Saturday, November 7, 2009

The economist, the manager, and the doctor


Whether you are an economist a manager or a doctor, you have been trained to predict: the economist predicts GDP and downturns, the manager schedules and costs and the doctor diagnoses and predicts the effect of cures. What makes life interesting is that those predictions are far from perfect... So here is the dilemma of this post: should you improve your prediction skills or should you focus on managing your mistakes?

Let's start with the economists... they rarely predict well the future, but damn! how confident and thorough they are in explaining what happens! No shame involved. They understand the rules of the game: they live with their imperfect predictions, manage their image and move on. Brilliant!

My relationship with doctors is more personal. Two years ago my son could have died. Why? Sickness and an inaccurate diagnosis: the doctors assumed the most probable diagnostic to be certain. My son was very sick and suffered from respiratory issues up to the point of loosing consciousness and needing reanimation. Unfortunately for him, his twin brother was tested positive to RSV (an aggressive respiratory disease) while he was tested negative: "It could be a false negative Mr.Atria, he didn't have enough saliva for the test" they said. The 2nd day, in the hospital, they missed the time-window for the confirmation test: "It's not a big deal, we do the test only to confirm; we are pretty sure that he has RSV". The 3rd day they tested negative for the  RSV again... so they assumed he had another similar respiratory infection, and continued the treatment. To make a long story short, the poor kid had newborn's apnea and needed to be treated with caffeine. If only the doctors would have seriously considered the possibility that their predictions where wrong!

For the manager, what lesson can we take from the economists and those (bad) doctors? In my experience there is a higher pay-off for addressing the risks of an inaccurate prediction than for improving the prediction itself.

Here are some tips on how to do that:

Tip 1 - Do not try to confirm your predictions. It can be pointless. I'm often pulled-in into discussions where engineers are trying to diagnose some kind of technical problem. Most of the time, they have big discussions on what to test next and they end-up trying to perform tests that can confirm or refute their predictions. This sometimes works, but when it does not, they end-up having multiple hypothesis-test iterations, loosing critical time and money. Many times you don't have to know how something happens, but how to deal with what happens... so why bother knowing?
Tip 2 - Don't fall in love with your predictions. We all hate the unknown and --like a mirage in the desert-- we can easily be tricked by our own brain. Embrace the prediction at first, follow-it to the end and create a scenario that makes sense. When you are satisfied, throw your prediction away, call your alter ego Mr.Hide and start again. Continue collecting the scenarios, ask people around you to give you some new ones. Now you are ready to draw a comprehensive action plan.
Tip 3 - Build decision trees. This is a pretty good tool that can help you seeing the big picture. Many times the value of this exercise is not in the math or the probabilities of each branch, but the type of decision points you have, or their order.... which leads us to the next tip.
Tip 4 - Buy time. Why decide today if you can decide tomorrow? Don't jump to quickly on any action if you don't need to, delay your decision the most you can and let new information weight-in. You never know what tomorrow can bring. Be aware that this can be uncomfortable... it's in our genes, we hate the unknown!
Tip 5 - Buy options. Remember that the unknown works both ways... so be also an optimist and you'll be rewarded.  Assuming you have a grounded multi-scenario game plan, there are as many improbable bad things that can happen than good ones.

For what is worth....here is my prediction:
Failure will burn who does not mitigate risk and success will touch who's exposed to luck.

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1 comment:

  1. I like the story, the personal and the professional sides of it.
    My comment is that no matter what decision we
    are making and whoever the decision maker is, we need data. But data is vague and there's so much of it or is very scarce!
    That's why brilliant doctors, economists and managers have that special capability to identify relevant data when there's so much of it and leverage the existing data to model and extrapolate when data is scarce.

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