I saw this Ted Talk, Sebastian Wernicke’s How to use data to make a hit TV show.
The intro is funny when he discusses data analysis to make decisions. At about 8:57 into the talk, he starts talking about problem-solving. He says problem-solving with data has two parts. The first part is the take-apart phase, where you analyze the problem. In the second part, you put the pieces back together again to come to your conclusion.
He does say you might need to do this several times, the taking apart and the putting back together. Then he says something I found resonated with me:
“Data and data analysis is only good for the first part. … It’s not suited to put those pieces back together again and come to a conclusion.”
He goes on to say we need to use our brains for the conclusion part. Our expertise allows us to come to conclusions, even better than data by itself does.
Here’s why. With our brains, we can use serendipity. We take unrelated information, and can see new possibilities. With our brains, we can use the Rule of Three. (We need data to see our reality. Data might lead us to consider only one conclusion.)
Sometimes, our expertise works in our favor. Sometimes, not. It depends on our expertise. The more narrow our expertise, the more we try to fit the data to what we know is possible and correct. The wide our expertise, the more open we might be to discovering other alternatives.
Many years ago, I was a software developer on a machine vision project to inspect printed circuit boards. The “experts,” the people who had deep domain expertise in optics were stumped. We could not obtain images with sufficient resolution to test our algorithms.
I asked, “Can we try different color lights to light the board?” They scoffed at my idea. The next day on my way to work, I bought red, yellow, blue, and green fluorescent lights. I tried them in that order. Sure enough, the green lights provided enough contrast to see the pads on the boards. We shipped machines with green lights.
I was an expert in problem-solving, not optics. My expertise did not impede me from considering options. Sometimes, expertise prevents us from seeing alternatives because “it’s not possible.” If we don’t know we can’t do something, we might find a way to do it. In the same vein, data might lead us to believe “it can’t be possible.” With multiple alternatives, we might see other possibilities.
As a Medical Mystery, I can attest that data is useful, but not sufficient for making decisions about our health and bodies. Yes, we need data—it’s essential for our ability to understand where the problems might be. Once we have data, we might need to consider alternatives that—up until now—we had not considered.
Data is one reason I recommend we not use cost in evaluating the project portfolio. We tend to towards insular spiraling-in decisions when we do.
Dear readers, that is the question of the week: How do you use data?