Published date: Jan 01 2016

Journal Title: KnE Life Sciences

Issue title: International conference on Agro-industry (ICoA) 2015

Pages: 1-5

DOI: 10.18502/kls.v3i3.410

Teerada KhamphinitDepartment of Agro-Industrial Technology, Faculty of Agro-Industry, Kasetsart University 50 Ngam Wong Wan Rd. Lad Yao, Chatuchak, Bangkok 10900

Pornthipa Ongkunarukpornthipa.o@ku.ac.thDepartment of Agro-Industrial Technology, Faculty of Agro-Industry, Kasetsart University 50 Ngam Wong Wan Rd. Lad Yao, Chatuchak, Bangkok 10900

Demand forecasting is very important for the planning process. The forecast accuracy affects the efficiency of the procurement, production and delivery processes. Our research has the objective of increasing the sales forecasting accuracy of instant noodles for a case study company in Thailand. Many factors affect the sales of instant noodles, such as promotion, other commodities’ prices, national disaster and production capacity. Thus, we collected historical monthly sales data, analysed the data and their pattern and considered whether the data were irregular due to those factors. After obtaining the forecast data, data intervention by adjustment of the irregular effects was performed in accordance with our experience and judgement. Next, we used the predictor function in the Crystal Ball software to determine the best time series forecasting method for actual and adjusted sales data. Then, we verified the result with the actual sales data for one year. The result showed that the adjustment could increase the sales forecast accuracy by 46.14%, 22.53% and 56.42% for products A, B and C, respectively. In summary, the mean average percentage sales forecast error after adjustment was 6.48%–11.62%, which is better than the current method of forecasting based on experts.  

Keywords: Instant Noodle; Intervention; Qualitative Forecasting; Sales Adjustment; Time Ser ies Forecasting 

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