sum, years of time, minute by minute, person by person.
Enter ThoughtBurner. Part of what this blog and website hopes to accomplish, in addition to providing unique economic commentary on variety of issues, is to incur the cost of research and analysis for the ‘little things’ in life, the daily optimization problems. Drive-through or park and go inside? Let’s do observational research and look at the evidence. How drunk should you really be before you hit your beer pong skill level peak? Time to record stats on beer pong players. Should I like my friends Facebook post or not? These are the sorts of questions that people ask themselves all the time, but that have never been inspected with the rigor of formal economic analysis, which is exactly what ThoughtBurner research is meant to provide.
My hope is that people will learn something useful from ThoughtBurner, whether it’s the answer to an everyday optimization problem they’ve faced or a new way for them to frame an old issue. I figure that, while I don’t know quite enough about economics to answers the ‘big questions’ (yet), I can probably handle the smaller ones, and I hope to do it in a way that is practical, entertaining and useful for everyone.