Practical System Dynamics Modeling

[@ProfeARios]

Thank you for sharing. Greetings from Panama 🇵🇦

[@ZhouYiling-v3t]

Learned a lot, it is very clear and helpful, thanks sir

[@womenfitness_helper]

Excellent sir

[@thomasjones9394]

Thank you. I thought system mapping started by identifying the variables and then the relationships between them.

[@ivan.taylor]

Hi Thomas, Here is something I wrote recently that might help you System Dynamics Methodology Two primary tools express the complexity of an SD model: a causal loop diagram, which qualitatively represents the feedback loops in the model, and a stock and flow diagram, which is used to develop the quantitative model using explicit parameters and equations. Causal loop diagrams (CLDs) are used to visualise the feedback structure of systems by representing the relationships between endogenous and exogenous variables. These variables are connected by arrows indicating either positive or negative polarity. A positive polarity means that the two variables move in the same direction-if one increases, the other also increases (or decreases together). Conversely, negative polarity means the variables move in opposite directions-if one increases, the other decreases. By tracing the connections between variables, feedback loops can be identified. Reinforcing loops (R) are formed when the feedback intensifies changes in the system, either driving exponential growth or decline. On the other hand, balancing loops (B) stabilise the system by counteracting changes, pushing the system toward equilibrium. The interplay of these reinforcing and balancing loops helps explain complex dynamic behaviour in systems, allowing for the identification of key leverage points for intervention or improvement. In a Stock and Flow Diagram (SFD), stocks represent accumulations or quantities within the system, such as resources, populations, or materials. These core elements define the system's state at any given time. Stocks are affected by flows, increasing or decreasing their levels over time. Flows represent the rates at which stocks change. Flows can be inflows, adding to a stock, or outflows, depleting it. Each flow is governed by an equation that defines the rate of change over time, often influenced by other variables in the system. In addition to stocks and flows, two other essential building blocks of Stock and Flow Diagrams are connectors and converters, which work together to create a dynamic and interconnected system. Connectors are the links between different elements in the model. They transmit information or values between stocks, flows, and converters, creating dependencies between them. Connectors help establish the relationships between different components, allowing the model to capture feedback loops and complex interactions. Converters are used to transform or calculate values that affect flows and connectors. They typically represent variables or constants that provide input to the system, such as conversion rates, multipliers, or external factors. Converters simplify complex equations and allow for easy adjustments of parameters in the model. Together, these four building blocks-stocks, flows, connectors, and converters-interact to simulate the system's behaviour over time. Stocks accumulate or deplete based on flows, which are, in turn, influenced by variables transmitted through connectors and calculated by converters. This structure enables System Dynamics models to capture the complex feedback and dynamic behaviour inherent in real-world systems. System Dynamics (SD) model development typically follows a systematic process identifying the problem or system to be modelled. This is followed by constructing causal loop diagrams (CLDs) to visualise the feedback loops and interrelationships between variables qualitatively. Once the qualitative relationships are understood, the model transitions to a more quantitative approach by developing stock and flow diagrams. These diagrams formalise the system's dynamics by defining stocks (representing accumulations of materials) and flows (representing processes that affect these stocks). In this stage, parameters are assigned, and differential equations are formulated to capture the system's behaviour over time. The model is then calibrated with real-world data and tested for accuracy through validation processes, which may involve stakeholder feedback, sensitivity testing, and comparison to empirical results. This iterative development process ensures the model reflects the system and helps explore policy options and decision-making scenarios.

[@lenmalczynski9893]

Ivan, could you explain why you use system dynamics instead of Excel? I understand that Excel helps with parameter estimation for historic data. You could use Excel to run scenarios into the future.

[@ivan.taylor]

Yes, I sometimes do use Excel for the projections. Sometimes it is easier to compare different future scenarios in Vensim. Thanks for asking. I should make it clearer.

[@ivan.taylor]

Hello Len, I just saw this now. I could run scenarios into the future with Excel, but there is a slight complication that is unfortunate when you want to show the same parameter in multiple scenarios on the same graph. I will bring this up in future presentations. Thanks for the advice. I hope this helps. Ivan

[@renanrodrigues8984]

Thanks from a student in Brazil

[@ivan.taylor]

You're welcome