We live in a world of data spin, and without realizing it, you may start to believe your own hype
It's not news that in today's tough political and marketing world, it's largely about spin and hype. It's amazing how spokespersons can take one set of data and facts (I am using that term very loosely here) and say it means such-and-such. Then, when they get completely contradictory data, they effortlessly say it means the very same thing as in the first case. A few random examples:
∑ When the price of gold or real estate is low, they tell you now is a good time to buy. OK, I get that, it's the basic "buy low/sell high" approach. But when the price actually is high, they tell you it's also a good time to buy, since the price is absolutely, definitely on a positive trajectory.
∑ When the unemployment numbers are falling, we're told that's good, for obvious reasons. But when the numbers are rising, we are told that's also a good sign, since it is really due to more people entering the pool of job seekers. So either way, it's good.
∑ When climate data shows a rise in temperatures, that's due to "global warming". But when we have an extremely cold winter, that's really due to climate fluctuations caused by--you guessed it--global warming.
There are many other examples, but you get the picture. I am pretty sure that the readers of this column and these sites are not naÔve fools who are easily manipulated by such transparent spin.
But while we may be resistant to this spin-management of contradictory numbers when others do it to us, we may not see it in our own work. When we look at data from a test run, results of a performance assessment, or comments from beta users, we may see and conclude what we want to see and conclude. We may be so invested in the project that we unintentionally fool ourselves.
Here's an example which many of you may have experienced: the focus group. When an attendee in the group says "I like your feature 'x' ", we easily say "see, that supports my idea or proposal". But when an attendee says "I don't like "x' ", we just as easily brush it off as "that's just one data point, what does it really prove?" Either way, we get to the conclusion we want.
Back in the day when I was studying basic logic, we learned that the intersection of "A" and "not A" was the null set. But when it comes to spin, hype, and projection, such logic has left the room, and both "A" and "not A" lead to the same place. Somehow, that doesnít seem quite right. ?