Episode 6: Visualizing Decisions with Decision Trees
Have you ever been so stuck on a decision that you start Googling things like:
“Should I quit my job in Sales and join a startup?”
“Should I apply to grad school or am I just avoiding real life?”
“Should I move to San Diego and be closer to my friends even though it’s going to cost way more than my place in Boise?”
(No offense to Boise—but yeah, my instinct is that it’s probably worth making that move to San Diego.)
That’s not overthinking. That’s your brain trying to hold too many possibilities and balance too much information at once—it’s your brain looking around for a giant whiteboard.
And here’s the problem: we are actually terrible at visualizing complex decisions in our heads.
Our brains are not designed to juggle those 3 legs of the decision stool at the same time
Remember these 3 legs from last episode… values, alternatives, and information.
That’s why, in this episode, I’m introducing one of the most practical tools I learned as a decision analysis student: the decision tree.
Decision trees bring the three legs of the decision stool together nicely so you have a solid foundation -
Hey! Great news! You can have clarity of action and be more confident you’re making good decisions -- you won’t be on a stool that has a weak leg and feels wobbly.
By the end of this episode, you’ll be able to take the mess in your head, put it on paper, and see your options clearly to once again, think more clearly and make better choices.
OK, decision trees can get complex, and this topic can start to feel like a math class.
So I’m going to oversimplify things with the cleanest decision problem imaginable.
The absolute GOAT of decisions.
The coin flip.
Let’s say a guy named Mr. Flip comes up to you and says:
Flip: “We flip a fair coin. If it’s heads, I give you $10. If it’s tails, you give me $1.”
If you’re even mildly rational and you have a few dollars to spare, this is a pretty easy call.
You’ve got a 50% chance of winning $10 and a 50% chance of losing $1.
The expected value works out to $4.50.
In other words, if you played this game 100 times, you’d expect to walk away about $450 ahead.
Now, no one is actually walking around offering coin-flip games like this.
But what matters here isn’t the coin — it’s the structure of the decision.
And once you understand that structure, you can reuse it for decisions that actually matter.
So let’s do this! Let’s turn this into a decision tree.
First, the decision.
You draw a square and label it:
“Play the game?”
Two branches:
Yes
No
If you choose No, the decision ends. Nothing happens. Value is zero.
If you choose Yes, uncertainty enters the picture.
That’s where the circle comes in.
The circle represents something you care about but don’t control — in this case, the coin flip.
Two branches:
Heads (50%)
Tails (50%)
At the end of each branch, you write down the outcome value:
Heads: +$10
Tails: –$1
That’s it.
Square = decision with alternatives as branches.
Circle = uncertainty with outcomes as branches.
Numbers = value written at the end of each branch
Once it’s on paper, the decision becomes obvious — even before the coin is flipped.
In other words, we can know we are making a good decision even before the outcome happens. You’ve got Clarity of Action!
Now here’s the important part. This exact same structure shows up all over your real life.
Think about whether to go to a movie on a Friday night. It’s a movie that you feel 50% likely you are going to just LOVE as you are totally in the mood to laugh at a slapstick comedy, but there’s an equal chance based on your past experiences going to movies in this genre that you’re going to be kind of annoyed that you went and feel like you wasted your money.
The decision is: go to the movie OR not, (play the coin flip game or not)
If you don’t go, then there is no value.
If you go, you’re taking a risk. The uncertainty is
“LOVE the movie” (like getting heads and winning the $10)
“End up feeling kind of annoyed” (like getting tails and losing the $1)
So, if you did assign the same values to the outcomes of this decision, then just like the coin flip decision, it should be a simple choice to go to the movie.
Of course, if you felt like the movie had a greater chance of being annoying (not 50-50) or if you felt like being annoyed was equivalent to losing $100, then you’d likely stay home. But the point is you can now map out your decision visually and think about the various components of the stool. You have a visual framework for making better decisions!
OK, let’s not get so excited. I get it, the examples so far are not really major decisions, I get it.
And I’m not recommending we go around and start drawing diagrams about every decision we make?
But once you see how this works, you can use it to think clearly about bigger ticket items.
Think dental work people. And if you’ve ever had any serious dental work done, you know we’re talking about big ticket items both in terms of money and pain!
And this is based on a painfully true story.
Think about whether to get a crown for $2500 or go straight for the root canal even though it’s possible the crown could solve the problem because the dentist is not sure a root canal is needed.
The dentist said,
“Based on x-rays, you will need a crown for sure and you may need a root canal, but we won’t know that for sure until after we put on the crown and give it some time. Of course, I would suggest going right for the root canal as it’s pretty likely you’ll need it and it saves you an extra procedure, but then again, you might not need the root canal, the crown could be fine as is. It’s your call.”
