Have you ever found a surprising insight through analysis about your business, prepared a set of slides with a solid argument, presented to the senior leadership, which dismissed it immediately? I heard some head nods out there. You’re not alone… Sometimes that scenario is legitimate (“The leader knows that while your insight is likely true, they are about to change their business model and exit the business you’ve analyzed.”) But more often than not – especially regarding insights about people, they are following this golden rule:
“If your data matches my gut, then I am brilliant. Thank you for validating me. But if your data does not match my gut, your data is wrong, I’m right, and go away.”
I’ve been struggling with ways to overcome that golden rule for a while – it’s an intractable, very human, and understandable reaction to things we can’t accept yet. (There is a clinical name for this btw – it’s called Confirmation Bias.) I’m a big fan of Jonah Lehrer’s work on decision making. and Dan Ariely (Predictably Irrational and the Upside of Irrationality.) This weekend, Jonah wrote a piece for the Wall Street Journal that strikes at the heart of the golden rule problem, particularly within power. He writes about a set of experiments where one person is granted unthrottled power:
“This [study] suggests that even fleeting feelings of power can dramatically change the way people respond to information. Instead of analyzing the strength of the argument, those with authority focus on whether or not the argument confirms what they already believe. If it doesn’t, then the facts are conveniently ignored.”
Interestingly, those without unthrottled power can accept the rational argument – power can accept it less. For those of us who analyze human capital data, I think this problem is harder – it’s about people- a topic that most in power have a strong opinion about. I know I’m not ready to share a short, neat list of how to overcome this type of thorny problem (and open to your comments on how you’ve overcome it), but I know that good practices exist – we just need to come up with the list of “to dos” to help us all make our data more palatable to the people that need to act on it!