About delaying the decision

I don’t know whether it is education or what, I prefer certainty & correctness, I would delay the decision until everything is almost settled.

While delaying the decision have the benefit of outcomes with certainty [hence I am almost always “correct”], being correct and having a good outcome are two different things. Our true objective is to have a good outcome, not being correct all the time. But this often traps the people, especially those well-educated [winners from the exam system]

This pattern happens a lot in my previous life:

  • I like a girl, but I delay the decision to keep on collecting the information and guess
  • I want a job, but I delay the decision to ask, just prepare behind the scene
  • I want a hangout, but I delay the decision to ask until others also say they want to meet
  • I want a promotion, but I delay the decision to ask because I think the people should see my great works
  • I have a business idea, but I delay the decision to start until I see others execute & plan it poorly yet succeed

In the end, I am almost correct every time, I get what I correctly predict, unfortunately, that’s probably not the outcome I desire

70/30 rule

I notice this issue back in college time, I keep on pursuing the almost 95% certainty before I make the final decision. Once I make the decision, I could become super efficient. But situations often change, and those well-designed plans are no longer needed/useful

From my statistics background, I should be able to learn more lessons from the expected value formula earlier

  • Using imprecise language, the expected value is the average value you can get from repeated trials
    • lesson 1: If the outcome just hurts our feeling in the worst case, we should pick the strategy with the max outcome and play multiple times, and ignore the failures
    • lesson 2: Avoid things that make you cannot play multiple times, eg: illegal activities, life-risking activities
  • Empirically, P(X) and X are usually unproportional
    • lesson 3: If P(X) is high [you pretty certain about the outcome], X is usually low [outcome is bad], ie: low-risk low return
    • lesson 4: If P(X) is low [taking risk], X maybe high [outcome maybe great], ie: high risk [maybe] high return
    • lesson 5: from lesson 4, even if we take risks, only accept those with potentially high returns, ie: don’t cross a red light, don’t cross stop signs, these high-risk activities don’t have a high return

The rule of thumb for me then is the 70/30 rule, if:

  • I am 70% certain about positive expected value AND
  • I can afford the lousy outcome

Then I should just do it.

Interestingly, for that 30% of a bad outcome, even in the worst case, it is usually not a big deal in hindsight, ie: if you win, +ve value; if you lose, only small -ve value

Since our actions can also affect the outcome and its probability, based on mathematics, we should take more calculated risks and be optimists

This rule increases my options because I don’t need to be correct all the time. My objective function is the high positive expected value, not the high accuracy of predicted outcomes. Rejection and embarrassment are not the evaluation metrics in the former case

End this with an interesting quote: Pessimists are usually right and optimists are usually wrong. But all the great changes have been accomplished by optimists.