Publication Date: 2024/03/23
Abstract: This paper presents a novel approach to optimize business inventory management through the integration of ABC-XYZ analysis with advanced machine learning models. Inventory management plays a critical role in the operational efficiency and profitability of businesses across various industries. Traditional methods such as ABC analysis and XYZ analysis have been widely used to classify inventory items based on their importance and demand variability. However, the effectiveness of these methods can be further enhanced by leveraging machine learning techniques to analyze historical data and make accurate predictions. In this study, we propose a framework that combines ABC-XYZ analysis with machine learning algorithms to classify inventory items and optimize inventory control policies. We demonstrate the effectiveness of our approach through a case study conducted on a real-world business dataset, highlighting significant improvements in inventory turnover, cost reduction, and customer satisfaction.
Keywords: ABC-XYZ Analysis, Inventory Management, Machine Learning, Optimization, Business Efficiency.
DOI: https://doi.org/10.38124/ijisrt/IJISRT24FEB1099
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24FEB1099.pdf
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