Application of Forecasting Method for Reducing Storage Costs: Case Study of an Automotive Product Company

Abstract

This aim of this research was to create a comprehensive guide for predicting product requirements and managing storage costs through the application of the simple moving average (SMA) forecasting method. The investigation, initiated by filtering data from the total sales of a specific business, aimed to identify large-sized products within a designated product group, amounting to a total of 10 items. Subsequently, an in-depth analysis of the sales data for these products was conducted to identify a suitable forecasting method based on the observed data patterns. Following the analysis, it was determined that the optimal forecasting method for five of the products was the 6-month moving average, while the 2-month moving average was recommended for another four products. Additionally, one product was advised to utilize the 4-month moving average. The derived conclusion suggests that implementing these forecasting methods would result in an estimated annual reduction of approximately 9,729.70 Thai Baht per year in the overall cost of inventory management.