Learning to Embrace Ambiguity
Teaching Harvard Students to Embrace Design, Innovation, and Discomfort
Harvard students are typically taught to have the answers. Not in DPI-663, where students from across Harvard tackle real challenges with government clients.
In the course DPI-663: Technology and Innovation in Government — which I helped design, launch, and run when I was at the Harvard Kennedy School — clients come to their student teams with problems that don’t have clear solutions. Students must learn to avoid prescribing a solution too early. The course guides students through the design process as they work on public sector challenges with local and federal government clients, and getting comfortable with ambiguity is a key component of our course’s mindset and methodology.
Using a human-centered design methodology and an open mindset, students spend several weeks fully understanding their client’s problem through qualitative field research before jumping to conclusions. I’ve found that the students find this difficult — as they are practically wired to come up with the “correct” answer as quickly as possible. With the hairy government problems students encounter in DPI-663, the thread of research and reasoning is anything but straight.
One group of students, looking at an online assessing tool for the City of Boston, circled back on their research several times as they struggled with how to segment their user groups, by occupation, behavior, or task. They even created a diagram showing how they felt during what they called an “uncertain, iterative, and messy” stage in the process. We encouraged this circuitous process, because it is in this research and synthesis stage that students must lean into the ambiguity. IDEO partner, Sandy Speicher calls this moment “disequilibrium” — “when you begin to see things in the world that don’t make sense to you.” Students are forced, in that moment, to “create new frameworks and connect dissonant dots into new meaning.” We teach students methods to navigate this process, but it doesn’t make it feel any more straightforward.
DPI-663’s government clients have had to adjust to this way of working as well, as the teaching team encourages them to let go of predetermined solutions. In our very first class, one client presented their student team not with a challenge but with a desired product — specifically, a dashboard to better understand incidents and injuries in New York City construction sites. We urged the client and their student team to frame a more open challenge, such as “How might we use data to reduce construction-related incidents and injuries?” Perhaps a comprehensive visualization would address the original issue, but the students explored other interventions and made recommendations on incident response data collection and assessment and decision-making. When clients narrow their focus too early, they can stifle innovation and their teams may end up focusing on and solving the wrong problem.
When we first launched DPI-663 in spring 2016, the teaching team had an idea what a successful class would look like, but we also recognized that we had to be comfortable not having all the answers. We supplemented our experience and knowledge with guest speakers and we selectively formed teams (DPI-663 requires an application and is only open to 25 students) that could leverage their own experiences and teach each other throughout the semester.
I’m proud of making sure that student feedback was something we designed into the class. At the end of every class, we conducted a one-minute test where we ask students to share their biggest takeaway, biggest surprise, and biggest remaining question. This helps us understand what students are taking away each class. We also collected mid-semester and end-of-semester feedback to adapt our teaching and content as necessary. In the first year of the class, this helped us pivot mid-semester to begin running stand-ups in the morning — embracing the kinds of agile practices we discussed in class.
Creating DPI-663 was an important part of my time Harvard Kennedy School and the Graduate School of Design. I am currently a professional designer, consulting on government services for the Fjord digital studio at Accenture Federal Services. In this role too, I coach others through their discomfort with ambiguity. For example, when we partner with more traditional consultants, we try to bring them into the (calculated) chaos of our design studio to reveal the method to our madness. On one project — ironically another dashboard project — we showed our consulting partners walls filled with post-it notes. We had mapped the actions surfaced in our research to desired insights, metrics, and data sources. These connections helped us design the most effective data visualizations. While traditional consulting would have us merely start with the data we have, we began with human behaviors, the decisions our users make and actions they take based on their organization’s data.
One colleague calls this approach “making space for associations.” He schedules synthesis time on all his projects and doesn’t tell clients or partners what they’ll be doing with that time. Sometimes what emerges is a wall diagram that evokes A Beautiful Mind, sometimes it’s just word associations between teammates. He learned to embrace the ambiguity of the design process in his doctoral program where one professor kept a sign at the front of the room: a red circle that said “Rush to Solutions” with a slash through it. When it feels like we’re not making progress, like our research is yielding more questions than answers, we’re really honing on the true nature of our client’s challenge and making associations that will eventually lead to resolution.
In the spring of 2019, I had the honor of returning to Harvard to guest lecture in Professor Sinai’s fourth cohort of DPI-663 students. I came armed with frameworks and methods to help guide students through research synthesis — coding methods I had honed in other Harvard courses and analytical lenses I had learned on the job at Fjord. These frameworks helped coach students through a clear design process, recognizing that part of that process is simply becoming comfortable with the idea that you don’t know the answer.
