MINIMIZING RIPPLE EFFECT AND COMPLEXITIES IN A SUPPLY CHAIN

Abstract

The purpose of this project dissertation is to maximize the profits in a supply chain by using risk analysis tools to fulfill the customer demand within the constraints of ripple effect. The research approach used in this project dissertation is a combination of quantitative and qualitative methods. In quantitative analysis, the proposition is to use supply chain analytics tools like Risk analysis with the help of anyLogistix software. For qualitative analysis, we conducted a survey to rate the risk factors on the basis of their ability to create an exceptional impact on a supply chain in case of a rare occurrence of them. The risk analysis confirms the hypothesis that “supply chain analytics when applied to an organization can reduce the impact of the ripple effect”. The findings in the experiments conducted show a negative correlation of the duration of maximum disruption with the worst service level. Beside the service level by products, we have recorded the worst service level, and the worst fulfillment received (on-time) for each trial taken in an experiment, which has provided us with insights in the variation in these values depending on the experiment undertaken. It is difficult to objectively evaluate the effectiveness of the proposed methodology due to the lack of verification of statistical significance of the experimental results. There are very few empirical studies on simulation - based modeling of the ripple effect in a supply chain. The empirical results provide an insight into risk analysis and management in logistics and supply chain. This insight offers practical guidance for developing and deploying risk analysis tools to support efforts in preventing the ripple effect.