All Data is Not Created Equal

May 31, 2012 by Phil Simon in Data Management, Data Quality

My friend Mark Cenicola and I were having one of our power-packed breakfasts the other day in Sin City. Somehow, we arrived on the subject of the stock market and the P/E ratios of Amazon, Apple, Facebook, and Google. As of this writing (late May of 2012), the P/Es of Apple and Google are about 16:1. Pretty conservative, eh? Contrast that with the comparable numbers of Amazon and Facebook are more than 100:1. The word gaudy comes to mind.

If you think that Apple’s stock is expensive now, if Wall Street valued it the way that it values Amazon or Facebook (again, as of this writing), Apple would cost more than $3,000/share. Google’s in the same ballpark.

Note: I’m pretty sure that no one else eating pancakes at that Las Vegas’ restaurant was having that type of discussion that morning.

In the subsequent days, Mark tweeted the following post on stock market valuations by Jean-Louis Gassée. Yes, it’s long, but it’s an interesting read. To be sure, there are reasons (whether or not they are actually valid is anyone’s guess) as to why each company is valued as it is. I won’t pretend to fully understand the stock market. If I did, I wouldn’t write books, speak, and consult. The bottom line is that investors don’t view all data equally.

And our perceptions on the future of each company nonetheless color what we think of all sorts of investment data: earnings, profits, EBITA, gross and net margins, P/E ratios, and the like.

Simon Says

All data is not created equal – and it never really has been. If you want the data to tell you that Apple is a bargain, then it is (certainly relative to Facebook). If you think that Facebook is reasonably priced, then again I can’t argue with you. It’s certainly not the only company with a sky-high valuation.

On another level, certain data is clearly understood: an employee or a product come to mind. But do we agree on everything? Of course not. What is a customer? What is a monthly user? And how much is each worth?

Data only reduces uncertainty. It does not eliminate it, nor does it obviate the need for discussion and judgment.

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Tags: Data Management, Data Quality