Optimization of inventory management to fulfill consumer demand at odriigo fashion - Janadi Rammelsbergi Thamrin; Willy Agustian; Tengku Ine Hendriana; Ervie Nur Afifa Mukhlis (Institute of Computer Science (IOCS), 2026)
Fluctuations in demand in the fashion industry cause companies to face challenges in maintaining a balance between inventory availability and operational cost efficiency. Suboptimal inventory management has the potential to cause excess or shortage of stock, thus hampering the provision of consumer needs and increasing inventory costs. Although the Economic Order Quantity (EOQ) method has been widely used as an approach to determining economical order quantities, most previous studies still focus on quantitative calculation aspects and have not examined the implementation of EOQ as part of the inventory control system in micro, small, and medium enterprises (MSMEs). This study aims to analyze the optimization of merchandise inventory management through the application of the EOQ method at Odriigo Fashion and develop an EOQ implementation framework that supports the operational decision-making process. The study uses a quantitative descriptive approach with a case study design. Data were collected through observation, interviews, and documentation of data requests, ordering costs, and storage costs during the period March 2025 to February 2026, then analyzed using the EOQ method. The results show that the optimal order quantity is 5,678 units per order with an ordering frequency of 7 times per year, more efficient than the company's previous policy of 24 orders per year. The implementation of EOQ reduced ordering costs from Rp1,920,000 to Rp560,000 per year, resulting in an efficiency gain of Rp1,360,000. In addition to providing cost efficiency, this study produced an EOQ implementation framework that integrates analytical and operational aspects in inventory control for MSMEs. These findings contribute to the development of operations management studies and serve as a practical reference for MSMEs in developing more effective, systematic, and operationally efficient inventory control policies