How Expected Value Can Help You Make Good Decisions (Part 1)

If you want more success in your life, learn to take calculated risks when the outcome is uncertain. Get-It-Done Guy has a technique to help you make more good decisions.

Stever Robbins
5-minute read
Episode #313

Are you taking enough risks?

Today’s episode is on decision-making in uncertainty. It may be the most important episode I’ve ever written (and I've written more than 300 of them!). It gets a bit technical, but it’s worth taking the time to understand it. Master this technique and it can change the course of your life for the better.;

One of my favorite classes in business school was enterpreneurship. The professor asked us on the last day of class: Are you taking enough risks? Playing it too safe is a guaranteed way to get nowhere in life.

I’ve thought about this question a lot during my career. My answer is almost always “No.” But I’ve never known which risks to take, and which risks would be…well, too risky.

I can pinpoint 4 decisions in my life that were the wrong decisions. The very wrong decisions! Yet no matter how many times I’ve reviewed them, given the information available at the time, I’d do the same thing again. Luck played a big factor in the actual outcomes, and there was no obvious way to account for that in the decision-making process.

No obvious way until recently, until I met Billy Murphy of ForeverJobless.com

A 29-year-old former professional poker player, turned entrepreneur, Billy wrote an article that gave me the missing piece. In one reading, he changed how I think about decision-making forever. I’ve recorded an interview with Billy here. Be sure to check it out.

The tool he presents is something I learned in my first semester of business school, in the module on decision-making under uncertainty, back before those sucky decisions. But business school never taught when and how to use the tool; they just presented it as an isolated technique. It’s called “expected value.” Now that I understand how to use it, I wish I could replay the last 20 years of my life. In all 4 of my bad decisions, expected value is the missing piece that would have led me to make what ultimately would have been better decisions.

Cost/Benefit Analysis Doesn’t Work Well

We’re trained to evaluate a decision by looking at the costs and the benefits. Or maybe we do a worst case, expected case, and best case. Either way, we compare outcomes and choose what feels like the best path.

But this is a poor way to make decisions. First, we put far more emotional weight on avoiding loss than we do on gaining benefits, so we let the worst case overwhelm our thinking. And then there’s luck. Not all outcomes, costs, benefits, and cases are equally probable. Luck plays a big role, and humans are horrible at reasoning about luck.

Expected value gives a way to include the missing piece—the probability of each alternative—in our decision making.

Expected Value encourages calculated risks when it makes sense.

The expected value of a decision is the decision’s outcome multiplied by the probability of that decision. For example, imagine you have a rigged coin that flips heads 30% of the time, and tails 70% of the time. If it comes up heads, you get $100. If it comes up tails, you get nothing. The expected value of the coin flip is 30% times $100 or $30. If you take this bet 100 times in a row, over time, you’ll make about $3,000—roughly $30 per toss.

Both outcomes can have payoffs attached. Let’s change the game a bit. If heads pays $100 and tails pays $20, then the expected value is $100 x 30% plus $20 x 70%, or $30 plus $14 or $44. Under those terms, if you took the bet 100 times, you’d make around $4,400 or roughly $37 per toss.

See also: Is There a Difference Between Odds and Probability?


About the Author

Stever Robbins

Stever Robbins was the host of the podcast Get-it-Done Guy from 2007 to 2019. He is a graduate of W. Edward Deming’s Total Quality Management training program and a Certified Master Trainer Elite of NLP. He holds an MBA from the Harvard Business School and a BS in Computer Sciences from MIT.