At Stanford Engineering, I like being close to the people asking the questions and understanding the context at a fundamental level. I can see the impact of solving their puzzles through data – and seeing their subsequent decisions is so rewarding.
As the Director of Analytics here, it’s my team’s job to tell stories through data. If you give us your question, we will figure out the best modality and data sources to answer it – whether the most useful information ends up coming from central university databases or is lurking in hand-typed, color-coded Excel spreadsheets.
All we do is in support of helping leadership make smarter decisions. That could be something as relatively straightforward as understanding our faculty’s advising load – if it’s shared relatively equally among our faculty, if we’re advising more students from other schools on campus than they are of ours, etc. We also investigate highly complex and meaningful questions associated with, for example, diversity, equity and inclusion efforts, like how we’re doing with gender parity or how accessible engineering majors are for students by using data to see what pre-reqs they’ll need and how quickly they should take them. Data also gives us some surprising lighter nuggets (fun fact: SoE undergrads are disproportionately likely to minor in German!).
Ultimately, however, we’re tracking data to make sure SoE initiatives are going in the directions we hope they are. One of our core data-driven stories centers on tracking the patterns of undergrads interested in engineering. We had an intense eight-year period of growth where student data really made the difference in determining how to resource and staff up. Now we’re seeing relative stability – about 40 percent of Stanford’s students major in engineering – and that’s holding strong, making it much easier to plan appropriately.