Bias As Usual: Errors in Sample Size

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In the articles to follow, we’ll explore cognitive biases. These are the mental shortcuts we all occasionally use to make sense of the flood of information we face everyday. First up: Sample Size.

Imagine, for a moment, you are the lowest performer on a sales team. Complete fiction, I know. Now imagine that, for some reason, you enjoy wearing wearing khakis and polos to work while the rest of your team all wear suits. Is it fair to conclude that your lack of formality (and taste?) is the reason for your lower sales results?

Not so fast! Before we go explaining how formal clothing enhances credibility, there’s something more important to consider. Sample size. Exactly how many people are on your sales team?

According to Sociology expert, Daniel Kahneman, small sample sizes lend themselves to extreme results. In his book Thinking Fast and Slow, he and a group of experts questioned the belief that certain small towns have high disease rates due to toxic waste.

The result? The small sample size of residents in each town made extremely high or low disease prevalence more likely. This doesn’t, of course, prove industrial pollution to be harmless. It instead invalidates the data as proof that toxic waste was the cause of disease. Perhaps, if the towns studied were larger, the researchers’ conclusion may have been different.

Therefore, we in sales should be cautious about the quick interpretations we make of both success and failure. For example, it may neither be fair or helpful to compare the results of one sales rep with several medium-sized accounts to another who manages one or two large, make or break clients.

Ultimately, if we want to make better decisions, we must gather enough information and only then draw our conclusions.

Chris Pawar