Learning-by-doing and adaptive management require careful monitoring and evaluation of the outcomes of environmental policies and programs under implementation. Selecting relevant indicators is difficult, especially when monitoring over a longer period of time. Further challenges arise when policies are developed as a collaborative effort among multiple actors.
This paper discusses an approach to design frameworks for long-term monitoring and evaluation in multi-actor systems. It uses Dynamic Actor Network Analysis (DANA) as an actor-sensitive method to reconstruct program theories. This is combined with elements of assumption-based planning to identify critical assumptions and associated indicators to incorporate the dynamic aspects related to long-term monitoring.
An application of this approach is described for a case of water management in the Netherlands. Here, mapping multiple perspectives and identifying critical assumptions helped to broaden the scope of monitoring in important ways. Identifying associated indicators and expectations on their development in response to policy implementation proved more difficult.
From this case, it can be concluded that the approach is feasible, useful, but also demanding. However, with continuing trends of networked governance and adaptive management, additional efforts to reflect these trends in monitoring and evaluation, through this and similar approaches, are needed.