Value Stream Management (VSM) is a business methodology that focuses on optimizing the flow of materials and information across an organization and beyond to deliver maximum value to customers. It originated from lean manufacturing principles but has been adapted and applied in various domains, such as logistics and administration. To address some weaknesses of the conventional methodology and utilize the potential of increasing digitalization in supply chains in general and companies in particular, various studies explored the targeted application of modern technologies. A common approach in recent studies is to use a digital representation of the value stream, which is dynamically adjusted through continuous processing of operational business data. As reasoned by several studies, the application of data-driven techniques on current data and historical data in the areas of VSM offers several benefits and opens new opportunities in production and logistics management, such as real- time monitoring, early warning-system, enhanced decision-making, predictive analytics, discrete simulation and further ones. Combining VSM with Data Science techniques presents a synergy for organizations aiming to enhance efficiency and maximize value delivery. VSM provides a structured approach to visualizing and optimizing value streams, while Data Science techniques provide the means to gather and analyze big amounts of business data for improving and decision-making. By the present paper, the combined application of VSM and Data Science is investigated, aiming at the provision of an operation framework, which links the various elements of both domains.