…and we’re back!
Well… that was a long commercial break wasn’t it
In case you missed part 1 of our version of the show “deal or no deal”, you missed the big cliff-hanger and you really should read part 1 first. For the rest of you, to quickly recap, I came out of the closet and admitted by secret teenybopper shame, told the world that my wife had a teenage thing for Jean Claude Van Damme, showed the effect of beer goggles and introduced the notion of cognitive bias and how it can affect judgement.
i also demonstrated how, by altering the frame of reference, to a problem something that at first seems completely unquantifiable “how the hell do I know how many SharePoint developers drive yellow cars?”, is actually not as “impossible” as you may first think.
At the end of the last post I left you with a $10000 dilemma. You had to make a “deal or no deal” decision about going with your estimate about SharePoint developers who own yellow cars, or to instead cast your lot with a bag of marbles with a 9 in 10 chance of winning the prize. Just to refresh your memory, here is the salient part of the pub conversation.
- Me: Okay, so you are 90% sure that here are between 300 and 2000 SharePoint developers in the world with a yellow car?
- Them: Yes
- Me: So, let’s make this like the game show “deal or no deal”. If you are right and the answer is within your range, you will win $10000. BUT you have an alternative…
- Them: Ok…
- Me: What if I were to present you with a bag containing 9 red marbles and 1 black marble and offer you $10000 if you pull out a red marble. Pull the one black marble, and you miss out on the money. Do you want to stick to your estimate or do you want to draw a marble?
So have you decided? Now be honest and see how you went against the 4 outcomes that I have experienced when trying this on people. Here are the possible answers in order of popularity…
- The person chooses to pull from the bag of marbles rather than their ranged estimate. (This is the predominant answer for all people I have tried this with – perhaps 70-75% of all responses).
- The person chooses to use their estimate over the bag of marbles. (perhaps 25% of people have answered with this option)
- Upon hearing the bag option, the person wants to change their ranged estimate. (Happened to me once)
- The person doesn’t care which method.. (never happened to me)
So which is the right answer to this question?
(drumroll) Lets tackle the possible answer in order of likelihood.
“Take the marble! take the maaaaaarble!”
For the 70 odd percent of you who opted to take your chances with the bag of marbles, GONG! you lose!
Better double check your estimates in future because you have demonstrated that you are over-confident in your estimates. In other words, you are suffering from optimism bias. To explain why, think about the original question carefully. I asked originally for a ranged estimate that you were 90% confident with.
I then presented an alternative that has a 9 out of 10 chance of success – also 90%. From a statistical point of view, you should be completely ambivalent as to which option to use. Therefore, despite being asked for a range that you were 90% confident with, the range you actually estimated is not really 90% at all. It has to be less than 90% for you to prefer a clear 9/10 probability.
So that is why you are so stressed and busy! You keep giving crap estimates that make life harder for you! Either that or you are too nice and when your project manager looks at you with those big, sad project manager eyes, your heart melts and you relent.
Isn’t that cool in a nerdy way? It is very interesting to see people’s faces as the penny drops to this logic and they suddenly realise just how bad some of their past estimates have been as a result. The consolation prize is just about 4 out of 5 people do exactly the same as you and take the marbles.
“No deal, I will stick with my estimate”
For the smaller group who decide that their estimate is preferred, you also lose.
In this case, the reason why should be pretty obvious. You are so paranoid about getting it wrong, that you have made an estimate that is more like 95% or even 99% confident. Why? your range is too wide for 90% because when presented with a clear 9/10 chance of success, you chose your original estimate. While that may sound like you are confident, in reality you are a bit of a wuss, because in fact you are under confident with your estimate. So grow some balls you weenie
Honorary mention – “I want to change my estimate”
At the Best Practice Conference in DC, I attempted this pub trick on Yoav Lurie from Synteractive, who is much more of a business and strategic thinker than us IT nerds. His response I think, deserves an honorary mention for being the closest to winning the game. In this example, I asked him to estimate in feet, the wingspan of a Boeing 747. I knew instantly that he was a good estimator because of the logic he used to come to a range.
“Hmm, well an aircraft seat is maybe one and a half feet, and there will be 10 seats in the cabin, with two passages that are probably two feet in width…so that ads up to…”
What do you notice about what Yoav did? Straight away, he related the wingspan of an aircraft (a clear unknown), to something he could make a reasonable estimate of (the width of an aircraft seat). After all, we have all sat in an aircraft seat in sardine (economy) class and know how cramped it is. He knew there were three rows of seats and related this to the width of the cabin, which he then related to the size of the wing. Deducing that the wing might be 4 to 6 times the width of the cabin, he then was able to make a very good ranged estimate of the overall wingspan of the plane.
I was very impressed at his estimate and how he arrived at it, but I still got him
As soon as I presented him with the bag of marbles alternative, without missing a beat he said “I want to change my estimate”. It took only a split second of presenting a clear 90% probability made Yoav realise that his estimate was not 90% and he was still a little overconfident.
That being said, Yoav’s method of relating something known to help frame the reference to something unknown is the only time anyone has used any sort of rigour in forming an estimate and very impressive for the pub setting
The right answer
Okay, so as you may have guessed by now, the right answer is to shrug your shoulders and say “I don’t care” or wave your hand at me and say “pfft, whatever”. (This is one of the few times saying you couldn’t care less is the right answer). In doing so, you have placed equal weight upon the choices, based on the assumption that both are 90% probabilities.
Neat pub trick huh? It certainly gets people thinking.
How to calibrate yourself
Douglas Hubbard talks about “calibrated estimates” in his books and has an appendix of calibration questions, that are designed to help you perceive and account for cognitive bias in your estimating.
What you should take away from this exercise is that when asked to estimate on something you are uncertain about, make your initial estimate. Then, pretend you are in the game show and you have to pick between this estimate and the marble. If you feel that you would take the marble over your estimate, increase the width of your range until you feel that it doesn’t matter which option you pick.
Conversely, if you are one of the wimps who are under confident, then reduce the width of your range, until you feel that you have no particular preference of your estimate vs. the marbles.
In the same way that reframing a problem led from something being unquantifiable to something that indeed had a upper and lower range, by reframing the estimate against a unambiguous probability such as a bag of 10 marbles with 9 red, helps you to account for cognitive bias in your estimates.
So to reiterate my key points to this post
- Many things that seem unquantifiable are easier to quantify than you think, once you think in terms of ranged estimates and probability.
- Your bad taste in fashion and music when you were a teenager still manifests itself today and it is called cognitive bias.
- There are easy methods that you can use to calibrate yourself better so that your estimating radar is more finely tuned.
Most importantly of all however, you learned that my wife liked Jean Claude Van Damme in the 80’s and you know that I am in big trouble when she reads this! 😛
Thanks for reading