Lessons learned in using the ripple effects mapping (REM) method for evaluation

On February 20, 2020, Data for Impact (D4I) hosted the third webinar in a series sharing lessons learned in applying complexity-aware methods in evaluation. Today, evaluations require methods that are flexible; allow for the complexity of current public health programming in low-resource settings; and address field challenges such as strict budget and time constraints, limited baseline data, and lack of access to comparison groups. Under these circumstances, the Ripple Effects Mapping (REM) method is a useful tool for evaluators.