Use of forecasting techniques in automobile sales

• Main Author: Cheong, Wei Chin.
• Other Authors: Choi Haejin
• Format: Final Year Project
• Language: English
• Published: 2009
• Subjects: DRNTU::Engineering::Industrial engineering::Operations research
• Online Access: http://hdl.handle.net/10356/16790
• Institution: Nanyang Technological University

In this report, the author describes a forecasting method that has high potential to be used for strategic product development that requires statistically predict customers’ demands and wishes of a future market. By then, a company can strategically plan product development to capture the market share by introducing a right product to a right market at the right time. In this study, the author has tested a number of available forecasting methods, among which ARIMA (Auto Regressive Integrated Moving Average) method is proved to be the most effective and practical for our example, six US automobile models sales data. Several assistive software tools have been employed throughout the study, such as Matlab, Minitab, Forecast Pro and Microsoft Excel. From the experiments, it is understood that ARIMA performs well especially in the existence of seasonal and trend elements in time series. This yields accuracy and dependability for forecasting engineering product demands as most engineering products have their own development cycles and patterns that lead to design improvement and innovation.