POSTED ON 19 JUL 2022
READING TIME: 7 MINUTES
For some people, the term Network Operations Centre (NOC) might conjure up images of a control room from a seventies sci-fi film. Picture a room filled with giant screens, where people in beige shirts panic whenever a flashing light comes on.
That’s a far cry from the new generation of intelligent Network Operations Centres (iNOCs), which are no longer reactive centres where operators simply respond to alarms. iNOCs now help operators maintain network performance, anticipate infrastructure problems and inform investment strategy.
Network operators can now access more data than ever before. Making sense of that data can be a challenge, especially in a busy NOC. Throw in technological advances and changing customer habits and it’s easy to see why many teams are making the transition to a more data-driven approach. This uses the latest machine learning and AIOps tools to automate low-risk tasks and unlock new insights with predictive analytics.
A traditional NOC allows a technical team to identify potential threats and review the performance of your network. Specifically, it lets them:
That was once enough, but telecom operators now face new challenges, like storing and processing higher data volumes from increasingly diverse sources. That includes data from streaming sites, IoT services or over-the-top apps like WhatsApp and Facebook across a variety of connected devices.
In some cases, NOC teams are using data architectures that weren’t designed to handle such data volumes. A different approach is required to optimise the performance of a modern telecom ecosystem - one that takes advantage of efficient, highly-scaleable cloud infrastructure and next-generation tooling.
An iNOC can see all nodes, network applications, services and technologies, giving it a 360 degree view of the network and services. This makes it an invaluable source of data for network health assessment and planning. Better insights ultimately lead to improved efficiency and performance, and happier customers.
Traditional NOCs react well to inbound incidents but iNOCs take a proactive approach by anticipating potential threats before they happen. Remember that sci-fi film set? What if the lights flashed a week before an issue arose? If you knew when and where additional support would be required, service assurance teams could address a problem before it became a problem.
Modern networks have multiple technology layers that cooperate but operate independently. This makes traffic patterns difficult to forecast and challenging to decipher, even when working with seemingly simple KPIs. For example, the relationship between dozens of underlying technical metrics influences congestion, jitter, delay and packet loss.
An iNOC needs to be able to dynamically interpret vast amounts of raw metrics from multi-technology environments to uncover useful insights. This lets it understand and anticipate a network’s underlying patterns of behaviour to identify current or future problems. That’s where data science and machine learning models can help operators extract data from multi-vendor systems, predict trends, identify problems, assess customer impact and facilitate early intervention.
A modern iNOC uses AIOps tools and data science to better understand service performance and traffic flow (changes in traffic flow characteristics can point to deep-seated problems with the network or other third party issues). Here are a few examples:
An iNOC provides more detailed, granular views that allow technical teams to monitor and analyse system performance, preemptively tackling issues that could impact services. The evolution of data analytics and data science has resulted in new and inventive ways to identify warning signs or network issues. This helps to avoid service-level agreement breaches, which can result in costly penalties or reputational damage.
We know that network congestion or disruption can test customer loyalties. Consistent speeds and connectivity topped households’ wishlists in a recent EY Digital Home survey. Almost a third of respondents said they would pay more for backup connectivity. Addressing connectivity problems at source will keep your network operating at an optimal level, which ultimately improves customer retention.
An effective iNOC should:
The move to an iNOC can be a catalyst for organisations to transform their operating model and embrace digital transformation. It lets you adopt a proactive, data-driven approach that can require a cultural shift as much as a technological one. It can therefore be a challenge, requiring people and technology to work in harmony, with a clear operational strategy in place to support the transformation.
Not only can VisiMetrix predict traffic congestion and inefficiencies within their network, but it combines network performance visualisation, monitoring and analytics on a single platform, enabling end-to-end service management. It can extract data from multi-vendor systems, predict trends, assess customer impact and facilitate early intervention.
Other communication service providers are also taking steps to evolve their NOC. Each organisation has unique challenges and specific goals. The key is to understand your customer’s behaviour and how they interact with your services.
Evolving toward an iNOC will help you to manage that information and decide what to do with it. Improved analytics, better predictive modelling, data-driven insights, better network traffic flow – the tools to give your organisation a competitive edge already exist.
It’s a significant departure from the reactive NOCs of the past. iNOCs help you make proactive decisions based on more reliable information. That can serve your organisation and your customers, both now and in the months or years ahead.
If you want to know more about becoming an iNOC or adopting the technology to make the move, get in touch with us. We can discuss your needs, answer any questions, or provide a demonstration of VisiMetrix.