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System Dynamics
System Thinking/System Dynamics is a methodology for studying and managing complex systems over time. It is based on the knowledge that decisions are not made and actions are not taken in isolation but rather an action in any part of the organization can have positive and negative impacts on the system as a whole. Often these impacts are non-intuitive and not immediately realized. Because of the potential unintended consequences and the delay in feedback from our decisions, a methodology for representing and modeling the system in a holistic manner is necessary. From a systems’ perspective, it is not only decisions, but the organization’s structure interacting with those decisions, that drive the system’s behavior. Thus, the organization’s structure creates events or problems that prevent the organization from realizing its maximum performance. To make significant improvements and lasting change in an organization, changes must be made at the structural level, often to very non-intuitive leverage points. The systems thinking approach examines the organization’s structure and with the use of system dynamics modeling enables the development of robust strategies that allows a system to reach its full potential.
The tools of systems thinking lead the organization from the identification of the key issues, through the determination of structural relationships, to the development of tested action plans that can be implemented to change the organization’s performance. Figure 1 illustrates this roadmap and the approach which will be used by ProNamix during a project. A description of the primary tools is described below.
Causal Loop Diagramming is a core tool for exploring the structural interrelationships between the parts of a system. It captures graphically how each factor or variable in a system influences the others. A variable is defined as anything that can increase or decrease over time in the system. The variables can have either a definitive measurement scale (often captured as a metric) such as the “unemployment rate,” or they can have a subjective scale such as “employee morale.” Arrows are used to connect the variables and to indicate the direction of the influence together with a '+' or '-' sign to show whether an increase in the one variable leads to an increase or decrease in the other.
Causal Loop diagrams represent the system in the form of feedback loops. There are two generic types of feedback loops; reinforcing and balancing. Reinforcing feedback loops compound change with even more change. They result in either a vicious or virtuous cycle and are often referred to as snowball or bandwagon effects. They are responsible for the exponential growth or decline of various metrics. Common reinforcing loops include compound interest and population growth. Balancing loops on the other hand maintain balance in a system and negate a metric’s change in one direction by pushing the system to drive the metric in the opposite direction. The laws of supply and demand are both balancing loops.
System Archetypes are patterns of system structure that are routinely encountered when exploring the interrelationships between system elements. Although not all system behavior can be characterized by an archetype, they contain the basic causal loop structures that occur in most systems. Common archetypes that appear most often include “Fixes that Fail,” in which a short-term intervention or “fix” for a problem creates a long-term delayed system effect that exacerbates the original problem, and “Success to the Successful,” in which initially minor successes or mistakes can initiate self-fulfilling prophecies.
Stock and Flow Diagramming is an advanced tool for exploring system interrelationships. The tool underscores the difference between “Stock” variables and their rates of change, or “Flow.” This type of Diagramming is the basis for computer simulation models.
System Dynamics Modeling is a computer simulation that quantifies the relationships of the causal loop diagrams. Because of the complex nature of most systems it is difficult to visually sort through and analyze the behavior of the causal loop diagrams. Using system dynamics software, these relationships can be represented in the form of stock and flow diagrams and simulated. Simulation allows the user to (1) confirm that the structure hypothesized can lead to the observed behavior, (2) identify high-leverage points in the system that remain hidden from non-systems-based methodologies, and (3) test the effects of alternative policies on system performance over time.
Scenario Planning Matrix explores the cross impact of various planning options for identified high-leverage decisions. It allows easy viewing and evaluation of possible “What if” scenarios, aiding in the development of a robust strategy. It is typically used in conjunction with System Dynamics Modeling.
Strategy Matrix is a tool that aids the development of strategic plans. It visually represents the high-leverage decisions and actions that the organization may implement.
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The tools of systems thinking lead the organization from the identification of the key issues, through the determination of structural relationships, to the development of tested action plans that can be implemented to change the organization’s performance. Figure 1 illustrates this roadmap and the approach which will be used by ProNamix during a project. A description of the primary tools is described below.
Figure 1: Systems Thinking Roadmap to Strategy Development: From Issues to Actions
Causal Loop Diagramming is a core tool for exploring the structural interrelationships between the parts of a system. It captures graphically how each factor or variable in a system influences the others. A variable is defined as anything that can increase or decrease over time in the system. The variables can have either a definitive measurement scale (often captured as a metric) such as the “unemployment rate,” or they can have a subjective scale such as “employee morale.” Arrows are used to connect the variables and to indicate the direction of the influence together with a '+' or '-' sign to show whether an increase in the one variable leads to an increase or decrease in the other.
Causal Loop diagrams represent the system in the form of feedback loops. There are two generic types of feedback loops; reinforcing and balancing. Reinforcing feedback loops compound change with even more change. They result in either a vicious or virtuous cycle and are often referred to as snowball or bandwagon effects. They are responsible for the exponential growth or decline of various metrics. Common reinforcing loops include compound interest and population growth. Balancing loops on the other hand maintain balance in a system and negate a metric’s change in one direction by pushing the system to drive the metric in the opposite direction. The laws of supply and demand are both balancing loops.
System Archetypes are patterns of system structure that are routinely encountered when exploring the interrelationships between system elements. Although not all system behavior can be characterized by an archetype, they contain the basic causal loop structures that occur in most systems. Common archetypes that appear most often include “Fixes that Fail,” in which a short-term intervention or “fix” for a problem creates a long-term delayed system effect that exacerbates the original problem, and “Success to the Successful,” in which initially minor successes or mistakes can initiate self-fulfilling prophecies.
Stock and Flow Diagramming is an advanced tool for exploring system interrelationships. The tool underscores the difference between “Stock” variables and their rates of change, or “Flow.” This type of Diagramming is the basis for computer simulation models.
System Dynamics Modeling is a computer simulation that quantifies the relationships of the causal loop diagrams. Because of the complex nature of most systems it is difficult to visually sort through and analyze the behavior of the causal loop diagrams. Using system dynamics software, these relationships can be represented in the form of stock and flow diagrams and simulated. Simulation allows the user to (1) confirm that the structure hypothesized can lead to the observed behavior, (2) identify high-leverage points in the system that remain hidden from non-systems-based methodologies, and (3) test the effects of alternative policies on system performance over time.
Scenario Planning Matrix explores the cross impact of various planning options for identified high-leverage decisions. It allows easy viewing and evaluation of possible “What if” scenarios, aiding in the development of a robust strategy. It is typically used in conjunction with System Dynamics Modeling.
Strategy Matrix is a tool that aids the development of strategic plans. It visually represents the high-leverage decisions and actions that the organization may implement.
Go to: Business Services Business Creation Process Analysis Strategic Marketing Contact
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