Optimizing Operational Efficiency: The Convergence of Sensitivity Analysis and Supply Chain Simulation
Keywords:
Supply Chain Simulation, Sensitivity Analysis, Operational Efficiency, Lead Time, Inventory Management, Demand Variability, Cost Optimization, Performance Metrics, Supply Chain Strategy.Abstract
In today's fast-paced and competitive corporate world, supply chains need to run smoothly in order to stay profitable and keep customers happy. This study looked into how sensitivity analysis and supply chain simulation could be used together to find and fix problems. We created a simulated multi-echelon supply chain model and changed important variables including demand rate, lead time, and transportation cost in a controlled way to see how they affected total operational cost, service level, inventory turnover, and lead time. The results showed that even little adjustments in these variables had a big effect on overall performance. Sensitivity analysis showed which important aspects needed strategic attention, and simulation let us test multiple reaction scenarios without any risk. The integrated approach gave decision-makers useful information that would help them make the supply chain more resilient and responsive. This study showed how important predictive modeling is for making supply chain operations run smoothly and react to changes.
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