OPTIMIZING INVENTORY MANAGEMENT SYSTEMS A CASE STUDY OF FIX INTER TRADING CO., LTD.

Abstract

A case study of Fix Inter Trading Co., Ltd. revealed that the company did not have a formal inventory management system. Inventory records were maintained manually in notebooks, resulting in an average search time of 12.45 minutes per item. Inventory discrepancies accounted for 18.60% of total records. These limitations caused delays in verifying stock balances, tracking rental and return transactions, and planning customer service operations, ultimately leading to potential business opportunity losses and reduced operational efficiency. This study aimed 1) to examine the current condition of the inventory management system and 2) to identify appropriate approaches for improving inventory management efficiency through the implementation of an off-the-shelf software package. The research employed a mixed-method approach, combining qualitative data collection with quantitative performance evaluation. Data were gathered through in-depth interviews and system usage assessments from 23 employees directly involved in inventory-related operations. A five-point Likert scale questionnaire was used to evaluate user satisfaction. The collected data were analyzed using mean (), standard deviation (S.D.), and percentage to measure system performance and user perceptions. The findings indicated that after implementing the software package, the average search time decreased to 3.20 minutes per item, representing a 74.29% reduction in processing time. Inventory discrepancies were reduced to 4.15%, demonstrating improved data accuracy and control. User satisfaction was rated at a high level () = 4.36, S.D. = 0.58, equivalent to 87.20%. Respondents reported that the system enabled faster verification of rental and return records, provided real-time inventory balance updates, and generated automated alerts prior to due return dates. These improvements significantly reduced operational errors and enhanced managerial decision-making capabilities. The study recommends categorizing inventory based on the FSN Analysis approach and integrating barcode technology to further enhance tracking accuracy, improve stock control, and strengthen overall inventory management performance in the future