Using the CART principles and building on IPA’s extensive experience of evidence generation partnerships worldwide, IPA’s Right-Fit Evidence unit supports NGOs, social businesses, funders and governments to be smarter users of data and evidence.
Our approach involves the iterative development of a learning agenda that is prioritized, achievable, and integrated with program management. IPA may provide support at various stages in the cycle of creating and using evidence.
Below, we describe three ways IPA can help partners use this approach in practice:
To get in touch with the Right-Fit Evidence team, please email email@example.com.
Determining a learning agenda starts with the theory of change. A sharp theory of change allows organizations to identify clear, testable hypotheses about how their programs work. These hypotheses become the questions that are driving M&E activities. The CART principles help prioritize which questions can and should be tackled first.
For new programs, the immediate priority is often on questions that relate to early stages of the theory of change rather than downstream impact. This might include questions about quality of implementation, take-up, or targeting. Such situations call for an iterative approach using ongoing learning cycles (see next section). On the other hand, programs that have more defined and tested models may be better off investing in impact evaluations and contributing to global knowledge. Organizations that are scaling-up interventions already supported by a strong pre-existing body of evidence may prioritize monitoring-related data collection to ensure fidelity of implementation, rather than revisit questions of impact.
- Facilitated workshops to refine the theory of change and surface key assumptions
- Participatory development of a prioritized learning agenda for M&E activities
|A case from the portfolio: Plant with Purpose|
Plant with Purpose is a US-based NGO operating in 7 countries worldwide. Its core program aims to transform communities by providing integrated support to agricultural, environmental, and spiritual renewal activities. Plant with Purpose initially hired IPA to facilitate a two-day M&E workshop as part of their bi-annual directors gathering.
IPA can support partners to identify and collect the right data to answer their key M&E questions. The choice of study and data collection approach should be cost-effective, reliable, and provide timely feedback.
The right tool will depend on the question, but may include options like rapid A/B testing, remote sensing, cost-effective feedback surveys or qualitative research.
- Advice on study and data collection design
- Technical support in collecting and managing the data
- Assistance in analyzing data to derive credible insights
|A case from the portfolio: a large market-based WASH program in the Philippines|
A large international NGO is about to launch an innovative market-oriented water, sanitation and hygiene (WASH) program. It is planning to put learning at the center of its M&E strategy, and has been in discussions with IPA about supporting the program on its learning journey.
Right-Fit Evidence is not only about asking the right questions, designing the right data collection approaches to answer these questions, and analyzing the data appropriately. It is also about creating the space for these insights to translate into program decisions and improvements. To make evidence-driven management a reality, managers need to put routines in place to review the data and enact programming decisions and changes.
- Support to set up structured routines such as regular learning workshops to review findings, adapt programming and re-define priority questions
- Temporarily “embedded” IPA analysts within project management teams to help kick-start a shift in their M&E approach and empower organizations to conduct right-fit M&E on their own
- Advice on management and organizational structures that can embed learning
|A case from the portfolio: MineduLab|
MineduLAB is an innovation lab for education policy housed within the government of Peru. The lab pilots cost-effective innovations and rigorously evaluates them, allowing the Ministry of Education to use evidence to improve children’s learning throughout the country. The lab employs a policy cycle that tests and refines the innovations, using the Ministry’s own administrative data to evaluate them.