Evidence of Intent

This post is a warning about UPS in New York. I missed a UPS delivery 3 times, called the 1800 number and was told to pick it up at 522 Greenwich in downtown Manhattan. The pickup center could not find my package, and was staffed by rude and unmotivated personnel. They were also looking for the package by hand, without any type of computer help. The UPS call center has no connection with the pickup center, you have to call the pickup center itself to confirm that your package is there.

By setting up their central call center this way, UPS shows a blatant disregard for the worth of customer time. The disparity between the delivery logistics (which are quite good) and the end-point exception handling (absolutely terrible) is amazing.

Econtalk this week mentioned an incredible fact, that the US GDP has a very tight growth band around 3%:

I was surprised that I’ve never known this before. The reason, I think, is that usually we see plots of year on year GDP growth, which look like this:

It is difficult to see that not only does the average (well, the geometric mean of 1+growth, to be exact) come to 3%, but also that the averages for shorter intervals of time also come to 3%; the deviations are highly anti-correlated and cancel themselves out fairly quickly, but this is not visually obvious.

Additional reading:

http://www.econbrowser.com/archives/2009/03/trend_stationar.html
http://krugman.blogs.nytimes.com/2009/03/03/roots-of-evil-wonkish/
http://econlog.econlib.org/archives/2009/03/greg_mankiw_get.html

The reductionist analytic modeling recipe goes like this:

1. Pick a system to study, choosing a boundary around a region in the world and mentally sectioning it off – everything inside that boundary is the system and everything outside is the environment.
2. Simplify the system by picking a few details to pay attention to, ignoring everything else. Divide the system into components with defined states and define interactions between components. Some parts have defined interactions that reach through the boundary defined in step 1, and interact with the environment.
3. Assemble those parts back into the whole, building up complexity by computing how the various combinations of states of the various parts interact with each other.

Step 2 simplifies while step 3 complexifies. Step 2 is semantic while step 3 is syntactical. If the results from step 3 successfully predict the behavior of the system, then the simplifications in step 2 are said to capture the essential details of the problem.

By thinking of the work accomplished by analysis as due to these three types of work, you could find the limiting reagent and spend more time on that. The analytic engine you are improving could be personal, collective, flow or even batch-oriented.