My two most recent columns shared some background about a librarywide UX improvement project at North Carolina’s Chapel Hill Public Library (CHPL), as well as some actual projects on which we’re working. Now I want to spend some time on the role of data.

Gathering the right data

A good deal of user experience (UX) work involves gathering data, and projects at CHPL have been no exception. We’ve amassed all sorts of quantitative data: gate count, number of telephone calls received in a day, how often the different self-check machines are used, how often furniture is used, the cost of staff time compared to the cost of software, which pages on the website are actually accessed, and more.

We’ve also harvested qualitative data, answering questions like: How do people behave in the outer lobby, and why do some people choose to work there? Do people look at or use the many promotional flyers in the cubbies in the inner lobby? What is it like to use the restrooms and are they generally clean?

CHPL staff have invested a lot of time in gathering, sorting, and analyzing data, and the investment has paid off in more than one way. Working with facts about the library and the behavior of users elevates the discussion from being a collection of people’s opinions to one that’s grounded in reality. Oftentimes people’s opinions and reality are perfectly aligned, and that’s always a good thing. Even so, having a bit of data to confirm hunches is a really good thing.

Another way data gathering has been time well spent is that it is an inclusive process. Everyone in the library has been invited to join a project team to participate, do some research, and influence changes. Involving as many people as possible not only has the potential to increase buy-in, it can imbue projects with diverse perspectives.

Experimental outcomes

Evaluating experiments—integral to the concept of prototyping—is a form of data collection, and this process has been valuable in determining outcomes. For instance, CHPL staff identified a new conceivable location for the periodicals collection. Moving the magazines upstairs to a more prominent and comfortable spot seemed like a good idea, and the change was made but with an experimental mind-set.

What if the new space turned out to be a dud? No big deal, because nothing was carved in stone and we could try another area. In the end, our initial hunch was a good one: more people are using the periodicals in their new location. An unexpected benefit of this change is that it has transformed an otherwise empty-feeling space to one that is often filled with the quiet energy of people sitting and reading.

Mapping the process

Service blueprinting has been a very useful data-related tool. For a few library services we’ve defined, step-by-step, the process for delivering a service. This includes what’s required of both the library user and the staff member. Seeing all of the steps of, say, registering for a library card has helped us identify what’s working well and how it might be improved. After examining an actual process, service blueprinting provides a great way to do some quick and easy prototyping on the fly.

Defining the steps of different service flows on note cards or a spreadsheet enables you to experiment without actual implementation. Working through the details on paper and iterating based on multiple ideas is a way to ensure a quality outcome. In the case of CHPL patron registration, this evaluative process helped folks determine that paper forms are no longer needed.

Acting on inspiration

As useful as spreadsheet upon spreadsheet of data can be, not everything needs to be studied to death. In some cases it is all right to act on just plain good ideas and see what happens.

A recent string of fruitful meetings led to a number of such decisions. From removing the collection of ancient and beat-up Kindles to normalizing how some special item types are circulated to eliminating the library’s PC reservation system, the only data needed was the general agreement that these things should be done.

As with moving the magazines, nothing is final. Should there be an outcry about the devices no longer being available (doubtful), or if a lot of people start cuing up for computers (hasn’t happened in a while), the library can change course again.

Data can help a library make solid decisions, but it shouldn’t be the only thing driving those judgments. Data won’t materialize out of thin air, hitting you over the head with inspiration. Instead, look at your library with fresh eyes, and imagine the type of library you want to create. Then you can dig in to make it happen.