Exploring machine learning use cases in telecom

There are numerous potential use cases for ML in telecommunications networks (see Figure 1). In the area of system monitoring, anomaly detection systems are crucial for identifying performance issues and problematic network behavior. Proactively predicting the degradation of key performance indicators, and identifying the likely root cause, can help reduce and prevent outages. In the area of managed services, ML models can improve trouble ticket management by effectively classifying, prioritizing, and escalating incidents. Capacity planning and customer retention can be improved through explainable churn prediction.