Multi-Hierarchy Data Consistency via Optimization Linking
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Solution Overview
Problem
Existing systems fail to maintain consistency across multiple hierarchies within an organization, leading to disjointed planning and inaccurate projections across different levels and dimensions.
Innovation Solution
An optimization-based approach is implemented to adjust node values across common levels of multiple hierarchies, applying linking constraints to ensure consistency and minimize the impact on target level nodes, using a method that includes identifying common and target level nodes, applying linking constraints to generate updated node values, and computing disaggregation factors to enforce flow conservation properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing systems are used to manage multiple hierarchies, then each hierarchy can be maintained independently, but consistency across hierarchies is lost and projections become inaccurate
Solution Approach 1:
The patent merges multiple independent hierarchies into a unified structure by introducing common levels that are shared across all hierarchies. This allows consistent data to be maintained at common levels while preserving the independence of individual hierarchy branches. The optimization-based approach combines constraints from multiple hierarchies to resolve conflicts and ensure consistency across the entire hierarchy system.
Solution Approach 2:
The patent segments the hierarchy management into distinct common levels and target levels. Common levels are shared across all hierarchies and contain data that must be consistent across all hierarchies, while target levels are specific to each hierarchy branch. This segmentation allows the system to maintain consistency at common levels while allowing independent operations at target levels.
2Measurement precision
If node values are adjusted to ensure consistency across hierarchies, then projection accuracy improves, but the impact on target level nodes increases
Solution Approach 1:
The patent applies local quality by making different parts of the hierarchy have different properties. Common levels have data that must be consistent across all hierarchies, while target levels have hierarchy-specific data. The optimization approach applies different constraints and weights to different levels, allowing adjustments at common levels without propagating excessive changes to target levels.
Solution Approach 2:
The patent uses parameter changes through an optimization-based approach that adjusts node values by minimizing the squared distance between original and updated values. The system changes parameters (node values) at common levels to achieve consistency while using mathematical optimization to minimize the overall impact on the hierarchy system.
3Reliability
If linking constraints are applied to common level nodes, then consistency across hierarchies is achieved, but computational complexity increases
Solution Approach 1:
The patent replaces complex manual constraint application with an automated optimization-based system. Instead of mechanically applying constraints to each node individually, the system uses mathematical optimization algorithms to automatically adjust node values and enforce consistency across all hierarchies, reducing computational complexity through systematic approaches.
Solution Approach 2:
The patent creates a universal optimization framework that can handle multiple hierarchies simultaneously. The same mathematical model and constraint application process work across all hierarchies, making the system multi-functional and reducing overall computational complexity compared to handling each hierarchy separately.
Data Source
AI summary
Techniques and systems for adjusting multiple hierarchies for consistency within levels of the hierarchies, using an optimization-based approach that results in an accurate projection across dimensions and levels in hierarchies. The systems and methods may include receiving data associated with nodes of two or more hierarchies, wherein nodes are associated with original node values, identifying a common level node and a target level node for each of the hierarchies, identifying a linking constraint, wherein the linking constraint includes a rule to a node from a hierarchy to make it consistent with a node from another hierarchy, applying the linking constraint to the common level node of each of the hierarchies, wherein applying the linking constraint includes generating updated common node values associated with the common level nodes, and wherein updated common node values are the same node values, applying the updated common node values to the target level node of each of the hierarchies, wherein applying the updated common node values includes generating updated target node values, and generating a resolved hierarchy using the updated target node values.