Making sense of field data

The previous two chapters examined various methods of gathering rich and diverse qualitative data. Now the focus is on making sense of that data.

Regardless of whether you gathered qualitative data to better understand people’s needs or to test a new design, making sense of field data involves many tasks, the following being the core ones: giving some sort of order to the data, distinguishing relevant from irrelevant data, identifying significant patterns, and finding a way to communicate what the data revealed and how that informs design decisions and actions. While there is no recipe or unique way of performing these tasks, an important consideration applies to all qualitative analysis: get familiar with data first; look for categories later; generate meaning last. Be rigorous and systematic; don’t skip steps, even if you think you know the story after reading half the data or you are running out of time. Initial thoughts and ideas are likely to be assumptions. And even if you are correct, you aren’t allowing the possibility of finding unexpected insights that could later distinguish your design solution from others.