Data Usage Cost Allocation via Transaction Classification
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Solution Overview
Problem
Current systems lack the ability to effectively monitor, classify, and allocate costs for data usage transactions, leading to difficulties in managing and optimizing data usage, particularly with the rise of Over The Top (OTT) applications that reduce visibility into user activities and make it challenging to track costs on a granular level.
Innovation Solution
A system and method that analyze data transactions to classify usage into activity-based categories, using pattern recognition and resource consumption analysis, allowing for detailed cost allocation and reporting, even for OTT transactions, by extracting and matching data packets to application-specific units of measure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data usage monitoring is implemented at the transaction level, then cost allocation precision is improved, but system complexity increases
Solution Approach 1:
The patent segments data usage monitoring into distinct functional modules: data capture module, classification module, cost calculation module, and reporting module. Each module handles a specific aspect of the monitoring process, allowing the complex system to be managed through modular components that can be independently developed and maintained while achieving precise transaction-level cost allocation.
Solution Approach 2:
The patent introduces an intermediary classification layer that sits between raw data usage and cost allocation. This classification module categorizes data transactions into meaningful groups (e.g., business vs. personal, application types) before cost calculation, simplifying the overall system by adding a mediating step that makes the complex task of cost allocation more manageable and precise.
2Loss of information
If detailed data transaction analysis is performed, then visibility into user activities is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining classification rules and cost allocation parameters before data usage occurs. The system establishes classification criteria for different application types and usage patterns in advance, allowing rapid categorization of data transactions as they occur without requiring complex real-time analysis, thus reducing processing time while maintaining detailed visibility.
Solution Approach 2:
The patent implements partial action by focusing classification and detailed analysis only on specific data transactions that require cost allocation, rather than analyzing every single data packet in detail. The system applies different levels of analysis based on the transaction type, performing comprehensive classification on business-related usage while using simplified methods for personal usage, thereby reducing overall processing time while maintaining necessary visibility.
3Productivity
If cost allocation rules are applied to multiple accounts, then cost recovery capability is improved, but allocation complexity increases
Solution Approach 1:
The patent implements universality by creating a multi-functional cost allocation engine that can apply the same core allocation rules across multiple accounts and different types of data usage. The system uses a unified set of classification criteria and cost parameters that work consistently for various accounts (e.g., departmental accounts, project accounts, individual accounts), reducing allocation complexity through standardization while improving cost recovery capability across the entire organization.
Data Source
AI summary
A system and method that allows for information relating to data and communication resource usage to be gathered and analyzed such that particular data transactions and usage can be classified based on purpose and/or type. Further, the system and method provide reporting based on amount of usage and/or purpose or type of usage so that associated costs and usage can be calculated applied and allocated to particular accounts, divisions, groups or individuals within and outside of a company or entity. Further, the system may restrict data usage of devices to data usage that can be allocated to particular accounts based on purpose, source, destination or other.