Explaining data design and machine learning that supports order optimization.
From intuition and experience-based ordering to data-driven demand forecasting. How to create an AI system that predicts the "probability of selling" at the product level, including what data to use, what models to apply, and how to operate it. This article explains the key points of implementing and operating demand forecasting that combines sales performance, events, weather, and market attributes. For more details, please refer to the technical column in the related links.
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basic information
【Technical Elements】 - Demand forecasting using machine learning (predicting the probability of sales) - Data design for sales performance, events, weather, and market attributes - Order optimization - Operational design 【Category】AI Solutions / Retail DX * This will explain how to create demand forecasting AI from data design to operation.
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Applications/Examples of results
【Intended Use】 - Optimization of orders in retail and distribution - Reduction of inventory, stockouts, and waste loss - Production and purchasing planning based on demand forecasting 【Examples of Achievements】 - Supported the design and operation of demand forecasting AI that combines sales performance with weather, events, etc.
Company information
Technosphere Co., Ltd. is a system development company based in Osaka that tackles customer challenges in advanced technology areas such as AI, IoT, and web system development. Since its founding in 2021, the company has leveraged a flat team structure to achieve a flexible and speedy development style. We are engaged in solutions that directly address social issues, such as image inspection AI and smart factory support systems.
