Understanding decision frameworks


In our ‘Reframing our future’ series of articles, Head of Strategy, Greame Dunk, and I have been discussing a National Resilience Framework. Graeme has identified the National need, exploring three key elements for policy;

  • Vary the policy according to risk
  • Avoiding stove-piped policy settings
  • A need for a National Resilience Roadmap.

I have taken a methodological approach of exploring how we develop a National Resilience Framework from a Systems Thinking perspective.

In my last article, I provided an understanding of resilience in systems, or more correctly, resilient systems performance. This is the ability of systems to resist and recover from a shock to the original performance or better. In today’s article, I aim to provide an understanding of decision frameworks to provide an insight on how a National Resilience Framework can be constructed and applied in practice.

Decision Frameworks are diverse and vary in their application and, at their core, are designed to facilitate robust and contestable decisions. They include aspects such as problem definition, strategic goals, planning and observations, and provide a conceptual, or abstracted view, of the issues and insights that inform decision making. Structuring, or codifying these conceptual and integrated aspects, provides a richer picture to the decision maker. Decision Frameworks give structure to the information, integrating multi-disciplinary domain knowledge, thereby enhancing the understanding in the decision maker.

Decision Frameworks, based on systems thinking, support policymakers to understand the multi-domain and interrelated consequences. At Shoal, we employ model-based frameworks to improve our designing of resilient and elegant solutions to complex problems, whether they are physical, organisational, or societal. They provide us with three main outcomes:

  • They facilitate the exploration of options and capture decisions, with rationale
  • They integrate information from across multi-disciplinary domains
  • They enhance our knowledge transfer, providing a current and common understanding such that the knowledge from the mind of the producer (analyst) can be easily transferred to the mind of the consumer (decision maker).

As highlighted by Senator the Hon David Fawcett in his recent Covid-19 pandemic article in The Strategist, ‘failure mode effects and criticality analysis’, or FMECA, is a decision framework that supports the analysis of component systems, generally from different disciplines, in order to determine the failure probability of the whole system, such as an aircraft in Senator Fawcett’s example. This FMECA facilitates the exploration of failure probabilities with rationale (Outcome 1), integrates the knowledge from across the different system components (Outcome 2) and then communicates this to decision makers (Outcome 3).

Another example is the Causal Loop Diagram (CLD). A critical Systems Thinking tool, this aids decision making by representing the different interrelated components, and their relationships to inform decisions. Declan Bradley and co-authors published an article on “A systems approach to preventing and responding to COVID-19” that demonstrated the application of a simplified causal loop diagram to illustrate the interacting “components in a society responding to the threat of COVID-19”.  In this example, CLD provides a visualisation of the different interrelated components that represent societies response to COVID-19. The connections between components indicates either a positive or negative relationship which allows for the closed cycles to be discovered as either a reinforcing or balancing feedback loop. Their CLD facilitates the exploration and analysis of the components in society (Outcome 1), integrates the knowledge from across the different components (Outcome 2) and then communicates this to decision makers (Outcome 3).

As we can see from these two different examples, Decisions Frameworks have common principles, processes, and practices that enable information and analysis to inform decisions. They identify the problem, support the capture and analysis of information and build the knowledge towards informing decisions across all aspects of society. As Graeme identified in his last blog, Resilience – from policy to implementation, if we are to develop a National Resilience Framework, we “…must capture the relationships between the various components within society in order that the most effective decisions can be made.” A well-structured, model-based decision framework can allow us to achieve this and deliver the robust and contestable decisions we need.

Shoal’s model-based experience and approach to decision frameworks would provide the structured foundation that a National Resilience Framework will need.

Kevin Robinson

Kevin Robinson is Chief Engineer at Shoal. His background is in systems thinking and developing frameworks to model and analyse complex systems. He also leads research into resilient and adaptive complex systems.