2022 • 8 Months • 5 Specialists

Telecom Billing & Collections Analytics Transformation

Revolutionizing revenue assurance through advanced KPI design, automated reporting, and intelligent anomaly detection

34%
Bad Debt Reduction
12 Days
DSO Improvement
75%
Time Saved
94%
Detection Accuracy

Client: Major Telecom Operator

Multi-billion dollar telecommunications provider serving 15M+ subscribers across diverse market segments

Business Context & Challenges

Complex billing ecosystems require sophisticated analytics to maintain financial health and operational efficiency

📊

Manual Reporting Burden

40+ hours monthly spent on manual data compilation and report generation across departments

🔗

Fragmented Data Systems

12 disparate billing systems creating data silos and inconsistent metrics definitions

⚠️

Delayed Anomaly Detection

Payment irregularities identified days after occurrence, limiting recovery opportunities

📈

Inconsistent KPI Framework

Varying definitions of key metrics across departments hindering unified decision-making

👁️

Limited Collections Visibility

Insufficient real-time insights into collections performance and risk exposure

Strategic Actions & Methodology

Comprehensive approach combining KPI standardization, automation, and intelligent detection systems

1

KPI Suite Design & Standardization

Designed comprehensive KPI framework focusing on bad debt percentage, DSO trends, and DPD analytics with standardized definitions across all business units

Bad Debt % Days Sales Outstanding Days Past Due
2

Reporting Automation Implementation

Implemented end-to-end automated reporting pipeline, reducing manual effort by 75% while ensuring 99.2% data accuracy through robust QA frameworks

ETL Pipeline Auto-Generation QA Framework
3

Enhanced Anomaly Detection

Developed real-time anomaly detection system for payment patterns, reducing response time from 5 days to 2 hours with 94% accuracy

Real-time Monitoring Pattern Recognition Alert System
4

Executive Dashboard Creation

Created interactive executive dashboards with drill-down capabilities, providing unified visibility across all collections and billing operations

Interactive Dashboards Drill-down Analytics Executive Views

Impact & Quantifiable Results

Transformational outcomes across operational efficiency, risk reduction, and financial performance

4.2% → 2.8% Bad Debt Reduction

34% improvement in bad debt management through enhanced analytics and early intervention

45 → 33 Days DSO Improvement

27% reduction in Days Sales Outstanding, accelerating cash flow significantly

40 → 10 Hours Reporting Time

75% reduction in monthly reporting effort through comprehensive automation

5 Days → 2 Hours Response Time

98% faster anomaly detection and response capability

Return on Investment

ROI achieved within 6 months of implementation

Comprehensive analytics transformation delivering sustainable competitive advantages in revenue assurance and collections efficiency

Proof Artifacts & Deliverables

Professional documentation and visualization assets demonstrating solution depth and quality

Executive KPI Dashboard

Billing & Collections Analytics
Real-time • Updated 2 min ago
Bad Debt %
↓ 34%
2.8%
DSO Trend
↓ 12d
33 Days
DPD Analysis
Improving

Automated Reporting Pack

Monthly Collections Report
September 2022
Executive Summary
Collections Performance: +15% vs Target
Risk Exposure: Medium
Automation Coverage: 87%

QA Framework Checklist

Data Quality Assurance
Data source validation (12 systems)
KPI calculation accuracy verification
Anomaly detection threshold validation
Report generation automated testing
Dashboard refresh and accuracy check

KPI Dictionary Excerpt

Bad Debt Percentage
Definition: Percentage of total receivables written off as uncollectible
Formula: (Bad Debt Write-offs / Total Receivables) × 100
Frequency: Monthly calculation, weekly monitoring
Days Sales Outstanding (DSO)
Definition: Average number of days to collect receivables
Formula: (Accounts Receivable / Revenue) × Days in Period
Frequency: Daily tracking, monthly reporting