Forecasting raw material ordering demand and inventory management improvement: A case study of a cinema in Si Racha District

Abstract

This research aimed to 1) to analyze product segmentation based on inventory classification frameworks, analyzing items across the spectrum of high turnover, low- turnover and zero-turnover categorizes  (FSN analysis); 2) To apply the decomposition forecasting technique into the determination of   re- order point (ROP), economic orfer quantity (EOQ) and the safety stock levels. The population consisted of all 257 product stock keeping-units managed by specific cinema in the Sriracha district. The sample group comprised of the items categorized using FSN analysis framework. This study specifically focused on products within the raw material (popcorn, and packaging category, which were further classified according to FSN theory. The statistical forecasting techniques employed in this study include time series decomposition. The Economic Order Quantity (EOQ) model, Re-Order Point (ROP) determination, and Safety Stock (SS) level were integrated to analyze and to mitigate issue regarding excessive storage space occupancy relative to actual product demand. It was found that the product with the highest deviation was the 32-oz cup. The product with the least deviation was Material Popcorn Oil. The overall deviation of all 14 types of products was 42.76%. The average inventory level for good – in – process was reduced from 475 unit to 245 units per day, representing a 42% decrease across Packaging and Raw Material Popcorn categories. This production led to minimized storage occupancy and significantly lowered the risk of product spoilage before expiration.