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Forecasting Approaches for the High-Tech Industry

  1. Michael Gilliland

Published Online: 15 FEB 2011

DOI: 10.1002/9780470400531.eorms1018

Wiley Encyclopedia of Operations Research and Management Science

Wiley Encyclopedia of Operations Research and Management Science

How to Cite

Gilliland, M. 2011. Forecasting Approaches for the High-Tech Industry. Wiley Encyclopedia of Operations Research and Management Science. .

Author Information

  1. SAS Institute, Cary, North Carolina

Publication History

  1. Published Online: 15 FEB 2011

Abstract

Challenges in the high-tech industry, such as long supply chain lead times, short product lifecycles, and frequent new product introductions, make it unrealistic to expect highly accurate forecasting. However, there are methods to help high-tech organizations deal with this extra uncertainty, and this article focuses on two such methods: the “structured analogy” approach to new product forecasting, and forecast value added (FVA) analysis. The structured analogy approach utilizes data visualization and analytical software to augment “forecasting by analogy” (i.e., like items) with structured judgment. FVA analysis is a method adopted across a broad range of industries for identifying wasteful and bad practices in the forecasting process and is consistent with the “lean” approach to supply chain management. While neither method can guarantee highly accurate forecasts (nothing can do that), these methods help high-tech organizations forecast more efficiently (in less time, at less cost), more effectively (by eliminating process steps that just make the forecast worse), and to better understand and deal with the uncertainties and risks.

Keywords:

  • structured analogy;
  • forecast value added analysis;
  • FVA;
  • forecastability;
  • supply chain management;
  • forecasting performance metrics;
  • demand volatility