Business Process Management of Glutaraldehyde Import by Dynamic Decision Making and Demand Forecasting with Product Prices Fluctuation

Abstract

This research aimed to propose business process development of a chemical product merchandising business by improving Glutaraldehyde order process that had the highest business value with the highest merchandising in the company. Data were analyzed by using Glutaraldehyde Demand Forecasting and Glutaraldehyde Cost Forecasting by using time series forecasting technique. The results of the forecasting showed that Multiplicative Holt-Winters method had the least demand forecasting error, and Trend plus Seasonal Multiplicative Decomposition method had the least cost forecasting error. Moreover, the economy order quantity was analyzed to identify the lowest inventory cost by using Dynamic lot sizing model. Mathematic model of Wagner-Whitin was applied to reduce the inventory cost. The results of the comparison revealed that the inventory cost from the present order process was 10,764,896 baht per year when the inventory cost from the proposed order process by using Dynamic lot sizing model was 9,732,043 baht per year showing the reduced cost of 1,032,853 baht per year which was 10.61%.