CLDs represent a system in three basic elements: boxes, connections, and feedback loops. The boxes, or nodes, represent variables in the system; these can be anything as long it makes sense to think of them going up or down over some scale. The connections, or edges, represent causal influence, from one node to the other; either positive (i.e. they increase or decrease together) or negative (i.e. they change in opposite directions, if one goes up, the other goes down, and vice versa). So far, fairly similar to Fuzzy Cognitive Mapping or Participatory Systems Mapping. The third element is what makes CLDs more unique. The maps always show and focus on feedback loops, both in the construction of the map and in its visualisation. Loops are made conspicuous by the use of curved arrows to create circles. The loops are also sometimes colour coded to highlight them or are annotated with small arrows and ‘+’ or ‘-’ symbols to highlight if they are reinforcing (positive) or balancing (negative) feedback loops.
The feedback loops are usually focused around a ‘core system engine’, which is a set of nodes that are the core of the system. These are often visualised more prominently than other nodes in the map. The feedbacks strongly hint at dynamics in the system. It is common to use the maps to think at a slightly higher level than individual nodes and edges, bringing together the handful of feedbacks in the system to think about how these might play out together. The focus on feedbacks means the CLDs are a relatively disciplined way of looking at a system, which places the existence and effects of feedbacks at its core. It is common to see both simple (perhaps five or ten nodes) and more complex CLDs (dozens and dozens of nodes).
Let’s look at some examples. Figure 4.1 shows an example of a simple CLD. We can see how nodes and edges are connected with positive and negative connections, and how the feedback loops of ‘revenue generation’, ‘organizational legitimacy’, and ‘social action’ are emphasised through their positioning, and additional annotation. The ‘R1’, ‘R2’, and ‘B1’ refer to reinforcing and balancing loops.
The next example, shown in Fig. 4.2, is the well-known and much larger CLD of the obesity system in the UK. Here, nodes are in boxes and colour coded by theme, and the connections are shown with solid lines (positive connection) and dotted lines (negative connection). The core engine of ‘energy balance’ and its feedbacks are highlighted in the centre.
CLDs are used in a variety of ways. Most fundamentally, as with many methods in this book, they are a way of surfacing, visualising, and exploring mental models. Exploration of the full map is done in many ways, but qualitative analysis of the core engine and feedback loops is a common focus. CLDs are often a precursor to System Dynamics models (Chapter 8); used to begin the modelling process in an intuitive way, before the conversion to stock and flow diagrams and differential equations.
The maps can be built from all types of information, and in participatory modes, and the mix between these is fairly even in the literature. There is a lot of variety in the ways they are built and the exact purpose they are put to. However, there is less variety in what is actually constructed; the use of clear variables, arrows for influence, and focus on feedbacks is consistent. There is a lot of quite prescriptive guidance available, which helps to maintain this consistency. However, it is worth noting, there does appear to be a divide between those who use CLDs as a stand-alone method and those that use them as a stepping-stone to System Dynamics. The practice of each group does tend to have subtle differences, with the former being more inclusive and flexible in their use of the method, and the latter following clearer rules about how to develop a map. There is a little variety in the terminology used to describe CLDs; they are often referred to as ‘influence diagrams’, or simply ‘system maps’. There is also a small group of papers which use the term ‘Participatory Systems Mapping’ to refer to a participatory CLD approach (e.g. Lopes & Videira, 2016).