Forecasting techniques to reduce inventory costs Case study of textile industry

Abstract

The objectives of this research were 1) investigate product sales behavior; and 2) determine the best strategy for Group A products utilizing forecast data from the previous two years. Three forecasting techniques were compared in the study. These are some examples: 1) Simple moving average 2) A single-exponential function 3) The Winter Method Data was acquired using the Minitab 19 beta free trial program from January 2021 to December 2022. In order to identify the most successful forecasting methodologies, The results revealed that the seasonal forecast method resulted in the lowest average absolute percentage (MAPE) disposition in product types A and B, with item A having an average absolute percentage (MAPE) of 1.00 and product type B having an average absolute percentage (MAPE) of 2.00. As a result, the price has increased of sinking costs can be lowered from 5,800,000 baht per year to 4,640,410 baht per year, indicating a value reduction of 1,159,590 baht per year, or 29.99 percent.