How is the systems dynamics model to leverage points used in decision making?
In systems thinking and decision making, a leverage point can signify how much a change affects the system. If a change effort affects the system in a small way, then this is a low leverage point. However, if a change effort affects the system in a large way, then it is a high leverage point.
If you think about it, you are already familiar with leverage points in some form or fashion. Nam C. Nguyen and Ockie J.H. Bosch define an example for leverage points, especially in systems thinking. Nguyen (2013) explains, “Leverage points exist in all systems. For instance, a nation’s economy is a social system and its interest rate is an economical leverage point because a small change can influence the country’s entire socio-economic system.” (Nguyen, 2013).
Another example of a leverage point and the effect it has on systems is that of a vehicle. You can change the radio in your vehicle, and it won’t have an effect on the entire car and how it functions, it only affects the user. However, if you were to remove a spark plug from that vehicle it will then have a critical effect on the entire system and the way it functions.
Systems dynamics is the practice of using technology or data to gather information about all of the parts in a system and examining how they influence one another over time within a system. It looks more at a pattern in the big picture rather than each small detail of all the subsystems. Being able to look at the systems, dynamics, and data can assist in making a decision.
Referring to the vehicle example on leverage points, you would be able to use the knowledge you have gained about how a vehicle functions to make a decision to not remove a spark plug. Another instance would be if you have a vehicle that takes regular gasoline you would use knowledge of your vehicle’s system to determine that the best decision is to not put diesel fuel into the fuel tank.
In a similar fashion, you would look at the system dynamics of an organization in order to frame a decision on what changes to make and examine what effect the changes will have over time. Small things can be a stimulant to start the snowball of bigger problems.
In systems dynamics, there is what is known as a feedback loop. Sylvia Schweiger, Hendrik Stouten, and Inge L. Bleijenbergh explain the feedback loop in system dynamics. Schweiger et al (2018) state, “there are two kinds of feedback loops: reinforcing (positive feedback) and balancing (negative feedback). The ability to visualize the data of feedback loops in system dynamics provides a perspective of the behavior or reaction over time.” (Schweiger et al., 2018).
In conclusion, feedback, observation over time, understanding of system dynamics, and various leverage points that pinpoint a change and its effects can greatly benefit organizational learning at the individual, group, and organizational levels. These instances can provide a much broader picture in which to reduce resistance to change by being able to pinpoint where the resistance is originating or why. Knowing system dynamics, decision-making, and leverage points can also benefit organizational learning because it will allow the organization to determine what skills need to be developed in order to effectively and efficiently meet the needs of each situation.
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