Data-Driven Supply Chain Management

The supply chains in the pharmaceutical industry are facing increasing complexity due to the steadily rising product and market dynamics. This particularly affects the area of pharmaceutical logistics with its system-critical supply chains, as well as regulatory requirements. Disruptions in supply chains have more severe consequences: If sales forecasts are too low, the necessary goods are lacking. If forecasts are too high, warehouse space is consumed, capital is unnecessarily tied up, and products with short expiration dates are increasingly destroyed.

Although the future cannot be predicted with absolute certainty, reliable and adaptive forecasting models are essential tools for assessing future developments. Therefore, the research project "DaSuMa" focuses on demand forecasting and distribution logistics for pharmaceutical wholesalers in the greater Salzburg area. By incorporating current approaches and methods from the fields of Data Science, Machine Learning, and Data Analytics based on the state of the art, supply chains can be optimized, the digitization of pharmaceutical logistics can be advanced, and thus, the system-critical infrastructure can be stabilized.

Salzburg University of Applied Sciences brings experience and expertise in Data Science and Machine Learning from numerous digitization projects to this research project. The knowledge generated by the project offers opportunities for technology transfer to SMEs and thus contributes to strengthening Salzburg as a business location. Publicly accessible professional events are planned for this purpose. This project is strongly aligned with the research interests and knowledge areas of the "Business Informatics" program, established in 2021, and provides an opportunity to apply current, innovative, and application-oriented research to a concrete problem of the regional economy.