Modernization for demand forecasting utilizing existing systems in retail.
Transform existing IT assets into an AI-ready foundation. Optimize demand forecasting in retail through data integration.
In the retail industry, accurate demand forecasting that captures market changes and consumer trends is crucial for inventory optimization and reducing opportunity loss. However, in complex system environments where on-premises and SaaS coexist, it is often challenging to integrate and utilize the data necessary for AI applications. This document explains the method of "collaborative modernization," which allows for the gradual construction of an AI utilization foundation without completely overhauling existing systems. By utilizing data integration tools to connect internal data with AI, we support the improvement of demand forecasting accuracy. 【Usage Scenarios】 - Demand forecasting that integrates sales data from stores and e-commerce sites with external factor data - Automation of inventory management by linking existing core systems with AI tools - Building an AI analysis foundation using historical sales data from on-premises environments 【Benefits of Implementation】 - Development of a gradual AI utilization foundation that leverages existing systems - Improved demand forecasting accuracy and inventory optimization through data integration - Modernization of IT infrastructure while minimizing risks and costs associated with system overhauls
- Company：アステリア アステリア株式会社
- Price：Other
