Abstract for:Using Causal Loop Diagrams as an Evaluation Tool: A Case Example of Collective Impact
Unlike a scientific experiment, the process of communities working together to create collaborative change with collective impact is very complex and is constantly impacted by many uncontrollable factors (Minyard, Phillips, & Baker, 2016). As part of a recent evaluation of collective impact, the Georgia Health Policy Center (GHPC) used a realist evaluation lens and causal loop diagrams to help unravel the web of conditions and actions that influenced the success or failure of the initiative. By understanding the interactions of these factors, and how they enable or inhibit the anticipated outcomes, it was hoped that the findings would be more useful to decision-makers. The evaluation team leveraged the opportunity of reviewing data and information with a number of stakeholders so that everyone was engaged in identifying patterns that were emerging from the work. Examining data from the course of the initiative, the GHPC team observed multiple, recurring patterns. This evaluation approach of searching for how factors influence each other highlights when work is effective at generating desired outcomes, as well when work isn’t as effective as it could be, and therefore, offers an opportunity for groups to adapt, alter, or end a particular initiative.