Collective Analysis of Qualitative Data

What. Many students and practitioners do not know how to systematically process qualitative data once it is gathered—at least not as a collective effort. This chapter presents two workshop techniques, affinity diagramming and diagnostic mapping, that support collective analysis of large amounts of qualitative data. Affinity diagramming is used to make collective analysis and interpretations of qualitative data to identify core problems that need to be addressed in the design process. Diagnostic mapping supports collective interpretation and description of these problems and how to intervene in them. We explain the techniques through a case where they were used to analyze why a new elec- tronic medical record system introduced life-threatening situations for patients.

Why. Collective analyses offer all participants a voice, visualize their contributions, combine different actors’ perspectives, and anchor the result of the interpretation to the participating actors. Combining the techniques is a powerful way to analyze and intervene in situations before or after the introduction of new information technologies.

Where. The techniques are general tools that might be widely applied in different domains. In particular, collective analysis can be used to identify, understand, and act on complex design problems that emerge, for example, after the introduction of new tech- nologies. Such problems might be hard to clarify, and the basis for the analysis often involves large amounts of unstructured qualitative data, for example, from numerous interviews.

How. Affinity diagrams visualize “core categories” from the body of data. Diagnostic mapping visualizes problems, their causes, and their consequences, along with any ideas for solutions. Both techniques are used in workshop form where the participants jointly analyze, discuss, and interpret the empirical material visualized by pads of adhesive notes.