A Jack Handy Moment – Randomness and Infinity


Hang on to your socks for this one… ’cause it hurts my brain just trying to type it.

I had a Jack Handy moment the other day. Remember Jack Handy? The character from Saturday Night Live? Anyway…

I was sitting in a classroom half listening to a fellow student attempt to kiss up to the teacher by droaning on and on about financial theories and randomness and unpredictability. My mind started turning over the idea of an unpredictable stock market and all the variables that would have to go into being able to predict its behavior – “chaos theory” popped into my head as a term. Now whether or not “chaos theory” is actually applicable to this topic is beyond me. Sometimes I don’t know if my brain is really good at picking things up and applying them correctly or if my brain just likes to throw things into the mix to make me think I’m smart. My brain likes to mess with me.

I digress…

So as I sat there contemplating how many variables would have to go into predicting the stock market, it dawned on me that the size of the regression equation needed to predict such a thing would just go on and on and on… to infinity! That made me wonder if things we call “random” are really just variables to infinity? Which then made me think of all the times at work I watch people hand wave past “hard problems” as they spout “random” rather than digging into the process improvement – because THEY don’t see it as a process that can be improved. THEY see it as random when in reality, it might just be a really big set of variables but it’s NOT random. THEY are just lazy.

So, if we were to plot the number of variables in a process on the X axis and the loudness of an executive yelling “random” on the Y axis… I suspect we’d get an inelastic curve at around 3-4 variables. Everything beyond that on the X axis would result in one, giant, RANDOM scream from executives.