Decision making for transformative change: exploring model use, structural uncertainty and deep leverage points for change in decision making under deep uncertainty

Moving to a low carbon society requires pro-active decisions to transform social and physical systems and their supporting infrastructure. However, the inherent complexity of these systems leads to uncertainty in their responses to interventions, and their critical societal role means that stakes are high. Techniques for decision making under deep uncertainty (DMDU) have recently begun to be applied in the context of transformation to a low carbon society. Applying DMDU to support transformation necessitates careful attention to uncertainty in system relationships (structural uncertainty), and to actions targeting deep leverage points to transform system relationships. This paper presents outcomes of a structured literature review of 44 case studies in which DMDU is applied to infrastructure decisions. Around half of these studies are found to neglect structural uncertainty entirely, and no study explicitly considers alternative system conceptions. Three quarters of studies consider actions targeting only parameters, a shallow leverage point for system transformation. Where actions targeting deeper leverage points are included, models of system relationships are unable to represent the transformative change these interventions could effect. The lack of attention to structural uncertainty in these studies could lead to misleading results in complex and poorly understood systems. The lack of interventions targeting deep leverage points could lead to neglect of some of the most effective routes to achieving transformative change. This review recommends greater attention to deeper leverage points and structural uncertainty in applications of DMDU targeting transformative change.