Managing Risks in Supply Chains with Digital Twins and Simulation

Disruptive risks in supply chains often cause ripple effect. The ripple effect occurs if a disruption cannot be localized and its effect on network structure and parameters cascades downstream, affecting the logistics system performance.

To handle risk, disruption, and the ripple effect, supply chain managers need to have complete visibility of the complex interdependencies in their networks. The modern techniques of predictive and prescriptive analytics, such as optimization and simulation modeling, are proving to be the only ways capable of achieving this.

In addition, these methods make possible the creation of a supply chain digital twin – a special model that represents the state of the supply chain as it is now, allowing it to be examined for risk resilience.

This paper will define supply chain disruption, discuss what the ripple effect is, show different risk types and mitigation strategies, and explain the supply chain resilience concept. Finally, it will present a methodology to minimize the ripple effect – through the creation of a digital twin and the use of simulation and optimization.

About the Author

Prof. Dr. Dmitry Ivanov is Professor of Supply Chain Management at Berlin School of Economics and Law. He has been teaching and presenting his research for more than 20 years in disciplines related to operations and supply chain management at different universities worldwide. He is leading working groups, tracks and sessions on the Digital Supply Chain, Risk Management and Resilience in global research communities. He is the author of around 300 publications, including research papers in prestigious academic journals and books “Global Supply Chain and Operations Management” and "Structural Dynamics and Resilience in Supply Chain Risk Management".