Monitoring, evaluation, and learning (MEL) must go beyond bean counting to create sustainable impact. Too often standard data collection summarizes activities but fails to determine whether and why outcomes are achieved. Findings are summarized in lengthy reports that rarely reach audiences outside the project. These challenges—output instead of outcomes-focused metrics and limited translation of learning into action—cut across the environment, development, and similar sectors. So how can organizations design MEL to inform decision–making?
Start with Asking the Right Questions
Our experience shows us that grounding programs in a learning framework enables clients to go beyond static standard reporting. Strong learning frameworks provide structure to the data collection and sharing process, linking indicators and outcomes to the theory of change to capture program achievements.
When working with clients to develop learning frameworks, we ask:
- How will you achieve the desired program outcome? Begin by articulating a clear theory of change that outlines how each activity will lead to the desired outcome, including each step along the way.
- What are the underlying assumptions in the proposed theory of change? After creating a theory of change, identify and test the assumptions underlying the proposed process.
- What is beyond your control? Consider questioning beyond the manageable interest of your program to demonstrate how the activities may move the field toward intended outcomes.
Learning Frameworks in Practice
Facilitating evidenced–based learning is central to our work on USAID’s Measuring Impact II (MI2) project. Along with our partners Foundations of Success and ICF, we used these three questions to cocreate a learning framework with USAID’s Conservation Enterprises Collaborative Learning Group, a cross-mission initiative formed to strengthen the evidence base and share learnings around conservation enterprises (CEs).
How will you achieve the desired project outcome?
First, we adapted the Open Standards for the Conservation of Nature (CS) to visualize the step-by-step impacts of each CE activity that would lead to the desired project outcome: improved biodiversity conservation. With the CE Collaborative Learning Group, we facilitated the creation of a high-level theory of change (pictured below). The theory posits that if stakeholders gain benefits, such as increased incomes from CEs, then they will be motivated and enabled to change behaviors. By outlining these steps, we created a shared learning framework to help separate teams track progress toward biodiversity conversation.