A clear understanding of the full program logic is necessary for comprehensive learning. MCC conducts evaluations in order to hold itself accountable for the commitments it makes and to generate learning for future interventions. In addition to assessing whether interventions achieve their ultimate objectives, nuanced learning comes from assessing the various pathways through which we expected to achieve those objectives, beginning with assessing (i) the quality of designs, implementation and the resulting outputs (e.g., status of the infrastructure and the utility’s management thereof), (ii) intermediate outcomes (e.g., how consumers interact with the outputs), (iii) ultimate objectives (e.g., expected health and financial outcomes), and (iv) whether critical assumptions played out as expected. This kind of comprehensive assessment can highlight more precisely where successes or failures occur in the results chain so MCC can replicate or make educated adjustments in the future. This evaluation included this kind of comprehensive assessment of the program logic and will serve as a useful model for future evaluations.
Lesson Learned