SAP Labs Canada Investing in Data, Context and Design
UX Design Workshop at Labs Montreal
We conducted a design workshop in partnership with Yu Centrik, a Montreal-based design agency, to explore the role of contemporary design research in an age of data proliferation. At a time when it seems, increasingly, like the answers are available to us even before we ask the questions; is design research obsolete or is it more important than ever?
During the UX design workshop that was hosted in SAP Montreal’s Executive Briefing Center (EBC), representatives from Custom Development to IMS, as well as from Business Suite organization were present. Design is what helps bring them all under one roof, unifying these teams as “one SAP”.
To kick off, we considered a daunting and familiar Montreal situation, from the perspectives of commuters, pedestrians, parents of school children and the elderly.
- The hopes and fears that this situation evokes
- Facts about snowfall volume and frequency, snow removal costs, injuries associated with snow removal and municipal snow removal policy
We designed ways to make citizens’ lives better during a snowstorm.
We rapid-prototyped our design ideas by body-storming; a role-playing exercise in which we enacted snowstorm scenarios. Participants assumed the roles of users (i.e. a homebound elderly person), elements of the environment (i.e. an ice patch) and design components (i.e. a wearable airbag). In giving each player a voice to negotiate the interaction, the exercise surfaced unanticipated circumstances, obstacles and workarounds that inspired meaningful design refinements.
Reflecting on how our design concepts evolved throughout the day, we saw how statistics pointed us to aspects of the problem that needed design attention. Moreover, we also considered how the facts and numbers failed to capture the context and contingencies of the situation that triggered novel and effective design ideas.
We are not alone in this observation. There is a rising cohort of contemporary design researchers that are as equally committed to harnessing big data, as they are to exposing its limitations. Statistical analysis may tell us what is happening in a given context – as they point out, but understanding the why, how and what, would make better demand complementary methods. In her HBR article, The Hidden Biases in Big Data, Kate Crawford warns against ‘data fundamentalism’, which obscures the causes of peoples’ behaviour and calls for rigorous qualitative research to illuminate the biases and blind spots in our statistics. Wired opinion piece Your Big Data Is Worthless if You Don’t Bring It Into the Real World considers data points collected in isolation of contextual observation to the mere “traces of our actions and behaviors.” Anthropologist Tricia Wang argues that big data needs thick data or contextual insight to be useful to designers. For one thing, ethnographic or contextual research acts as a bridge, enabling organizations to identify what they do not know but need to. Lastly, contextual research “gives something that Big Data explicitly does not – inspiration.”
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