Monday, January 03, 2005

The Right Tools.

I was originally thinking of calling this post "Choice under Uncertainty", after the many mathematical textbooks expounding the wonders of statistical decision making. However this title seemed much more appropriate after I completed the post.

Calamariforthought and I were talking about blogging and he suggested (in jest) that I apply my spreadsheet skills to this problem. To build some form of simplifed Bayesian probability decision tree based on the weighted average of (subjective) expected utility value of each factor in my decision to stay / go.

Or he says it a lot more clearly. Paraphrasing him from memory: Put down all good things about Singapore. Then put down all the good things about Australia. In the next column, put weightage of importance of the factor. Then in the next column after that, put down a plus or minus depending on if the factor is positive or negative to my well-being. Eventually mathematically reducing the problem to a solution greater or smaller than a mathematical zero.

Why not? After all I have used similar probability-based decision-tree techniques to resolve other problems. And I use similar range-based spreadsheets to try to ferret out the intrinsic value of companies (based on DCF, liquidation, sum-of-parts, etc) in my hobby of stock picking.


I believe Calamariforthought knows as much as I do that this is the absolutely wrong tool for the job.

These mathematical tools have an underlying assumption that you are able to assign risks and work out probabilities of events. For a finite (okay, a limited) number of factors. Obviously not in this case, since most of the numbers are SWAGs.

There are plenty of decision-making theories, so here's another one. You arrive at a situation where you have to make a decision. Reduced to its most essential, there are always just two options. There might seem to be more options at first, but that is a fuzzy phase where everything is still confused, and in that phase there is a danger that the decision-maker suffers the stress of having too many considerations in mind, all at the same time. This won't do. If we analyse the situation, we will ultimately be able to break down all the possibilities down into two options, that are opposite and opposed to each other. Once you are in this phase, you will see the clarity of the choices before you, and you will realise the decision-making is actually rather simple.
- Grace Chow, A Pain in the Neck

As evidenced by this blog, I am still in that "fuzzy phase".
A special version of this “man with a hammer syndrome” is terrible, not only in economics but practically everywhere else, including business. It’s really terrible in business. You’ve got a complex system and it spews out a lot of wonderful numbers that enable you to measure some factors. But there are other factors that are terribly important, [yet] there’s no precise numbering you can put to these factors. You know they’re important, but you don’t have the numbers. Well practically everybody (1) overweighs the stuff that can be numbered, because it yields to the statistical techniques they’re taught in academia, and (2) doesn’t mix in the hard-to-measure stuff that may be more important. That is a mistake I’ve tried all my life to avoid, and I have no regrets for having done that.
- Charles T. Munger, at Herb Kay Undergraduate Lecture University of California, Santa Barbara Economics Department, October 3, 2003

Just because I can build a complex spreadsheet modelling the problem, does not necessarily provide any insights to the problem. Nor does it mean that the spreadsheet correlates to anything in real life.

To a person who only has a hammer, every problem looks like a nail. And a big part about understanding your thinking tools is knowing when not to use them. And I lack the appropriate tools. I do not even know what the appropriate tools are!


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