Attribute-Based Hierarchy Management for Forecasting
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Solution Overview
Problem
Organizational data stored in physical hierarchies is often not adequately structured to handle complex forecasting and estimation scenarios, requiring significant preprocessing and limiting the flexibility and efficiency of analysis.
Innovation Solution
The creation of an attribute-based hierarchy from physical hierarchical data, using attribute input data to insert new levels and generate a mapping table that restructures the data for more efficient and diverse calculations, enabling simplified complex forecasting and estimation models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If physical hierarchical data structure is used for data storage, then data storage requirements are satisfied, but forecasting and estimation analysis capability is limited
Solution Approach 1:
The patent segments the physical hierarchy into multiple attribute-based hierarchies, where each hierarchy is organized around a specific attribute (e.g., geographic, temporal, product). This segmentation allows forecasting models to access data organized by relevant attributes without being constrained by the original physical storage structure, thereby improving analysis capability while maintaining storage efficiency.
Solution Approach 2:
The patent introduces attribute-based hierarchies as intermediary structures between the physical data storage and forecasting analysis systems. These hierarchies act as mediators that translate physical storage requirements into analysis-friendly structures, enabling complex forecasting without requiring changes to the underlying physical data storage architecture.
2Productivity
If physical hierarchy is used directly for forecasting analysis, then data storage efficiency is maintained, but preprocessing requirements increase
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing attribute-based hierarchies from the physical data during data loading or off-peak periods. This preliminary organization of data by various attributes enables forecasting models to directly access pre-processed data without requiring extensive preprocessing at the time of analysis, thereby reducing preprocessing time and improving forecasting productivity.
3Adaptability or versatility
If physical hierarchy structure is maintained, then operational framework representation is preserved, but flexibility for diverse calculations is reduced
Solution Approach 1:
The patent adds another dimension to the data structure by creating attribute-based hierarchies that organize data along different attribute dimensions (geographic, temporal, product, etc.) while maintaining the original physical hierarchy structure. This multi-dimensional approach provides calculation flexibility for diverse forecasting scenarios without destabilizing the core operational framework representation.
Data Source
AI summary
Computer-implemented systems and methods generate forecasts or estimates with respect to one or more attributes contained in an attribute-based hierarchy. Physical hierarchical data and attribute input data are received so that an attribute-based hierarchy can be created. A mapping table is created that indicates relationships between the attribute-based hierarchy and the physical hierarchy, wherein the attribute-based hierarchy is accessed during model forecasting analysis or model estimation analysis.