Seven methods for mapping systems

By Pete Barbrook-Johnson and Alexandra S. Penn

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1. Pete Barbrook-Johnson (biography)
2. Alexandra S. Penn (biography)

What are some effective approaches for developing causal maps of systems in participatory ways? How do different approaches relate to each other and what are the ways in which systems maps can be useful?

Here we focus on seven system mapping methods, described briefly in alphabetical order.

1. Bayesian Belief Networks: a network of variables representing their conditional dependencies (ie., the likelihood of the variable taking different states depending on the states of the variables that influence them). The networks follow a strict acyclic structure (ie., no feedbacks), and nodes tend to be restricted to maximum two incoming arrows. These maps are analysed using the conditional probabilities to compute the potential impact of changes to certain variables, or the influence of certain variables given an observed outcome.

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Problem framing and co-creation

By Graeme Nicholas

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Graeme Nicholas (biography)

How can people with quite different ways of ‘seeing’ and thinking about a problem discover and negotiate these differences?

A key element of co-creation is joint problem definition. However, problem definition is likely to be a matter of perspective, or a matter of how each person involved ‘frames’ the problem. Differing frames are inevitable when participants bring their differing expertise and experience to a problem. Methods and processes to support co-creation, then, need to manage the coming together of people with differing ways of framing the problem, so participants can contribute to joint problem definition.

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