Decision-Making Bias – What, Me Worry?
RFG POV: The results of decision-making bias can come back to bite you. Decision-making bias exists and is challenging to eliminate! In my last post, I discussed the thesis put forward by Nobel Laureate Daniel Kahneman and co-authors Dan Lovallo, and Olivier Sibony in their June 2011 Harvard Business Review (HBR) article entitled "Before You Make That Big Decision…". With the right HBR subscription you can read the original article here. Executives must find and neutralize decision-making bias.
The authors discuss the impossibility of identifying and eliminating decision-making bias in ourselves, but leave open the door to finding decision-making bias in our processes and in our organization. Even better, beyond detecting bias you may be able to compensate for it and make sounder decisions as a result. Kahneman and his McKinsey and Co. co-authors state:
We may not be able to control our own intuition, but we can apply rational thought to detect others' faulty intuition and improve their judgment.
Take a systematic approach to decision-making bias detection and correction
The authors suggest a systematic approach to detecting decision-making bias. They distill their thinking into a dozen rules to apply when taking important decisions based on recommendations of others. The authors are not alone in their thinking!
In an earlier post on critical thinking, I mentioned the Baloney Detection Kit. You can find the "Baloney Detection Kit" for grown-ups from the Richard Dawkins Foundation for Reason and Science and Skeptic Magazine editor Dr. Michael Shermer on the Brainpickings.org website, along with a great video on the subject.
Decision-making Bias Detection and Baloney Detection
How similar are Decision-bias Detection and Baloney Detection? You can judge for yourself by looking at the table following. I’ve put each list in the order that it was originally presented, and made no attempt to cross-reference the entries. Yet it is easy to see the common threads of skepticism and inquiry. It is all about asking good questions, and anticipating familiar patterns of biased thought. Of course, basing the analysis on good quality data is critical!
Decision-Bias Detection and Baloney Detection Side by Side
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Decision-Bias Detection
|
Baloney Detection
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|---|---|
| Is there any reason to suspect errors driven by your team's self-interest? | How reliable is the source of the claim |
| Have the people making the decision fallen in love with it? | Does the source of the claim make similar claims? |
| Were there any dissenting opinions on the team? | Have the claims been verified by someone else (other than the claimant?) |
| Could the diagnosis of the situation be overly influenced by salient analogies? | Does this claim fit with the way the world works? |
| Have credible alternatives been considered? | Has anyone tried to disprove the claim? |
| If you had to make this decision again in a year, what information would you want, and can you get more of it now? | Where does the preponderance of the evidence point? |
| Do you know where the numbers came from | Is the claimant playing by the rules of science? |
| Can you see the "Halo" effect? (the story seems simpler and more emotional than it really is." | Is the claimant providing positive evidence? |
| Are the people making the recommendation overly attached to past decisions? | Does the new theory account for as many phenomena as the old theory? |
| Is the base case overly optimistic? | Are personal beliefs driving the claim? |
| Is the worst case bad enough? | ---------------------------- |
| Is the recommending team overly cautious? | ---------------------------- |
Conclusion
While I have blogged about the negative business outcomes due to poor data quality, good quality data alone will not save you from the decision-making bias of your recommendations team. When good-quality data is miss-applied or miss-interpreted, absent from the decision-making process, or ignored due to personal "gut" feelings, decision-making bias is right there, ready to bite you Stay alert, and stay skeptical!
reprinted by permission of Stu Selip, Principal Consulting LLC