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Measuring ROI on Autonomous Networks

Telecom operators worldwide are investing heavily in autonomous networks; networks capable of self-monitoring, self-healing, self-optimizing, and self-configuring with minimal or no human intervention. Autonomous networks promise enhanced operational efficiency, faster service delivery, improved customer experience, and significant cost savings, positioning telcos to compete effectively in today’s digital landscape.

Defining Autonomous Networks and Measuring Levels

Autonomous networks are dynamic, self-governing systems leveraging AI and automation to manage network functions and services with minimal human oversight. To help telecom operators assess and benchmark their autonomous network levels, TM Forum has developed the Autonomous Network Levels Evaluation Tool (ANLET).

The TM Forum defines six levels (L0–L5) of network autonomy:

  • Level 0 – Manual management: the system delivers assisted monitoring capabilities, which means all dynamic tasks must be executed manually.
  • Level 1 – Assisted management: the system executes a certain repetitive sub-task based on pre-configuration to increase execution efficiency.
  • Level 2 – Partially Autonomous Networks: the system enables partial automatic O&M for certain units based on pre-defined rules or policies under certain external environments.
  • Level 3 – Conditionally Autonomous Networks: building on L2 capabilities, the system with awareness can sense real-time environmental changes, and in certain network domains, optimize and adjust itself to the external environment.
  • Level 4 – Highly Autonomous Networks: building on L3 capabilities, the system enables, in a more complicated cross-domain environment, analysis and decision-making based on predictive or active closed-loop management of service and customer experience-driven networks.
  • Level 5 – Fully Autonomous Networks: this level is the goal for telecom network evolution. The system possesses closed-loop automation capabilities across multiple services, multiple domains and the entire lifecycle, achieving Autonomous Networks.

(Source: Autonomous Networks Framework v2.0.0 (IG1218F), TM Forum)

These levels provide a structured roadmap, enabling telcos to evaluate their current “as-is” state, plan incremental advancements, and define their future “to-be” autonomous network goals aligned with strategic business objectives. It is worth noting that, from our experience, not all operators are aiming for Level 5, and that the immediate focus is on achieving practical levels of network autonomy (typically Level 3 or 4) in specific, high-value domains.

From Level Scores to ROI Metrics

While ANLET scores offer clear, quantifiable evidence of progress and a valuable benchmarking tool, these levels may not fully satisfy executive stakeholders who seek tangible business outcomes. This prompted us to conduct a preliminary analysis of multiple autonomous network pilot and real projects and identified recurring themes and metrics that telcos track to quantify their Return On Investment (ROI). These metrics, which sometimes overlap and vary by project scope, fall into four key categories:

[1/4] Operational Efficiency

This category captures how network autonomy accelerates operations and reduces manual workload:

  • # of Fault Tickets
  • Service Onboarding Time
  • Time Spent in Troubleshooting
  • Root-Cause Detection Speed
  • Ticket Handling Time
  • Repair Time
  • MTTR (Mean Time To Resolve)
  • Customer Support Interaction Duration

[2/4] Process and Workforce Automation

These metrics reflect network autonomy’s impact on workforce efficiency, which also contributes to operational efficiency:

  • % of Backend Manpower Replaced by AI Agents
  • % of Frontline Manpower Replaced by AI Agents
  •  % of Operations Performed by Agents
  • % of Automated Resolution Workflows
  • % of Manual Operations

[3/4] Customer Experience

Autonomous networks enhance customer satisfaction by minimizing downtime and elevating service quality. Key metrics include:

  • # of Customer Complaints
  • Complaint Pre-emption Rate
  • Customer Experience Improvement Scores

[4/4] Cost Optimization

ROI is markedly influenced by decreased costs and better resource utilization:

  • OPEX
  • CAPEX
  • SLA Credits
  • Cost of Ownership
  • Energy Consumption
  • Resource Utilization

Telecoms investing in autonomous networks have reported substantial ROI that transcends abstract levels. Here are some time savings, which contributed to enhanced operational efficiency, as reported by telecom operators:

↓ Service onboarding time, reduced by 95%
↓ Time spent in troubleshooting, reduced by 80%
↓ Repair time, reduced by 70%
↓ Ticket handling time, reduced by 25%
↓ Customer support interaction duration, reduced from 30 minutes to realtime self-service

And regarding MTTR (Mean Time To Resolve):

↓ MTTR in IP backhaul fault handling, reduced by 25%
↓ MTTR in RAN fault management, reduced by 27%
↓ MTTR in home broadband complaint handling, reduced by 50%
↓ MTTR in end-to-end complaint handling, reduced by 65%
↓ MTTR in core network fault handling, reduced by 87%

(Source: All data is from public case studies on autonomous networks published by the TM Forum).

While TM Forum’s ANLET scoring provides a valuable framework for telcos to plan and track their transformation journey towards Autonomous Networks, real business value is realized through measurable improvements in operational efficiency, workforce automation, customer experience, and cost optimization. By understanding and monitoring effective ROI metrics, telecom executives can confidently justify investments, steer transformation initiatives, and maximize the value derived from autonomous network deployments.

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