The output from qualitative research is often overwhelming. Unlike quant research, qual findings are often messy and hard to decipher. Here are some techniques to manage the voluminous data of qualitative studies.
- Start with clear research questions: in an earlier post I explained how to set up a design research project, step by step. One of the most important steps is to create a clear and answerable research question. This seems like an obvious point, but often it isn’t. Qualitative research often appears to be “just talking to people,” which gives us all the mistaken impression that it is entirely unstructured. It isn’t. Take the time to define research questions.
- Summarize frequently: Let’s say you’ve chosen to do in-depth interviews. After each interview, take 20 minutes to write out a brief summary of what you remember being the most important points of the interview (note that this is not a substitute to taking notes during the interview). These notes are the first step toward analysis. You are reducing “clutter” and irrelevant information. You are also exploring connections with previous interviews.
- Reduce, reduce, reduce: You will always have more data (e.g., videos, photos, transcriptions) than you can use. Be ruthless by reducing what’s important. Edit down your videos to only the clips that are most important (keep the raw data for another time). Reduce your transcriptions down to select quotes that speak to your research question (and again, save the entire transcription for another time). The goal is to have a workable set of artifacts.
- Visualize the results: Many qualitative researchers make use of summary tables and diagrams to further summarize results. My favourite visualization method is the mental model, which can convey a huge amount of information in a synthetic way, quickly. Other tools include mind maps and even the simple bulleted list.
- Hunt for connections: There is no science to this process. It is iterative and intuitive. But there are approaches you can use to find connections. I frequently use the “open sort” technique, with nothing more than a blank wall and post-it notes. Scribble themes onto post-it notes. Sort them into categories. Name the categories. Collapse as many categories as you can until you only have 4 or 5 “buckets” that explain your findings. If you’re researching children’s commutes to school, for example, you may have a category called “independence” which would talk about kids’ desires to be grown up, to have their own transportation method, and the knowledge to get to school. They are related only through the higher-order notion of “independence” and not the lower-order ideas of “transportation” or “age.”
- Ask “So what?” often: When I was in journalism school, I had a professor who tirelessly quizzed us with his version of so what: “What does it mean to metro?” he would demand, meaning, why should the people of this city care? Why should your design team care about these results? What does it mean for their process? Why should the users of this product care about your results? How might it make their lives easier or more pleasant? And of course, why should bean counters of all sorts care? How much money will it actually save?
These general guidelines will help you in your journey to deciphering meaning. But no qualitative project can be save from poor research design. Make sure you’re using the right approach.