Why Does Making a Rational Argument to Power, Fail?

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!

So that’s why recovery.org doesn’t suck….

I was listening to On the Media’s interview with Edward Tufte (the pre-eminent visual data designer) and was pleasantly surprised to heat that’ he’s been working on recovery.org’s web site.  I don’t know the onVia software, so let’s assume that Edward isn’t the only reason the visuals don’t suck, but that he’s working on it is very cool:

Found in a Box of Old Floppies

Sometimes I forget how long I’ve been working with reporting software… I unearthed a box of floppies in my basement (in addition to the Tandy MS-DOS/BASIC disk I’m staring at circa 1984) I found the first reporting SW package I used. I was too young to be running reports on a PC. My friends were playing Zork…

Quick Recap: SAS Premier Leadership Series Conference

I’m back from the SAS conference in Las Vegas and though I’d jot down some notes:

First, totally worth going to. I was initially skeptical, but meeting with fellow data wonks for 3 days turned out to be a good idea.  What was interesting to me is less that there was good analysis going in at the user level (and there is…), but that so many of the sessions were aspirational vs. a report of work completed. We are still in a steep upward slope in many of the aspects of leveraging data for competitive advantage.

The panel of Malcolm Gladwell, Thornton May, and Tom Davenport easily was the highlight of the conference. There was also a wickedly good session with the head of Disney’s formidable Insight team, Cameron Davies.   And, Yan Chow from Kaiser Permanente has a permanent place in my index of amazing people in BI. His team is doing things with health care analytics most won’t be able to do for years… I should move to a place where Kaiser has a hospital – I’ve live longer I suspect…

I drew during many of the sessions, including one with Malcolm Gladwell (author of Blink, and Outliers). Honestly, I hadn’t dug in too deep into his work until recently, but I get his appeal. I drew the sketch below , which probably won’t come out too clearly, but basically has this point in mind: Sometimes, condensing data into what “matters” will help people make better decisions in 2 ways: It gives you focus, and it helps to put your subconscious bias in a box…  Using the example of heart patients in an ER: until recently, doctors took any data from the patient and used that to diagnose a heart attack. Apparently, that doesn’t work too well. But taking 4 key indicators have a much higher likelihood of correctly diagnosing a heart attack, and saving someone’s life. I vote for the 4 fact version please…