## 7 The Decision Support System  
After presenting the results to the managers of TE-Logistics, the aim of using the potential of the model-based planning approach to support operational planners in their transshipment decisions was expressed. The next step was to develop and provide a decision support system (DSS). To design the future process and tool, we organized various workshops to collect the requirements and ideas of the planners and management. The DSS should be implemented in Python, depending on the internal approval processes for IT systems. Information is provided to the planners via Microsoft Excel, as the planners are familiar with its functionality. In addition, requirements were identified by TE-Logistics that a comprehensive DSS should fulfill. Compared to the MILP and rule-based heuristic algorithm, these requirements represent additional restrictions for the resulting DSS. Requirement (R.1). An estimate of the capacity utilization or the free storage locations in the network should be made daily by the planner, as the dimensions of the prototype parts and the storage areas in the system are not known. Only the planner has an overview of free storage spaces in the internal and external warehouse and knows the dimensions of the prototype parts. Requirement (R.2). Decisions made by the DSS do not have to be adopted by the planner. If the planner decides against implementing the recommendation, this decision should be taken into account for future decision support. A distinction must be made as to whether a transshipment was rejected due to short-term restrictions such as limited warehouse, employee, or vehicle capacities or due to strategic company policy decisions, such as ensuring a minimum waiting time for pick up special parts when ordering. Accordingly, planners should not be repeatedly confronted with transshipment proposals that have been determined by strategic decisions. For this reason, long-term decisions should be adopted and retained by the system for decision support. Requirement (R.3). The data from ERP should be forwarded to the DSS without manual effort. We therefore have stored the required data in the form of stock levels in a data warehouse, from where it can be imported into the DSS. The data are updated every night in order to process the latest information. In addition, the planner has the option of manually updating the ERP data in order to make it available to the DSS. Requirement (R.4). A user-friendly interface for the decision support is required. A clear interface should improve user acceptance of the system. Based on R.2, the planner is provided with various filter options for decision support. Accordingly, it should be possible to hide parts that should not be transshipped due to previous strategic decisions. Requirement (R.5). Various key figures should provide planners and management with an overview of the distribution of parts across the warehouses. Based on the results of the rule-based heuristic algorithm, which led to the optimum solution, the decision rules from Section 6.3 are introduced for the future transshipment decision process. A suitable DSS for the planner was developed according to the decision rules. The transshipment decision process is shown in Figure 10.  
Figure 10 shows that the planner receives the information on demand on a daily basis. The planner then checks whether reactive transshipments are necessary to satisfy the demand. If the demanded parts for assembly are in the external warehouse, the planner must react to this and order transport from the LSP. The process of transshipment of incoming parts in the hub has been adopted identically to the decision rules from Figure 9.  
According to the decision rules, proactive transshipments only occur if some parts have to be transshipped reactively. To support the decision on proactive transshipments, the planner receives a list of parts for which a transshipment leads to a reduction in the total sum of approximated future transshipment costs (see Section 4.3 Formula (4)).