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March 25, 2006

We Are What We Measure


It has often been said that we are what we eat. That might be true chemically but mentally we are what we measure.

Number systems:

Years ago a colleague at work asked me with a straight face what happened in the year 2724.
Me: How would I know? That is in the future.
Steve: Columbus discovered America in 2724.
Me: What?
Steve: Columbus discovered America in 2724. In the octal (8) number system 2724 is the same as 1492 in decimal system.
Steve bordered on genius even if he did come up with crazy ideas. But the point is that recently a forum poster was super happy to get post number 12,000 because of the three zeros. But those three zeros are just a quirk of the decimal numbering system. In octal it would have been post number 27,340, a most undistinguished number.

Sometimes we do weird things because of the way we count.

Investing:

Here is a quote from BuildMWell talking about Philip Morris:
In early 2000, the shares were at their low CAGR and I was a buyer at $24/share and continued buying all the way down to $19/share. The price went to $50/share in under three years. But, in 2003 you will notice that the shares dropped to an even lower CAGR level relative to the stock's history. Most people would never see the 2003 price of $30/share as being more desirable than a $20/share price three years earlier, would they? But, the BMW Method shows this to us very graphically. Seeing how the underlying CAGR of the business affects the prices explains a great deal about the correct logic in buying a stock for us.
It is entirely counterintuitive that $30 is cheaper that $20 and the only way to discover this is by using the right kind of measuring stick, a CAGR chart. If we measure dollars, clearly $20 is less than $30 but if we measure CAGR then $20 might be more than $30. As soon as you start using the BMW method of measuring stock value you become a different kind of investor because we are what we measure.

World Economy:

In Our Brave New World GaveKal Research compares what accountants measure vs. what economists measure and they come to some interesting conclusions. Here is the example:
Let us assume that a Dell PC sells in the US for US$700. Now let's have a look at how this simple transaction is recorded in a) Accounting 101 and in b) Economics 101.

Accounting 101:

The flat screen, built in Taiwan, costs US$300. The margin of the Taiwanese manufacturer is US$30. The mechanical part and the box, built in China, cost US$100, with a margin of US$5. The Intel chip (designed in the US but made by TSMC in Taiwan) cost US$70 with a margin of US$35 going back to Intel and US$5 going to TSMC. The Microsoft software costs US$200, with a margin of 90%, or US$180. Dell tacks on a US$30 profit for selling the PC.

Profits for the US economy: US$35 (Intel) + US$180 (Microsoft) + US$30 (Dell) = US$245

Profits for foreign economies: US$30 (Taiwanese flat screen maker) + US$5 (TSMC) + US$5 (Chinese assembly line) = US$40

Difference: + US$205 on behalf of US companies.

Conclusion: this looks like a good deal all around for the US: the US consumer gets a cheap PC and US companies capture most of the profits in the process. On an accounting basis, everything looks rosy...

Economics 101:

Imports: US$470 (price of PC minus the Dell mark-up and Microsoft software); Exports: US$0
Trade deficit = US$470
Increase in GDP, due to Microsoft, Dell and Intel profits = US$245
Net loss for the US economy, US$470 - US$245 = - US$225

The conclusion drawn by economists: This is a really unsustainable situation. The US economy is moving more and more in debt to foreigners who one day could decide not to sell in the US anymore, leading to a collapse in the US$, a rise in US interest rates, etc.
These data are fed to US lawmakers who decide how the US should interact with the rest of the world. We are what we measure.

Conclusion:

In our scientific culture we place a lot of faith in measuring and counting and often we forget about the underlying values that we are adding up and even the numbering system we are using to do so. This often leads to unreasonable results. It is not enough to know what the numbers say. We also have to know why the numbers say what they say.

Denny Schlesinger
Caracas - Venezuela



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Last updated June 22, 2003