{"id":9069,"date":"2024-11-14T09:47:00","date_gmt":"2024-11-14T09:47:00","guid":{"rendered":"https:\/\/www.gsma.com\/get-involved\/gsma-foundry\/?post_type=gsma_theme_resources&p=9069"},"modified":"2025-09-19T11:49:12","modified_gmt":"2025-09-19T11:49:12","slug":"identifying-service-degradation-across-telco-layers-ericsson","status":"publish","type":"gsma_theme_resources","link":"https:\/\/www.gsma.com\/get-involved\/gsma-foundry\/gsma_resources\/identifying-service-degradation-across-telco-layers-ericsson\/","title":{"rendered":"Ericsson: Identifying service degradation across telco layers"},"content":{"rendered":"\n

Challenge:<\/strong>  Mobile operators spend billions of dollars every year addressing network outages and service degradations. These issues can take days to fix, as engineers spend valuable time troubleshooting the root cause of the faults.<\/p>\n\n\n\n

Solution:<\/strong> To reduce the time to resolve network issues, Ericsson<\/a> is using key performance indicator (KPI) metrics to correlate service degradation information across the different layers in the telecoms network. It then inputs the KPI metric data into a machine learning model, which can detect anomalous points and identify the degradation of the service in real time. <\/p>\n\n\n\n

Impact:<\/strong> By delivering accurate predictions that enable mobile network operators to take effective proactive measures and perform efficient root cause analysis, the solution promises to reduce the mean time-to-resolution (MTTR) of network faults. Faster troubleshooting will lower operators\u2019 operating expenditure, while improving the end-user experience.<\/p>\n\n\n\n

Topic:<\/strong> Operations and maintenance<\/p>\n\n\n\n

Cost:<\/strong> Medium<\/p>\n\n\n\n

MNO:<\/strong> Ericsson<\/p>\n\n\n\n

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