DESIGNING FLEXIBLE INVENTORY MANAGEMENT SYSTEMS FOR TCF ENTERPRISES

Abstract

This article examines the challenges and solutions in inventory management for textile, clothing, and footwear (TCF) enterprises operating under unstable market conditions. TCF companies face significant difficulties due to demand variability, seasonality, rapid changes in fashion trends, and supply chain disruptions. These factors often lead to either surplus or shortage of raw materials, directly affecting production continuity and financial stability. Traditional inventory models such as EOQ, JIT, and ABC/XYZ analysis, while widely used, often fail to address the specific needs of light industry enterprises, particularly small and medium-sized businesses with limited resources.

The study analyzes the peculiarities of inventory formation in light industry, emphasizing the influence of external factors like seasonality and consumer trends. It reviews existing inventory management models and highlights the need for more adaptive approaches. The author proposes the VARI-FLEX model a flexible inventory management system that integrates segmentation, forecasting, automatic ordering, and monitoring. Segmentation allows for classifying materials and products by demand frequency and seasonality. Forecasting uses adaptive methods, considering both short-term trends and internal data, to improve demand prediction accuracy. Automatic ordering is triggered by inventory thresholds, ensuring timely replenishment. Continuous monitoring of key indicators enables rapid adjustment of strategies in response to market changes.

The VARI-FLEX model is designed for easy implementation and high adaptability, making it suitable for enterprises facing rapid market shifts and resource constraints. Practical scenarios demonstrate its effectiveness in both stable and crisis conditions. The article concludes that strategic, flexible inventory management - combining structural simplicity with functional adaptability can significantly enhance operational efficiency and competitiveness for light industry enterprises in uncertain environments.