In recent years, we have seen the evolution of technology like never before. The dawn of Artificial Intelligence and Machine Learning ensures that technology is meant to make us work smarter by handling all of the time-consuming, laborious tasks consistently. Due to this, many companies opt for the automation of various business operations across departments.
Even the Network Operations Center (NOC) can’t shy away from automation as it needs to be done to improve the efficiency and effectiveness of NOC management. No matter how big your NOC team is or what NOC monitoring practices you have incorporated into your IT infrastructure, NOC automation is the way to go. It is an effective way of analyzing and filtering data stored in the IT environment.
Engineers could never deal with a plethora of data in IT environments. That’s where AIOPs, Artificial Intelligence for IT Operations, realizes its purpose. With AIOPs, IT-based businesses can effectively automate their NOC support by extracting essential data from their network management system with the help of machine learning systems.
As its name suggests, NOC automation is adding tools and processes in network management systems to make NOC management more machine-oriented. Currently, engineers of the NOC team monitor and resolve the day-to-day network management issues that may arrive for various reasons. With NOC automation, programming machines can do NOC monitoring more efficiently.
NOC automation can only benefit various companies’ existing network management systems. Activities like matching the alert data, raising tickets, and notifying the concerned individual about NOC support can be handled more efficiently and effectively. That being said, it can partially replace the NOC team for the better in the future and assist us in making an advanced network management system.
Typically, the network operations center (NOC) has served as a curator, ensuring the network runs smoothly with minimum interruptions and outages. The company usually regards it as a business enabler tasked with preventing crucial outages and resulting revenue loss.
However, shifting market dynamics indicate that the NOC’s position will go from that of a troubleshooter to that of an enabler of business change. However, carriers must develop a change plan for their NOCs to re-evaluate their objectives to meet shifting demands and stay relevant.
The key to generating new income is network optimization and improvement; Chief Experience Officers (CXO) are concentrating on spending money on network upgrades and enhancements, especially 5G, which will serve a wide variety of applications with very different service needs. A correspondingly advanced, agile, and customer-centric organizational setup will be necessary for complicated network settings and sophisticated services.
As a result, the NOC must step up, reorganize, and adapt to shifting business objectives. To place the NOC as a facilitator of business change, it must change from a support activity to a proactive one, performing various tasks with distinct KPIs.
Transformation efforts should concentrate on three critical areas:
1. Organizational framework
2. Technology, and
3. People and talent types.
All three areas must be handled concurrently to move the NOC up the development slope. For instance, moving the Tier 1 NOC towards an automatic thin layer requires the effective implementation of new tools to achieve zero-touch processes, which requires the NOC team to have technological expertise and change management experience.
In the NOC, telecom companies generally have a tier-based system with a big agent workforce. Each layer works diligently to improve network uptime while minimizing the consumer effect. However, to be successful in the future, the NOC must be structured differently, with thin borders, working more widely, and high automation and digital powers. Figure 3 compares conventional and future-fit NOC models and outlines genuine transformation efforts.
In reality, various responsibilities and capabilities may be needed, team compositions may change, and the working model may be modified to reflect the NOC’s new strategic planning. All of these shifts should be viewed as obstacles to be overcome to transform the company and create new business possibilities.
However, they may be viewed as threats by the employees involved, such as apprehension about the unknown, loss of position or employment, uncertainty due to a lack of competence, pressure to produce results, and a lack of faith or conviction in the desired future. Management plays a significant role in this, and its participation in administration is a crucial success element.
As technology evolves and businesses become increasingly reliant on digital infrastructure, the demands placed on Network Operations Centers (NOCs) continue to grow. In response, automation has emerged as a critical component of the modern NOC. By automating routine tasks and leveraging machine learning algorithms, NOCs can free up their staff to focus on more complex issues and improve their overall efficiency. But what does it take to build a truly automatic NOC? In this section, we’ll explore three key factors that can help drive the transition from a reactive to proactive NOC:
The network must automatically identify and address service-impacting incidents in real-time, and the NOC-required procedures. Better yet, something that can stop events from happening in the first place. Responding to negative occurrences or consumer tickets could be more effective and affordable. Using automation and machine learning, you can improve your ability to anticipate and stop problems before they happen.
After data has been consolidated onto a single platform, you must rapidly identify, examine, and address the underlying causes of service-impacting occurrences. A system can assist you in eliminating and suppressing massive quantities of noise to ensure that your operations department always responds appropriately to events that generally result in impacted services.
You can use ML and event analytics to normalize data and ensure correct patterns are put into the ML engine by combining industry-standard ML techniques with specific data filters.
The answer uses these data sources to identify abnormalities such as time deviations, statistical rarities, and uncommon behaviors to produce a single underlying causal event.
Any network operations team’s ability to rapidly compile and process information is essential to their performance. Only now, Managed Service Providers (MSPs), Communication Service Providers (CSPs), and other businesses have battled to swiftly and correctly depict their growing networks in a single view, depending on outdated tools and manual practices to watch crucial network functions and services.
As a result of mergers, siloed apps, an abundance of inventory control, and shattered network infrastructures, there are now major visibility holes for the NOC, which has a negative effect on output and raises costs.
The scope of change required would differ for each company because there is no “one size suits all” strategy, but the NOC should not be afraid to set lofty objectives. The change blueprint should include several specific initiatives for general purposes and be planned in stages. There should be measurable benefits at each step, especially the NOC advancing up the maturity curve.
Finally, the NOC transition should be regarded as a journey rather than a goal, as it can develop along the road. The defined plan should be evaluated and adjusted regularly to stay pertinent to new technology and company requirements.