Reciprocal Models for Enterprise Resource Allocation
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Solution Overview
Problem
Large enterprises face difficulties in developing and generating resource allocation models due to the complexity and size of modern resource allocation models, leading to prohibitively long computation times and challenges in generating reporting information.
Innovation Solution
The implementation of a reciprocal model-based approach that uses a memory buffer to store allocation ratio and fixed resource value information, allowing for efficient resource allocation by solving a linear system corresponding to the allocation ratio and fixed resource value information, and providing resource information to the data model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If modern resource allocation models track more activities and elements, then the accuracy and comprehensiveness of resource allocation improves, but the complexity of the underlying data model increases
Solution Approach 1:
The patent segments the complex resource allocation data model into multiple simplified reciprocal models, each representing a specific resource type or allocation scenario. This allows the system to maintain high measurement precision for resource allocation while reducing the complexity of individual models by dividing them into manageable segments that can be processed separately.
Solution Approach 2:
The patent introduces reciprocal models as intermediary representations between the complex original data model and the analysis processes. These reciprocal models serve as simplified mediators that capture essential allocation relationships without the full complexity of the original model, enabling efficient computation while preserving allocation accuracy.
2Adaptability or versatility
If enterprise scale resource modeling includes more items and entities, then the coverage and usefulness of resource models improves, but the difficulty of model development increases
Solution Approach 1:
The patent divides enterprise-scale resource models into multiple reciprocal models focused on specific resource types or departments. This segmentation allows the system to cover diverse enterprise needs across multiple specialized models while reducing the development difficulty of each individual model, as each reciprocal model can be developed and validated independently.
Solution Approach 2:
The patent creates reciprocal models that serve multiple functions - they can represent different resource types, support various analysis scenarios, and be applied across different enterprise contexts. This universality allows a single reciprocal model framework to provide broad resource model coverage while maintaining ease of development through standardized structures and methods.
3Loss of information
If resource allocation models become larger and more complex, then the completeness of resource tracking improves, but the computation time for generating reporting information becomes prohibitively long
Solution Approach 1:
The patent segments the large complex resource allocation model into multiple smaller reciprocal models that can be processed independently and in parallel. This segmentation maintains complete resource tracking information across all models while significantly reducing the computation time for generating reporting information, as each smaller model requires less computational resources and can be processed concurrently.
Solution Approach 2:
The patent applies partial action by creating reciprocal models that capture the essential allocation relationships needed for specific reporting purposes, rather than processing the entire complex model for every analysis. This allows the system to maintain complete resource tracking capability while using only the necessary portions of the data model for each specific computation, thereby reducing overall computation time.
Data Source
AI summary
Embodiments are directed to managing data models for managing resource allocation. A data model portion may be provided. Allocation information based on resource allocations associated with pass-through objects that may be included in the data model portion. A memory buffer may be configured to include allocation ratio information and fixed resource value information. A reciprocal model based on the memory buffer and the data model portion may be provided. Providing the reciprocal model may include providing an effective resource value engine based on solving a linear system corresponding to the allocation ratio information and the fixed resource value information. If resource information for a pass-through object associated with the reciprocal model may be requested, the reciprocal model may be employed to provide the resource information to the data model.