FORLOG

BAVARIAN RESEARCH ASSOCIATION FOR SUPRA-ADAPTIVE LOGISTIC SYSTEMS

Logo FORLOG

TransLog

Field of work:

Network Partners

Objectives The logistics challenges for enterprises of the automotive value chains increase and with them the necessity to design supra-adaptive logistics structures. A holistic perspective of these value chains requires a seamless integration of logistics service providers (LSP). The integration of LSP in automotive value chains results from outsourcing of logistics services. Value chains can only be called adaptive if a successful matching of adaptation demands (required by producers) and adaptation capability provided by LSP is achieved. The aim of the sub-project TransLog is to qualify LSP to contribute their part of supra-adaptation in automotive value chains. Therefore, new business models of LSP are to be designed, considering the following objectives: • How should outsourcing relationships between LSP and producers of the automotive industry be designed optimal in respect of depths and breadth to ensure a high level of adaptation? • Which internal structures, services and organisational configurations should LSP provide to realize an optimum of adaptation? • How should the geographical and capacity related mix of resources, interfaces and services of LSP be created to fulfil the adaptation demands of the automotive industry? • Which parameters are necessary for the develop-ment of a systematic, empirically tested know-how database for the optimum usage of LSP in supra-adaptive value chains? Procedure To answer these questions, both primary and secondary data are gathered. A focal significance is given to the empirical survey of primary information, which is the determination of relevant areas in practice. In order to analyze the large spectrum of different peculiarities and require-ments of the actors in logistics outsourcing, expert interviews are conducted with participants of the automotive industry and LSP. Reflecting the adaptation demands of the automotive industry with the status quo of the adaptation capability of LSP, mismatches are identified for deeper analyses as part of TransLog. A clustering of mismatches into strategic, tactical and operative problem fields helps with the search for specific recommendations. In each cluster benchmarking analysis is intended. Thereby, the determination of best practices should not be limited to the narrow circle of ForLog project partners. To improve the quality of research results, additional enterprises of the automotive industry and other industrial sectors are likely to be integrated. Results of these benchmarks will be translated into innovative design recommendations for practitioners. A set of scenarios is created by using IF-THEN-rules describing the optimal integration of LSP for different situations. Design recommendations not only aim at LSP, but also at producers of the automotive industry. The implementation of design recommendations is scheduled at the end of the project. Therefore, promising concepts/concept elements are to be chosen in a discourse of project partners. Pilot projects are also implemented mutually with project participants. The efforts are attended by the staff of the TransLog project team. Results Results of the sub-project TransLog support in the first instance LSP in securing and extending their competitive situation by the consideration and implementation of adaptation demands. At the same time, producers of the automotive industry are addressed. This target group can profit from the results through a better integration of their logistics partners and by adapting their own adaptation requirements and structures, if necessary. The following results are aspired: • Demonstration of the development of the automotive industry in respect to adaptation requirements and integration of LSP into automotive value chains. • Design of optimum, supra-adaptive logistics outsourcing relationships. • Development and description of suitable business models for logistics service providers.

Information

Launching date

09.2004

End

11.2007

Funded by

Bayerische Forschungsstiftung