Theme 2:
Discover,
Learn and Adapt

Harness discovery, learning and adaptation as a primary engine of scaling and capacity building. Integrate international science with local wisdom and base learning on a combination of rigorous approaches to data, continuous tracking and analysis of outcomes, and inclusive, peer-to-peer community and family engagement.

• The family, community and cultural contexts of whole child development innovations are varied and change across geographies and over time. Since context matters for programs that deal with intimate relationships, scaling such programs generally requires local adaptation or reinvention, rather than pure adherence to central models.
• A shared, iterative process of discovery, learning and adaptation is a primary engine for successful scaling and capacity-building. The learning process must be underpinned by rigorous measurement and analysis of outcomes and the factors that lead to improvement in outcomes.
• As a foundation for outcome-driven learning, engage families using the program in defining the desired outcomes and have local leaders buy into them and hold themselves accountable for delivering them.
• A well-designed Monitoring, Evaluation and Learning (MEL) system is the core technical infrastructure to enable this learning process. It should be shared across stakeholder groups involved in the program.
• Shared MEL can then enable joint detection of adaptation needs, with all relevant stakeholders participating in finding solutions.
• A core social infrastructure of the learning process is for leaders across the program, including at the front line and in communities, to engage with each other in communities of practice. “Communities of practice are groups of people who share a concern or a passion for something they do and learn how to do it better as they interact regularly” (E. Wenger and B. Wenger-Trayner, Introduction to Communities of Practice). This approach promotes the dignity and development of leaders, allows variations in outcomes to be understood and become a source of learning, and accelerates the spread of promising practices.
• Seek opportunities to use technology for data collection and communication in ways that support the front line, e.g., by providing feedback to service providers and families and by supplying data for analysis.
• The empirical richness that scale provides can be harnessed to enable both convincing summative evaluation and effective formative improvement. To achieve this, innovators can gather and analyse outcome data in two complementary ways: medium-term impact assessments (typically through experimental designs such as randomized control trials); and ongoing attention to high-quality outcome indicators for everyone being served (even outside specific trials, and ideally using data collected cost effectively through existing large, e.g., public, systems).