A Good Rule Of Thumb For Solving Complex Problems
16/04/17 19:06
“Choose the right level of complexity for the particular problem, at the time that you have the resources to do it.” - Shian-Jiann “S. J.” Lin, NOAA (Climate and Weather Modeler)
I love this quote. S.J. Lin is a leading climate and weather modeler at NOAA. The quote was in the context of Lin’s earlier experience of trying to model tornados in the early 90’s when computer technology hadn’t advanced enough to model events at that small a scale. HIs attempt ended up in failure, but like any failure, there are learning experiences if you can do the post mortem.
My simple interpretation of his quote is simply that you have a problem that you want to solve. You also have constraints. Note, I am referring to real constraints, not obstacles, there is a difference, though at the time it may be difficult to tell the difference. Your solution must take into account these constraints. In Lin’s case, the computing power needed to create an accurate tornado model, where basically he was trying to model the tornado at almost molecular level, just didn’t exist at the time he was trying to do it (early 90’s)
Where I find this interesting is in the financial and economic models. If we were going to try and break these down into their finite parts, similar to a physical model at the molecular, then those models would go to individuals, or perhaps households. I think this presents several obstacles, some of which might turn out to be insurmountable constraints. One, I am not sure we have a full understanding of household finances. Yes, we have surveys and the shift to debit/credit card transactions are making it easier to model that, but it is still not fully developed. Addressing privacy concerns will also be a very challenge, but not insurmountable. The one area that might be an obstacle is consumer behavior. Current models are based on rational behavior, but that just doesn’t seem to be the case.
I love this quote. S.J. Lin is a leading climate and weather modeler at NOAA. The quote was in the context of Lin’s earlier experience of trying to model tornados in the early 90’s when computer technology hadn’t advanced enough to model events at that small a scale. HIs attempt ended up in failure, but like any failure, there are learning experiences if you can do the post mortem.
My simple interpretation of his quote is simply that you have a problem that you want to solve. You also have constraints. Note, I am referring to real constraints, not obstacles, there is a difference, though at the time it may be difficult to tell the difference. Your solution must take into account these constraints. In Lin’s case, the computing power needed to create an accurate tornado model, where basically he was trying to model the tornado at almost molecular level, just didn’t exist at the time he was trying to do it (early 90’s)
Where I find this interesting is in the financial and economic models. If we were going to try and break these down into their finite parts, similar to a physical model at the molecular, then those models would go to individuals, or perhaps households. I think this presents several obstacles, some of which might turn out to be insurmountable constraints. One, I am not sure we have a full understanding of household finances. Yes, we have surveys and the shift to debit/credit card transactions are making it easier to model that, but it is still not fully developed. Addressing privacy concerns will also be a very challenge, but not insurmountable. The one area that might be an obstacle is consumer behavior. Current models are based on rational behavior, but that just doesn’t seem to be the case.
