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Telecommunications networks are becoming increasingly complex. The expansion of 5G, the evolution towards more open architectures, the growth in data volume, and the need to offer highly available services mean that manual operation or operation based exclusively on traditional monitoring systems is no longer sufficient.
In this scenario, the need arises to develop increasingly autonomous networks capable of identifying abnormal situations, analyzing information, making decisions, and executing actions automatically. But before investing in new tools and technologies, it’s essential to know what is the current level of network autonomy and what are the main gaps that need to be eliminated?.
It is precisely in this context that the Measurement and Optimization of Telecom Network Autonomy.
What is Network Autonomy Measurement and Optimization?
This is a structured approach to assess the level of autonomy maturity of a telecommunications network, identify opportunities for evolution, and establish a plan to progressively increase its capacity to operate in an automated and intelligent way.
The goal is not simply to verify if a network has automation. It is necessary to analyze how much of the operation is manual, assisted, automated, or effectively autonomous?, considering different processes, technologies and infrastructure domains.
For this purpose, international references can be used, such as the model.Autonomous Network Levels (ANL) from TM Forum, which offers models, methodologies, and tools to assess network maturity and guide its evolution.
Why measure network autonomy?
A company can possess various automation tools and still exhibit a low level of autonomy.
This happens because autonomy depends on the combination of several elements: processes, systems, integration, data, artificial intelligence, orchestration, decision-making capacity, and automated execution mechanisms.
Measurement allows you to identify the organization’s true situation and answer important questions:
- Which operations still require manual intervention?
- Which processes are already automated?
- Can the network detect and correct faults automatically?
- Can systems make decisions based on data?
- Is there integration between different network domains?
- Which investments should be prioritized?
With this information, the company can direct its investments to the areas that truly need improvement.
How does the evaluation process work?
Measuring and optimizing the autonomy of telecom networks can be structured in different stages.
1. Initial diagnosis
The first step is to understand the current state of the network and its operational processes.
Aspects related to operation, monitoring, provisioning, fault management, system integration, and the use of automation and analytical intelligence resources are analyzed.
This step allows you to identify the existing level of maturity and establish a benchmark for further development.
2. Team training
The teams’ knowledge is fundamental to the success of the evaluation.
Therefore, the methodology may include training in the fundamentals of ANL, Intention-Driven Autonomous Networks (IDAN) and Fundamentals of AI and Automation with ODA allowing professionals to understand the concepts used in measurement and participate more effectively in the process.
3. Measuring maturity
The next step involves applying metrics and indicators, including theKey Effectiveness Indicators (KEIs).
Among the aspects that can be evaluated are:
- Response time to events;
- Provisioning automation;
- Fault detection capability;
- Self-healing capacity;
- Use of artificial intelligence;
- Integration between systems;
- Capacity for process automation.
The assessment can be carried out in different infrastructure domains, such as RAN, Transport, Core, IP and Cloud.
4. Benchmarking
Comparison with international benchmarks helps the organization understand its position in relation to the market.
Models such as ANL e ANLET do TM Forum can support this process by allowing the identification of opportunities and the establishment of more consistent development goals.
5. Evolution Plan
After identifying the gaps, a technological and organizational roadmap is developed.
This plan may include investments in:
- Orchestration;
- Machine Learning;
- Artificial intelligence;
- Systems integration;
- Process automation;
- Closed-Loop Automation;
- Predictive analytics.
The goal is to establish a gradual evolution aligned with business priorities.
What are the benefits?
The evolution of network autonomy can provide significant gains for operators and companies that depend on connectivity.
Among the main benefits are reduction of operational costs, greater reliability and resilience of the infrastructure, reduced incident response time, and greater agility in deploying new services.
Autonomy also allows the company to move from a predominantly reactive approach to a more proactive and predictive one.
Instead of simply responding to a failure after it happens, the network can use data and algorithms to identify degradation trends and allow actions to be taken before the problem affects the service.
Network autonomy is a business strategy.
It is important to understand that network autonomy should not be treated exclusively as a technological project.
A more autonomous network allows to operate with lower costs, grow with greater control, make decisions faster, and offer a better customer experience..
This aspect makes maturity measurement especially important. Before defining large investments in automation, artificial intelligence, or new platforms, the company needs to understand where it is and where it intends to go.
Who is it suitable for?
Measuring and Optimizing the Autonomy of Telecom Networks is primarily indicated for CSPs, ISPs, digital companies, industries that rely on IoT, and organizations that own critical networks..
This approach can also be applied to different infrastructure domains, not limited to RAN. Core, Transport and IP networks can also evolve towards higher levels of autonomy.
With the expansion of 5G and preparations for future generations of networks, this evolution is likely to gain even more importance.
Measuring and Optimizing Telecom Network Autonomy allows companies to transform technological evolution into a structured journey. Through diagnosis, training, maturity measurement, gap identification, and roadmap creation, the company can define priorities and advance consistently.
More than just automating tasks, the goal is to build networks capable of…to perceive, analyze, decide, and act., reducing reliance on manual intervention and increasing the efficiency, reliability, and quality of services.
For companies that want to evolve towards smarter and more autonomous networks, measuring their current level of maturity is the first step in defining a solid and sustainable transformation strategy.
