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Imagine you are sitting on the board of the largest global bank. The data used in the board meetings should be pretty accurate, right? Now imagine you are a middle manager with a local manufacturing company. The data used to make a decision regarding equipment upgrades should be just as accurate, if not more so. You have to verify the data in order to trust the data.
Yesterday I received one of those random junk emails that get passed around. Warren Buffett claimed that he could end the deficit by passing “a law that says that anytime there is a deficit of more than 3% of GDP, all sitting members of Congress are ineligible for re-election.” Since I got this on the internet it must be true.
There were many things about the email that made it believable. First and foremost, Warren Buffett said it. There were many statistics on amendments to the Constitution, such as how long it took for them to be passed. There was even a proposed “Congressional Reform Act of 2012” that listed in detail, how Warren Buffett would fix the deficit.
But, there were a few things that made the email unbelievable. At one point Buffett was spelled incorrectly with only one “T.” Anyone can type an email these days. Heck, anyone can write a blog post. I am living proof of that. I was also curious as to how such a good idea was not plastered all over the front page of every newspaper in the world for three months. We all know how politics works so I am not going there.
It turns out the Buffett statement was true after all. The bottom line is trust your instinct. But sometimes you have to question your instinct. Trust but verify. Don’t just assume the data is accurate, we all know what happens when we assume.
Make sure you understand the mechanics behind the data. Take the time to learn the value of the operation, the cost of the machinery, how many workers it takes, the amount of raw materials used, the cost to deliver the product to the customer, and anything else you can value. How can you recalculate the spreadsheet if you do not know the underlying process? Do not just trust the data, verify it.