Demand Prediction Assistance with Weighted Error Reassessment
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Solution Overview
Problem
Existing demand prediction systems require costly and inefficient product-by-product reassessment due to the wide variety of products being predicted, leading to increased costs.
Innovation Solution
A demand prediction assistance apparatus and method that displays product-by-product prediction accuracies, identifies products requiring reassessment based on error ratios and weight values, and allows user selection for targeted reassessment analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If demand prediction is performed for a wide variety of products, then prediction coverage is improved, but reassessment cost increases
Solution Approach 1:
The patent segments the wide variety of products into manageable groups or categories, allowing demand prediction to be performed at the group level rather than individually for each product. This segmentation reduces the number of reassessments needed while maintaining comprehensive coverage across all products.
Solution Approach 2:
The patent performs demand prediction for all products (excessive action for coverage) but only conducts costly reassessment for selected products or groups (partial action for cost reduction). This selective reassessment approach maintains prediction coverage while significantly reducing reassessment costs.
2Measurement precision
If product-by-product prediction reassessment is performed, then prediction accuracy is improved, but time consumption increases
Solution Approach 1:
The patent divides products into segments or groups based on characteristics such as category, sales volume, or error rate. Reassessment is then performed at the segment level rather than for each individual product, significantly reducing the time required while maintaining accuracy for critical segments.
Solution Approach 2:
The patent performs comprehensive prediction for all products but limits reassessment to only those products or segments where it is most needed (e.g., high-error segments or strategically important products), thereby reducing overall reassessment time while preserving accuracy where it matters most.
Data Source
AI summary
This demand prediction assistance apparatus displays a plurality of pieces of information which indicate the accuracies of demand predictions of a plurality of products belonging to a class designated by a user, accepts a display instruction that a prediction accuracy should be displayed product by product, displays, based on an index obtained for each of the plurality of products belonging to the class by multiplying the absolute value of an error ratio of a demand prediction of that product by a weight value assigned to that product, information indicating a product which has a high possibility of requiring a prediction reassessment, in a case where the display instruction is accepted, accepts a selection made by the user with respect to the product displayed, and displays an analysis result regarding demand for a product corresponding to the selection accepted.