Why are you always in the longest line at the grocery store, post office, or in the slow lane of traffic?

You might think you suffer from Murphy’s Law. You sigh and think that everything that could go wrong does go wrong with sinister ruthlessness. These poor souls even have a Facebook group.

Or, you might think that it’s a trick of the brain. You reason that you only notice long lines simply because they are the ones that are memorably infuriating. The short, can-I-help-you?, lines never exactly bought real estate in your memory because they were so quick and effortless. You conclude that long lines are a symptom of your faulty memory.

In any case you’re wrong.

The truth of the matter is–you generally are in the longest line and in the slowest lane of traffic. This happens because, on average, big lines have more people in them. You are more likely, on average, to be in a longer line. This happens because long lines, by their evil nature, require more people. More often than not you help make long lines the way they are. After all, someone has to. This doesn’t mean you always get stuck in long lines. It just means, on average, you do.

Our thinking about lines is a type of bias in thinking. We don’t always look at the right facts in the right ways. In the case of long lines we selected specific events to study and incorrectly deduced we were either prone to bad luck or victims of observational hiccups. We rarely pause to think that maybe, just maybe, we are, on average, going to be stuck in the longer queue.

This bias, this mental stumble, can have serious implications for how we look at numbers and data. Suppose, in a simple exercise, you wanted to rate the best sales people in your company. You look at how long everyone worked and how much they have sold, draw up averages, and start to compare the numbers. Should the results be taken seriously? Not really. They don’t factor in where exactly the sales people are working for one. Neighborhoods, population, and local income, big factors in sales, are absent from the results.

The point is simple. When you have to make a big decision based on numbers and data make sure they aren’t pushing you to towards a particular conclusion. Data, along with your perceptions, can be biased. Be wary of selection biases creeping up on your choices.  The crucial thing to ask before making a decision is whether or not some bias if forcing your hand. Like Einstein said, “We can’t solve problems by using the same kind of thinking we used when we created them.”