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Welcome to the HBR idea cast from Harvard Business Review. I'm Allison Beard. We all want to make better

decisions, whether we're hiring a new employee, choosing a marketing campaign, or allocating funds

between different departments. Good Judgment is an essential part of any job, and it's ultimately

what makes individuals, teams, and organizations successful. But we know that as humans, we're

all flawed. We're pretty terrible at making predictions. We come with preconceived opinions. We make

tons of mistakes. Even the greatest leaders trip up from time to time. We talk a lot about how to

eliminate bias in decision making. That's the tendency to swing in one direction as a single person

or a group. Maybe it's always thinking a project will get done faster than it will, or consistently

underestimating costs, or hiring only people whose name sound familiar. Today's guests say that

we're overlooking another big problem, what they call noise, or random variability in the decisions

made by different people, doctors, judges, managers. It's pervasive, and it affects all industries.

But noise is also something that once we understand, we can come back. Daniel Coniman is a Nobel Prize

winner, an emeritus professor at Princeton University. Olivier Sivini is a professor of strategy at

HEC Paris, and they're the co-authors along with Cass Sunstein of a new book, Noise, a flaw in human

judgment. Danny Olivier, thanks so much for joining me. You're my pleasure. Thanks for having us.

So as I said, organizations around the world have become much more aware of bias in their decision

making, and a lot seem to be working to try to fix it. How is noise different, and why is it

also just as important? Well, biases become almost a synonym for error, that is when people make

or see errors of judgments, they attribute them to biases. But there is another form of error.

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