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Modelling Complex Planning Processes in Supply Chains

In: Operational Excellence in Logistics and Supply Chains: Optimization Methods, Data-driven Approaches and Security Insights. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 22

Author

Listed:
  • Wallner, Martin
  • Brunner, Uwe
  • Zsifkovits, Helmut

Abstract

Demand planning has become a key issue for the performance of supply chains. However, the right quantity is dependent on many factors. Besides market influences, like changing demands, there are also inner-company variables such as the availability of resources. Decision makers often lack a clear picture of what influences their decisions and perceive a state of complexity. There are several theoretical models for managing complexity, but they are not designed to identify the complexity in demand planning. The aim of this paper is to establish a methodology for visualizing and reducing the complexity in the demand planning process. The first result is a model for visualizing the complexity in the planning process. The model shows the factors which influence planned quantities in a chronological order, and, makes cause-effect relations regarding time, responsibility and system support visible. The second result is a structured compilation of methods and tools to actively influence the complexity in the demand planning process. The identified approaches are either assigned to complexity design - reducing complexity by simplifying the supply chain - or complexity control - reducing complexity by decreasing the uncertainty in planning.

Suggested Citation

  • Wallner, Martin & Brunner, Uwe & Zsifkovits, Helmut, 2015. "Modelling Complex Planning Processes in Supply Chains," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Blecker, Thorsten & Kersten, Wolfgang & Ringle, Christian M. (ed.), Operational Excellence in Logistics and Supply Chains: Optimization Methods, Data-driven Approaches and Security Insights. Proceedings of the Hamburg , volume 22, pages 3-30, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:209279
    DOI: 10.15480/882.1265
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