On Friday I had a call with Helen O’Connor from the Prince’s Trust and Maddie Dinwoodie from UK Youth to discuss the My Best Life programme. It started me thinking about how we fit together good quality user research with a codesign process that delivers workable prototypes within the budget—in the words of Stanford d.school’s Bernie Roth: keeping both a bias toward action and empathy toward who you’re designing for. It also made me reflect on some of the challenges I’ve faced when doing upfront scoping research in the past.
I think the answer is about rethinking what we had originally planned as an upfront research phase. This isn’t an argument to not do research—good user research is essential. Instead it’s an argument to do it differently. To move research out of explicit upfront research phases and into the cycles of service and product development. In this blog I’ll reflect a bit on some of the problems with doing an upfront research phase and in the next I’ll talk a bit about how we might shift from thinking to doing by using prototyping as our core research method.
Closing the gap between thinking and doing
User research dates quickly, and it gets old even faster for digital services. Technologies move on, social contexts shift, and user expectations evolve constantly. And this often leaves us lagging behind, reading and writing reports instead of making change. To develop better services, we need to get closer to our users, close the gap between thinking and doing and move research out of setup into the development of services.
This idea isn’t new. Design researchers often blur the line between practice and research—for example the ‘cultural probes’ originally developed by Gaver, Dunne and Pacenti as a method for design inspiration are now deployed as a form of auto-ethnography to help designers learn about user contexts while also prompting creative ideas.
3 problems of ‘scoping’ research for service design
1. Too much information
The more information you have, the harder it is to digest. Meaningful information can be swamped by meaningless noise and working out what to pay attention to in the absence of a concrete proposition can become nearly impossible. The tempting response to this is to do even more research to confirm findings but this just keeps the cycle going. Finally, you end up with more information than anyone is ever going to read (let alone use) and you put the report in a drawer to gather dust. For My Best Life we need to try to do just enough. Just enough to understand the problems and set the context so that we can get to that first testable idea.
2. Interpreting data is a subjective process
When we analyse research data we do so through the lens of our own experiences and personal understandings of how the world works. There are always multiple ways to interpret research findings and researchers often (consciously or unconsciously) tend to choose those that support their existing worldviews. This doesn’t just happen in qualitative research, which we might think of as more subjective, the choices made in quantitative analysis can also result in very different conclusions. Collecting more data can’t solve this problem. Doing more research can even bolster instead of challenging assumptions as in a large pool of data it’s easier to find support for any position.
3. Testing abstract propositions is really hard
Anyone who has ever tried to run a focus group or write a survey to ask people about something that doesn’t yet exist knows that it’s nearly impossible to do well. Mostly people just say yes. Yes that sounds plausible, yes that could be a good idea, yes I’d like one of those, yes sure whatever yes. But what do all those yesses mean? Will they really use that extra feature? Will they really turn up to that after-school session? Did they even really follow what you were asking?
For My Best Life we’re going to avoid asking in the abstract and instead talk about tangible prototypes. My next blog will talk more about this and set out how we intend to use prototyping as our primary research method.