{"id":1044216,"date":"2021-03-28T00:00:00","date_gmt":"2021-03-28T00:00:00","guid":{"rendered":"https:\/\/www.beyondsoft.com\/sg\/customer-stories\/telecom-operator-increases-efficiency-with-predictive-analytics\/"},"modified":"2021-03-28T00:00:00","modified_gmt":"2021-03-28T00:00:00","slug":"telecom-operator-increases-efficiency-with-predictive-analytics","status":"publish","type":"customer-story","link":"https:\/\/www.beyondsoft.com\/jp\/en\/customer-stories\/telecom-operator-increases-efficiency-with-predictive-analytics\/","title":{"rendered":"Telecom operator increases efficiency with predictive analytics"},"content":{"rendered":"

THE CHALLENGE<\/strong><\/p>\n\n\n

The client\u2019s environment was comprised of 100+ subsystems that had over 10,000 components. The systems averaged one to four million alerts a day with an accuracy of 45%. The client wanted to reach an accuracy rating of 75% through the use of predictive analytics.<\/p>\n\n\n

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THE SOLUTION<\/strong><\/p>\n\n\n

The solution included organizing existing workflows and knowledge base, labeling data for common issues and resolutions, then building machine learning (ML) model-based data to identify anomalies and find associations.<\/p>\n\n\n

By combining repeating alerts and categorizing similar ones, the volume of alerts was reduced 95.2%. Efficiency was further improved by automating the alert-handling process where automated detection and diagnosis were implemented to minimize human engagement. Alerts were also batch-processed to increase the throughput.<\/p>\n\n\n

At the system and data level, Beyondsoft performed the association analysis to identify 40 hidden relationships amongst alerts. With the help of the expert system, this effort allowed a comprehensive data collection and integration that successfully facilitated root cause analysis.<\/p>\n\n\n

With the benefits generated by accurate prediction, anomaly detection, association analysis, and resolution recommendation, the client achieved several important efficiency improvements:<\/p>\n\n\n