FORESIGHT, Issue 56

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Winter 2020

Special Features

1. Forecasting for Remanufacturing by Thanos Goltsos and Aris Syntetos
Operations decisions in circular economic contexts, like remanufacturing, face dual uncertainties. They not only rely on demand forecasts but also on forecasts of returned items. It is net demand (demand minus returns) that drives replenishment. So how does this dual-source uncertainty affect the forecasting task? In this article, Thanos and Aris discuss the circular economy and the challenges of forecasting returns in a remanufacturing context.

  • Commentary: Why Is Forecasting for Remanufacturing Hard? by Ram Ganeshan

2. Strategic IBP: Driving Profitable Growth in Complex Global Organizations by Dean Sorenson
Dean Sorensen offers his perspective on IBP (Integrated Business Planning), with a specific focus on global manufacturers (GMs). He thinks that what we have been calling IBP is too narrow to be considered “fully integrated.” What is missing, Dean explains, is the strategic element of a truly integrated process, with the consequence that GMs are unable to realize the value from effective management of complexity. It is a call to arms for a rethink of how we can optimize organizational resources.

  • Commentary: Strategic IBP by Pete Alle and response by Dean Sorenson, author

Articles

  1. Smarter Supply Chains through AI by Duncan Klett
    In this article, Duncan Klett portrays a supply chain as a multifaceted control system in which a reduction in latency (delays) offers the most leverage for improved supply-chain performance. He sees a broad role for AI/ML in furthering this goal, through automating processes, validating data, segmenting items, and generating forecasts.
  2. Monitoring Forecast Models Using Control Charts by Joseph Katz
    Joe Katz presents a new application of control charts for automatic monitoring of forecast errors. He reviews the traditional rules for statistical process control and then applies these along with custom rules to determine whether a forecasting model should be maintained, adjusted/refit, or discarded and replaced.
  3. Could These Recent Findings Improve Your Judgmental Forecasts? by Paul Goodwin
    An introduction to automated machine learning and its possible next-generation realization, continual learning (CL). CL advances the state of the art by attempting to automatically learn different tasks while retaining knowledge from previous model implementations. This article presents an application of CL to investment decisions. It also offers the interesting perspective that complexity is not simply a technical characteristic of a model formulation, but also a resultant of the application of human judgment.
  4. Chris Gray: In Memoriam, by Len Tashman, Editor in Chief

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