When it comes to 5G, its important to note that the functionality, the differentiation and the majority of the use cases that bring revenue happen at the core of the network. While the 5G core network presents somewhat of a minimal portion of the investment compared to the radio, there is immense value in utilizing automation and analytics in the 5G core to unlock crucial customer and operational insights.
By 2025, 5G networks are likely to cover one-third of the world’s population, with 1.2 billion connections. In fact, a recent IDC report forecast that within the next three years there will be 55.7B connected devices, and in that same time connected devices will generate 50 times the amount of data of the consumer internet. Essentially, in the next three years data generated globally will outpace the total data from the past three decades. With this in mind, we must build networks that are capable, flexible and efficient enough to support a multitude of different services — from small scale to hyperscale — and build an organization around it that can react quickly to deploy new capabilities for opportunities as they arise.
Further, as of January 2023, the GSA reports 243 commercial 5G launches worldwide with 112 operators investing in 5G standalone. This commercialization will lead to new B2C and B2B use cases, and as they do, operators will need to make sure they have the ability to scale capacity and flexibly change service levels and resources.
Automation is the only way to meet the imminent network, system and operational challenges in 5G. Historically, there were just voice and data services within networks, but today billions of events of data are generated daily from the many services we have running on the internet, supported by the telco network. Such massive volumes must be extracted from traditional sources such as network operations or customer management, and from new sources including the core of the network and any device or service ecosystem feeds, before being cleaned and analyzed. Pulling data assets from these sources and then completing analysis is a challenge. This is where automation is critical to leveraging analytics.
In the previous generations of mobile technology, automation tools were mostly rules-based and designed around one specific outcome for traditional workflow management applications and database. These systems are often based largely on vendor-specific applications and data models, operate in a silo and use only a subset of the data. Today’s insight driven systems however are built by looking at all the data — a colossal task that can only be enabled by automation.
Encouragingly, the standard bodies are furthering the industry’s progress with insight-driven analytics, 3GPP has now introduced analytics capabilities at the 5G core network level with new functionality such as the Network Data Analytics Function (NWDAF) — a 3GPP-defined function that runs within the 5G standalone core network. NWDAF standardizes how data is collected and consumed within the core network, enabling use cases that are designed based on expected outcomes and anomalies while monitoring network slice load levels. Just like the 5G standalone core network, NWDAF is built using a cloud native microservice architecture. This allows it to operate and collect data from the network functions in a standardized and streamlined way to deliver insights for reporting, solve interface challenges, or perhaps most importantly, enable automation.
Insight-driven analytics can marry customer data with operational and network data to answer the most important questions for carriers’ decisions around what they want to optimize and how to differentiate in the market. It can help identify where the best business park is to build fiber into, or what the next offer should be for a specific class of customer. Data can be used across different lifecycles of the network, and it can be mined to support any business objectives.
However, the automation journey for operators has its own set of unique challenges mainly the critical need for the skills of professionals in the data science and engineering industries. As a part of their journey to automation operators need to identify the right team, environment and intent which requires coupling data scientists with network engineers. The different skillsets brought from a cross-functional team will be necessary to success.
We are beginning to reach a point in the communications industry where the fabric of the network is not just programmable, but intelligent. It is promising to see the industry transforming as we are assembling the building blocks to automate operations across the core with capabilities eventually able to feed insights into the network and support optimization of policies and applications through predictive analytics.
As one of the first steps of this transformation, operators will need to embrace data-driven insights to make more informed business decisions based on trusted, historical data. As tools are leveraged to increase pattern detection with machine learning, operators will be able to determine predictions and make strategic decisions based on what’s to come. And finally, with analytics mastery, carriers will be optimizing operations by using trusted data pervasively, and enriching analytics with services that drive automation. And as the carrier automation and analytics journey evolves, mastering analytics will not only provide valuable business insights, but also recommend actions to higher level management tiers such as service orchestration or a service assurance platform. Ultimately, network operations will be fully automated.
As we think about 5G and all of the new abilities, experiences and revenue streams it will bring in the coming years it’s very clear that automation is at the heart of taking advantage of these opportunities. With the right implementation of tools, and automation, operators will be able to conquer the complexity, scale and diversity of the fifth-generation network.
The communications industry is moving into a new era — one with new customers – enterprises rather than consumers — new technologies in 5G and cloud, and entirely new approaches to working in order to deliver agile, fast service through analytics and data science. While this precipice of change can seem daunting, the outlook suggests it will be well worth the journey.
