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Can trend forecasting improve stability in supply chains? A response to Forrester's challenge in Appendix L of Industrial Dynamics
Author(s) -
Saeed Khalid
Publication year - 2009
Publication title -
system dynamics review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.491
H-Index - 57
eISSN - 1099-1727
pISSN - 0883-7066
DOI - 10.1002/sdr.411
Subject(s) - certainty , stability (learning theory) , supply chain , computer science , control (management) , economics , derivative (finance) , mathematical economics , operations research , econometrics , mathematics , artificial intelligence , machine learning , financial economics , law , political science , geometry
This paper revisits the use of trend forecasting in driving ordering policies in supply chains by comparing it with derivative control in classical control theory. While both processes involve use of trend to determine policies for achieving reliable performance, the former often worsens instability, while the latter can improve stability with certainty. The similarities and differences between the two processes are discussed and a framework suggested for improving the efficacy of trend forecasting in ordering policies. Copyright © 2009 John Wiley & Sons, Ltd.