Every once in a while we have one of those massive life changing decisions. Should I go back to school? Should I change cities? Is now the right time to get married? There a few decisions we all get that we either look back on as a great triumph or torment us constantly.
Unfortunately there’s no way to guarantee success, nature has a big say in anything would do. But with a simple framework we can drastically improve our odds of making a good decision, and more importantly limit the downside.
Many people think that being successful involves taking huge risks and heroically watching as they pay off. But in reality making a difficult decision is less about nailing that one in a million great opportunity and more about limiting the downside.
Life as a junior analyst at the WB
When I was just starting out in my career, I found myself in a position that most young graduates do. I had worked hard but I wasn’t really happy with what I was doing. On the outside it appeared to be a great job for any newly graduated. But I was becoming increasingly frustrated. In the summer of 2013, I had a choice go to California and learn more programming or stay in DC and work at the World Bank.
Framework for Decision Making
When we use decision theory we’re breaking down our problem into three things a choice, states and the outcome. The easiest way Ive been able to understand it is through visualizing it. The first step is to understand the decision or choice, what are the two options facing you?
In my situation the choice was do I stay in DC or move to California?
The state is where outside forces have a play. In the staying in New York scenario they would be asking for a promotion. In the California scenario it would be applying to jobs.
Finally we have the outcomes. For the move it came down to four scenarios. Im unemployed in California or I do the program and find a job. In the staying in DC scenario, receiving a promotion or staying in the same position would be the outcome.
Making the Decision
I estimated there was a 60% chance of me getting a job in California there in 3 months. And with the little funds I had if that didn’t work out I’d be moving back home to New York where I could find a low paying job. I calculated that overall I would be looking at the following.
Option A: Move to California 60% chance of getting a job in California 80,000 salary from new career 40% going back home to New York 35,000 salary Equity Value = (80,000 * .6) + (35,000 * .4) Equity Value = $62,000 Option B: Stay in DC 85% chance of keeping the same job in DC 40,000 job at the world bank 15% chance of getting a promotion 50,000 job at the world bank with a promotion Equity Value = (40,000 * .85) + (50,000 * .15) Equity Value = 41,500
I ultimately ended up decided to go to California. And fortunately it worked out but more than luck what it came down to was asymmetrical risk. If I failed there was a small downside I’d take a minor payout and work in NYC. If it worked, I would be on a different career path with a much larger salary.
Asymmetrical risk and decision theory is largely about taking risks that have a small downside but huge upside. The hard part is just figuring out whether a risk is such a scenario.
This model certainly isn’t for everything. You can make it in the grocery store without decision theory or a decision tree. And for some people they’ll say that sounds good and well but its soo much work.
All I can point to is this your life and those few big decisions are the ones that you’ll spend reflecting on forever. Wouldn’t you rather look back regardless of the outcome and say I did the best given the circumstances. Decision theory will empower you to do so.