It’s clear from the number of daily page views this blog gets, and the amount of feedback I receive personally, that there is a strong interest in data mining and predictive modeling for fundraising. I can only surmise that demand for expert opinion on the subject is outstripping the supply, because let me be clear: I’m no expert.
That is, I’m not an expert in the sense that I’ve figured it all out, that my models all do what they’re supposed to do, that I understand what “degrees of freedom” means. (I’m beginning to suspect that no one can explain what degrees of freedom means. One statistician I read will say only that it’s an “elusive concept”. I get that much.)
I’m not an expert – I’m an explorer. I recognize that this predictive modeling stuff can be a powerful tool. Others have shown that certain simple techniques can be learned by anyone looking to harness some of that power for the benefit of their institution, and I’ve tried to learn those as best I can.
I also recognize that there is no end of learning. Where’s the summit of this mountain? I’ve no idea, but I sometimes catch a glimpse when I post a question to this data mining listserv. As the responses roll in from people who have been doing this a long time, I realize I’m at Base Camp 1 without enough oxygen.
Now, there’s nothing wrong with Base Camp 1. The view is nice. A person can do quite a lot of good from here, including trying to help others reach that level.
Allow me a metaphor shift …
I drive a car. It gets me places, allows me to do things I otherwise could not do. I understand the vague outlines of the workings of the machinery inside. I know the general idea of how the propulsive thrust is generated and transmitted to the wheels. Keeping an eye on the gas gauge and speedometer, I know enough to drive safely, and to recognize trouble.
But I am not a mechanic!
It’s the same with regression analysis. I know the interior workings only in outline. For the rest, I simply try to define my destination as accurately as I can, and then keep my eye on the indicators I see on the dashboard: the p-values, R-squared and so on. They keep my on the road, and tell me if I’m getting into trouble. (When I do get into trouble, I consult a mechanic. They’re out there, and they are helpful.)
I don’t choose to be ignorant about my car. Learning more about how it works will never be a waste of time, and it might save me someday. But being a non-expert is no reason to avoid getting behind the wheel. The number of us who are coming to appreciate data and analytics via our careers in fundraising is growing every year: Wherever you find yourself stranded on this road, someone will be by to help!
P.S. — Startled to discover this evening (28 June 2010) that Jacob Cohen et al. used exactly this automotive metaphor in the opening pages of the landmark book, “Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences.” They write: “We note that to drive a car, one does not need to be a physicist, nor an automotive engineer, nor even a highly skilled auto mechanic, although some of the latter’s skills are useful when one is stuck on the highway.” I didn’t (knowingly) lift this idea!