Decision Journals and Framing Your Bets

Decision journals are designed to create a log of the decisions you’ve made and why you made them. To both capture a snapshot of your thinking at the start, then use the notes to improve your decision making process when you review it later.

I first heard about decision journaling when Ian Stewart pointed to a Farnham Street post a few years back. Then it came up again in late 2017 via Matt on the OFF RCRD podcast. I decided to take another look.

Screenshot of the Farnham Street post about decision journals, highlighting the need for quality control of our decisions.

“You can think of a decision journal as quality control” for your decisions — yes, that fits my mindset. A quality check in six months or a year to prevent hindsight bias.

Here’s the Farnham Street template as a downloadable PDF: Decision Journal Template.

I haven’t made this a standard practice yet, probably because it feels like too much overhead. These days when reviewing success and failure I find myself reflecting back without a full picture of where my mind was at the start. What have a I learned in between? Will I repeat the same mistakes? How can I repeat the top bets that paid off?

For example, for a given decision, what do I expect to change? What am I betting on, and how will I know if I’m right or wrong?

In 2018 I hope to be better at stating my intentions ahead — taking the time to create the snapshot of my thinking at the start. Blogging this publicly to keep myself accountable for journaling the decisions at the start.

Bonus: Two recent mental models for framing your decisions as “bets” that I’ve come across, in case you find them helpful.

  • Mind the Product’s bet matrix, via Brie Demkiw. “I bet that [this decision] will create [this outcome]. I’ll know I’m right when I see [this evidence].

    Screenshot of the Bet Matrix by Mind the Product.

  • Ray Dalio’s expected value calculation in Principles (see my book review):

    Make your decisions as expected value calculations. Think of every decision as a bet with a probability and a reward for being right and a probability and a penalty for being wrong. Suppose something that has only a one-in-five chance (20%) of succeeding will return ten times (e.g., $1,000) the amount that it will cost you if it fails ($100). Its expected value is positive ($120), so it’s probably a smart decision, even though the odds are against you, as long as you can also cover the loss.


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