How can predictive analysis unlock the potential of 5G?

Last updated: 12 July 2021

The discussion around the key benefits of 5G is nothing new. Whether it’s the hyper-fast download speeds, low latency or its ability to unlock the full potential of smart technology, we have all come to understand what we can expect from the next generation of mobile connectivity.

However, there is one aspect of the 5G revolution that has been somewhat underappreciated – the increased quantities of data which mobile network operators (MNOs) will have access to. MNOs already process unfathomable quantities of data. But with the number of 5G users predicted to reach 4.14 billion by 2025, the quantity of data produced is set to reach new levels.

While MNOs will need the right tools to process this unprecedented level of data, the opportunities for predictive analysis using this data could be key to unlocking the potential of 5G. Here are three data-driven benefits that 5G presents to MNOs and their customers:

Improved user experience

Network operators are changing their approach from reactive to predictive and the customer experience is a key source of differentiation for the MNOs. This is driving a shift towards a ‘customer-centric’ operations that is very focused on delivering superior customer experience. But this shift isn’t just about providing a smooth network performance. It encompasses the implementation of a more complete data-driven approach to operations. Data is defining the operating model for MNOs. Simply put, MNOs need data to help manage their customers.

The increase in data from 5G also means that MNOs will receive much deeper insight into their consumers’ behaviours across a wide range of activities. What’s more, with the dramatic increase in IoT devices in both corporate and consumer settings, MNOs are getting unprecedented insight into how each user is experiencing and interacting with their network and services.

As a result, this data offers MNOs the opportunity to be more responsive and accurate when improving the user experience. By using real-time data, MNOs can quickly respond to network related issues when they occur, while also being able to optimise their users’ network experience to fit their needs.

Enhanced system functioning

Core to a MNO’s service is ensuring that their network is reliable. Particularly in a time where connectivity has truly become an invaluable resource, the pressure on MNOs to run a seamless mobile network service is greater than ever. And while problems are inevitable, anticipating and preparing for these problems could go a long way to ensuring that a MNO’s network runs as smoothly as possible.

This is where predictive analysis using 5G network data comes in. With the right solutions, data can be analysed to diagnose and fix operational issues in real time. What’s more, MNO’s can feed this data into algorithms to create automated solutions that optimise operations and flag network problems. Instead of waiting for problems to arise, MNOs can use this data to perform predictive maintenance on a network, allowing them to stay ahead of potential oncoming issues.

Intelligent Automation

Network traffic growth is driven by both the rising number of mobile subscriptions and an increasing average data volume per subscriber, fed by increased viewing of video content. In a dynamic network, operators find it challenging to relate low-level network performance metrics to a customer’s experience in real time, thus impairing an MNO’s ability to take timely decisions and subsequent necessary actions. And with the increase of encrypted data, operators have challenges in understanding their subscribers’ Quality of Experience (QoE). This means that service degradation can occur and go unnoticed by the operator. When this happens, especially with subscribers that heavily use OTT applications available on other networks, subscribers will blame the operator. They could churn even though a 3rd party provides the overall service.

Monitoring all this data and pinpointing to a customer-affecting network degradation is like looking for a needle in a haystack. It is apparent that for 5G, the traditional telecom network operation tools and the existing mode of network problem resolution based on an aggregated view of network quality is not sufficient. 5G requires an intelligent and more automated network. MNOs need AI-driven automation and micro-segmented view of service quality for successful operations.

By leveraging Machine Learning (ML) and Artificial Intelligence (AI) algorithms, MNOs can gain accurate, real-time, application-level visibility into what is happening in their network and understand their subscribers’ quality of experience. Streaming service degradations show in real time, what constitutes a normal versus aberrant experience at a micro-segment level, resulting in true customer impact reporting. Service Fingerprinting and Autonomous Anomaly Detection can automatically identify fingerprints per service from all RPIs (real performance indicators). Customer segmentation creates multiple levels of granularity to detect streaming service degradations within those segments. This enables network, service and care operations to proactively address customer-impacting network problems and prevent network-related churn. Ultra-fast orchestration will accelerate problem resolution to reduce customer churn by learning what’s normal and providing insights before network issues become customer issues.

The deployment of 5G networks signifies a new dawn in the telecoms industry. It will change the game, not only in terms of business opportunities but also in the skills needed to process and protect the new quantities of data flowing between users. Through using predictive data analysis, MNOs can position themselves to reap the benefits that 5G offers while best serving their customers in the process.

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