Field maintenance is a big component of those increased costs and reactive maintenance is expensive due to the stringent terms of service level agreements (SLAs). So as a first step towards AN, Telefónica Germany and Tech Mahindra implemented an AI-driven, cloud-based, predictive maintenance solution that uses a closed-loop mechanism. It can be used in multi-vendor and multi-domain environments.

It will gradually replace reactive maintenance operations with predictive operations, foreseeing and preventing problems to continuously enhance the network’s performance and availability.

The solution applies advanced correlation algorithms to structured and unstructured network data to predict potential network issues and trigger preventive actions. AI-assisted root cause analysis can pinpoint potential issues, down to a specific card or port on a network node, helping to predict failures that are beyond the capabilities of usual network monitoring systems.  

The solution analyses data sets like performance counters, topology, network configurations, customers’ complaints, and weather forecasts to continuously improve the accuracy of predictions.  

The solution is also integrated with Telefonica’s trouble ticket system for automatic ticket creation, supporting closed-loop network operations and enhancing operational efficiency.