I have been coming across this idea again and again. Importance of structured decision making over reasoning with your emotions.
The scientist Paul Meehl asserted that simple heuristics lead to better decisions. That is, one could create a simple check-list of rules to predict the outcome of an uncertain event, and that check list would trump most experts in accurate prediction.
Algorithms are free of biases after they are created. Though their creation itself may be biased according to the creator’s subjective assessments, once they are codified, they don’t take case to case decisions based on emotions. Thus, they are more robust.
The same idea gets reinforced in Superforecasting by Philip Tetlock. People who forecast accurately are almost hyper-rational and go by base probabilities and clear rules. They ignore what they ‘like’ or ‘feel’. So, for example, when faced with a question of will a startup succeed, a good forecaster will not just look at the team and vision. The first number to think will be the base rate – how many startups succeed? That should be around 1%. From then, a good forecaster will refine the base rate as he or she gets more information – about the market, the product, and the team. The good forecaster is also more likely to clarify the question (what is meant by ‘succeed’ in case of startups?).
The hedge-fund manager Ray Dalio, in this book Principles, offers his own checklist, which he calls his ‘principles’ for life and work. The underlying point is – make clear rules, test them, refine them, repeat. And make decisions with these rules instead of your instincts or feelings.
My own experience aligns with this. In high-stakes decisions, having an ‘all-round’ checklist works. It takes a bit longer to make the decision, but the final outcome is disproportionately better. In looking for a home to rent at Bangalore, I made an exhaustive, almost laughable list of parameters, and kept refining it as I looked at more of them. Finally, we got a really nice place and enjoyed almost 3 years in it before leaving the city.
From these books and articles, some broad principles stand out:
- Be hyper-real. Try to get to the facts as much as possible.
- Get multiple perspectives. People who could look at situations from multiple perspectives were better at predicting the future than people who were very good in one area.
- Bounce off ideas against people who have a successful track record in taking decisions in the given area.
- Test your algorithms against data (if possible, check them on historical data), and keep refining them according to changes in the real world as well as your own learnings.
(this list itself comes from multiple perspectives. Two people are psychologists, one is a medical doctor, and one is a hedge fund manager.)