What’s the State of Your Stats: Ugly or Lovely Origami?
Several CS-SIS members (myself included!) took part in the TS-SIS sponsored session “Data, Stats, Go: Navigating the Intersections of Cataloging, E-Resource, and Web Analytics Reporting” for AALL’s 2020 annual conference live stream programming last week. In case you missed it, or had issues with the live stream, attendees can now watch the recording on-demand by visiting: https://cdmcd.co/Wv977d
Select “handouts” to access the slides PDF as well as a 2-page handout at the end of the file, and choose “on-demand recording” to watch the video. The content of this session included a wide range of examples showing the types of data we are all collecting for our institutions, and organization represented included both law firm and academic libraries. Several platforms were shared about, and their data types compared including repositories, integrated library systems, websites, ticketing, and more.
We broke down our data-driven discussion into three major parts:
- The Landscape (WHERE you pull your data from, and analytics versus statistic)
- The [Pain] Points (WHAT you are gathering, with an emphasis on process vs. technology pain points)
- The Life of the Story (WHY you are reporting, WHO you share it with, and HOW you visualize it)
The live session featured interactive polling for each section of the presentation, and an “ugly origami” exercise where participants were asked to write on and fold a single sheet of paper to create a symbol of their statistics (…the catch was not knowing exactly what you were doing in advance)! We had fun literally visualizing how ugly our stats truly are when we don’t think about what, why, and how we collect our data in advance. We shared our favorite tools for leveling up stats visualization, and encouraged attendees to think more critically and creatively about their library’s data.
Whether you watched the session live, plan to re-watch it later, or only have time to read this blog post, we encourage you to use this set of questions as a guide for using your data to tell more meaningful and powerful stories about your users, services, and resources:
- What stories to you need to tell using data?
- What systems can you get that data from?
- Does the data actually represent what you think it does?
- What tools could you use, if any, to visualize or report it?
- What impact or result do you want your data to have?
- How could you improve the usefulness of your data moving forward?
- What data do you wish you had tracked?
- What data do you track that you no longer need?
- Do you need changes to your procedures?
- What unintended issues could your changes introduce to other data tracked?
Thank you to everyone who attended. Now, data, stats, go…!
