Complex development challenges require complex interventions and consequently more complex evaluation designs. Multi-dimensional questions and the need to not only measure the impacts, but also to understand the underlying causal mechanisms, require an extension of the toolbox of researchers and evaluators. Facing these challenges for impact evaluation in the field of development co-operation today, only the systematic integration of different forms of causal inference can sufficiently address this demand. Certainly, (quasi-) experimental designs that allow for high levels of rigor and attribution are one important piece in the evaluators’ toolbox in complex impact evaluations. However, they are best understood as one of the elements in a complex evaluation design.

The design of advanced mixed-method approaches explicitly follows the particular epistemological interest of the evaluation questions. Through the smart and systematic integration of methods, they are superior to single-method approaches, as they can better address the complexity of interventions, making any discussion on “gold standards” obsolete.

Thus, future development of impact evaluation designs should focus on enhancing the capacities of multi/mixed-method approaches beyond simply sequential or triangulation strategies.