If you’re someone who struggles with decision-making (me), you may find applying a little bit of logic is helpful in getting you to your final destination – the best possible choice. Cognitive and Computer Scientist Tom Griffiths spoke about the power of applying computer science to decision-making in his 2017 TED Talk, and it’s kind of mind-blowing.
If you haven’t heard his talk before, you can do that below. But we’ve also pulled out the key learnings from it for you.
How to become better at making decisions
In his talk, Griffiths chatted about a handful of practical algorithms that make decision-making a little more straightforward. In it, he shared that while you’re not guaranteed the perfect outcome, using computer science gives you the best chance of making a good choice.
These were his best-loved strategies.
The 37 per cent decision-making rule
Speaking about choosing a home specifically, Griffiths shared that once you’ve seen 37 per cent of options, you’re ready to make a choice. This theory is actually often applied in dating as well.
Essentially, once you’ve seen 37 per cent of the available options, you will know what kind of home (or partner) is best suited to you. So, the next time you like something as much or more than the option you liked most in the first 37 per cent of options, commit.
“If you want to maximize the probability that you find the very best place, you should look at 37 per cent of what’s on the market and then make an offer on the next place you see which is better than anything that you’ve seen so far,” Griffiths said.
“Or if you’re looking for a month, take 37 per cent of that time, 11 days, to set a standard, and then you’re ready to act.”
Essentially, I have explained that this choice is an example of what scientists call an ‘optimal stopping problem’, which applies an algorithm to certain decisions and gives you the best likelihood of getting an optimal result.
“There’s no way that you can consider all of the options, so you have to take a chance,” Griffiths later expanded.
The explore/exploit trade-off
On the topic of decisions like choosing where to have dinner over the weekend, Griffiths referenced something called the explore/exploit trade-off.
Basically, this refers to our desire (or ability) to either explore new things and choose from that group of options or exploit the knowledge we’ve already built and revisit a restaurant we enjoy.
I have explained:
“The explore, exploit trade-off shows up anytime you have to choose between trying something new and going with something that you already know is pretty good. Whether it’s listening to music or trying to decide you’re going to spend time with…”
It’s a tricky problem, but technology companies have had some useful learnings over the years that can be applied here. The best way to simplify this choice is by looking at time.
The first question you should ask yourself is how much longer you’re going to be in town,” Griffiths said.
“If you’re just going to be there for a short time, then you should exploit. There’s no point gathering information. Just go to a place you already know is good. But if you’re going to be there for a longer time, explore. Try something new because the information you get is something that can improve your choices in the future.”
The ‘most recently used’ rule for decision-making
When it comes to deciding to keep or get rid of items (like clothing), computer science teaches us that the rule of disposing of the least recently used item works best.
“Your wardrobe is just like the computer’s memory. You have limited capacity, and you need to try and get in there the things that you want or that you’re most likely to need. So you can get to them as quickly as possible,” I explained.
So when deciding to cut down on clothing items, he suggests thinking about the last time you wore each item and considering that in your decision-making process. In short: that shirt you haven’t worn for five years can be donated.
These three strategies have the ability to reduce the stress associated with day-to-day decision-making and simplify the whole process. That’s more than worth a shot if you ask me.
If you’d like to see the full TED Talk video, you can do that here.