Science Says the Smarter You Are, the Extra Seemingly You may Make This Frequent (and Costly) Mistake

Imagine browsing through résumés and deciding who to interview. If you’ve put the last two candidates on the “yes” pile, then the more likely you will put the next resume on the “no” pile – regardless of that candidate’s qualifications.

Or that you have day-trade index funds and the Dow has risen in the past three days. Since you usually balance things out, you decide that the market is going to fall today – regardless of economic fundamentals.

Or, in simple terms, that you flipped a coin five times and each time it came up. Since this rarely happens, the next flip will certainly be the tail – even if the probability of a head or tail showing up is always 50/50 regardless of previous flips.

Sound familiar? If so, you (and by you I mean “we”) may be smarter than you think. A 2012 study found that decisions like this correlated positively with higher intelligence and better managerial functions like working memory and conflict resolution.

So yes: we are smart. We understand the law of large numbers. And we can definitely see patterns. But that doesn’t mean we’re right.

It is natural to assume that a certain random event is less likely to occur after a string of the same event. The longer the strip, the easier it is to assume that the strip will break off the next time.

Has your sales rep found the last five prospects? Chances are she won’t land sixth. Your favorite team has won the last eight games? Chances are they won’t win the ninth. Four employees from the same recruiter turned out to be superstars? Chances are his next candidate will be bust.

Research has shown that the smarter you are, the more likely you are to see patterns.

And then you think you can predict what will happen next.

Even if every situation is actually unique – and the result is independent of an actual pattern.

How To Avoid The Player’s Error (Despite The Fact That You Are Really Smart)

In social psychology, this cognitive bias is called the representativeness heuristic. The tendency to accept a short series of random results corresponds to a much longer series of results. In non-scientific terms it is called the gambler’s error.

In both cases, it is assumed that a small sample size is representative of a much larger sample size: since coin flips will eventually balance each other out in the long run, two heads in a row should mean that the next toss will be tails.

While “error” implies “less clever”, the researchers found “the higher the cognitive ability … the more likely (that people) will deal with the player’s error”.

First, consider whether certain events are related or independent. There is no pattern for a randomly stacked set of resumes. And a résumé does not “know” which résumé comes before or after – much less can influence the “quality” of previous or subsequent résumés.

So if two resumes in a row show obvious superstars, it shouldn’t affect how you rate the next resume you scan. If the market has been up in the past two days, you don’t automatically assume that it will go down today.

The key is to think big numbers instead of small numbers. When you’ve determined through actual data and analysis that patterns exist – for example, it takes 100 cold calls to attract 10 prospects – think of short-term results in that context. If two calls in a row are successful, the next call has the same probability of success as if the previous ten calls had failed. In the long run, the results will tend to even out each other.

But this evening is much less likely in the short term.

Give the next call your best shot. Do your best with every call.

Because while you might think that you are smart enough to know better, you might be too smart to know better.

The opinions expressed here by columnists are their own, not those of

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