In this case, you might want to map out a decision tree to get a better idea of your options to ensure you are making the best possible choice. I will write up a sample decision tree for this dental decision in case you want to see that one. And by the way, there is a whole field of medical decision analysis that I’m guessing you can start to imagine how that might work with decision trees if you’re following this dental example.
Wow - we’re ending on a dental example! But, we’ve covered what you need to know about decision trees to apply this super practical tool to map out important decisions for years to come.
And now for your assignment. You guessed it!
Pick a decision you are making now or in the near future and create a decision tree.
Take a look at your decision tree and notice the places where you are in control, the decisions, and how they branch into the uncertainties which ultimately lead to an outcome.
Does the decision tree help you see the overall decision and how your choices intersect with uncertainties? Are you missing any information? Do you feel pretty accurate about the chances of each branch coming out of your uncertainty circles? If not, you may have identified the information you need to make a better choice.
Taking the time to map out your decision tree should give you a better grasp of the decision problem. And creating the tree and looking at it may be all that is needed for you to make a decision with confidence.
However, here is a bonus exercise for those of you who are super quantitative and want to calculate the expected value of each decision:
Do the math to calculate the expected value of each decision.
For each decision, simply multiply the probability of each branch coming out of uncertainty nodes by the value you assign to the outcome… Then, add up each outcome weighted by its probability to get the expected value. If you need help, reach out to me directly and share your tree. I’m happy to do these calculations for you!
Congratulations! You’ve made it through these first 6 episodes of the 20Something ToolKit!
These episodes covered what I feel are the essential tools for making great decisions.
Next, we’re going to shift gears a bit and get into something even more foundational.
Learning how to learn.
Lifelong learning turns out to be one of the strongest predictors of long-term happiness, adaptability, and confidence as you get older.
And your 20s is the perfect time to get these learning habits in place as this is your defining decade.
In the next episode, I’ll introduce you to the single most important idea I learned about teaching and learning during my two years at Stanford’s Center for Teaching and Learning.
It’s called expositors
You can think of expositors as vehicles for understanding.
Once you know them, you’ll be able to:
Ask better questions
Measure your understanding
And accelerate your learning of any difficult concept—inside or outside the classroom
Thanks for listening.
See you next time!
Have you ever been so stuck on a decision that you start Googling things like:
“Should I quit my job in Sales and join a startup?”
“Should I apply to grad school or am I just avoiding real life?”
“Should I move to San Diego and be closer to my friends even though it’s going to cost way more than my place in Boise?”
(No offense to Boise—but yeah, my instinct is that it’s probably worth making that move to San Diego.)
That’s not overthinking. That’s your brain trying to hold too many possibilities and balance too much information at once—it’s your brain looking around for a giant whiteboard.
And here’s the problem: we are actually terrible at visualizing complex decisions in our heads.
Our brains are not designed to juggle those 3 legs of the decision stool at the same time
Remember these 3 legs from last episode… values, alternatives, and information.
That’s why, in this episode, I’m introducing one of the most practical tools I learned as a decision analysis student: the decision tree.
Decision trees bring the three legs of the decision stool together nicely so you have a solid foundation -
Hey! Great news! You can have clarity of action and be more confident you’re making good decisions -- you won’t be on a stool that has a weak leg and feels wobbly.
By the end of this episode, you’ll be able to take the mess in your head, put it on paper, and see your options clearly to once again, think more clearly and make better choices.
OK, decision trees can get complex, and this topic can start to feel like a math class.
So I’m going to oversimplify things with the cleanest decision problem imaginable.
The absolute GOAT of decisions.
The coin flip.
Let’s say a guy named Mr. Flip comes up to you and says:
Flip: “We flip a fair coin. If it’s heads, I give you $10. If it’s tails, you give me $1.”
If you’re even mildly rational and you have a few dollars to spare, this is a pretty easy call.
You’ve got a 50% chance of winning $10 and a 50% chance of losing $1.
The expected value works out to $4.50.
In other words, if you played this game 100 times, you’d expect to walk away about $450 ahead.
Now, no one is actually walking around offering coin-flip games like this.
But what matters here isn’t the coin — it’s the structure of the decision.
And once you understand that structure, you can reuse it for decisions that actually matter.
So let’s do this! Let’s turn this into a decision tree.
First, the decision.
You draw a square and label it:
“Play the game?”
Two branches:
Yes
No
If you choose No, the decision ends. Nothing happens. Value is zero.
If you choose Yes, uncertainty enters the picture.
That’s where the circle comes in.
