5 Questions to Ask Yourself When You Look at Your Data

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, try asking yourself these questions when you look at your data.

ASK Sign

Look at your data: What’s changed?

What has changed – good or bad – that helps provide context for the data? If data are presented as random numbers – 86, 75, 309– then sharing them just makes you sound like a Sunday quarterback. Make sure the information is heard and understood by making the numbers meaningful with the context and stories.

What does everyone else’s trend chart look like?

Sometimes things are not what they seem. For example, suppose your numbers went up a little. Great! Improvement! But what if everyone else’s went up a lot? Maybe not so much to brag about. It is important to have external context – which means networking and keeping up with your colleagues to know what is happening at other institutions.

What data would I like to have that would help tell a richer story?

Look to related data to help paint a more complete picture. Perhaps adding in finance data or student survey results will add more to the story. When you bring in additional elements, you set the stage for your colleagues to better connect with the data.

Does this really need to be done?

Sometimes we get in the habit of doing the same thing over and over again. All to come to find out…no one looks at that report anymore. Since our time would be better spent, developing a new report or enhancing an existing one, it’s important that every so often we assess whether or not what were doing is useful.

Man yelling important into megaphone

Is it important? Or just interesting?

Research for the sake of research is great…when you have all the time in the world. But collecting interesting data that isn’t also important can have more drawbacks than just wasting your time. It can lead to scope creep. It can make the data confusing. Certainly, no one completing a survey ever thought, “Gee, I wish they’d ask more seemingly irrelevant questions.”