New customer experience use cases take us closer to customer-centric zero-touch networks

Of all the advances in mobile technology resulting from 5G, among the most revolutionary is zero-touch networks: AI and automation so advanced that they can detect and correct network faults with minimal human intervention, enabling higher-performance 5G customer experience, and with it next-generation digital services across the globe. Yet developing and implementing zero-touch networks is far from straightforward. The industry must implement it while facing critical challenges such as the management and operation of increasingly complex networks, which are in turn compounded by new open architectures, virtualization, and 5G’s rapid evolution, among other pressures.

To help address these issues and accelerate the journey towards zero-touch, Telefónica has established the Autonomous Network Journey Program. One of the initiative’s key objectives is to understand how zero-touch could be implemented in, and overcome, this complex context – to anticipate customer pain-points and proactively implement autonomous solutions before any service degradation occurs.

This objective has since been extended and shared with the wider industry via the Autonomous customer experience index for zero-touch 5G network – Phase II Catalyst. Building on its first phase, which developed the customer-centric 5G network environment, Phase II further advances zero-touch by implementing a trusted customer experience index (CEI) calibrated with crowdsourcing data. This data is processed in conjunction with AI and ML techniques to automatically change radio network configuration and intervene to guarantee customer experience required values.

Customer experience zero-touch use cases

The solution has been tested against three use cases using data from Telefónica’s 5G network:

• CEI calculation of a trusted and customer-oriented KPI using network data and crowdsourcing. Here the CEI acts as a key performance indicator with a value between 0 and 100, making it easy to visualize, and provides a measure that accurately and reliably represents the real customer’s perception of the quality of experience. The crowdsourcing data is then used to validate and calibrate the CEI so that the final result is as close as possible to customer perceptions.
• Anomaly detection – the goal in this use case is to use the CEI to identify and autonomously correct real-time network issues causing degradation in the quality of experience perceived by the customers.
• Dynamic planning – this use case is designed to enable dynamic network planning based on CEI indicators which use network slicing and ML and AI technologies to trigger network configuration and resource allocation.

The success of this Catalyst is taking the industry closer than ever to the realization of customer-centric autonomous networks, helping to usher in a generational shift in customer experience. According to Julia Martinez Arenas, Customer Experience Manager and Global CTIO at Telefónica, “with this Catalyst we can improve customer experience by proactively acting before any service degradation occurs and, in the process, significantly reduce churn and create a much more cost-efficient operation.”

To learn ore about TM Forum Catalysts, visit tmforum.org/catalyst