Unpopular ideas are just that . . . unpopular. So, when you have a new idea or way of looking at the data, you often wonder if you should go out on a limb to share it. Wouldn’t it be great if there were others who think like...
Sometimes it feels like reports detailing college and university data might as well be written in a foreign language. Lots of numbers, tons of bar graphs, size 5 font. Footnotes aplenty. And data questions galore. Reports are jam-packed with so much information that it's hard to identify key takeaways. And it’s often a challenge to even...
“What gets measured, gets managed.” We’ve all heard this phrase (written by Peter Drucker in 1954). Some 65+ years later it has been used a TON—and misused almost as often. Some folks have taken it as a license to ‘add one more metric’ that should...
Completion Rate. The beacon of institutional success. The metric that everyone points to to say whether or not an institution is successful. The metric used to justify funding and support. The metric used to decide which institutions are better than others. Graduation Rate. The metric that...
Throughout the years, we’ve seen a variety of different measures of what makes a college or university successful. Does the institution prepare students for future careers? Is the institution contributing to the well-being of its local community? Are the students satisfied with their experience? What...
Benchmarking, both formal and informal, is pretty common in higher education. We take a look at what other colleges and universities are doing and compare our efforts and outcomes. Analyze whether or not our performance is on par. Look for opportunities for improvement. Dig deep...
At the start of the new year, many of us take a good long look at ourselves and identify somethings we'd like to do better or differently in the new year. Have you thought about doing the same with your data, though? To get started,...
So often, one of the biggest hurdles to using data effectively lies in the conversations we have about the data. What are we trying to study? What data do we need? How should we collect it? What type of analyses will we do? With so...
