Imagine a society where people could access the best possible services and solutions. In that society, a newcomer settlement agency might have dedicated capacity to conduct frontline research on language service usage while also facilitating the settlement of refugees and generating new supports to enhance the settlement experience. A humanitarian organization might have in-house capacity to develop a platform that connects people who have been displaced, by, say, wildfires, with people who have extra space to house them—while continuing to bring aid to others more recently affected and establishing more agile internal processes along the way. That society might also have an organization working alongside adults with cognitive disabilities, and simultaneously developing and refining a platform for lifelong learning rooted in the latest research—enhancing the efforts of a network of agencies delivering social services.

These organizations already exist—in Halifax, Ottawa, and Vancouver, respectively. And they’re not alone in their approach. In fact, a small but growing number of nonprofits and charities across Canada are delivering services even as they research, design, develop, and deliver new practices and services. These organizations are increasing design capacity, producing new knowledge, and creating new kinds of value. They are pursuing what, in the private sector, one would call research and development, or R&D. Given the social sector’s chronic funding restrictions and adversity to risk, these are extremely bold steps.

Focusing on Strategic Inquiry

The words “research and development” conjure up images of scientists in white coats methodically running experiments in controlled laboratory environments. This quest for incontrovertible knowledge is what authors Ian Mitroff and Ralph Kilmann call operational inquiry. They contrast operational ways of knowing with strategic ways of understanding the world:

Where the operational scientist is governed by the need to break problems and issues down into their elemental parts, the strategic scientist is governed by his need to pereive problems as part of a larger global “whole” or framework. … Where the one believes in the search for a single best (optimal) answer to question, the other believes that there are multiple possible ways of posing and responding to any question.

Social R&D draws heavily on strategic inquiry. It can be described as the art and science of applying research and experimental processes on the frontline to generate new insights and innovations that transform services, products, organizations, and—ultimately—lives. It uses diverse methods, including behavioral science, randomized control trials, lean prototyping, positive deviance, and ethnography. The questions it seeks to answer are situated in the decidedly messy and evolving realm of human experience. How do we address growing social isolation and loneliness? How do we combat rising homelessness and opioid deaths? Such challenges are by-products of complex systems; the unit of focus isn’t simply the individual but the dynamic relationship between the individual and her environment. Because there are no singular solutions, the innovations that emerge from social R&D bear little resemblance to penicillin or the space rover.

Take Alcoholics Anonymous (AA) or the World Organization of the Scout Movement. Started in 1935 with two members, AA had some 2 million members and more than 100,000 groups in 2016. The Scouts, established in 1908 with 20 youth, now number about 28 million. Unpack each innovation and what you have are roles, relationships, rewards, and routines. But AA isn’t the solution to addiction; scouting isn’t the solution to youth disengagement. Both innovations emanate from lived experience and continuous development. Alcoholics Bill Wilson and Dr. Bob Smith formed a peer-support group out of desperation. Far from undertaking an objective inquiry process in a controlled environment, they learned through personal trial and error in a halfway house. And despite its reach, AA’s efficacy is mixed. Randomized control trials are inconclusive. For a segment of users, AA is effective. For others, not at all. Far from bringing us certainty, much social R&D gives us opportunities to engage within uncertainty. It is the back-and-forth process of moving between lived experience and codified principles and practices within complex environments. It relies on connections with people and connections to systems.

Connections with People

Tapping into lived experiences requires immersive kinds of data—what anthropologist Clifford Geertz has termed “thick description.” Thick description goes beyond big or hard data to explore how and why people interact in the world—their routines, habits, preferences, motivations, and aspirations. Such intelligence offers starting points for generating ideas and prototyping alternative responses with people. Indeed, where hard data can shed light on the nature of a problem (for example, changing demographics or low service utilization rates), thick data can help to elucidate the types of solutions that are attractive to people and thus more likely to have lasting impact.

Increasingly, private sector companies such as LEGO and Disney are investing in thick data to develop products and services that better reflect user needs and desires. And yet, there has been no equivalent or concerted focus on the data capability of social sector organizations. Sectors such as education and health, however, offer a few helpful clues. For example, AltSchool, a Silicon Valley startup, has hard and thick data at its core. Its two-story buildings feature collaborative learning spaces on the first floor and research labs on the second. Designers, developers, engineers, marketers, and education professors work alongside teachers and students and empower them to capture their experiences, identify patterns and trends, and co-make and test new educational tools, interactions, and pedagogical processes.

Connections to Systems

For local innovations to achieve impact at scale, they must engage with complex systems that operate at multiple levels of society. Complex systems are characterized by opaqueness (no one can understand the whole system), co-evolution (problems change in response to solutions), unintended consequences, and context sensitivity (similar conditions may lead to dissimilar outcomes). This means that existing solutions tend to become less effective over time, and copying best practices from one jurisdiction to another rarely works as intended. In short, complexity means we need to think differently about scale.

