Data migration plays a crucial role in the implementation of ERP. Migration scenarios can be quite complex and prolonged, requiring significant resources and a high level of expertise from organization personnel. Inadequate assessment of available resources may lead to a substantial increase in costs and disruption of the planned timelines for the launch of the ERP system. However, the complexity of migration scenarios is often underestimated. The majority of existing research primarily focuses on the technical aspects of data migration, while conceptual elements, such as the relationship between data migration and business processes, remain insufficiently explored. The aim of the study. This article aims to develop a data migration model that considers the interaction between business processes and data during the ERP system implementation, with the goal of enhancing the effectiveness of migration projects and minimizing risks. Materials and methods. The study employs algorithmic modeling techniques and Business Process Model and Notation (BPMN) to create an incremental data migration strategy. Results. The outcome of the research is a data migration model that reflects the interrelationship between data and business proces-ses. This model includes the definition of migration states and transitions between them, necessary parameters and variables that reflect the involvement of stakeholders at various stages of migration, and the execution of relevant tasks to ensure the data migration process. The model also establishes key performance indicators that enable more accurate assessment of risks and resources required for the successful completion of migration. Conclusion. The proposed model can serve as a foundation for effective planning of data migration within the framework of ERP system implementation, which is a requisite condition for achieving business objectives and enhancing operational efficiency in organizations.
Loginovskiy et al. (Wed,) studied this question.