Case Study: Leading Telecom Company achieves 80% fewer data issues with Mu Sigma’s Data Quality Management Model

Streamlining Telecom Supply Chain using a Data Quality Management Model

Leading Telecom Company partnered with Mu Sigma to address major data quality challenges in its supply chain reporting. The team relied on multiple inventory, promotional, and sales reports, but inconsistencies, blank outputs, missing KPIs, and manual issue resolution made it difficult to generate reliable, timely decisions.

Mu Sigma implemented a data quality management (DQM) framework using data quality assessment, business rules, math-based anomaly detection, and machine learning for predictive correction. The solution also included automated alerts, a governance framework, and a monitoring interface, resulting in an 80% reduction in data issues, 70% faster resolution time, and monitoring across more than 120 tables.