System Engineering (SE) and Model Based System Engineering (MBSE) are increasingly seen as essential for addressing the complexities of modern products and associated processes (design, production, support, exploitation, upgrade, renewal, recycling) in a volatile environment with many economic, political, regulation and environmental issues. Their aim is to enhance understanding of system architectures, requirements, and interdependencies, facilitating informed decision-making and collaboration among multidisciplinary teams. SE and MBSE also help to reduce costs and risks by identifying issues early in development, promoting agility through the exploration of alternative solutions, and ensuring compliance with industry standards. However, deploying SE and MBSE faces challenges similar to those encountered with computer-aided design and Product Lifecycle Management (PLM) two decades ago, including processes, applications, and technological heterogeneity. Many organizations have developed their own MBSE frameworks, languages, and tools, preventing usage of external open standards shared by a community of practice. Critics argue that existing languages and tools are too complex and time-consuming, leading to calls for new standards. This further complicates the implementation of digital continuity in an increasingly complex and digitally connected environment. Additionally, the rise of cloud technology, data-related paradigms, and emerging Artificial Intelligence (AI) technologies add to the complexity of decision-making in this context. This paper presents a holistic approach for preparing and building the continuous operational interoperability required in a Common Working Environment (CWE) for SE and MBSE in a PLM context.