system
The system addresses inefficient inventory management by using historical and environmental data with machine learning to forecast demand, optimizing order quantities and timings, and improving forecasting accuracy through a feedback loop.
JP2026096672APending Publication Date: 2026-06-15SOFTBANK GROUP CORP
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- SOFTBANK GROUP CORP
- Filing Date
- 2024-12-03
- Publication Date
- 2026-06-15
AI Technical Summary
⚠Technical Problem
Inventory management in retail and food industries is inefficient, leading to opportunity losses and excess inventory due to inaccurate demand forecasting, which is costly and time-consuming for small and medium-sized operators.
⚗Method used
A system that collects and preprocesses historical sales data, weather information, and promotional event data, using machine learning to forecast demand and determine optimal order quantities and timings, with a feedback loop for model improvement.
🎯Benefits of technology
Enables efficient inventory management by reducing ordering errors and costs, allowing for accurate demand forecasting and quick response to environmental and promotional changes.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure 2026096672000001_ABST
Abstract
We provide the system. [Solution] A means for collecting past sales data, weather information, seasonal information, and promotional event information, and for pre-processing this data, A means of generating forecast data by using a machine learning model to perform demand forecasting based on preprocessed data, A means for determining the optimal order quantity and timing, taking into account the characteristics of each store and product, based on demand forecasts. A means to automatically execute the generated order proposal, A means to evaluate the difference between actual sales data and forecast data, and to improve the forecasting model, A system that includes this.
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