The FinLab Toolkit

HUMAN CENTERED DESIGN | DEFINE

Affinity Mapping

60 Min

Affinity Mapping is a synthesis tool aimed at identifying insights from qualitative research, observations and findings. It involves organising key data points into clusters (called Affinities) that are logical, thematic, and consistent, and then discussing the clusters so that clear learnings and insights can emerge.

USE CASES

  • Organise research findings into buckets of information and themes that make sense.
  • Map emerging learnings and insights from patterns of information.

LIMITATIONS

While Affinity Mapping is a great way to look for patterns and insights, it can be an exhausting exercise - What observations and data points should you consider? Are the clusters distinct enough? How macro or micro should the clusters be? What is the relationship between clusters? etc. Not all questions can be answered, and some can lead to confusion and inconclusive debate. It is important for teams to look at the exercise as something that requires iteration.

Affinity Mapping | Playbook

UNDERSTANDING THE TOOL

  • Information for this exercise should be sourced from either secondary or primary research activities the team has conducted.
  • Observation, Quote, Data, Fact, these are the kinds of information that can be used by a team. Mentioning the source of the data (for example, the particular respondent, a blog, a particular expert, a particular train station, etc.) adds credibility to the notes shared.
  • Any information should be written down on a sticky note and mapped on a surface (like a wall). Each note should be complete, not too short or too wordy. One data point per sticky note.
  • ‘Themes’ start emerging as grouping of similar or complementary information starts taking place. There is no one set rule for identifying a theme; it is a matter of making sure each theme is complete in itself, and that it makes basic conceptual, logical, and emotional sense.
  • If there are close connections or interdependencies between themes, describing that relationship is important.
  • Learnings and insights are derived from the information collected under each theme. A team needs to discuss what the information collected means for them.

STEP BY STEP

  1. Review the research: Ask team members to review data collected during research. Use sticky notes to document critical observations, quotes from users, data and facts, etc. Use one sticky note per data point.
  2. Organise the findings: Each person should describe their individual notes, and start mapping them on a surface. As related points come up, the team should start forming clusters, group similar points and findings together.
  3. Break clusters down: If at any point there seem to be multiple number of themes emerging under one cluster, this meta cluster should be broken down further into smaller clusters.
  4. Define clusters: After all the information has been mapped, and clusters recognised, the team should discuss what each cluster means as a theme.
  5. Discuss learnings: Finally, the team should review the clusters and discuss what they mean in terms of learnings and insights.

HOW TO FOR FACILITATORS

  1. At the start: Have everyone spend time reviewing their research notes, and ask them to make a note of valuable information on sticky notes. One piece of information per sticky note.
  2. During the exercise: Help teams form clusters, feel free to make suggestions regarding the creation of sub clusters. Help them define the emerging themes.
  3. At the close: Have participants present and discuss their mapping and learning.

FACILITATORS QUESTION BANK

  • Have the teams made a note of their key data points on sticky notes? Have you provided sources for at least the key ones?
  • Who will start in each team? How will you keep a check on what themes are emerging?
  • What clusters are starting to emerge? Can the team walk me through them?
  • Should any cluster be broken down further?
  • Has anything come up that felt new, surprising, refreshing? Consider using different coloured sticky notes to make a note of it.
  • Are there things that can sit under two or more themes? Are they represented in both clusters?
  • What are the most important themes that have emerged?
  • What do your themes mean for you? What are some of your key learnings and insights?

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