Value Based Order Prioritizing in Production Control – Integrating Customer Value Management into the Logistics Goal-setting

INTRODUCTION Customer orders in international supply networks can have different importance due to e.g. various order sizes or customer values (Pardoe, Stone 2005). Thus, customer orders should be assessed and treated individually in order to distinct between more or less profitable ones, as creating superior customer value is a key element for companies' suc-This concept explicitly focuses on the financial impact of a specific customer order and analyzes the corresponding customer value (Stirling 2000). It aims for a maximum lifetime profit from the entire customer base (Pease 2001). However, by implementing the CVM, the logistics goals of a system might be affected (Lummus, Vokurka 1999, Woodruff 1997). For example, if more important orders are prioritized over less important ones, the overall due date reliability of the company is likely to decrease as the prioritized orders interfere with the planned production sequence (Nyhuis, Wiendahl 2008). In consequence, the CVM has to be integrated with the logistics goal-setting in order to ensure both: matching logistics goals as well as prioritizing orders due to their financial importance (Martin 2005). Current approaches of order prioritization do not integrate logistics goals (e.g. high due date reliability or high machinery utilization (Nyhuis, Wiendahl 2008)) with financial goals obtained by the CVM (maximum lifetime profit from the entire customer base (Pease 2001)). Hence, a comparability and prioritization for balancing different customer orders with respect to logistics and financial requirements is not possible. Therefore, the paper aims to develop a solution, which incorporates the financial and the logistics perspective by combining CVM and production control methods. One approach in production logistics to deal with this challenge is the so-called autonomous product construction cycle (APCC). It applies the idea of autonomously acting smart objects, which are able to route their way through a production process according to their goals (Windt, Jeken 2009). The smart objects decide at each step of production. The idea is to base the decision not only on logistics goals but also on the customer value obtained by applying the CVM. Thus, the logistics goal-setting of each object can be weighted according to the specific customer order's value (Mentzer et al. 2001). The overarching idea of this paper is to develop a prioritizing model for balancing logistics and financial requirements of customer orders in production control in order to rank different orders based on their importance. Thus, the aims are threefold: Firstly, logistics goals, financial goals, …