Dialogos Blog

How to tackle perceptive distortions and unwanted divergence of judgements

Many people understand the way in which biases can creep into decision-making. Biases are errors in perceiving which lead to inapt choice making. Whereas noise refers to an unwanted variability in judgments. Here, unwanted is crucial. Take as an example a doctor’s diagnosis. If two doctors give two different diagnoses, then one of them is supposed to be wrong. In such a case, noise means the two different directions or unwanted variabilities. There can also be noise within an individual. For instance, when presented with the same problem twice, but giving two different answers.

People do underestimate noise levels. This is one of the research results described in Daniel Kahneman’s new book “Noise” (New York, 2021). “The research shows that when we evaluate someone’s performance, only about one-quarter of the rating is related to actual performance. The other three-quarters are related to noise” (Olivier Sibony, co-author of “Noise”, in McKinsey & Company, “Sounding the alarm on system noise”, May 2021). So, wherever there is judgement, there is noise, and often much more than expected.

If companies wish to know more about noise in within their inner and outer world of business, a noise audit is a helpful, systematic, and structured way to reduce noise. Kahneman points out that reducing noise also leads to reduction of bias. One of the origins of bias is that people tend to jump into conclusions early, based on very little information. They find information that confirms their existing opinions, and they look for information in a selective way. Noise audits break such patterns and prompt people in the organization to view a problem with a minimal of intuition.

Key words: bias, noise, noise-audit