Muhammad Hanafi, MBA, IPU, Chairman of the Professional Council of Metallurgical Engineers (PII) and an expert in system dynamics modeling, shared his insights into applying system dynamics models in policy decision-making during a virtual guest lecture. The lecture, “Application of System Dynamics Modeling in Decision Making,” was delivered to the Blemba 69 IA ITB-HK class at SBM ITB, on Saturday (2/11).
Hanafi emphasized the value of system dynamics models in analyzing complex problems that are difficult to address using traditional policy-making approaches. He explained that these models enable a deeper understanding of the interactions between various system variables, allowing users to predict how changes in one variable impact others.
“System dynamics models help us think systemically and understand the cause-and-effect relationships within a problem,” Muhammad Hanafi stated. “This approach allows us to design policies that are more effective and efficient.”
An MBA and DSM graduate from SBM ITB, Hanafi guided participants through the foundational concepts of system dynamics modeling, including causal loops, stock and flow diagrams, and their practical applications in areas, such as nickel resource management. He highlighted the method’s versatility, explaining that system dynamics models can be applied to analyze various policies, from government regulations to corporate strategies.
The purpose of policy analysis with system dynamics models is to thoroughly understand a system or problem (description); assess the impacts of existing or proposed policies (evaluation); and provide well-informed policy recommendations (prescription). He underscored the importance of accurate and relevant data collection in building effective system dynamics models and the need for critical and creative thinking in designing appropriate model.
Hanafi conducted a live demonstration using Power Sim software to enhance the participants’ comprehension, showcasing how system dynamics models can be practically implemented. The demonstration clearly illustrated the model’s potential to address real-world policy challenges.