The circle represents something you care about but don’t control — in this case, the coin flip.
Two branches:
Heads (50%)
Tails (50%)
At the end of each branch, you write down the outcome value:
Heads: +$10
Tails: –$1
That’s it.
Square = decision with alternatives as branches.
Circle = uncertainty with outcomes as branches.
Numbers = value written at the end of each branch
Once it’s on paper, the decision becomes obvious — even before the coin is flipped.
In other words, we can know we are making a good decision even before the outcome happens. You’ve got Clarity of Action!
Now here’s the important part. This exact same structure shows up all over your real life.
Think about whether to go to a movie on a Friday night. It’s a movie that you feel 50% likely you are going to just LOVE as you are totally in the mood to laugh at a slapstick comedy, but there’s an equal chance based on your past experiences going to movies in this genre that you’re going to be kind of annoyed that you went and feel like you wasted your money.
The decision is: go to the movie OR not, (play the coin flip game or not)
If you don’t go, then there is no value.
If you go, you’re taking a risk. The uncertainty is
“LOVE the movie” (like getting heads and winning the $10)
“End up feeling kind of annoyed” (like getting tails and losing the $1)
So, if you did assign the same values to the outcomes of this decision, then just like the coin flip decision, it should be a simple choice to go to the movie.
Of course, if you felt like the movie had a greater chance of being annoying (not 50-50) or if you felt like being annoyed was equivalent to losing $100, then you’d likely stay home. But the point is you can now map out your decision visually and think about the various components of the stool. You have a visual framework for making better decisions!
OK, let’s not get so excited. I get it, the examples so far are not really major decisions, I get it.
And I’m not recommending we go around and start drawing diagrams about every decision we make?
But once you see how this works, you can use it to think clearly about bigger ticket items.
Think dental work people. And if you’ve ever had any serious dental work done, you know we’re talking about big ticket items both in terms of money and pain!
And this is based on a painfully true story.
Think about whether to get a crown for $2500 or go straight for the root canal even though it’s possible the crown could solve the problem because the dentist is not sure a root canal is needed.
The dentist said,
“Based on x-rays, you will need a crown for sure and you may need a root canal, but we won’t know that for sure until after we put on the crown and give it some time. Of course, I would suggest going right for the root canal as it’s pretty likely you’ll need it and it saves you an extra procedure, but then again, you might not need the root canal, the crown could be fine as is. It’s your call.”
In this case, you might want to map out a decision tree to get a better idea of your options to ensure you are making the best possible choice. I will write up a sample decision tree for this dental decision in case you want to see that one. And by the way, there is a whole field of medical decision analysis that I’m guessing you can start to imagine how that might work with decision trees if you’re following this dental example.
Wow - we’re ending on a dental example! But, we’ve covered what you need to know about decision trees to apply this super practical tool to map out important decisions for years to come.
And now for your assignment. You guessed it!
Pick a decision you are making now or in the near future and create a decision tree.
Take a look at your decision tree and notice the places where you are in control, the decisions, and how they branch into the uncertainties which ultimately lead to an outcome.
Does the decision tree help you see the overall decision and how your choices intersect with uncertainties? Are you missing any information? Do you feel pretty accurate about the chances of each branch coming out of your uncertainty circles? If not, you may have identified the information you need to make a better choice.
Taking the time to map out your decision tree should give you a better grasp of the decision problem. And creating the tree and looking at it may be all that is needed for you to make a decision with confidence.
However, here is a bonus exercise for those of you who are super quantitative and want to calculate the expected value of each decision:
Do the math to calculate the expected value of each decision.
For each decision, simply multiply the probability of each branch coming out of uncertainty nodes by the value you assign to the outcome… Then, add up each outcome weighted by its probability to get the expected value. If you need help, reach out to me directly and share your tree. I’m happy to do these calculations for you!
Congratulations! You’ve made it through these first 6 episodes of the 20Something ToolKit!
These episodes covered what I feel are the essential tools for making great decisions.
Next, we’re going to shift gears a bit and get into something even more foundational.
Learning how to learn.
Lifelong learning turns out to be one of the strongest predictors of long-term happiness, adaptability, and confidence as you get older.
And your 20s is the perfect time to get these learning habits in place as this is your defining decade.
In the next episode, I’ll introduce you to the single most important idea I learned about teaching and learning during my two years at Stanford’s Center for Teaching and Learning.
It’s called expositors
You can think of expositors as vehicles for understanding.
Once you know them, you’ll be able to:
Ask better questions
Measure your understanding
And accelerate your learning of any difficult concept—inside or outside the classroom
Thanks for listening.
See you next time!
