Decision Making / 6 / 6.9 / 6.9.1

6.9.1 A Critique Of The Use Causal Loop Diagrams

This section is provided for readers who have previous experience with casual loop diagrams or who wish to investigate them further. First-time readers should skip this section, returning later if necessary. The systems thinking/system dynamics methodology described in this chapter is a significant departure from that taught at, say MIT, and as advocated by Sterman (2000) in his comprehensive tome on the subject. The latter is reliant on the development of causal loop diagrams from the earliest stages of conceptualisation, both in the divergent and convergent thinking tasks described above. A considerable part of the systems thinking and system dynamics literature (Goodman, 1989; Kim and Senge 1994, Senge 1990…) advocates the use of causal loop diagrams and high-level systems archetypes, and the Systems Thinker (Kim, et al., 1990) is dedicated to advancing the use of causal loop diagrams. Causal loop diagrams can be useful when used, as conceptualisation tools, particularly in conjunction with stock/flow diagrams to depict the factors which influence flows (rates) or the factors to be considered in the calculation of auxiliary parametric values. Causal loop diagrams suffer from a number of significant deficiencies. Richardson (1986) originally raised a number of concerns about causal loop diagrams. The debate about their use continues.

By themselves causal loop diagrams do not differentiate between stocks (levels) and flows (rates), and totally neglect any consideration of dimensional integrity. For this reason, when causal loop diagrams are used it is strongly suggested they be used in conjunction with stock and flow diagrams. Those who advocate use of causal loop diagrams, particularly during the early stages of problem conceptualisation apparently assume that there is a high degree of familiarity with, or understanding of, the causes underlying extant problems. From the cases studied in Chapters 2 and 3, there was no evidence to support such an assumption. Indeed, there was considerable evidence to suggest that there was little such understanding even amongst those who should have known most about the problem situations. For this reason, and just because causal loop diagramming is popular, does not mean we should assume it represents best practice.

Best practice in causal diagramming is embodied in the form of influence diagram developed by Coyle (1996: 18-83). This claim is not meant to suggest that causal loop diagrams do not have an important role in the analysis of dynamic hypotheses. They do, mainly as a means of summarising the main causal feedbacks. It is argued that those trying to find out about a problem situation would not be equipped to generate such summaries until they have spent considerable effort developing an understanding of the problem as demonstrated in this chapter. They will be unable to do so until they are highly familiar with the problem. That familiarity only comes much later.

A systems archetype, expressed as a causal loop diagram, is a set of dynamic hypotheses about a given problem situation. In order to establish validity of the systems archetype in relation to the problem situation at hand, each separate hypothesis must be validated. As far as IISD is concerned, causal loop diagramming is recommended as a device for summarising major feedback mechanisms, and only when the problem situation is very well understood, after concept mapping or SSM, and influence diagramming have been applied to investigate the problem situation.