Hybrid, virtual and cloud networks are becoming more difficult to operate effectively. Operations teams are being squeezed between increasing complexity—due to new technologies and massive scaling—shrinking budgets and the pressure to continually improve customer quality of experience (QoE) to minimize churn. Traditional tools for monitoring service assurance and network quality lack the required scalability and flexibility—and cost too much. A new paradigm is needed—one that embraces the open, dynamic, distributed nature of virtual and cloud networks, leverages machine learning (ML) and artificial intelligence (AI) to bring greater insight and speed to customer management and telecom network management—and does it all at a lower cost.
EXFO’s Nova adaptive service assurance platform is the industry’s first service assurance-centric automation platform. It automatically provides the right data at the right time to detect, diagnose and resolve —or predict and prevent—customer-impacting events originating from communications network infrastructure and services.
The Nova platform uses adaptive automation to automate time-consuming manual monitoring, diagnosis and decision-making processes that monopolize operations. This frees resources to proactively improve network performance and customer experience, and to deploy new services and revenue faster. It orchestrates the real-time interworking of EXFO solutions with existing monitoring, operations and network management systems, while adapting to the current context. It dynamically collects and analyzes the right mix of system, monitoring and telemetry data to perform real-time network monitoring and inform effective action.
Adaptive service assurance acts as a catalyst to help service providers evolve from simple process automation to realizing fully orchestrated, closed loop networks—unlocking value at each step on the journey.
The Nova adaptive service assurance platform delivers a diverse set of benefits across the entire service provider organization. Its unique ability to build customized workflows among state-of-the-art tools such as active and passive monitoring, real-time anomaly detection, topology modeling and correlation as well as AI-based analytics, make it an extremely powerful and flexible platform for everyone from operations to the c-suite.
By automating many of the routine operations tasks and time-consuming activities, such as root cause analysis or service activation testing, operators will be able to significantly improve efficiency and eliminate many unnecessary truck rolls. At the same time, by allowing staff in key-skill positions to remain focused on their primary jobs—rather than being called in to fight fires—service providers will be able to implement more preventative maintenance activities further reducing the need for expensive troubleshooting and repair.
Get the tools and solutions designed specifically with customer quality of experience management in mind. With the rise in importance of the service operations center (SOC) and the demands on customer care teams to prioritize VIP customers and critical services, having tools that provide visibility into even the smallest issues impacting services and automatically correlating issues to find common root cause will be key to keeping customers happy and reducing churn.
A significant area of focus for digitally-transformed carriers is the elimination of maintenance and provisioning errors introduced inadvertently through manual operations processes. Whether it’s a mistake in data entry or not following methods and procedures properly, the result is lost time and money due to inconsistent inventory data. Automation eliminates the issue of manual data entry errors and can guide technicians through complex processes to ensure consistent results.
By automating many of the error-prone activities of service instantiation and provisioning, and by automating the ongoing monitoring of service and network quality, carriers can deploy services faster and with greater consistency. Also, they can detect and correct issues, possibly even before the customer notices, leading to a better, more consistent quality of experience. And when issues do arise, they have the ability to proactively engage customers to keep them better informed.
By automating many of the manual processes to improve consistency of implementation—as well as automating fault detection, identification and customer impact—carriers will be able to better manage customer QoE, reduce churn and justify premium rates for premium services.