Managing Customized and Profitable Product Portfolios Using Advanced Analytics

Due to heterogeneous and volatile customer requirements as well as a growing demand for individualized products, companies nowadays face a highly uncertain environment. As a consequence, the number of product variants offered has increased drastically in recent years and across all industries. That way, the complexity of the product portfolio increased, too. Due to this complexity, internal costs rise and often outweigh possible sales revenues. Under these circumstances, to satisfy various customer requirements and to keep profitability high, a dynamic optimization of the product portfolio is necessary. Existing literature discusses the topic of configuration management for product portfolios regarding diverse circumstances. While current research focuses on the tracking of costs related to configuration changes either while they occur or retrospectively, no approach succeeds in cost and demand prediction. In this paper, the topics of product portfolio management and advanced analytics are combined to overcome the limitation of retrospective modeling. A concept for a methodology to dynamically optimize the product portfolio during the use phase is suggested. Moreover, the methodology aims at predicting the optimal portfolio configuration using real-time data and advanced analytics. That way, customized and profitable product portfolios are realized efficiently.