DECLARATION 2- PUBLICATIONS
2.4 Systems thinking theoretical and conceptual framework
2.4.4 Systems theory modelling framework
This section outlines symbols and conventions that are used in systems theory models. In practice, systems thinking has been applied in form of causal loop diagrams, to reveal cause and effect interrelationships between systems so as to help in directing efforts and/or resources to appropriate areas. The causal loop diagrams serve as statements of cause and effect. The causal loop models must be chosen so that they are able to predict the characteristic behavior or pattern of the system [28], [29], [36], [41].
Dynamic systems are often characterized by attributes such as compensating loops, reinforcing loops, balancing feedback (stability through self-correction), delays and archetypes [26], [28].
These attributes can best be explained in terms of dynamic system behavior as alluded to in [28].
First, a compensating feedback refers to strategies or interventions that result in system responses that counteract the intended benefits of the strategies [28]. For example, in a deregulated electricity market, the increase in power system reliability can result in increase in the number of satisfied customers, which in turn will exert pressure on system capacity and operating contingency [26], [2]. In this case, the capacity constraint tends to counteract the intended purpose of improvement of reliability.
Second, a reinforcing feedback system refers to a loop that describes how small inputs (actions) produce amplified results, as is the case when a few satisfied customers spread the news, with their word of mouth, which results in more customers getting (buying) the product [28].
Third, a balancing feedback stands for constraints imposed by reinforcing processes as they seek stability through self-correction [28]. An example of a reinforcing process is the component aging. This is typified when asset managers carry out asset renewal or maintenance processes to improve the asset condition, but the aging process tends to degrade the system [26].
Fourth, a delay can be imposed on the system either due to decision time-lags or when the effect of one variable on another is not immediately evident. In a study from the agricultural sector, a compelling example of a delay is shown when elimination of one pest, hoped to eradicate the crop damage problem, produces momentary pest control effects [40]. In this case, the pest controllers did not know that the pest that was eradicated provided a biological control of another, more dangerous type of pest. In the absence of a predator to keep the population of the deadlier pest under control, the later pest multiplied to uncontrollable proportions so that the crop damage caused by the later pest was greater than that caused by the former one. This was evident after a number of years had passed. Another example of delay often occurs when power utilities outsource refurbishment works, but the impact of the outsourcing action on the retention of maintenance skills only becomes evident after a long time. Another example of the delayed effect is when a firm retrenched its staff in order to reduce costs, but later on it turned out that the action resulted in irreversible loss of technical skills, thereby forcing the organization to hire consultants at a higher cost than before the retrenchment time [25].
Fifth, archetypes are generic system traits or patterns that tend to occur at different hierarchies (levels) of the system [28], [42]. Archetypes can be in form of very well-known constraints (limitations) to company growth or a phenomenon, which can be used to provide insights for improvement of systems. For example, asset managers can deal with the limitations to growth by eliminating them (the limitations), if possible [28]. For a phenomenon like sub-contracting of maintenance (technical) work, the revelation that unbalanced outsourcing can lead to loss of vital
skills provides the managers with leverage (motivation) for instituting changes in the AM strategies [25].
Figure 2-4 illustrates how causal loop diagrams can be employed to represent causal typologies (relationships). The figure shows the cause and effect relationships existing in the process of outsourcing of maintenance works.
: Reinforcing feedback loop s
s
s
o
s s
Host institution’s focus on other/core activities
Host institution’s asset condition
Host institution’s financial returns Outsourced
maintenance works
Host institution’s maintenance skills
Outsourced contractor’s maintenance activities
Outsourced contractor’s financial
returns
s B
R R
s
s
≡ : Delay
B R s ≡
o ≡
: Amplification : Attenuation +
- : Balancing feedback loop
Key
Figure 2-4: Symbols and conventions used in causal loop diagrams
The symbols and conventions that apply to causal loop diagrams (Figure 2-4) are described as follows:
1) A ‘+ or S’ sign at an arrow head can be used to show that when an independent variable (at the beginning of the arrow) changes, the value of the dependent variable (where the arrow points) will be higher than the value it had before the input from the independent variable. Alternatively, these symbols represent the amplification effect.
2) A ‘– or O’ sign at the arrow head indicates that when an independent variable changes, the value of the dependent variable will be less than what it was before the input from the independent variable. In other ways, these symbols stand for the attenuation effect.
3) A cross-hatch or valve symbol stands for a delay.
4) The R symbol with a curved arrow and the B symbol with a curved arrow represent a reinforcing and balanced (compensating) feedback loop, respectively.
Figure 2-4 indicates that outsourced maintenance works increase the host institution’s focus on core activities, which in turn reduces the host institution’s maintenance skills. As the host institution’s maintenance skills increase, it improves the asset condition, financial returns and the amount of outsourced maintenance work-load. In addition, as the host institution’s maintenance skills increase, the outsourced contractor’s maintenance activities will reduce. On the other hand, as the activities increase, the contractor’s financial returns will increase, thereby raising the potential for more outsourced maintenance works.
In systems theory, the validity of the chosen model is judged by the ability of causal relationships to determine dynamic rather than detail complexity [28], [42]. Once the causality has been established, systems modelers need to develop a dynamic hypothesis, that is, a theory describing how the problem propagated [41]. The dynamic hypothesis can be applied to develop modelling equations that can be used for simulation studies.