Design research is foundational to creating products, services, and systems that respond to human needs. In the public and international development sectors, understanding and meeting human needs are critical for improved livelihoods and better governance.
Yet despite its utility, design research is largely overlooked by many institutions important to an effective society. This oversight is unsurprising — the definition, purpose, and role of design research is not well understood. But in collecting the critical data they need to run their programs, these institutions do engage in ‘design research’. The information they gather, however, is often purely functional — ‘just good enough’. But a lack of deliberation and formalization in process limits the value of research, and thus the utility of collected data.
I’ve been privileged to learn the art and science of design research from one of the best in the game. Time and again, I’ve seen what can happen both when design research is overlooked and when it is thoughtfully applied. So, to advance the conversation, I wanted to lay out some basic principles, approaches, and tools of design research so public institutions can better understand how it serves their work.
What is Design Research?
By ‘design research’, I mean research specifically undertaken to support the strategic design and development of products, services, and programs. Sometimes confused with market research, the practices differ in a few key ways.
Market research identifies and acts upon optimal market and consumer leverage points to achieve success. Its definition of success is not absolute, though metrics are often financial. Design research, on the other hand, is founded in the belief that we already know the optimal market and consumer leverage points: human needs. Unearthing and satisfying those needs is thus the surest measure of success. Through this process, we earn people’s respect and loyalty.
Both market and design research are necessary in developing effective solutions. I’ve drafted the following table to help clarify their complementary yet differing approaches and their roles as part of a larger strategy:
In design research, the methods and data collected differ from those emphasized in market or academic research. Ethnographic approaches to participant interaction clarifies complex human needs, behaviours, and perspectives. Field immersions unearth contextual and environmental factors that shape user experience. Rigorous, old-fashioned desk research and expert consultation support the fieldwork.
But let’s be clear: good design research doesn’t end with good data. The contextual study (sometimes called ‘field study’, though I personally dislike the usage of ‘field’ in these contexts) is just the beginning. Once we have the data — often thousands upon thousands of photos, and dozens or even hundreds of interviews- the real work begins. The next steps include:
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- Process the data into useful formats. This includes filtering the data for relevancy; anonymizing outputs for participant privacy; tagging all artifacts with metadata; and categorizing data using taxonomies that support future needs and opportunities.
- Make sense of the data. Using processes collectively known as ‘synthesis’, we prioritize, evaluate, and make connections between all collected data points. This often involves exercises to map the data in meaningful ways. Tools include: visualizations of the stakeholder ecosystems, diagrams of user experiences, detailed personas that give dimensionality and depth to those we are designing for, and affinity maps to draw relationships between data points. These outputs help us decipher the information and identify the most critical for the task at hand.
- Distill data into insights. The tools above produce insights that inform the problem-solving process. Insights may include revelations on why people currently do the things they do and hypotheses on how their experiences can be improved. I’ll be writing more on this process in an upcoming post.
- Test insights against existing knowledge. How do the generated insights map against broader social and industry patterns? How to they map against institutional strengths and capacities? How do they measure against known best-practices? Are they suitable for both institutions and the people they serve?
- Translate insights into actionable formats. The data must be easily accessible to all stakeholders who may need it, and immediately useful to the design process. In this stage, we extrapolate initial design concepts to work on — our ‘best-guess’ attempt at how to solve the problem based on all the information we have gathered and processed.
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An example of what this looks like in practice: Prior to co-founding Reboot, I had the privilege of working with a fantastic, forward-thinking team at UNICEF. While there, I led a study in Suriname on education in the jungle interior, where politically and economically marginalized tribes lack access to basic rights and services. These populations fall below the national average across numerous developmental indicators. Recognizing that poor education often sustains oppression, UNICEF sought to improve access to education and information.
Our study brought us to seven remote villages in Suriname. We sought to understand the challenges faced by all individuals involved in the education system, from frustrated headmasters, to indifferent parents, to children with varying attitudes towards schooling. We met with representatives from the Surinamese Ministry of Education and other local institutions to better understand the system, and to get their input and buy-in for reform. The research focused on individuals, the analysis on the system.
We discovered the key issues weren’t poor school infrastructure or teacher attendance, though they certainly played a role. The main challenges, in fact, were an irrelevant curriculum and a lack of education’s demonstrable value to the indigenous tribes. Universally, people evaluate their investments against expected returns. Though many of us correlate investments in education to future economic and social opportunities, the Surinamese villagers saw it differently. There were no jobs in the local economy and villagers lived in small communities of only a few families. Thus, education yielded neither a rise in economic or social status. Many complained they were wasting time in learning an irrelevant language — Dutch, one of two national languages, was a colonial vestige only spoken in the cities. So why bother?
Weeks of research unearthed deeper needs of the rural Surinamese, and they weren’t the abstract notion of ‘being educated’. They wanted concrete knowledge that could serve them in their day-to-day life, a life that we had not previously understood in such rich detail. Our new understanding allowed us to map solutions that were relevant and thus appreciated, and a sustainable roadmap for the development of the interior.
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And this is but one example. To understand how to meet the needs of diverse people, I’ve done a long of observing, interviewing and, perhaps most importantly, listening. From migrant workers in China, Burmese refugees in Malaysia, and sex trade workers in Indonesia, to shopkeepers in India, street hustlers in Myanmar, schoolchildren in Jordan, and police officers in Afghanistan. By understanding the richness and diversity of human need and behaviours, we can start to detect meaningful patterns that inform the development of inclusive systems and services everywhere. And inclusive systems are what we strive for at Reboot, because we believe all people deserve solutions tailored to their unique, ever-evolving needs, and no one should settle for inferior derivatives of current market offerings or feeble extensions of good-enough legacy programs.
Design Research for Public Service
Design research is a vote against hunch-based reasoning. It prevents the need for endless testing, and provides a basis for evidence-based decision-making. Today’s leading private sector organizations are wielding it with great success. They are developing products and services that improve the lives of their customers and, as a result, building loyalty for their products and brands. Procter & Gamble, for one, has employed design research for years as part of a larger commitment to integrating design methods in their organizational strategy. This has yielded many market successes. Intel is another example of using design research to develop products that meet needs users have yet to even articulate to themselves.
We must bring the same value to the public sector. Driven by different considerations than private corporations, the fruits of design research have, to some extent, remained unclaimed among institutions that serve the common good. Our hope is that more formalized methods for gathering, using, and processing information — both new and existing — will help public institutions better serve their constituencies and communities.
(Images: Peter Durand of AlphaChimp Studios, created during the PopTech Social Innovation Fellowship Program 2010.)
