The Challenge

The Commercial Data Management team faced major challenges managing a vast data ecosystem integrating feeds from multiple partners and vendors. Ensuring data quality in their Microsoft Azure-based 'Commercial Data Hub' (CDH) was crucial, but manual processes, limited automation, and lack of reliable insights hindered their ability to scale and maintain high-quality standards effectively.

Our Solution

Agilisium’s Data Observability is a customized solution designed to monitor and enhance the reliability of the client’s data. Custom frameworks and sophisticated ML models were leveraged to detect anomalies, errors, and inconsistencies based on historical data and then provide actionable insights. The solution enabled the client to gain competitive advantage by streamlining QC activities and enhanced their ability to respond swiftly to data anomalies.

Data-Driven Insights

Business users gained the ability to visualize overall prescription (Rx) volumes for the client’s products, including future forecasts, providing greater insights into sales trends.

Automated QC Processes

Automation within the Commercial Data Hub reduced the need for manual intervention, ensuring higher data integrity.

Predictive Analytics

Predicts the lower and upper bounds of Rx volumes, allowing the client to forecast with greater accuracy and prepare for potential business outcomes.

Proactive Alerts

A system of automated alerts was set up to notify the Data Management team of any data QC issues, enabling swift action to mitigate potential problems.

Key Impact

40%

Reduction in time spent on manual checks

32%

Increase in Data Accuracy

The customer

A neuroscience-focused, biopharmaceutical company renowned for its commitment to uncovering new treatments for rare conditions.

The Outcomes

Improved Data Quality and Commercial Success

This solution resulted in a more agile and efficient data management process, allowing the client to maintain high data quality standards while optimizing business operations and performance in the market.