Using Distance Measures and Cluster Algorithms for Production Logistics-oriented Evaluation of Products and Product Portfolios

Business success is increasingly dependent on portfolio management and assessment through increased individualization of products. Evaluation of product portfolios from the perspective of production logistics offers new valuable insights in addition to existing market-oriented approaches. Regarding product portfolio management, deleting problematic products is often seen as an unfavorable decision, inducing the potential of unnecessarily overloaded and overcomplex product portfolios. This paper presents a product portfolio assessment and management approach based on production-related distance measures to identify and remove logistically problematic products. In addition, proposed distance measures are identified considering their general meaningfulness and usefulness for cluster analysis. Finally, the presented approach is used on an existing production dataset of a global manufacturer, showing the potential of a production logistics-oriented perspective for product portfolio assessment and management.