Dynamic Charge Computation for Billing Cycle Peak Load Reduction
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Solution Overview
Problem
Current billing systems face peak loads and delays due to end-of-cycle computations for charge verification and unbilled revenue reporting, which can lead to resource constraints and inefficiencies.
Innovation Solution
Implementing dynamic charge computation methods that calculate charges in real-time as changes occur, allowing for continuous computation and verification throughout the billing cycle, rather than at its end, thereby reducing peak loads and enabling immediate error fixes and unbilled revenue adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If charge computations are performed at the completion of billing cycles, then billing accuracy is improved, but system peak load increases and processing delays occur
Solution Approach 1:
The system performs charge computations incrementally as events occur throughout the billing cycle, rather than waiting until the end. This preliminary action distributes the computational workload across multiple time points, preventing peak load while maintaining billing accuracy through continuous updates to the charge data model.
Solution Approach 2:
The billing cycle is segmented into multiple computation events triggered by specific actions (e.g., service activation, modification, deactivation). Each segment processes only the charges relevant to that event, dividing the overall computational burden into manageable portions that can be handled without causing system peak load.
2Measurement precision
If bill verifications are performed after end-of-cycle computations, then verification accuracy is improved, but error detection and fix time increases
Solution Approach 1:
Verifications are performed preliminarily at each charge computation event throughout the billing cycle, not just after all computations are complete. This allows errors to be detected and corrected incrementally as they occur, reducing the overall time to identify and fix issues while maintaining verification accuracy through consistent validation rules.
3Productivity
If multiple billing cycles are used to accommodate large customer bases, then billing capacity is improved, but computational complexity increases
Solution Approach 1:
A single unified charge data model and computation framework is used across all billing cycles and customer segments. This universal approach allows the system to handle large customer bases without requiring separate complex processing logic for each billing cycle, reducing overall system complexity while maintaining high billing capacity.
Data Source
AI summary
As described herein, a system, method, and computer program are provided for dynamic charge computation. In use, a change made to a subscription of a customer is detected, wherein the subscription is associated with a billing cycle. Further, responsive to detecting the change and prior to an end of the billing cycle, at least one charge is computed for the subscription.