The telecom company faced several challenges related to network outages and machine learning model interpretability. Frequent network outages were impacting customer experience and causing downtime for business clients. The machine learning models implemented to optimise network performance were opaque and difficult to interpret, hindering the company’s ability to make informed decisions. The complexity of the telecom network and the large number of variables involved made it difficult to identify the root causes of the network outages and develop effective solutions.
Increased operational efficiency: The XAI solution improved the interpretability of the machine learning models, allowing network engineers to make informed decisions and optimise the network more efficiently. This led to a 15% improvement in operational efficiency, reducing costs and increasing profitability for the telecom company. This had an indirect impact in reducing network outages and hence improved performance.