Four key lessons for building scale-up partnerships

Scaling up programs that have strong evidence of effectiveness is a vital but often complicated step along the evidence-to-policy journey. Ultimately, scaling is both a science and an art, and after a decade of successes and setbacks in partnerships for scale, J-PAL has learned a lot about collaborating with policymakers to translate research into large-scale action.

J-PAL has devoted considerable resources over the past two decades to the science part of the scaling equation—conducting replication studies, testing multiple versions of programs, and designing randomized evaluations to identify key mechanisms driving impact in order to understand when findings generalize (or don’t) from one context to another. 

In a book chapter recently published in The Scale-Up Effect in Early Childhood and Public Policy: Why Interventions Lose Impact at Scale and What We Can Do About It (Routledge 2021), we dive into the ways in which scaling is also an art—one that takes a coalition of committed partners with diverse expertise and political savvy working together to make change happen. (The full volume, which explores both threats and enabling factors for scalability in the early childhood field, was edited by John A. List, Dana Suskind, and Lauren H. Supplee.) 

Our chapter, “Forging Collaborations for Scale: Catalyzing Partnerships Among Policy Makers, Practitioners, Researchers, Funders, and Evidence-to-Policy Organizations,” recognizes that despite growing interest in evidence-informed policy making, we still have a long way to go to fully understanding how to scale up effective programs. Successfully scaling up an evidence-informed program or intervention requires (at minimum): 

• a deep understanding of both global evidence and the specific local context and systems, 
• a policy window in which change is possible, 
• political will to change the status quo, 
• adequate funding resources, and 
• capacity to monitor and implement the program well. 

Because no single organization’s mandate covers all of these conditions, collaborations between policy makers, researchers, practitioners, funders, and evidence-to-policy organizations can make it more likely that these scale-up conditions are met. 

We draw on more than a decade of J-PAL’s experience worldwide to share four key lessons for forging successful scaling collaborations. 

1. Invest in long-term partnerships and develop the resources to respond to policy windows in real time. Nearly all of the scale-ups to which J-PAL has contributed happened in the context of a multi-year partnership that included a mix of collaborative research, capacity building, and policy work. Although it may seem counterintuitive, investing in these long-term partnerships is the key to quick response times when new evidence-to-policy windows arise, as you can only learn about these opportunities in the first place if you have established trust and lines of communication. This is the art part—and requires a deep understanding of the strengths, incentives, and constraints of each collaborator. In our chapter, we discuss challenges to long-term thinking and how to overcome them. 
2. Use several complementary types of data and evidence to inform every scaling effort. Here, we touch on the science side of the equation, and discuss data sources including rigorous evidence of effectiveness, descriptive research, continuous feedback from participants and front-line implementers, administrative data, and a globally informed but locally grounded approach to evidence generation and use. Evidence from randomized controlled trials is crucial, but so are many other types of data in order to successfully scale a program. In our chapter, we discuss not only what data is useful but also when this data should be used (that is to say, continuously rather than just at the beginning or the end of a scale-up) and where it should come from (ideally, both global and local sources). 
3. Help institutionalize a broader culture of evidence-informed policymaking that goes beyond individual programs. Here, we especially drew on lessons learned from our government partnerships in Latin America. This type of data-driven culture can be fostered through innovation funds that incentivize evidence generation and use, embedded labs that create space for evidence to be used as a tool for learning, or policies that require the use of evidence as a step in the policymaking process. In our chapter, we discuss steps to support champions to build an institutional culture of data and evidence use. 
4. Leverage evidence-to-policy (E2P) organizations that can play a critical role in bringing different stakeholders together to make change happen. For example, more than 400 million people have been reached by programs that were scaled up after being evaluated by J-PAL affiliated researchers. Although collaborations can of course happen without a convener, E2P organizations can play a vital role in innovation, generating rigorous evidence, relationship-building, and institutionalizing systems for evidence to scale. In our chapter, we discuss factors that must hold for E2P organizations to be effective as well as the services that they can provide in return. 

The partnerships from which we drew these lessons span years and continents, but they all demonstrate the importance of careful and intentional collaboration. We hope the lessons in our chapter can provide guidance to a variety of actors hoping to build collaborations with an eye toward scale. And we are honored to be part of a volume that includes so many thoughtful perspectives on how to best use evidence to scale programs effectively and reach as many lives as possible.