cross-posted from Laird's Commentary on Community and Consensus
Every now and then the right book comes along just as I'm ready to benefit from its message. That happened last month when I consumed Noise, by Daniel Kahneman (author of Thinking, Fast and Slow), Oliver Sibony, and Cass Sunstein.
This book came out last year and explores the concept of bad decisions and why people make them, distinguishing between bias and randomness. With bias, things are slanted in a particular direction (consciously or unconsciously). With noise, the range of responses is randomly diffused—the more noise, the wider the diffusion. Things you'd prefer be consistent, turn out not to be. Examples include the sentences judges give people convicted of the same offense, insurance rates that adjusters set for the same coverage, the wide range of agreement among evaluators in assessing personnel candidates.
It turns out that wherever judgment is involved, there is noise—and more of it than most realize. Worse, it's not just found in differences between people. It also occurs when the same person faces the same situation, but at a different time of day, or on a different day of the week, or after the local sports team won over the weekend.
The authors have a number of specific suggestions for how to approach decision-making to reduce noise.
• Delay discussing solutions (potential decisions) until you've first agreed on the criteria you'll use to assess the evaluate candidate proposals. Further, allow people an opportunity to think about what they believe the criteria should be by themselves before discussing it collectively, as groups tend to be strongly influenced by the first couple of people who speak, and ideas are less likely to be lost if they have been written down ahead of time.
• To the extent possible, consider focusing attention on how the candidates rate, one criteria at a time, delaying a discussion of the whole until the end.
• Evaluation will be less noisy if you ask different people or teams to assess candidates in different criteria (the idea being that the wisdom of the group is typically better than the wisdom of an individual).
• In expressing where a candidate proposal stands with respect to each criteria, it's generally better to rank them comparatively rather than on an absolute scale, as there tends to be much tighter agreement about comparative standing than what is meant by an arbitrary numerical scale.
Impact of Noise in Cooperative Groups
While this was not a lens through which the authors of Noise looked, it occurs to me that this book has some things to say about how cooperative groups might enhance their decision-making. To wit:
—Matching the process investment to the stakes. The above outline for how to reduce noise needs to be in some reasonable proportion to consequences. When the outcome matters a lot, you can justify being more careful. When the impact is low, it may not be worth it.
—In cooperative groups, how a decision is made typically matters as much as what decision gets made. With that in mind, there can be a large value placed on inclusivity (the lowest possible barrier for someone's relevant input to be expressed and considered), and it behooves groups to be especially mindful of how default open discussion and rounds tend to inadvertently favor the quick, and those who are comfortable speaking in front of the group. Or, in situations where the group is unskilled at working with disagreement or with the expression of strong feelings, how those with thick skin or a loud voice can have more sway—independent of whether they have better discernment.
—Delegating to a manager or team may be expedient and efficient, but it probably means more noise. It might be useful to reflect on that tradeoff before blithely embracing it.
Who knew that paying attention to noise could be so productive?
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