Christopher Madan has a nice article on the usefulness of open data (i.e. making public the underlying data for a research article) for developing teaching materials. In business schools, MBA teaching relies heavily on cases, particularly Harvard Business Review cases. Since I started teaching, I’ve been puzzled that almost none of the cases provide data that can be statistically analyzed.  Of the few that do, as far as I know, the data is simulated or at least doesn’t claim to be the actual data. This seems like an odd way to teach students about the increasingly analytics-based practice of making business decisions.

For the past few months, I’ve been developing an MBA course on experimental methods (think online A/B testing, test-markets, in-store stocking experiments, direct-mail tests, advertising and communications experiments, etc..). After not finding suitable cases, we started writing cases based on published field (not lab) experiments.  The catch was that I wanted field experiments with publicly available data, so that the students could go through the data analysis process themselves, using real data.

I’ve found some very nice examples to develop into cases, but I was surprised at how difficult it was.  Even in those research journals which require (or at least strongly encourage) making data public, the data for many papers had restrictions or were completely unavailable due to the data being proprietary. Often this is because of requirements that companies have before they will share data with researchers. I’m sensitive to companies’ concerns about how their data might be used if made public, of course. But the benefits of open data (and the value of papers that make their data public) go far beyond just checking up on the authors’ analyses.