Lies, D^%&*^ Lies and Statistics
Recently, I was in two separate meetings where the discussion was about the leadership of organizations receiving statistical, hard-data evidence of problems in leadership, or another path to take to get work done. One of the organizations had done multiple studies.
The leadership’s response was very interesting.
In one case, the leaders decided to get very scientific about the stats that represented major red flags about the organization’s leadership. They looked at the data from multiple angle, tried to correlate messages across the multiple studies, parsed language (“too negative” was one phrase). They inspected the data, a lot.
The inspector mode is an often unconscious reaction to uncomfortable information. You study it further, and then further, and then some more. You may have heard the term “paralysis by analysis.” Sometimes in 360-assessment data that are heavily negative, individuals want to question validity, reliability, statistical significance and just about anything else they can find to throw sand in the bull’s eye.
The other thing that gets paralyzed in these cases is employees. Having contributed their perspectives multiple times and hearing or seeing nothing constructive back, they often throw their hands up.
It culminated in a comment from one leader, who reportedly (full disclosure — this is second-hand) said, “I’m tired of hearing about it. I just want people to get the job done.” In this case, the inspection created fatigue that eclipsed the messages in the data. There is something very self-fulfilling about such an approach.
Second story: The other organization had studied how a group of employees perform when given the option to telecommute. Productivity, responsiveness and quality all went up by significant amounts. When a recommendation was made to expand telecommuting based on the results, the response of the leadership (which I was told doesn’t trust the employees) was “There are lies, d#$%^%$& lies and statistics.”
In other words, you can prove the case all day long, but if it collides with a view, mental model, belief or perception, then the facts don’t really matter. There is all kinds of work that has been done in the areas of cognition and emotion that explains this phenomenon. Filtering, bias and perceptual errors abound.
How do you react to information that may rock your boat? What is your response to feedback? How do you treat the messenger? Do you go to Inspector mode, say the information doesn’t support your pre-conceived notions, or do you stop to ask yourself one vital question of leadership: “Is this true?”
