Increasingly dynamic markets, fast paced technological changes, and anticipated high levels of flexibility and reliability make it increasingly difficult to stay competitive on global markets. Observations of inventory constitute an important lever to increase a company’s performance and success, due to the fact that inventory management decisions directly influence logistics performance measures like delivery reliability, customer satisfaction, and capital commitment costs. In the course of this thesis, inventory management of HOERBIGER was analysed. Due to the mentioned dynamic markets, HOERBIGER’s customer demands are strongly fluctuating and diversified and lead to a high-mix low-volume environment. This situation increases the challenge of covering customer demands on time while simultaneously keeping capital commitment costs at a moderate level. Considering the company’s strategic goals, this thesis focuses on how to balance the inventory key success factors, service level, and costs, to find an appropriate position within those targets. The theoretical part of this thesis focuses on Supply Chain Management, inventory management, basic terms and inventory optimization techniques. The practical part covers the development of an optimized inventory management concept based on target service levels. This concept is built upon a CUBE classification method, which allows a detailed differentiation of predefined material characteristics. Dependent on these attributes, target service levels are defined to form the foundation of calculating specific disposition parameters in order to optimize disposition activities. The applications of advanced service level calculations instead of traditional formulas lead to precise results regarding the required safety stock level. Balancing the safety stock level directly influences the average inventory level and hence the capital commitment costs. As a result, the development of this CUBE model, with its underlying logic, allows differing between certain material indicators, defining fitting disposition parameters, and reacting on specific aspects. Applied simulations and their results showed practical applicability, realistic outputs, potential cost savings, and the supportiveness for responsible employees in their daily business as well as for future inventory decisions.