From Supply Chain Resilience to Ecosystem Viability: Lessons from and Thinking Beyond the COVID-19 Pandemic
Dmitry Ivanov, Berlin School of Economics and Law, Germany
The Difficult Path to Become Datadriven
Lionel Rigaud, CTO/CEO of TRIMANE and Chief Data Officer at The Blockchain Group, France
From Supply Chain Resilience to Ecosystem Viability: Lessons from and Thinking Beyond the COVID-19 Pandemic
Dmitry Ivanov
Berlin School of Economics and Law
Germany
Brief Bio
Prof. Dr. Dr. habil. Dmitry Ivanov is professor for Supply Chain and Operations Management, deputy director and executive board member of Institute for Logistics (IfL) at Berlin School of Economics and Law (Germany). His main research interests and results span the ripple effect in supply chains, supply chain resilience and viability, smart manufacturing and Industry 4.0, and digital supply chain twins. He gained Dr., Dr. Sc., and Dr. habil. degrees and won several research excellence awards. His research record counts around 360 publications, with more than 110 papers in prestigious academic journals and the leading books “Global Supply Chain and Operations Management” (three editions), “Introduction to Supply Chain Resilience”, „Structural Dynamics and Resilience in Supply Chain Risk Management“, “Scheduling in Industry 4.0 and Cloud Manufacturing”, “Digital Supply Chain” and „Handbook of Ripple Effects in the Supply Chain“. He serves to international research community by leading working groups, tracks and sessions on the Supply Chain Resilience and Digital Supply Chain. He delivered invited plenary, keynote and panel talks at the conferences of INFORMS, IFPR, IFIP, IFAC, DSI and POM. He co-edits International Journal of Integrated Supply Management and is an associate editor of the International Journal of Production Research, International Transactions in Operational Research, and International Journal of Systems Science, and guest editor in many leading international journals such as IISE Transactions, Omega and IJPE. He is Chairman of IFAC TC 5.2 “Manufacturing Modelling for Management and Control” and has been General Conference Chair of 9th IFAC MIM 2019 conference as well as IPC and advisory board member of over 60 international conferences.
Abstract
In this talk, we discuss fundamental theoretical constructs and practical applications to engineer and manage disruption-resistant supply chain networks to mitigate the ripple effects in the context of the COVID-19 pandemic. We collate and review the existing knowledge in modelling the ripple effect in supply chains at different pandemic stages. Subsequently, we debate about extensions of the existing theories and practices of supply chain resilience towards viability. We present the Viable Supply Chain model and associated concepts of ecosystem viability, intertwined supply networks, and reconfigurable supply chains. Finally, we discuss the role of digital supply chain twins and platforms in managing resilience and viability at the times of super disruptions, and project the lessons learned during the COVID-19 pandemic on possible future stressors to supply chains and ecosystems.
The Difficult Path to Become Datadriven
Lionel Rigaud
CTO/CEO of TRIMANE and Chief Data Officer at The Blockchain Group
France
Brief Bio
With an engineering diploma from Sup’Aero, Lionel RIGAUD has specialised in data issues for more than 25 years. He heads TRIMANE, a 100 people strong data intelligence consultancy company he created in 2005. He is also Chief Data Officer of the Blockchain Group since 2021.
Lionel headed for several years a MSC in business intelligence in a French engineering school. He is a guest lecturer in strategy/datascience at the ISAE Supaero. He is also Chairman of the board of Hodosia, a French school for the resiliency of the economic entities.
Abstract
Data is an essential cornerstone of business strategy: more and more companies want to become data-driven. Many theoretical or applied research topics provide methods for setting up projects that allow companies to quickly migrate to a data vision and thus optimize the value of the company. But the transition to all data is a long, painful and complicated process that is difficult to model. Indeed, most of the tools, methods and theories take for granted that the companie’s KPI (Key Performance Indicator) are well defined, accurate and stable, that the data source is correct, that data governance is efficient. Thus in this conference, we are going to focus on the different elements that prevent theoretical visions (even validated by POCs) from going live. We will first present the challenges companies face with data, the different solutions and methods that have been proposed to cope with them, and the different “real life” constraints that render those solutions pretty useless. Finally, we will propose some ideas for research topics to be carried out that could overcome these difficulties.