Quote
"Data don't make decisions; people do."
Toto Wolff; Box to Box. (2024). Formula 1.
THE MEAT (The Main Idea)
Simply put, decisions shouldn't be solely dictated by data. Data should be shaped by human interpretation. Certain industries, like trading markets or weather forecasting heavily rely on data. In these situations, numbers are produced, and a one-to-one correlation, devoid of human emotion produces a verdict. However, it's crucial to recognize that even in these fields, the involvement of humans in refining algorithms, interpreting results, and addressing unforeseen situations remains critical.
Decisions made solely by data miss the intricacies of individual experiences, emotions, and the dynamic nature of human interactions. Leadership and education thrive on a delicate balance - a fusion of analytical aptitude of data and invaluable insights derived from human judgment, experience, and intuition. This balance serves as a reminder that decisions extend beyond statistical analysis and algorithmic predictions. This intersection where the precision of data intersects seamlessly with the depth of human understanding is the crux of the quote.
THE CHEESE (Added Depth)
In the world of education and leadership, the mere mention of data can give people big feelings. This brings to our attention the gap between the empirical and the intuitive and the need to bridge this gap.
Integrating data-driven approaches with the inherent wisdom of human judgment, experience, and intuition poses both challenges and opportunities. Take for example, the concept of "teacher gut," where educators rely on their intuition about student's potential or performance on things like standardized tests. While teacher gut is a real phenomenon, its reliability is not always guaranteed. The goal is not to replace valuable tools, such as teacher gut, but to harmonize them.
How then, do we strike a balance between teacher gut and data? One effective approach is the use of data protocols- a structured framework designed to bring clarity and efficiency to meetings. These human-developed protocols consider nuances in human behavior and desired outcomes. When facilitated by someone well-versed in protocols, meetings flow predictably, freeing participants' mental energy from the burden of "what's next."
Various data protocols exist, such as benchmark analysis, ATLAS, or the 5 Why's. My personal favorite, and one I use most often, the Five-Phase Protocol for school leaders, enhances the original 4-Phase version, guiding participants to set actionable steps.
The Five-Phase data protocol steps include predicting outcomes, visualizing data, observing trends, questioning findings, and developing next steps. It empowers educational leaders to leverage data effectively for informed decision-making. Suited for collaboration, this protocol fosters a team-oriented approach.
Another method for a harmonized approach between statistical analysis and human interpretation is the use of effective questioning techniques. Rather than just looking at the data, ask about the "why" behind the data. What is the data saying? What is the data not telling us? These types of questions ultimately lead to better decision-making.
THE OLIVES (A Surprising Element)
To truly appreciate the power of data and human intuition, let's take a pit stop in the world of Formula 1 - something I have Netflix to thank for my recent small obsession. Now, before you go imagining me zipping around any sort of racetrack like Lewis Hamilton, let me clarify- my only experience with Formula 1 racing involves navigating local rush-hour traffic. And to be even more clear, the only pole position I've achieved is right behind the guy who just cut me off.
If you are unfamiliar with the world of Formula 1- allow me to be your armchair "expert." Formula 1 is a sport where the stakes are as high as the speeds they achieve. These drivers, in their high-performance cars, reach speeds of 200-230 mph. The engines are loud and the pit stops are fast. Here, the cars are not just vehicles, they are state-of-the-art marvels that can easily surpass ten million dollars per car. The costs are so exorbitant because the slightest tweak to the car from week to week can cost anywhere between $3,000 to $100,000. Teams are willing to spend this money because these small tweaks may mean the difference between first place and "nice try, maybe next time."
As the tweaks and adjustments are made to the car, the driver tests it out and the car's computers send bucket-loads of data about the car's aerodynamics, turning capabilities, etc. You see, data is not just a tool- it's the lifeline of Formula 1. They are willing to spend the 15 million on a car because it's a 2.5 billion dollar industry.
Teachers might not have a pit crew-fine tuning their daily lesson plans (wouldn't that be nice), but much like Formula 1, schools navigate their own high-stakes tracks with teachers at the wheel and students as their prized vehicles. In education, the data collected becomes the compass navigating the course for daily decisions on instruction and interventions.
Just like the millions invested in tweaking a Formula 1 car for that extra edge, the value of educational data lies in the small nuanced interpretations and the decisions made. These small tweaks do indeed make big differences. Interpretation of the data can make the difference between a student reaching their academic podium and a "nice try, maybe next time." The parallel is not just striking, it's the defining factor in the pursuit of excellence.