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Sustainability 2016, 8(3), 263; doi:10.3390/su8030263

Development of an Adaptive Forecasting System: A Case Study of a PC Manufacturer in South Korea

1
Computer Integrated Manufacturing Group, Global Foundries Inc., 400 Stonebreak Road Extension, Malta, New York, NY 12020, USA
2
Department of System and Management Engineering, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon 200-701, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Marc A. Rosen
Received: 30 September 2015 / Revised: 22 February 2016 / Accepted: 7 March 2016 / Published: 10 March 2016
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Abstract

We present a case study of the development of an adaptive forecasting system for a leading personal computer (PC) manufacturer in South Korea. It is widely accepted that demand forecasting for products with short product life cycles (PLCs) is difficult, and the PLC of a PC is generally very short. The firm has various types of products, and the volatile demand patterns differ by product. Moreover, we found that different departments have different requirements when it comes to the accuracy, point-of-time and range of the forecasts. We divide the demand forecasting process into three stages depending on the requirements and purposes. The systematic forecasting process is then introduced to improve the accuracy of demand forecasting and to meet the department-specific requirements. Moreover, a newly devised short-term forecasting method is presented, which utilizes the long-term forecasting results of the preceding stages. We evaluate our systematic forecasting methods based on actual sales data from the PC manufacturer, where our forecasting methods have been implemented. View Full-Text
Keywords: demand forecasting; product life cycle; Bass diffusion model; Bayesian updating demand forecasting; product life cycle; Bass diffusion model; Bayesian updating
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Jung, C.; Lim, D.-E. Development of an Adaptive Forecasting System: A Case Study of a PC Manufacturer in South Korea. Sustainability 2016, 8, 263.

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