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Sounding the alarm on system noise

Source | | McKinsey Quarterly

Daniel Kahneman and Olivier Sibony, renowned experts in cognitive biases and decision making, explain how noise—or unwanted variability—clouds organizations’ judgments, and what to do about it

By now, most people understand the ways in which biases can creep into important decisions. Most are much less aware, however, of how much noise can affect their choice making, according to psychology and strategy experts Daniel Kahneman and Olivier Sibony. In this case, noise refers not to the clatter in the room but to the high variability in inputs and cognitive processing that people must contend with when making singular and collective judgments.

The concept is less well-known, in part because there has been much more research on bias than on noise—something Kahneman and Sibony are seeking to change with their recent book, Noise: A Flaw in Human Judgment (Hachette Book Group, May 2021), coauthored with Harvard professor Cass R. Sunstein. In this edited conversation with McKinsey’s Julia Sperling-Magro and Roberta Fusaro, Kahneman and Sibony explain what noise is, how it relates to bias, and what people can do about it.

McKinsey: You both have researched and written so much about decision making and cognitive biases. What brought you to the topic of noise? And why now?

Daniel Kahneman: I’ve been working on errors of judgment for most of my career, more than 50 years, and most of that time, I’ve been studying biases and how they lead to errors in judgment. But about seven years ago, I encountered another type of error, which is noise. It’s something I hadn’t thought about earlier—neither had a lot of other people. So that became a topic of thinking and, ultimately, of the book. As to the question, “Why now?” I would say the book is, in a way, premature. The normal sequence would be, you have an idea, you spend 15 years researching, teaching, and living the topic. Given my age [87], we didn’t have 15 years to wait [laughs], so the book came out a bit early—it’s still green, not ripe, but that’s the best that we could do [see sidebar, “Making Noise: A closer look at the creative process”].

Olivier Sibony: In some of the work I was doing with companies to address the problem of bias, it struck me quite often that the effect of bias is not actually predictable, as we would normally assume. It is often something much more random, and when Danny started talking about noise, I realized that we were talking about the same thing.

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