I am in the process of reading “Principles: Life and Work” by Ray Dalio. Overall the book is very good and informative but one chapter really caught my attention: Learn How to Make Decisions Effectively.

In particular, what stood out there was the author’s explanation of making decisions as expected value calculations.

When you make a decision or take action that can either result in success or a failure, you have these factors to consider:

- the probability that the action will result in success
- reward gained if the action results in success
- the probability that the action will result in failure
- penalty/loss if the action results in failure

The expected value (EV) for such a decision then can be defined as follows:

EV = Probability of success * reward – probability of failure * penalty

EV greater than zero can be thought as a winning decision and if you have multiple choices, pick one that has the highest expected value.

A quick example from the book: let’s say the reward for being right is 100$ and the chance of you being right is 60% (0.6). The penalty is also $100 dollars (and the probability is 0.4 arrive at 1-0.6). Then EV = 0.6 * 100 – 0.4 * 100 = +20.

This simple example is all well and good but check out couple thoughts now to branch out further.

The best bet is not always a bet with the highest probability. If something is very probably but has a small positive outcome and very large negative outcome, the EV is negative.

A decision can have a relatively small chance of success but if the payoff is much larger than the cost if you fail, that decision has a positive EV and is the right choice as long as you can cover the loss. This is where investments in risky but highly rewarding endeavors can pay off greatly. Again, as long as you can cover the losses.

If you stick to “playing” with EV positive outcomes, over time you will come on top. The key is to make sure you have a good information and feel for the event’s probabilities and costs.

What’s cool is that when taking an action or making a decision, you have four things that you can leverage to increase your EV: increase your chance of success, increase your positive outcome, decrease the chance of failure, decrease the penalty. Not always all four are malleable but you would be surprised how often there are other options to consider that increase the expected value. Following such thought process teaches your brain to search for alternatives that influence the four factors I just mentioned.

Furthermore, when you start searching for different options with better odds, the actual odd value is less important than knowing that the decision you are picking is either less risky (you are decreasing the chance of failure) than the previous one or is more rewarding, etc.

Now whenever I am working on let’s say a feature release, I consider expected value formula and ask myself: what’s my confidence level that what I am releasing will work correctly? In my profession (software) this is often tied to proper and extensive testing and validation. If I get a feeling that I could have done more testing, I right away do so to increase the chance of success. If the release goes wrong, what is the worst that can happen? This often makes me re-evaluate the size and scope of the release and if possible I break things up into smaller pieces which means the impact of a negative outcome will be smaller.

I am continuing to dig and have thought exercises with this rule but so far it has been very beneficial.