Thursday, March 31, 2011

The Price of Parking

I live in the Philadelphia area. If you've ever been to a Philadelphia sporting event you understand that there exists a certain kind of crazy that envelops the area just before game time and hangs around to varying degrees after the game depending on the outcome. If you are a true Philly fan you drink the crazy Kool-Aid. I don't, but my father-in-law has season tickets to the Flyers so occasionally I pretend to get a little punch drunk.

I don't live in an area that makes it feasible to take public transportation so I usually end up driving to the stadium from work. Parking is an assumed cost (as is $7 beers) but the last game I went to the price was pretty steep: $15. That is opposed to just three years earlier when I could get a spot for a mere $10. This was painful enough to force me to look at it more when I got home - and so I did.

There wasn't much to be gleaned from the fact that prices had risen over the past few years. Especially since Phildelphia built three new stadiums in the last ten years and, unfortunately, there is a blanket excuse to raise prices without cause lately: the poor economy. In either case, in thinking about all of this I started to consider how information can be used to manipulate people. More specifically, I imagined how the owner of the lot might try to explain away the increase to his (or her) customers.

As a consumer, I might approach the situation with the argument that the cost of parking has risen exponentially over the past five years. Certainly, from the following representation that might make sense:

Of course, that is presented in precisely the right way: the scale is only large enough to include the data points being shown; there is no history previous to 2007 where a consistent price may have been held (the two data points at $10 hint at this, however); and there is no comparison to other lots and/or prices in the area.                           

The counter to that point of view might look something like this:
Plenty going on here. First, and probably most important, is the scale: adjusting the scale results in a trend that appears closer to linear than exponential. Other factors: extending the range (going back to 2001); a carefully chosen cost of living number - modest, but keeps total profit negative; keeping the number of games high (it is a multiplier of the profit). In addition, the loss is not exactly negative income per patron, it is lost profit against the chosen cost of living increase.

In exploring this thought experiment I've only enforced what I already know: we, as presenters of data, have an obligation to be honest and straightforward. Data can be made to tell any convenient story; we would do well to remember that when consuming and producing information.

"The most dangerous untruths are truths moderately distorted." - Georg Lichtenberg

Incidentally, I had to leave that game early due to my daughter being very tired. On the way out I was helping my daughter put on her coat and a boy came over and asked if he could give her a puck. It seems he caught the puck during the game and wanted my daughter to have it. Well her eyes lit up and, of course, it completely made my night. Certainly worth the price of parking if you ask me.

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