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Demand & Inventory Management

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Forecasting demand and inventory management using Bayesian time series

T.A. Spedding University of Greenwich, Chatham Maritime, Kent, UK K.K. Chan Nanyang Technological University, Singapore

Batch production, Demand, Forecasting, Inventory management, Bayesian statistics, Time series

Keywords

Introduction
A typical scenario in a manufacturing company in Singapore is one in which all the strategic decisions, including forecasting of future demand, are provided by an overseas office. The forecast model provided by the overseas office is often inaccurate because the forecasting is performed before the actual production schedule and it is based on marketing survey results and historical data from an overseas research team. This …show more content…

Bayesian dynamics time series and forecasting techniques can be used to solve inventory problems because Bayesian inference statistics has the analogue idea that posterior knowledge (actual sales demand) can be derived from prior knowledge (such as the manager's experience) and the likelihood (the similar or expected trend) of the product demand (Box and Tioa, 1973; Jeffreys, 1961; Lee, 1988; Press, 1989). In many real life forecasting problems (for example when previous demand data are not available for newly launched products), there is little or no useful information

This work was carried out while the author was Associate Professor in the School of Mechanical and Production Engineering at Nanyang Technical University in Singapore.

Integrated Manufacturing Systems 11/5 [2000] 331±339 # MCB University Press [ISSN 0957-6061]

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T.A. Spedding and K.K. Chan Forecasting demand and inventory management using Bayesian time series Integrated Manufacturing Systems 11/5 [2000] 331±339

available at the time when the initial forecast is required. Hence, the early forecast must be based largely on subjective considerations (such as the manager's experience and the general demand of a similar or comparable product). As the latest information (actual sales demand) becomes available, the forecasting model is modified with the subjective estimation in the presence of the actual data. This

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