We uncover methodological principles of data-driven disruption risk management and propose a vision of digital supply chain (SC) twins as part of a generalized design of a decision-support system with integrated data-driven analytical models. Particularly, we show which risk data is needed in model-based decision-making support in SC disruption management, and how to integrate this data in simulation-optimization models in order to improve the quality of proactive resilient network design, reactive real-time disruption control, and performance impact assessments. With the results of this study, we contribute to the research and practice of SC disruption risk management by enhancing decision-makers’ understanding of the value and use of harnessing risk data for predictive and reactive decisions. The methodological principles and generalized design of a decision-support system based on the digital twin principles can potentially enhance research on proactive and reactive resilience strategies and contingency plans by using the advantages of SC visibility, historical disruption data analysis, and real-time disruption data to ensure business continuity in global companies. The findings presented can also guide firms in properly maintaining data for model-based decision-making support and highlight potentials of transition from offline to online simulation and optimization. Relying on offline simulation only and ignoring accurate data on supplier and route disruptions, advanced supply signal recognition, and real-time disruption detection can result in misleading disruption scenarios for SC resilience analysis and late or inefficient deployment of recovery policies.
Prof. Dr. Dr. habil. Dmitry Ivanov is professor of Supply Chain Management at Berlin School of Economics and Law (HWR Berlin), deputy director and executive board member of Institute for Logistics (IfL) at HWR Berlin, and director of master program in Global Supply Chain and Operations Management at HWR Berlin.
He has been teaching classes for more than 20 years in operations management, supply chain management, logistics, management information systems, and strategic management at undergraduate, master’s, PhD, and executive MBA levels at different universities worldwide in English, German, and Russian. He has given guest lectures, presented scholarly papers and has been a visiting professor at numerous universities in Asia, Europe and North America.
His research explores supply chain structural dynamics and control, with an emphasis on global supply chain design with disruption risks, optimal control and scheduling in Industry 4.0 systems, supply chain simulation and risk analytics in the digital era. He is co-author of structural dynamics control methods for supply chain management. His academic background includes industrial engineering and management, operations research, and applied control theory. He studied industrial engineering and production management in St. Petersburg and Chemnitz and graduated with honors. He gained his PhD (Dr.rer.pol.), Doctor of Science (ScD), and Habilitation degrees in 2006 (TU Chemnitz), 2008 (FINEC St. Petersburg), and 2011 (TU Chemnitz) respectively. Prior to becoming an academic, he was mainly engaged in industry and consulting, especially for process optimization in manufacturing and logistics and ERP systems. His practical expertise includes numerous projects on the application of operations research and process optimization methods to operations design, logistics, scheduling and supply chain optimization. Prior to joining the Berlin School of Economics and Law, he was professor and acting chair of Operations Management at University of Hamburg.
More info about Prof. Dmitry Ivanov