The Planning Bullwhip: A Complex Dynamic Phenomenon in Hierarchical Systems

  • Philip MoscosoEmail author
  • Jan Fransoo
  • Dieter Fischer
  • Toni Wäfler


Instabilities in production planning and control have received considerable attention due to their negative impact on planning performance. However, extant research has been limited to theoretical (e.g. simulation) settings and has focused on specific methodologies (e.g. mathematical) to overcome instabilities. The objective of this chapter is to make two contributions to the theory development on production planning instabilities. First, it aims to make an empirical contribution through an in-depth case study, and second, it introduces a holistic framework that supports analysis of hierarchical planning systems and their potential instabilities.

The in-depth case study is carried out on an industrial company that has difficulty to meet its customer deadlines and faces a significant order backlog. Planners of the company at different hierarchical levels and order chasers on the shop floor end up rescheduling open orders and updating lead times continuously when trying to meet deadlines, but eventually are not able to improve order fulfillment. Only after the introduction of an Advanced Planning System and centralization of planning decisions in a single department, on-time delivery was significantly improved and order back log drastically reduced. This case study allows studying of the underlying mechanism of such planning instabilities, with a particular focus on the impact on stability of human and organizational factors. On the basis of our findings and additional conceptual research we have then developed a framework constituted by six key planning systems attributes. By taking into consideration these factors, a firm can address the root causes of planning instabilities, rather than merely focus on its symptoms.


Supply Chain Lead Time Planning System Shop Floor Planning Decision 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2010

Authors and Affiliations

  • Philip Moscoso
    • 1
    Email author
  • Jan Fransoo
    • 2
  • Dieter Fischer
    • 3
  • Toni Wäfler
    • 4
  1. 1.IESE Business SchoolUniversidad de NavarraPamplonaSpain
  2. 2.School of Industrial EngineeringEindhoven University of TechnologyEindhovenThe Netherlands
  3. 3.Institute for Business EngineeringUniversity of Applied Sciences Northwestern SwitzerlandBruggSwitzerland
  4. 4.School of Applied PsychologyUniversity of Applied Sciences Northwestern SwitzerlandOltenSwitzerland

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