Affinity Diagramming

“Affinity diagramming is a technique used to externalize, make sense of, and organize large amounts of unstructured, far-ranging, and seemingly dissimilar qualitative data.”

Lucero, Andrés. “Using Affinity Diagrams to Evaluate Interactive Prototypes.” Human-Computer Interaction – INTERACT 2015 Lecture Notes in Computer Science, 2015, pp. 231–248.

Definition

Affinity diagramming is a common method for organizing separate pieces of information into patterns, themes, and connections.

Context

Constructive design

Use Case and Procedure

I engaged with two other design students to create an affinity diagram. Our goal was to identify opportunities for e-waste collection.

1. For the first part of our affinity diagramming, our team compiled all of the data we had researched. We brought our what-if scenarios, maps, toolkits, secondary research, photos, and notes collected from our contextual inquiries and walking probe.

2. On yellow post-it notes, we wrote details such as the name, context, location, quotes, and descriptions as to what happened or was said. This gave a clear and specific point of data. As we did this, we sat together in case we needed to ask each other questions. All of us completed around 35 posts each.

3. After that, we laid out all of our post-it notes onto a table so everyone could see them. Silently, we began to place the notes on a white board together into groups that related to each other. Those groups were marked with an orange post-it note.

4. Our AI for the class noticed that our initial descriptions for these groups were very vague. She encouraged us to use the groups to uncover the meaning behind the pairings. For instance, the pairing below shows how I iterated on a grouping to make it more specific.

5. After creating numerous groups, we began to notice a split in the notes. Some of the groups dealt with the IU Surplus store, others dealt with students, and some fell in between. I decided to physically lay out this separation on the wall to make this gap more apparent. I even drew a visual “opportunity gap” to represent this separation. We also bucketed the groups into larger themes such as “IU priorities” and outlined them on the white board.

Data Analysis

The best way I was able to make sense of the data was to talk it over with my team. Together, we reflected on our organized collage and generated three main findings based on the three regions on the board: IU Surplus store, strategies, and students. Despite being a long and tedious process, affinity diagramming gave our team a clear direction to take our design.