Strategische Lagerkapazitätsplanung

Strategische Lagerkapazitätsplanung. Ein Konzept zur stärkeren Integration in den strategischen Supply Chain Planungsprozess am Beispiel der pharmazeutischen Industrie

Researcher:

F. Friemann

Studies indicate that companies that call themselves data-driven exhibit better performance than competitors. For example, in terms of public awareness, Google and Facebook demonstrate that the handling of data in innovative ways makes the behavior of the objects of study more predictable and thus generates competitive advantages. In the area of supply chain planning, the decision support systems are called advanced planning systems (APS). However, planning decisions in practice are often not made in a sufficiently data-driven manner. The reasons for that are manifold. For example, the relevant information might not be available in the right format because the capabilities of today’s information systems were not available at the time when the planning processes were introduced. Strategic planning decisions that are not optimal for this reason may result in long-term negative consequences for the competitiveness of the company. The focus of the thesis is on the improvement of strategic warehouse capacity planning in the context of the research-based pharmaceutical industry. It has been noted that the warehouse capacity planning processes in practice are often conducted decentralized with simple planning models or based on rough assumptions and therefore lead to insufficient results.

The findings are based on a study of 11 of the 20 largest multinational research-based pharmaceutical companies according to sales as well as on an extensive case study with one of these companies. Within the thesis, the state of warehouse capacity planning in the pharmaceutical industry was examined as well as current conditions and future requirements. Based on this, a concept was developed to further integrate the information systems within the company. Specifically, historical operational logistics data will be used in the strategic planning process to a greater extent. Through development and implementation of a procedure and simulation model in collaboration with a case study partner, the practical feasibility of the concept was successfully proven.

Especially in Switzerland, the pharmaceutical industry is of high economic importance. The area of investigation of the thesis is limited to research-based pharmaceutical companies. This is where a capability gap has been found in practice. In contrast to the currently deployed strategic warehouse capacity planning processes in the pharmaceutical industry, this work demonstrates how tactical and operational logistics data can be aggregated in a practical way and used for the strategic planning process in order to lead to better planning results. Increased reliance on data-driven planning and a more effective strategic warehouse capacity planning should improve the relevant logistics key performance indicators within the industry in the long-term.