How to judge a decision
Lets conduct an experiment with 3 heart surgeons. The experiment is to ask them to carry out a difficult operation 5 times. Over the years, we know that the probability of success is 80% or conversely the probability of dying is 20%. Now, in this experiment,
- With surgeon A, no one dies
- With surgeon B, one dies
- With surgeon C, two die
If you think like most people, you will rate A the best, B second best and C the worst. Right?
- In the case of the surgeons, you can guess that the sample size was too small rendering your conclusion meaningless. One can only judge a surgeon if one knows about the field, have carefully monitored the patient and his/her state before the operation, the preparation and execution of the operation etc. In other words, what we need to assess is the process and not the outcome!
- To be fair, in this case, you could also take a larger sample; say 100 or even 1000 operations each and say that there is a 33% chance that no one will die, a 41% chance that one person will die and then a 20% chance that two people will die. This is a simple calculation of probability.
- What stands out in this case is that there is no huge difference between zero dead and two dead. Therefore to assess the surgeons purely on the basis of outcomes will not only be negligent but also unethical.
We are all too aware of this phenomenon in our lives. Welcome to the world of the outcome bias!
- Remember how we blame the selectors of a cricket team for failures post selection? The data and factors, which led to the selection, were relied upon for the initial selection and not the outcome of a series, post the selection.
- Remember how VC’s blame their investee companies or vice versa? The data relied upon for investing or the selection of a VC by the investee was what led to the investment decision.
- Remember that divorces do happen. However, the decision to get married was based on the data, notwithstanding the matching of horoscopes and the assumption that things will work fine, leading to eternal bliss.
- Remember how organisations blame people or vice versa? … the list goes on.
Point of view
A bad result does not indicate a bad decision or vice versa. What is important to understand is the following while judging a decision.
- Were you rational?
- Where your reasons rational?
- Was the data you depended on to take your decision correct?
- Would you still take the same decision given the original data set?
If you answer yes to the above, you decision was correct, though you did not strike lucky the first time.
Founder - SABCONS | Consulting & Training in Project Management, Leadership, Strategy & MS Project
4 年I decided to come out of the corporate world as an employees and start my own venture. Referring to the 4 points in your check-list: 1. I was rational. No impulsive action. 2. Reasons were more emotional than rational. 3. Hardly any relevant data. 4. Yes, of course. Outcome was excellent. Curios to know, did I take the right decision, based on the information given? Thanks for the post, RV Iyer