Leveraging System Dynamics in Supply Chain Planning
Key Takeaways
⇨ Any analytics technique or any analytics jargon, whether it's data science or advanced analytics, is eventually all about leveraging data or information to extract insights and knowledge based on specific techniques.
⇨ However, using defined techniques sometimes leads to challenges or failures when companies try to leverage these algorithms in the real world.
⇨ Some methodologies, like system dynamics simulation modeling, can be leveraged for problems that do not fall within the rigid bounds of a specific approach. The system dynamics approach can be particularly useful in modeling unique and customized inventory management systems.
Any analytics technique or any analytics jargon, whether it's data science or advanced analytics, is eventually all about leveraging data or information to extract insights and knowledge based on specific techniques. However, using defined techniques sometimes leads to challenges or failures when companies try to leverage these algorithms in the real world. The reason we cannot translate a significant amount of academic work into the world of business at a high level can be put into two categories. First, many of these technologies and cutting-edge research do not have any immediate application in the industry. The second category of reason can be defined by saying that in academic environments, those who experiment with these algorithms typically experiment with problems that are a very good fit for the specific algorithm being leveraged by them. However, some methodologies, like system dynamics simulation modeling, can be leveraged for problems that do not fall within the rigid bounds of a specific approach. The system dynamics approach can be particularly useful in modeling unique and customized inventory management systems.
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