Causal Loop Diagrams (CLD) represent the influence and feedback of variables around a system. CLD is used to visualise these relationships, to enable a joint understanding of how the variables within a system in question work, and enable analysis of how to improve problems with the system.
CLD uses just a few different symbols, shown below:
This image shows a basic feedback loop. A loop is
created with a number of variables linked by arrows showing
causal relationships between the variables. A loop must be
closed - that is linked all the way round. The loop
on the left describes the feedback between stress and rate of errors of
a human working on a machine. The diagram tells us that
rising stress increases error rate, which in turn increases
stress. The elements of the diagram are:
|
|
This image shows the same causal loop as above, but has introduced a second loop. This new loop says that as the number of errors increases, so does the number of work breaks the operator takes, which in turn reduces the amount of stress. This new loop is a balancing loop as it is self correcting. |
To work out whether a loop is Reinforcing or Balancing, you simply count the number of "-" link identifiers:
If the CLD is more complex and the polarity cannot be easily identified, then the loop should be broken open at any variable and a small change traced around the loop to identify the polarity. In our example above we could break the loop at "Work Breaks": more work breaks > less stress > lower error rate > less work breaks: the loop is balancing as the feedback to the variable "Work Breaks" opposes the original change.
The loop polarity relates to the "gain" of the system, which is the strength of amplification or increase each time we go around the loop. A gain of 2 (a reinforcing loop) would mean that for each cycle around the loop the size of the variables would be doubled. This is therefore an exponential gain loop. A gain of 0.5 (a balancing loop) would mean that the variables would halve, which has a controlling effect around the loop. Using mathematics within CLDs enables analysis of growth / decline of different interconnecting loops, and therefore the expected behaviour of the model. Changes to the model including mitigating variables can then be sized to balance undesired effects in the CLD.
The example on the left shows a CLD for maintaining
an asset with a maintenance resource. The loop is
reinforcing:
So monitoring the system is very important if the asset performance is to remain high. The CLD can help identify what to measure around the system, and also inform what contingency plans will help stabilise the loop. This stabilisation can come from either an external input, or by adding something into the loop to "balance" it. |
|
In order to balance the reinforcing loop we have added a new loop with "contract resource hire". Now when errors increases leading to the time fixing errors also increasing, the adverse effect on planned maintenance resource can be balanced out by contract resource hire. This balancing loop can also be used to reduce resource levels as asset errors continues to fall. |