Telecom Profitability Management via Billing Data Normalization
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Solution Overview
Problem
Telecommunications companies face difficulties in identifying profitability due to fluctuating prices from vendors and incorrect billing, leading to challenges in determining accurate profit margins.
Innovation Solution
A computer-implemented software application normalizes and validates billing data from disparate sources to calculate true profit margins by invoice, vendor, geographic location, customer, or circuit, using a parsing and normalization process that identifies key data and creates necessary fields for association with external data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If billing data is collected from multiple vendor sources, then comprehensive profitability analysis is enabled, but data format diversity and complexity increase
Solution Approach 1:
The patent introduces a normalization layer as an intermediary between diverse vendor data sources and the profitability calculation system. This normalization layer converts various vendor-specific data formats into a unified internal representation, enabling the system to handle multiple vendor formats without increasing core processing complexity. The normalization rules act as mediators that translate between different data schemas.
Solution Approach 2:
The data processing system is segmented into distinct modules: data collection, normalization, validation, and profitability calculation. Each module handles specific aspects of data processing independently, allowing the system to manage complexity through modular architecture. The normalization module separately processes format conversion, while the validation module separately checks data accuracy.
2Reliability
If manual billing verification is performed, then billing accuracy improves, but processing time and labor costs increase
Solution Approach 1:
The system performs self-verification of billing data through automated validation rules that check for logical inconsistencies, price anomalies, and formatting errors. The normalization process automatically aligns vendor data with expected formats and structures, enabling the system to verify its own data quality without requiring manual intervention for routine checking.
Solution Approach 2:
The validation module provides immediate feedback on billing data quality by identifying errors and anomalies in real-time. This feedback mechanism allows the system to correct billing inaccuracies automatically before they affect profitability calculations, maintaining high reliability while reducing the need for manual verification time.
3Loss of information
If detailed profitability tracking by multiple dimensions is implemented, then business insights improve, but data processing complexity increases
Solution Approach 1:
The normalized data structure serves multiple functions simultaneously: it stores billing information, validates data quality, provides the basis for profitability calculations, and enables analysis across multiple dimensions (customer, product, geographic, temporal). This universal data representation eliminates the need for separate processing pipelines for each analysis dimension, reducing overall system complexity while maintaining information completeness.
Data Source
AI summary
Billing data associated with telecom products provided by a variety of vendors is captured, normalized, and processed to calculate true profit margins by invoice, by vendor, by geographic location, by end-customer, by circuit, or combinations of these. A bill may be received from the vendor, and associated with a specific vendor profile. The vendor profile may include a validation routine specific to the vendor. A plurality of telephone numbers associated with an end-customer may be extracted from the bill based on the vendor profile and stored on a storage device. A previous bill from the vendor may be accessed in response to receiving the bill from the vendor. End-customer profitability may be determined for a first time period based on data extracted from the received bill and displayed.