I feel very fortunate that I grew up in a time when broken household items were more likely to be repaired than discarded.
My parents were just married when the Great Depression occurred; they rarely discarded something that could be repaired. Consequently, I grew up watching my father repair countless small and large appliances and watching my mother mend various material items such as clothes or furniture slipcovers.
My parents were just married when the Great Depression occurred; they rarely discarded something that could be repaired. Consequently, I grew up watching my father repair countless small and large appliances and watching my mother mend various material items such as clothes or furniture slipcovers.
I was drawn more to appliance repair than to sewing, I think because I have a natural curiosity about how things work. Appliance repair involved taking something apart, determining how it worked, identifying what needed to be repaired, and putting it all back together so that it worked properly. To this day, I try to repair what I can and I am thrilled when I put something back together and it works.
In a way, we want to instill in our analytics majors an intellectual curiosity about looking at a problem (or opportunity), taking the situation apart, understanding how it “works,” and putting things back together in some improved condition so that the situation works better.
A few years ago, I “graduated” from small appliances to building a car. My wife and I tackled the restoration of a 1971 MGB roadster. It turned out to be a four-year project. We dismantled everything. We rebuilt, restored, refurbished, and replaced nearly every part—onto a new body. Along the way, I used old workshop manuals, wiring diagrams, and a lot of extrapolation of experience from years of small appliance repair.
I hope our analytics students have the same attitude about solving problems that I had about building a car. Each task is a new problem. We want them to use a process of analysis and problem solving.
What, exactly, is the problem (why don’t the wipers work)? What data (parts) do I have? How should they fit together (manual, wiring diagram)? How will I know the situation has improved (what do good wipers do)?
The specific techniques we teach, such as regression or time series analysis, are important, but I believe true analysis is grounded in wanting to understand. I suspect our best students have a curiosity to understand what they are analyzing.
Maybe someday one of them will take me for a ride in a car she restored.
David Paradice
Raymond J. Harbert Eminent Scholar & Professor in Business Analytics
Chair, Department of Systems & Technology
