Reflection is a Team Sport
Reflection can imply a quiet study, a dusty book, and silent soul-searching. In design, it is exactly the opposite. Often overlooked, it is an active, often messy process that welcomes and thrives on team participation.
IBM Design Thinking is characterized by the “loop.” The loop is a constant cycle through stages of observing, reflecting, and making. For design researchers, this process often manifests as observing and listening to users (or potential users) of a product or service, reflecting on that data, and making the actionable recommendations a design team needs to move forward. Repeat as needed.
While the value of observing and learning from users is widely understood, “reflecting” is more mysterious. This suspected veer toward quiet contemplation may be why design research pain points often surface here. “Reflecting” can feel overwhelming; there is a mountain of data to process. It can feel slow. It can feel lonely; often others on the design team are too busy to help. In a recent gathering, a group of IBM design researchers discussed how to foster an environment that encourages team reflection on the data gathered in research to come to actionable insights.
First, why is it important for a team to participate in reflection?
- Involving several members of the team who can bring different perspectives to the observations helps to ensure that interpretation of the qualitative data is rich and well-informed.
- When the team reflects together, there’s a better chance everyone feels ownership of the findings and feels good about taking the time to make sense of the observations.
- Greater ownership of insights, as well as greater alignment, helps ensure the findings make their way into product designs and decisions.
So what should design teams do?
1) Debrief as a team
Some design researchers we spoke with mentioned inviting team members to listen in to remote sessions with users. In these cases, reflection often takes the form of a 15-minute team debrief at the end of a user inquiry, once the participant has left. This is an excellent practice. The benefits include immediate, team-wide understanding of what a user said or did.
However, when the whole team can’t attend every session, deep connections between different users are not necessarily made. Some design researchers feel that they conduct this additional, necessary reflection alone, often in a rush, to get the findings back to the team. The solo process can surface deep connections and insights, but not necessarily rich ones informed by multiple perspectives. Additionally, teams may not feel they share equal “ownership” of the findings with researchers, making it more difficult to translate insights into product design.
2) Interpret as a team
Listening to and observing users can be inspiring. But it is not enough. The hard work of generating insights has not yet been done. With data alone, one may be able to address the glaring problems, but non-obvious insights are what drive innovative “to-be” scenarios and products. These insights come from interpreting the data, and asking “why” the observed patterns and themes have arisen.
A great example of interpreting data comes from “Know Your Customers’ Job to Be Done” by Clayton M. Christensen, Taddy Hall, Karen Dillon and David S. Duncan. The authors tell a story about Bob Moesta, an innovation consultant tasked with increasing condominium sales for a company in Detroit. Moesta talked with people who had bought condos, and noted that they frequently spoke of wanting to get rid of their dining room tables before they moved. If Moesta had stopped there to conduct a shallow reflection, his conclusions might have been, “People want to get rid of dining room tables, and they don’t want a formal dining room.” Instead, Moesta took a moment to go deeper in interpretation. He asked himself, “why?”
“[…] as Moesta sat at his own dining room table with his family over Christmas, he suddenly understood. Every birthday was spent around that table. Every holiday. Homework was spread out on it. The table represented family.”
Moesta’s interpretation relied on his worldview, his previous experiences with family holidays and daily tasks in his culture — what he ‘brought to the table,’ so to speak, and he was able to bring this interpretation back to his team. But Moesta is just one person. How much richer (and potentially faster) could interpretations like these be if there is even greater representation of different perspectives all engaged equally in this kind of reflection?
In short, the company focused on alleviating this anxiety by providing, among other things, a storage space so buyers would have time to sort out their furniture (and feelings) gradually, rather than before a move. This is a non-intuitive solution that the competitors wouldn’t have come to without doing similar research and interpretive reflection. The impact of the interpretation is clear:
“By 2007, when industry sales were off by 49% and the market was plummeting, the developers had actually grown business by 25%.”
In my experience, going through this interpretation process yields good, actionable insights. Going through this process as a team yields better-informed, richer insights that are more actionable because the team feels ownership of the findings. Which leads me to…
3) Own the insights as a team
Not only is team reflection informed by multiple perspectives, it also fosters a feeling of team investment in the findings. Have you ever been really proud of something you made? In a 2011 study, researchers found that consumers placed a disproportionately high value on things they helped make themselves. This is called the “Ikea effect,” and it explains why someone might love their Ingatorp table so much even though it took them several painful hours to assemble.
The same principle goes for crafting design research insights. When the team goes through the process of looking at all the data, finding the themes, connections, and anomalies, and making sense of those connections together, there is a greater feeling of “owning” the insights. Team members have more confidence that the insights that are driving product decisions actually derived from user needs and behaviors. More importantly, engaging directly with data gathered in research encourages a sense of empathy for users, which also influences product decisions for the better.
From debriefing, to interpreting data, to owning insights as a team, there are many ways to make “reflection” an energetic, communal activity that helps transform research from data into effective product direction.
Have other thoughts on reflection and design research? Please add your insights to the comments below.
Referenced works:
IBM Design Thinking | The Loop: http://www.ibm.com/design/thinking/loop/
Christensen, Clayton M. Hall, Taddy. Dillon, Karen. Duncan, David S. “Know Your Customers’ Jobs to be Done.” September 2016 issue. https://hbr.org/2016/09/know-your-customers-jobs-to-be-done. Accessed Nov 17. 2016.
Norton, Michael I. Mochon, Daniel. Ariely, Dan. “The “IKEA Effect”: When Labor Leads to Love.” Harvard Business School.http://www.hbs.edu/faculty/Publication%20Files/11-091.pdf. Accessed Nov. 17. 2016.
