The order processing strategy directly influences the economic and logistic objectives of manufacturing companies. In industrial practice, the order processing strategy is usually chosen based on a few primarily qualitative decision criteria or employees’ experience. The increasingly volatile markets require a differentiated decision of the order processing strategy for each product and a continuous review of the decisions made. The high number of factors influencing the decision of order processing strategy and a wide range of products offered by manufacturing companies make it impossible to manually make a fast and at the same time holistic decision. The digitalization and the increasing availability of data and its quality provide the basis for developing a decision support system. This paper presents an approach for a data based analysis of order processing strategies. As logistic models reflect the interdependencies of conflicting economic and logistic objectives, they are applied to derive the costs of the strategies based on desired adherence to the delivery time and the desired service level of the finished goods store. In addition to the description of the procedure for comparing different order processing strategies, the transfer of the theoretical model into a software demonstrator is outlined. A case study is presented to show the practicality of the proposed approach.