Most people who work in administration these days are being encouraged to rely more and more heavily on data. This encouragement even has a name: DDDM (Data-Driven Decision Management) or DIDM (Data Informed Decision Making). In some ways, we are looking at the automation and digitalization of another sector of the economy. With more data, the argument goes, we can make smarter decisions with fewer people. Supervisors do not need to have first-hand experience if they have graphs and charts.
I have a memory of a discussion between teachers and administrators at a school I taught at and I think it relates here. A policy had been implemented that allowed students to have cell phones in school. I would argue that about a third of the teenagers in the school had perfect control over their cell phone use and could leave the things alone in class. About a third were Facebook message addicts and could not stand to have them and not look at them. About a third were in between. I am sure that I generalize. Ultimately, the policy that allowed cell phones was detrimental to the very students who were already in trouble because of their poor executive function. And the enforcement of the cell phone policy became a distraction to people like me who just wanted to teach and preferred to have as few “policing duties” as possible in the classroom.
At the end of the year, an assembly of the teachers was called to discuss the policy and it became clear that what was important to the administration in making the decision was the “data” - the numbers of complaints and disciplinary actions that had been formally submitted. The fact that a room full of teachers who rarely had the time or energy to file a disciplinary action every time one might have been justified was making one argument and the “data” that had been compiled from their experiences was making the opposing argument was almost comical. The teachers were saying “It’s a problem” The data that the teachers had submitted over the year was saying that it was not. I certainly knew that I had not submitted a paper form every time I had taken someone’s cell phone in class and understood the limitations of the data collected because I knew how it was collected.
What does this have to do with a movie about a pilot force landing a plane full of people into the Hudson River?
I suppose it has to do with the way that the Aviation officials in the film attempt to determine if the pilot was to blame for taking the risk he did when two airport runways were only miles away. They run computer simulations and human flight simulations to determine if the return to the airports could have been successfully completed. What these data sources say is that a computer or a prepared pilot could have successfully taken the planes to land safely at nearby airports if they had known everything that was known immediately after birds took out the engines. In a perfect world of information where everything that needed to be known was known at the moment one would need to know it, a “Data-Informed” computer would have done a better job flying the plane than the human pilot.
What we see in this movie is Captain Chesley “Sully” Sullenberger making as good a decision as a human can make in the time that it would take a human to sift through all the possible pieces of data that should matter. We suspect that if given only the data that mattered and nothing else, he might have made the decision more quickly and perhaps more “correctly” as defined by a computer. The film reminds us that decisions are always easier in hindsight than in real time and that it would be wise to remember that when other people make poor decisions that affect us.
Question for Comment: When you think about the best and worst decisions you have made in life, what causes you the most regret? Not having had the information you needed? Not seeing which pieces of information were more or less important? Not looking for more information when you should have? Permitting yourself to go into denial about some of the information? Not making the decision more collaboratively? Relying on flawed data? Or relying too much on data altogether?