Analytics play a vital role from the early stages of planning and design. For example, by leveraging analytics early on, carriers can prioritize locations and define deployment parameters with the most potential to generate revenue. This enables providers to be more purposeful with their resources, minimizing the risk of deploying expensive network assets in unsuitable regions.

Once the network is operational, data analytics can help carriers optimize business outcomes and customer experience. Cohesive analytics from planning through operations equip carriers to react better to changes, challenges, and opportunities. Carriers can pull analytics from multiple sources, including customer data, third-party data, and network-generated data, to pinpoint areas of concern and optimization in the network, operations, and services layers. Benefits include a more personalized customer experience, better managed supply chain, informed financial decisions, and improved quality assurance.

The integration of analytics throughout the network lifecycle enables CSPs to gain a comprehensive understanding of their operations and customer behaviors. This holistic view allows for more effective decision making and the ability to anticipate and respond to market trends and customer demands.

For example, the 3GPP Network Data Analytics Function (NWDAF) standardizes data collection and consumption within the 5G standalone core network. This enables use cases designed based on expected outcomes and anomalies while monitoring network slice load levels. Examples include Quality of Service (QoS) sustainability, service experience computation and prediction, user equipment mobility analytics, expected behavior prediction, and more.

By embedding analytics into the core of their operations, CSPs can unlock new opportunities for service innovation and differentiation. This data-driven approach empowers CSPs to deliver more targeted and relevant services, enhancing customer satisfaction and garnering loyalty.

Adding Agility Through Automation

Automation is critical to leveraging analytics effectively. The volume and velocity of data being generated is increasing, requiring advanced methods for extraction, cleaning, and analysis. Automation efforts were previously designed around specific outcomes or rules-based approaches, but today’s insights-driven systems analyze all data — an unmanageable task without automation. Providers should look to hyperscalers and the open source community for tooling and services, as well as disciplines and practices.

With the 5G network operational, new revenue opportunities will arise. Insight-driven analytics can marry customer data with operational and network data to answer critical business questions. Automation creates a more agile approach for the business and can shape strategy. As CSPs compete in the enterprise space and meet consumer demands for instant gratification, automation will be crucial. A cloud native, service-based architecture lays the foundation for a data flow that enables an insight-driven system, potentially eliminating the need for human intervention.

Despite the capabilities of automation, skilled professionals in data science and engineering remain essential. Operators must identify the right team, environment, and intent, coupling data scientists with network engineers for success.

Automation also enhances operational efficiency by streamlining routine tasks and processes. This reduces the burden on human resources, allowing them to focus on more strategic and value-added activities. Automation can improve network performance by enabling real-time monitoring and adjustments, ensuring optimal service delivery.

Furthermore, automation plays a key role in supporting the scalability and flexibility of networks. As demand for services fluctuates, automated systems can dynamically allocate resources to meet changing requirements. This adaptability is crucial in maintaining service quality and meeting customer expectations in an increasingly competitive market.

Conclusion

In order to thrive in the evolving telecommunications landscape, CSPs must embrace cloud native frameworks, open industry standards, analytics/AI, and automation. These foundational elements enhance operational efficiency and scalability, enabling CSPs to innovate and create value in transformative ways. By doing so, CSPs can stay ahead of the competition, meet enterprise market demands, and secure a prosperous future in the communications industry.

Adopting a cloud native approach provides the flexibility and scalability needed to support new services and applications. Open industry standards ensure interoperability and collaboration, fostering innovation across the sector. Analytics empower CSPs with valuable insights for informed decision-making, while automation streamlines operations and enhances efficiency.

By integrating these elements, CSPs can build a robust and agile infrastructure that supports continuous innovation and growth. This strategic approach not only addresses current challenges but also positions CSPs to capitalize on future opportunities in the ever-evolving telecommunications landscape. The future of communications lies in the ability to adapt, innovate, and deliver exceptional value to customers and partners alike.