Local Product Storage Data Processing for Store Order Accuracy
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Solution Overview
Problem
Existing systems for determining product order amounts are based solely on past data, leading to low accuracy.
Innovation Solution
An information processing device that acquires product storage information including product type, effective time limit, and quantity before consumption for each user, totals this information for users within a predetermined range from a store, and outputs results to recognize potential demand and stimulate sales through privilege information and product reservations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems use only past data for order determination, then the system complexity is low, but the accuracy of product order determination is low
Solution Approach 1:
The system performs preliminary actions by acquiring product storage information from users before consumption occurs, and conducting totaling operations in advance to determine order quantities. This allows the system to proactively identify product needs based on actual storage data rather than relying solely on historical patterns, thereby improving order determination accuracy while managing complexity through structured data collection processes
2Loss of information
If the system acquires and processes product storage information for multiple users, then the accuracy of demand recognition is improved, but the amount of information to be processed increases
Solution Approach 1:
The system merges product storage information from multiple users by conducting totaling operations that aggregate quantities and user counts for each product type and effective time limit. This combining approach consolidates scattered individual user data into comprehensive demand information, ensuring complete demand recognition while reducing the processing burden through systematic aggregation rather than handling each user's data separately
3Measurement precision
If the system targets users within a predetermined range from the store, then the relevance of demand information is improved, but the complexity of location-based filtering increases
Solution Approach 1:
The system applies local quality by focusing demand recognition on a specific local area - users within a predetermined range from the store. This geographic filtering ensures that the demand information collected is highly relevant to the store's actual service area and potential customers. The complexity of location-based filtering is managed by establishing clear spatial boundaries that define the target user population for demand aggregation
Data Source
AI summary
An information processing device according to one embodiment includes an acquisition unit, a totaling unit, and an output control unit. The acquisition unit acquires, as product storage information, information including a product type, an effective time limit, and a quantity of a product before consumption, for each of users. The totaling unit determines a totaled quantity of the product and a totaled number of users each storing the product, for each of effective time limits, from the product storage information for users living within a predetermined range from a store selling the product, based on the product storage information for each of the users acquired by the acquisition unit and address information of the users. The output control unit outputs results determined by the totaling unit.