“Cold data” is data as we know it: quantitative metrics that capture a single variable at a time, at a single point in time.
Grades. Retention. Giving rate. Net Promoter Score. And so on.
We use metrics like these all the time to keep track of how we are doing, how our institutions are doing, and how our constituents are doing. These metrics can be powerful! There’s no denying that.
But metrics like these have their limitations, too. Two big ones come to mind for me. First, these data are narrow in scope—they tell us one thing and lack context. Second, these data don’t tell us why—why did a student fail that class, why did they drop out, why didn’t they make a gift? These limitations are what make these data “cold.”