Application of ABC Analysis and Linear Regression Model in Inventory Management

Due to the competitive environment of commerce of today, supply chain management has become the core part of running a series of industries, earning profits, and having a direct impact on market response and customer feedback. Optimizing and managing inventory to reduce waste and increase profit becomes the main focus of todays supply chain. Therefore, this research focuses on analyzing inventory management through linear regression analysis and ABC analysis to investigate its potential problems. The research uses a dataset including product information, inventory status, and purchase and sale order information. Linear regression was used to analyze the company's inventory, and it was found that sales volume and sales profit were on a decreasing trend. The reasons for the decreasing trend were analyzed using ABC analysis and reveals that a significant portion of the inventory is occupied by poorly selling products, with few brands demonstrating strong sales performance. Based on a comparison of statistical analysis and machine learning predictions, it was concluded that the linear model was more suitable for tracking the data, while the ABC analysis indicated the focus of the different brands. Using these two methods together gives a more comprehensive view of the companys situation.