Abstract
Globally, we are continually confronted with many complex problems ranging from climate change to persisting racial, gender, and health inequities to the growing burden of chronic diseases and related determinants to fragile health systems and weak governance. The COVID-19 pandemic has reinforced the need to examine our assumptions about how best to recover and contribute to a healthier and more sustainable future. One of the challenges social actors face is what combination of policies, programs, and other innovations can be implemented, scaled, and sustained to effectively address these complex problems and improve population health and economic well-being, while leaving no one behind.
Robert McLean and John Gargani tackle one of these thorny issues in Scaling Impact: Innovation for the Public Good. They define “scaling impact” as …seeking an optimal result where the impacts that are proven effective and desirable to stakeholders are cultivated and encouraged; and those that may cause harm, lead to waste, or are not desired by the impacted community are inhibited. p. 189
Much has been written on the importance of scaling programs and other innovations in fields like global health and on the barriers and facilitators that contribute to scaling and are faced by innovators, program implementers, and researchers. This book makes a novel contribution to the research for development literature by inviting its readers to reflect on what we actually mean by the scaling of research findings and innovations—why and with what purpose and to what end.
“Scaling Impact” at a Glance
The authors begin by reviewing what is known about the emerging paradigm of scaling science as the basis for challenging dominant thinking that more is better. In my view, this kind of thinking also permeates global development agendas, which challenge the achievement of critical goals of equity for all people and the sustainability of our planet. The authors explicitly acknowledge this dominant paradigm but don’t stop there. Using concrete examples, they helpfully draw out distinctions between the different (but at times conflated) uses of the term scale—scaling up, scaling out, scaling deep, and scaling impact.
They further propose four guiding principles that can be applied by different organizations designing and evaluating scaling strategies. These guiding principles about scaling impact—justification, optimal scale, coordination, and dynamic evaluation—anchor the book. Justification calls attention to who governs and is impacted by scaling and the associated evidence, values, and shared risks. Optimal scale is about trade-offs involved in achieving balanced and judicious results. Coordination centers the role and involvement of a complex array of actors in the scaling process. Finally, the principle of dynamic evaluation signals that scaling interventions can be evaluated and that learning is iterative. These four principles are then explored through case examples from IDRC-funded research, with attention paid to the following: the scaling system (or setting in which the innovation operates), the scaling process (or stages contributing toward achieving impact at an optimal scale), the dynamic and plurality of actors involved in the scaling process, and the means to coordinate several innovations for impact (or the portfolio approach).
The five case studies also address a variety of issues in different geographical contexts (e.g., scaling locally fortified sunflower oil using e-vouchers in Tanzania, scaling access to justice for survivors of sexual violence in India). Building on the guiding principles and case studies, the authors then reflect on five different pathways to scale. This typology of pathways should serve as a starting point. The pathways should be considered as nonmutually exclusive, nonhierarchical, and nonexhaustive. The authors conclude with some reflections to guide the advancement of the science of scaling.
Toward a New Vision for Scaling
The last three centuries have been marked by advances in industrialization and technology that have contributed to a systemic bias toward more-is-better thinking. The authors rightfully challenge a premise that has prevailed in efforts to scale science—that there are known solutions to such development problems. This is clearly not always the case. In fact, many of our preexisting solutions are too simplistic to effectively address complex and context-dependent health, social, and environmental problems, where the level of uncertainty is considerable.
McLean and Gargani call out the “who,” the “why,” the “what,” and the “to what end” behind most scaling efforts. For example, when scaling scientific research findings, researchers as innovators (or vice versa) are usually in the driver’s seat (who). The authors contrast the traditional approach to scaling with the principle-based approach to the science of scaling that is the focus of this book (what). The latter approach invites readers, particularly scaling scientists and practitioners, to engage in more critical, creative, and reflexive thinking about the assumptions that underpin the testing and scaling of innovations for social impact (why). For instance, the section on justification turns on its head the scaling imperative, which privileges the act of scaling. Rather, we are encouraged to ask under what contextual conditions should we scale or scale at all? (to what end).
The authors also invite us to be clear in our definitions and use of concepts, including what principles underpin scaling, and more fundamentally to reimagine how we conceptualize the scaling process. Leading by example, the authors clearly articulate what they mean when using certain concepts and terms. For instance, scaling should be about impact—a recurring term that is not always sufficiently nuanced in research for development efforts. McLean and Gargani invite continued reflection on the potential impacts that may result from scaling—anticipated versus unanticipated, desirable versus undesirable, and intended versus unintended impacts. They further recommend taking a more holistic view to encourage evaluators and innovators to remain open to the intersections and tensions that exist between the magnitude, variety, sustainability, and equity dimensions of scaling.
I appreciated their unpacking of the scaling system. In my view, too often more reductionist approaches are used in research and evaluation to manage uncertainty rather than embracing the complexity that can help us better understand a social phenomenon like scaling. Shifting away from a more simplistic analysis of facilitators or barriers to scaling, the authors encourage us to map the roles that different actors play, how their efforts are coordinated (or not), and the power asymmetries that operate in the scaling system. They refer to these various different roles as the initiators, the enablers, the competitors (alternatives to scaling the innovation), and the impacted. In my opinion, centering an analysis of the dynamic power asymmetries in our evaluations of the scaling process is crucial to understanding the impact of scaling. For example, there are many asymmetries at play between market, social, and political forms of power that can impact the scaling process. A pluralist model acknowledges the diffuse nature of power as circulating between different social actors and would allow for a more nuanced understanding of the dynamic scaling process.
Given all of this guidance, how can our evaluations be reoriented to better assess the intervention pathways to scale? The authors describe the principle of dynamic evaluation. It starts by reimagining what we consider the object of study to be—in this case, scaling is an intervention. Guided by a dynamic and flexible orientation to evaluating the collection of impacts, we are pushed to think about the innovation at a given level of scale, to be more sensitive to the breaking points when scale comes into effect, and to be attentive to how social norms and other contextual influences may disrupt the scaling process over space and time. The authors also explore multiple pathways to scale. Several scenarios are painted that relate to policy, program, and change in behavior or skill, product or technology, or methodology pathways to scale. These pathways differ depending on who benefits, constraints on the research process such as data availability and quality, researcher and knowledge-use capacity, and readiness. When evaluating scaling process, the key is to articulate the pathway to scale, identify the possible trade-offs, and also be open to changing the plan.
A Strong Foundation for Scaling Science
As scaling science is an emerging field, I welcome the authors’ call for greater attention to, investments in, and evaluation of scaling with intentionality. With the guiding principles and practical applications, McLean and Gargani have provided us with a strong foundation on which to further build the field of scaling science. To advance knowledge about scaling for impact on the public good, we need to continually reflect on and critique our assumptions about scaling; test different theories, tools, and methodological approaches in our evaluations; and learn not only from our successes but also our failures. I highly recommend Scaling Impact: Innovation for the Public Good. It will be of particular relevance to development innovators, researchers, evaluators, policy makers, and students interested in scaling impact for transformative change. Given increased attention to effectively transitioning interventions to scale, this book should also be considered by global donors as it can provide useful guidance for steering programming investments in research and innovations. For evaluators, this book will be an invaluable resource in designing and implementing evaluations about scaling interventions in different sociopolitical and geographical contexts.
