Logistic assistant systems for effective supply chain planning

Considering new challenges in global markets, companies are forced to plan their supply chains relating to more flexibility, effectiveness and cost reduction. Today, Advanced Planning Systems (APS) are applied to manage availability of supply goods (available/capable-to-promise ATP/CTP) and to smooth inventory levels due to fluctuating demands and insecure market forecasts. High-value-added branches, like the automotive industry, are characterized by complex, often sales-based product configurations resulting in literally millions of possible product variants. Furthermore a high percentage of value creation is done by global supply networks with high order lead times, dynamic and risky transport relations and high transfer stocks. Today, the necessity of global ATP taking dynamic supply network behavior and collaborative partnerships into account is not covered by given APS-Software. This paper will introduce Logistic Assistant Systems (LAS) as a new generation of SCM-Software, which allows dynamic and collaborative supply chain planning by providing APS-like-functionalities with a simulation based approach. The developed simulation component is able to handle the complexity of high-value-added branches with efficient algorithms, to forecast the supply chain behavior (future stock range monitoring, dynamic ATP and resulting costs) taking different scenarios into account. It has been demonstrated to produce convincing results e.g. in projects with Volkswagen AG.