The Challenge
PTCL operates Pakistan's largest fiber backbone spanning 5,000+ km, serving as the critical infrastructure for national internet connectivity, enterprise WANs, and wholesale carrier services. Network faults were being detected reactively through customer complaints, resulting in extended outages and SLA penalties.
Key Pain Points
- 1Average 4.2 hours Mean Time to Detect (MTTD) for fiber faults
- 2Manual fault correlation across 12 legacy monitoring tools
- 3PKR 45M monthly in enterprise SLA penalty payments
- 4No predictive capability for preventive maintenance
- 5Skilled NOC staff shortage with 40% annual turnover
- 6Fragmented visibility across transport, IP, and access layers
- 7No unified view for management dashboards
Business Impact: Extended MTTD was causing average 6-hour outages affecting thousands of enterprise customers. PTCL was paying PKR 45M monthly in SLA penalties and losing large accounts to competitors with better reliability.
The Opportunity
A modern, AI-powered NOC could transform PTCL's operations from reactive to predictive, dramatically reducing MTTD and enabling preventive maintenance before faults impact customers.
Project Scope
End-to-end monitoring of PTCL's national infrastructure: 5,000+ km fiber backbone, 200+ PoPs, 15,000+ enterprise circuits, and integration with regional NOCs across all four provinces.
The Solution
HNL designed and operates a state-of-the-art Network Operations Center with AI/ML-powered fault detection, automated correlation, and predictive analytics. The solution unified 12 legacy tools into a single pane of glass with intelligent automation.
Unified Monitoring Platform
Integrated all 12 legacy monitoring tools into a unified platform providing single-pane-of-glass visibility across transport (DWDM), IP/MPLS, access networks, and customer CPE.
AI-Powered Fault Detection
Deployed ML models trained on 3 years of historical fault data to detect anomalies before they become outages. The system identifies degrading fiber spans, failing equipment, and capacity bottlenecks.
Automated Event Correlation
Smart correlation engine that analyzes thousands of alarms and identifies root cause within seconds, reducing alarm noise by 85% and presenting operators with actionable insights.
Predictive Maintenance Engine
ML models predict equipment failures 2-4 weeks in advance based on performance trends, enabling scheduled maintenance during low-traffic windows.
Tiered Response Framework
Structured escalation with L1 (monitoring & triage), L2 (technical resolution), and L3 (expert engineering) tiers. Clear SLAs and automated escalation triggers.
Executive Dashboards
Real-time KPI dashboards for PTCL management showing network health, SLA performance, capacity utilization, and trend analysis.
Technical Specifications
| coverage | 5,000+ km fiber backbone |
| Po Ps | 200+ Points of Presence |
| circuits | 15,000+ enterprise circuits |
| alarm Processing | 500,000+ alarms/day processed |
| M T T D | <5 minutes (from 4.2 hours) |
| correlation | 85% alarm noise reduction |
| staffing | 24/7 x 365, 45 FTE |
| tools | ServiceNow, SolarWinds, custom AI platform |
Execution Timeline
Phase 1: Assessment & Design
Months 1-3- Audit of existing monitoring tools and processes
- Network topology discovery and documentation
- SLA and KPI framework definition
- NOC facility design and equipment planning
- Staffing model and training curriculum development
- AI/ML model requirements definition
Phase 2: Platform Deployment
Months 4-6- Unified monitoring platform deployment
- Integration with 12 legacy tools via APIs
- Custom dashboard development
- Initial AI model training on historical data
- NOC facility build-out and equipment installation
Phase 3: Operational Go-Live
Months 7-9- Staff recruitment and intensive training
- Phased transition from PTCL's internal NOC
- 24/7 operations commencement
- Process refinement and playbook development
- AI model fine-tuning with live data
Phase 4: Continuous Improvement
Ongoing- Monthly AI model retraining
- Quarterly process optimization
- New circuit onboarding
- Technology refresh and tool upgrades
- Performance reporting and SLA reviews
Project Gallery
HNL's 24/7 Network Operations Center
Unified monitoring dashboard with AI alerts
National fiber backbone infrastructure
NOC platform infrastructure
The Outcome
Faster - MTTD reduced from 4.2 hours to <5 minutes
National fiber backbone monitored 24/7
Reduction in monthly penalty payments
Noise reduced through smart correlation
Failures prevented monthly through prediction
Average time to dispatch field team
Business Impact
"HNL's NOC has revolutionized how we manage our network. We've gone from finding out about outages through customer complaints to predicting and preventing them before they happen. The AI-powered correlation has been a game-changer - our operators now focus on real issues instead of drowning in alarms."
RRashid AhmedVP Network Operations, PTCL
Key Learnings
- AI/ML transforms NOC from reactive to predictive operations
- Tool consolidation dramatically improves operator effectiveness
- Automated correlation reduces alarm fatigue by 85%
- Predictive maintenance ROI exceeds monitoring cost within 6 months
- Tiered staffing model balances cost with expertise availability
- Executive dashboards drive organizational alignment on network quality