Non-participant observation is a tool where designers take a ‘fly on the wall approach’ and observe individuals and groups without getting involved in the life of the persons. That is, the role of the designer is of an outsider.
PREPARATION: 1-3 hours
DESIGN PHASE: Insights
DURATION: 1-4 hours per round
TEMPLATE OR GUIDELINES: Create own observation guidelines see the 3 sample templates attached
FACILITATORS: 1-5 , design team members
RESOURCES: Notebook, photo camera, video camera, voice recorder
PARTICIPANTS: 5–20, users, employees, or other stakeholders
EXPECTED OUTCOME: Field data such as notes, photos, videos, audio recordings, sketches
By using the non-participant observation tool, designers collect data by observing behaviour without actively interacting with the subjects. The subjects are often users, employees, or other stakeholders, who are observed in situations that are relevant to the design challenge.
Define the focus of what you are interested in and consider what you want to do with the findings (build personas, journey maps, system maps, etc.).
Based on the selected focus area, define criteria for selecting suitable locations and situations for the non-participant observations. Think about whom to observe and in what situation, or if it might be more important to focus on the situational context: the when and where. Think about what types of data are allowed to be collected, and think of ways to blend in so that you do not affect the circumstances. Write up the observation guidelines based on what you want to find out. Decide on how the observations will be documented, e.g. videos, voice recordings, photos, and field notes.
During the non-participant observation, try to interfere as little as possible with the subjects. For example, you can use a video camera, smartphone or any other unobtrusive device to collect the primary data.
Write up key learnings right afterwards. You might use Affinity Diagram tool to organize the collected data. Review all the input data and highlight important issues whilst trying to recognize categories – patterns within the data. Make a short presentation that includes the key findings and examples from the data that exemplify these, such as quotes, photos, or videos.