Smarter Research for the Connected World
I once had the opportunity to interview a vampire about smelly armpits and white underarm stains. I’ve spent time in the infamous mental ward of Cook County Jail to learn about mental health treatment for the incarcerated. I’ve been in shelters to observe how people react to the daily lottery of who’s in and who’s out at a safe place for sleeping that night. And I’ve watched a grown man nearly cry with frustration as he tried to get his pick-up truck bed cover to close over a newly purchased refrigerator.
I’ve had the opportunity to witness such a diverse cast of characters because of my day job at IDEO as an applied anthropologist working in the field of design. One of the core tenants of design research is to try, as much as possible, to inhabit the world of the people for whom we are designing. This involves more than simply observing and talking to people. It’s about understanding all of the factors that go into making them think, behave, and feel the way they do. By getting to know my respondents better, removing the cognitive, emotional, and behavioral differences between us, I can begin to turn knowledge into something actionable.
There are many traditional ethnographic tools to help do this. In-context fieldwork allows for observation in natural surroundings. Deep interviews and participation enable a meaningful engagement with people about their thoughts and actions. Surveys and feedback provide large data sets about a group of people.
These techniques, or some variation of them, are the bread and butter of design researchers. When used together, these methods complement each other to help build a robust picture of what’s happening in someone’s life. However, we can introduce an additional approach that augments our knowledge by reducing some of the current limitations, capturing new types of information, and turning research into a design tool.
With the rapid evolution of personalized wearables, the proliferation and accuracy of low-cost sensors, the social acceptance of sharing information, and new communication platforms for connectivity, now we can use personal and dynamic data as a powerful input in our design.
From episodic to continuous research
We were working with a client recently who asked us to help learn about how people are managing a chronic health condition. If we were following a typical research approach, we’d interview patients, doctors, and family members about their condition, spend a day watching their treatment routine, and ask them to document their experience with photographs. But we also knew that people were managing their chronic health conditions hundreds of times a day when we wouldn’t be in the room with them. To really understand what it’s like to live with a chronic condition, we needed to have a way of being there when we couldn’t physically be.
In order to extend the reach of our time with our respondents, we gave them smartwatches. By creating a shared communication platform with them, along with access to their accounts, we were able to invisibly learn from them in real time. For instance, we could see that some followed their treatment patterns better on weekdays, while others were more adherent in the early morning and late evening. We could see that when one respondent’s work hours changed to a third shift, her entire structure deteriorated. While we followed up with the respondents in person to help fill in the emotional and analytical gaps, we would have missed these patterns without the tool.
Gathering otherwise invisible information
Not only were we able to spend more time with the respondents, we were also able to gather new types of information. “There are unknown unknowns” is a famous NASA quote. As a researcher, my knowledge about a person or culture is limited by what I ask to hear or see. The consequence to the design team is that we can only be inspired by, and solve for, what we’re also able to experience.
To try to expand our depth of knowledge, we used two types of features inherent in the smartwatch. First, we pulled in native data like time of day, heart rate and movement, etc., something that traditional ethnographic methods would not be able to discern. However, data without context isn’t very helpful to a designer. So, in addition to pulling the agnostic information about respondents, we asked them to push small bits of information back to us. For example, not only would they receive automated messages reminding them to enter information about a health test, but we could also customize our communication to probe further. By coupling new data with real-time clarity and explanations, the team could begin to feel a greater degree of empathy about respondents’ experiences.
Converging research and design
One additional advantage of using a smartwatch as a dynamic data tool is that it’s both discreet and, ideally, minimally intrusive in someone’s day. As many others have written, the smartwatch UI design should enable a much quicker, easier interaction compared to a phone or computer (which tends to suck the user into an interaction).
These constraints were instrumental as we used the watch not only to gather information, but to prototype designs. In addition to collecting information, we wanted to offer respondents design provocations to help them gain a stronger sense of control in managing their disorder. As a result, the respondents also took on the role of co-designer. In order to do this, we leveraged the other two advantages of using live data. For one, we could see what people were doing in real time. In addition, we could communicate with them in real time, experimenting with things like tone (more congratulatory vs. compensatory to help with adherence) and messaging. By noting what kind of response each stimulus garnered from respondents, we could hone in on which aspects of our design were successful and why. Unlike a more traditional approach where we have phases focused on learning, synthesizing, building, evaluating, and then iterating, we were able to collapse them together to turn research and design into a single activity.
By designing the concepts — and evaluating them — based on live insights, we were able to move a step closer to inhabiting the lives of our respondents. There is, and always should be, a human element to learning, probing, reviewing, and evaluating design. But there’s also great potential to scale the story collection process through digital data that traditional methods can’t provide. While this particular project used the smartwatch to both collect personal information and evaluate design, it’s easy to see the realm of possibilities in which live data could influence design in other industries: using a car’s driving data to help recommend tires; integrating quantified health data to help with predictive analytics; or using someone’s meta-data on computer file organization to create a customized workflow.
As researchers and designers, success is based on understanding the essence of our respondents and building a service or product that solves something for them. The more facts we can learn about someone, the more nuanced and complete our designs can be.
