Affinity Mapping
Affinity Mapping, also known as Affinity Diagramming, is a collaborative technique for organizing and categorizing large amounts of ideas, observations, or data into groups based on their similarities or natural connections. It's commonly used in agile project management, UX, and design thinking.
Origin
The technique was developed by the Japanese anthropologist Jiro Kawakita in the 1960s and is also known as the KJ method, after its creator. Kawakita designed it to organize qualitative field-research data in a meaningful way, as a way of dealing with complexity and ambiguity without imposing predefined categories. Since then it has been adapted to many contexts: project management, product design, user research, retrospectives, and innovation processes.
How to apply it
This is a visual, collaborative technique. The session shouldn't run longer than an hour and a half, regardless of the volume of ideas.
- Generate ideas: through brainstorming, interviews, surveys, or research data. Each idea is written on its own sticky note or card, one per card.
- Lay out the ideas: all the cards are placed on a wall or board visible to everyone, with no prior order.
- Group by instinct: participants move the cards in silence, grouping them by similarity. There's no discussion at this stage—you act on intuition. If someone moves a card another person has just placed, they simply move it again; the discussion comes later.
- Name the categories: the team works together to identify and name the groups that have emerged.
- Analysis and discussion: the team discusses what each group means and its implications for decision-making, planning, or design.
Practical considerations
- A skilled facilitator matters for keeping focus and pace, especially with large groups.
- Groups of more than eight people can get chaotic. With large teams, it's best to split into subgroups and consolidate afterward.
- Flexibility in the categories is essential: there are no right answers, and categories can be refined as the process goes on.
Affinity Mapping with AI
AI tools are starting to make their way into affinity mapping workflows, especially in remote sessions:
- Platforms like Miro and FigJam include AI features that can suggest automatic groupings of sticky notes, speeding up the initial phase.
- Language models can be used to analyze large volumes of user responses and propose thematic categories before the session.
The risk is that handing the grouping over to AI removes exactly what's most valuable about the technique: the process of the team forming its own mental connections. The categories that emerge from a human affinity mapping session aren't just a result; they're also a process of cognitive alignment for the team. Using AI as a starting point for discussion is useful; using it to replace the session is not.
Common mistake
Discussing during the grouping phase. When someone explains out loud why they're moving a card to a particular group, they impose their logic on everyone else before the others can form their own. Silence during grouping isn't a formality: it's the mechanism that ensures collective patterns emerge, rather than those of the team's most vocal member.
References
- Kawakita, Jiro. (1967). Hassō-hō [The abduction method, in Japanese]. Chūōkōron-sha.
See also
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