Graph-Based Financial Allocation Model With Heritage Cost Propagation
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Solution Overview
Problem
Large and complex financial allocation models in businesses make it difficult to accurately determine the total cost of ownership for products and services, especially for larger enterprises, due to the complexity of allocating costs between various entities and items.
Innovation Solution
A system and method for allocating costs using a graph-based financial allocation model that incorporates heritage information, allowing for the propagation of cost allocation rules across multiple objects and categories, enabling more accurate and detailed cost distribution through the use of assignment ratios and heritage objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of tracked activities and elements increases to improve modeling accuracy, then the complexity of the financial allocation model increases, making it difficult to design allocation rules and ascertain total cost of ownership
Solution Approach 1:
The patent segments the financial allocation model into distinct entities (cost objects, cost drivers, allocation rules) and their relationships. This segmentation allows the system to handle complex allocation scenarios by breaking down the allocation process into manageable components, each with specific roles and responsibilities, thereby reducing the cognitive load on the model designer while maintaining high modeling accuracy.
Solution Approach 2:
The patent introduces allocation rules as intermediary elements that mediate between cost objects and cost drivers. These allocation rules serve as the bridge that translates raw cost data into meaningful allocations, simplifying the relationship between numerous tracked activities and elements. The intermediary allocation rules make the complex allocation process transparent and easier to design and maintain.
2Quantity of substance
If sophisticated computer programs are used to assist in generating budgets, then the ability to handle large numbers of items improves, but the difficulty of developing modeling applications increases
Solution Approach 1:
The patent designs a universal financial allocation model framework that can handle diverse items and entities through a common set of allocation rules and data structures. This multi-functional approach allows the same system to accommodate various allocation scenarios (direct costs, indirect costs, shared resources) without requiring separate development for each case, thereby reducing development difficulty while maintaining the ability to process large numbers of items.
Solution Approach 2:
The patent employs parameter changes to adapt the allocation model to different scenarios. By allowing flexible configuration of allocation rules, cost objects, and cost drivers through parameter modification rather than structural redesign, the system can handle large numbers of items efficiently. This parameter-driven approach simplifies development by avoiding the need to rewrite code for each new item type, while still maintaining comprehensive tracking capability.
Data Source
AI summary
Various embodiments are directed towards including heritage information when allocating costs for a plurality of cost objects. A target object, a source object and heritage objects may be determined from a data model. At least one line item in the source object may be generated by allocating costs from the heritage objects with the generated source object line items corresponding to a line item from a heritage object. At least one line item in the target object may be generated based on allocating costs from the source object. And, at least one generated target object line item may be based on at least one source object line item and its corresponding heritage object line item. A final cost value for the target object may be generated based on a sum of each target object line item and displayed in the data model.