Forecasting and Risk Analysis in Supply Chain Management: GARCH Proof of Concept

  • Shoumen Datta
  • Don P. Graham
  • Nikhil Sagar
  • Pat Doody
  • Reuben Slone
  • Olli-Pekka Hilmola


Forecasting is an underestimated field of research in supply chain management. Recently advanced methods are coming into use. Initial results presented in this chapter are encouraging, but may require changes in policies for collaboration and transparency. In this chapter we explore advanced forecasting tools for decision support in supply chain scenarios and provide preliminary simulation results from their impact on demand amplification. Preliminary results presented in this chapter, suggests that advanced methods may be useful to predict oscillated demand but their performance may be constrained by current structural and operating policies as well as limited availability of data. Improvements to reduce demand amplification, for example, may decrease the risk of out of stock but increase operating cost or risk of excess inventory.


Supply Chain Supply Chain Management GARCH Model Supply Chain Performance Bullwhip Effect 
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-Verlag London Limited 2009

Authors and Affiliations

  • Shoumen Datta
    • 1
  • Don P. Graham
    • 2
  • Nikhil Sagar
    • 3
  • Pat Doody
    • 4
  • Reuben Slone
    • 5
  • Olli-Pekka Hilmola
    • 6
  1. 1.Engineering Systems Division, Department of Civil and Environmental Engineering, MIT Forum for Supply Chain Innovation, School of EngineeringMassachusetts Institute of TechnologyCambridgeUSA
  3. 3.Retail Inventory ManagementOfficeMax IncNapervilleUSA
  4. 4.Department of Mathematics and Computing, Centre for Innovation in Distributed SystemsInstitute of Technology TraleeTraleeIreland
  5. 5.OfficeMax IncNapervilleUSA
  6. 6.Kouvola Research UnitLappeenranta University of TechnologyKouvolaFinland

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