Measuring the Progress and Impact of Collaborative Learning Networks: A Framework in Action

 In the global development or social impact field, teams have long grappled with how best to catalyze systems change (in health systems, education systems, etc.) by working with and through networks of local actors. These Collaborative Learning Networks convene system change agents (e.g., government officials, sector experts, civil society actors, technical partners) from different countries or regions around a common or shared purpose in a way that allows them to collaboratively learn and co-create knowledge and tools to address challenges of common interest. However, this indirect, networked way of contributing to impact can pose a challenge when measuring progress and impact. Because ‘collaborative learning’ is a silo-busting, participatory approach, it is much more difficult to measure than more direct interventions that utilize concrete metrics such as number of vaccines distributed. In this session, we will shed light on the process of co-creating a framework that is adaptable enough to work with a diverse array of Collaborative Learning Networks (CLNs) and across a wide breadth of sectoral and geographical contexts while also providing a unified methodological and analytical framework architecture that supports learning, not just within a given CLN, but across networks as well. This session will feature the experience of a CLN that has stress-tested and adapted our bespoke Measurement & Learning Framework: Linked Immunisation Action Network (Linked). Panelists will describe the co-creation process for developing and stress-testing the framework and will explain how the process enabled a flexible and adaptive use of the framework by the network members themselves. What’s more, panelists will describe how networks can adapt the framework to implement a utilization-focused approach to measuring their network’s progress and impact. Finally, we will open the floor to a discussion around the ways in which the framework might be useful for evaluators, researchers, practitioners, and policymakers alike as we work to enhance shared understanding around what’s working well –and what’s not working so well– through our collaborative network-driven approach to systems change.