Anthony King M5.3 Systems Thinking and Complexity
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Dec 6, 2023
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Module 5.3: Systems Thinking and Complexity
Anthony King
College of Aeronautics, Embry-Riddle Aeronautical University
SYSE 515: Math Applications in Systems Engineering
Federica Robinson-Bryant Instructor
November 18, 2023
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Module 5.3: Systems Thinking and Complexity
After reviewing Sterman’s and Gardner’s articles, I have gathered a list of takeaways about systems thinking and complex systems. The takeaways are:
Role of Feedback Loops:
The Beer Game vividly illustrates the critical role of feedback loops in complex systems. Delays and distortions in information flow among players result in amplified oscillations and the bullwhip effect. Managing feedback loops is essential to prevent unintended consequences and systemic fluctuations (Gardner, n.d.).
Tools of System Dynamics:
The Beer Game underscores the dynamic nature of complex systems. Small changes or decisions in one part of the system can cascade into significant
downstream effects, impacting the entire system. It stresses the importance of considering
long-term consequences and understanding how system components are interconnected (Gardner, n.d.).
Importance of Collaboration and Communication:
Effective collaboration and communication are highlighted in the game. Players must share information, coordinate actions, and align decisions to optimize system performance. Insufficient communication and coordination can lead to suboptimal outcomes and exacerbate systemic issues (Gardner, n.d.).
Causal Loop Diagrams (CLDs):
Sterman’s article introduces the utility of causal loop diagrams as a visual tool for understanding and analyzing complex systems. CLDs aid in identifying feedback loops and causal relationships, empowering stakeholders to develop a comprehensive understanding and make well-informed decisions (Sterman, 2001).
Systemic Thinking:
Both articles underscore the necessity of systemic thinking when addressing complex problems. This approach involves understanding the
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interdependencies, interactions, and structures within a system. It requires considering the
broader context, anticipating unintended consequences, and identifying leverage points for positive change.
Learning and Adaptation:
The Beer Game serves as a valuable learning experience, illustrating the challenges of managing complex systems. It emphasizes the importance of
continuous learning, adaptation, and the ability to respond to changing conditions. Participants, through reflection on feedback and adjustment of strategies, can enhance their understanding of the system and make more informed decisions (Gardner, n.d.).
The CLD described in the Supply Chain Systems Thinking video helped me understand that a new product’s demand is very unpredictable making forecast accuracy to decrease resulting in poor service levels. This makes the customer unhappy and affects the demand for the
product, which would start a decline in revenue and profit. This then forces higher inventory results, costs, and obsolescence to put pressure on profits. So, by increasing demand from launching many new products, a company could end up losing revenue and profit.
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A CLD example I discovered to expand my understanding of CLD model is for a pizza restaurant. The example states that a new pizzeria with a focus on home delivery has recently opened. Initially, the demand is moderate, but the pizzeria stands out for its exceptional pizza quality and prompt delivery service. Over time, the establishment gains attention and is featured in a local online food blog, causing a significant surge in pizza orders. Despite the sudden increase in demand, the pizzeria owners hesitate to invest in expanding their delivery and production capacities, including more delivery vehicles and personnel, as well as additional pizza
ovens (Visual Paradigm Online, n.d.).
This reluctance leads to extended delivery times and a higher proportion of undercooked pizzas, resulting in a decline in the number of loyal customers. Consequently, the need for additional investment in both delivery and production capacity diminishes. Surprisingly, the pizzeria owners find themselves content with their decision to postpone additional investments, as it aligns with the current level of demand and prevents unnecessary expenditure (Visual Paradigm Online, n.d.).
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They would need to start their investment in a larger establishment, more ovens, and more staff. If they can start there, they will be able to get more pizzas to the customer at the expected time and the pizzas will return to their high-quality state.
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References
Gardner, D. (n.d.). The Case for Applying Systems Thinking to Global Supply Chain Management. https://img1.wsimg.com/blobby/go/0f9470de-fdd4-4fe9-bbb1-
f03339401181/downloads/Systems%20Thinking%20for%20Supply%20Chain
%20Management%20.pdf?ver=1616785600022
Sterman, J. D. (2001). System Dynamics Modeling: Tools for Learning in a Complex World.
California Management Review, 43
(4), 8-25. https://www.proquest.com/scholarly-
journals/system-dynamics-modeling-tools-learning-complex/docview/216143802/se-2
Visual Paradigm Online. (n.d.). What is a Closed Loop Diagram? (With Examples). https://online.visual-paradigm.com/knowledge/causal-loop-diagram/what-is-causal-loop-
diagram/
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