To detect field problems swiftly, we centralized data from consumer devices and mobile apps into the cloud data warehouse. We defined key metrics for real-time monitoring through retrospective analysis of customer complaints and used advanced analytics and machine learning to detect anomalies in time series data. An alert system was established to notify teams of significant deviations, enabling prompt investigation and resolution. Continuous improvement was emphasized, with regular reviews and adjustments based on feedback and evolving data patterns to ensure accurate detection and efficient responses, thereby maintaining optimal device performance and user satisfaction.