Operational Excellence: The Engine Room of Innovation

A culture of bold innovation flourishes only when built on a solid foundation of operational excellence. For Sunrise, this means finding the right balance between the speed of change needed to stay competitive and the stability and reliability that customers expect. The environment presents a significant challenge, with teams implementing thousands of network changes each month.

An integrated quality framework ensures that every action, from major technology rollouts to routine maintenance, is evaluated based on its impact on the end-user experience. “We always ensure that every single intervention in the network, whether it stems from innovation and development or from maintenance and incident management, is assessed for its effect on user experience and satisfaction, for both residential and B2B customers,” Fabrizio states.

To navigate the complexity at scale, Sunrise is increasingly investing in intelligent automation. “We’re investing in automation, AI, and machine learning to enhance human expertise. This enables quicker anomaly detection, smarter root cause analysis, and more efficient resolutions. It’s about scaling innovation without sacrificing stability,” he adds.

A Pragmatic Journey into AI and a Vision for the Future

Looking ahead, the next frontier in enhancing customer experience lies in the intelligent use of AI and machine learning. Sunrise has embarked on this journey with a clear and pragmatic focus: leveraging data to transition from reactive problem-solving to proactive and predictive service quality management.

Sunrise’s initial pilots have already yielded valuable insights. “One of the most significant lessons from our early initiatives has been the power of telemetry, extracting anonymized technical parameters from customer devices, correlating them with optimal values, and automatically enhancing mobile connectivity or in-home setups without any customer interaction,” Fabrizio observes.

However, he acknowledges that the true challenge lies not in deploying the technology itself but in achieving effective organizational adoption. “The real challenge with AI and machine learning is not merely the introduction of a new tool but its effective adoption. The focus must remain on the objectives: enhancing customer experience, strengthening network reliability, and driving operational efficiency, without letting the tools themselves become distractions.”

Fabrizio cautions against what he refers to as the “reality-hype gap,” emphasizing the importance of keeping the ultimate goal in focus: tangible improvements in both customer experience and operational efficiency. Such a pragmatic approach will guide how Sunrise leverages its extensive data resources to create a more intelligent and responsive network.

So, what does this mean for the typical Sunrise customer in the coming years? Fabrizio envisions a clear picture of a seamless and reliable future: “AI will enable us to observe service performance in greater depth, uncovering patterns of hidden defects in network services or hardware that would otherwise go unnoticed or be masked by telemetry noise. It makes fixes and improvements significantly more efficient.”

Sunrise is further enhancing how it monitors the network and correlates alarms and issues. The goal is to detect interruptions and identify root causes much more quickly and in a more automated manner, proactively maintaining and repairing infrastructure before outages or degradation lead to service interruptions.