Based on a decade of experiments investing in social innovation across Canada, the McConnell Foundation has found that systemic impact requires a combination of three scaling strategies: scaling out, scaling up, and scaling deep. Scaling out includes replication and dissemination; scaling up includes changing policies, laws, and rules; and scaling deep includes changing cultural values and beliefs. By building an evidence base on what works, social R&D can help challenge entrenched assumptions, raise capital, catalyze social movements, and advocate for policy change. Systems change also requires an ecosystem of connected changemakers. Social R&D must be integrated with, not isolated from, the groups and institutions that manage the current system.

The success of the Escuela Nueva learning model illustrates the role of social R&D in addressing complex challenges. The program started in a single demonstration school in Pamplona, Colombia, in 1971 and today has reached more than five million children in 14 countries. By 2000, a UNESCO study found that the model’s use resulted in Colombian rural schools outperforming their urban counterparts in spite of deep structural inequalities. This achievement was made possible by disciplined social R&D over decades that built innovative new practices in tandem with a supporting evidence base in demonstration schools, field trials in the most deprived settings, and evaluation of educational outcomes both traditional (language and mathematics) and new (self-esteem and democratic behavior). Escuela Nueva cofounder Vicky Colbert rose to become vice minister of education in Colombia, where she made Escuela Nueva national policy implemented in 20,000 rural schools. In 1987, she founded the nonprofit Fundacion Escuela Nueva to continue to innovate and expand the model. How did Escuela Nueva create systems change at this scale? According to Colbert, the reason was simple: “We had evidence and results.” Escuela Nueva cofounder Beryl Levinger adds, “If you’re going to innovate, you have to embrace the idea that you don’t know what the innovation looks like when you start.”

Children participate in an Escuela Nueva program at San Pablo School in Apartadó, Colombia. (Photograph courtesy of Fundacion Escuela Nueva) 

Seeding an Enabling Ecosystem

If we aspire to create an R&D-rich social impact ecosystem, where we can generate more innovations like AA, Scouts, or Escuela Nueva, it is insufficient to have pockets of skills or capital or knowledge scattered across Canada’s vast geography. We cannot rely on exchanges of ideas and talents solely between disparate individuals. We must address systemic barriers to social R&D.

We may be early in the process of shaping a robust social R&D ecosystem, but the time to start is now. There is no single formula for doing this. But we have observed that our embryonic R&D ecosystem benefits when those of us involved let it flow from the bottom up, appreciate multiple ways of knowing and doing, connect people to pursue mutual gain, build tribes of trust, create informal feedback loops, and celebrate role models and peer learning. We are learning that there is a necessary interplay between “hard” and “soft” assets within ecosystems. Hard assets in include people (including practitioners, grantmakers, academics, and end users), infrastructure (technology, equipment, financial capital, data, and physical space), policy (incentives, regulation, services, and matching funding), and skills and competencies (the theory, tools, and “street craft” of design, experimentation, and delivery). Soft assets include feedback and efficacy, motivation, recognition, norms and values, voice, and a sense of belonging.

We are also beginning to see three types of R&D clusters emerging: issue-based, craft-based, and policy-based.

Issue-based clusters pursue shared research and experiments to transform interventions in a specific domain, such as social services. These include Grounded Space, a cross-organizational R&D function focused on the social services sector. Grounded Space is itself an experiment, led by social design agency InWithForward. Frustrated with how hard it can be to implement ideas, Grounded Space recognizes that moving from problems to ideas to scaled innovations requires permanent infrastructure. Instead of relying on one-off grants, other organizations are pooling resources and sharing in the talent, data, and routines required to both develop and deeply embed new models and practices.

Craft-based clusters focus on strengthening the competencies and tools of R&D in social contexts. Labwise, a pan-Canadian network of practice, is one such cluster. It focuses on improving social innovation lab processes to help practitioners build capacity, integrate collaborative research, prototype solutions, embed continuous evaluation and learning in their work, and hone action-planning processes across traditional boundaries. Innoweave is an online learning platform for Canadian nonprofits and charities to learn about topics such as experimentation, developmental evaluation, collective impact, social innovation labs, and cloud computing.

Policy clusters, generally nested inside government or on the edge of government, have mandates around policy research, experimentation, and innovation. The Alberta CoLab, for example, is a research, design, and development team with the province of Alberta’s Department of Energy. MaRS Solutions Lab works outside government but supports policy development for all levels of Canadian government and specializes in innovation for cross-sector challenges that transcend the government, corporate, academic, and nonprofit sectors.

Ultimately, we imagine a Canadian ecosystem of connected changemakers learning from peers and generating social innovation, with a supporting evidence base in multiple domains, from hunger to gender equality to literacy. There are many pathways to scale and spread social innovations from the frontline to change organizational routines, government regulations, and social behavior. The cumulative impact of community organizations is greater than the sum of their parts. The first bold step we must take is to more systematically and intentionally grow a thriving R&D culture, capacity, and practice in Canada’s social impact sector that respects all three dimensions outlined above: a connection to people, a connection to systemic change, and a connection to an enabling ecosystem.