To me, Jan Chipchase is a pioneer in applying anthropological methods and thinking to business contexts. I first heard of him when he was working at Nokia years and years ago. Since then he’s been named by Fast Company as the ‘James Bond of Design Research’. He is the founder and CEO of Studio D Radiodurans a research, design and strategy consultancy which according to their website ‘provides discreet international research, design and strategy services to multinational clients’. He is due to release his third book The Fieldstudy Handbook in June 2017 which is a guide to running international field research projects.
This interview with him has some great info and perspectives including how human-centred design has evolved, which he outlines as:
Human-centered design is not static. Over time, the trajectory of it in the industry has gone from:
- “Help us fix this” usability testing, to
- “Help us make this” user experience design, to
- “What should we make?” foundational research + ideation + design, to
- “What is interesting and why?” exploratory field work (+ ideation + concepting + prototyping + design & engineering), to
- “What are the second order effects of x?” anticipatory design (strategy, design fiction, scenario planning)
Other useful points for me on the following topics were:
Conducting research: unusual questions can reveal shaky assumptions (it’s almost about infusing childlike play as a research tactic); the skill during fieldwork is knowing when to step away from the process that has been planned in detail and allow things to play out naturally; embracing the creative diversity of research teams; he aims for a state of flow and immersion with research teams which can lead to a team being engaged for 16 hours a day without it feeling like work and also has produced some of the best and most rewarding work from team members.
Future research trends: more technology will be involved that can bring contexts closer to research teams without them being there, but he cautions that technology can only capture so much and that the researcher will need to factor in what is missing and how it impacts the approach; mining of historical data will become more prevalent to make future predictions and if the volume of data is sufficient, it may not matter whether you understand why because the required outcome—a reasonable probability of understanding of what will happen next—is possible. However, this carries a risk of offering short-term value (of things that are known and measurable) and mask longer-term risks (of things that are not yet known, and therefore not yet measurable); The reality behind the assumption that more data equates to better insight is that most of the new data is an iteration on what is measurable, and thus what is already known.