Summary
Sonata helped the client modernize its decade-old activity-based costing (ABC) model by redesigning it on Microsoft Fabric, OneLake, and Power BI. The solution automated manual data ingestion and transformation processes, improved cost allocation accuracy, and enabled real-time financial insights for finance, commercial, and operational teams. The transformation delivered an 80% reduction in manual effort and over £250K in estimated savings through automation.
Customer overview
One of UK’s largest independent private hospitals, known for advanced clinical care, specialist expertise, and patient-centric outcomes.
Pressure points
The legacy ABC model, built in Microsoft Access, was over a decade old and lacked scalability, automation, and integration
Cost allocation for key services like outpatients and interventional radiology was incomplete or inaccurate
Finance and operational teams lacked real-time insights for strategic decision-making
Manual data ingestion and transformation processes led to delays, errors, and limited reporting capabilities
Limited user access, governance, and auditability posed operational risks
Solution highlights
Re-designed implementation of the ABC model using MS-Fabric, OneLake, and Power BI
SQL and Python/Spark-based transformation logic integrated into Fabric
Power Apps for manual GL mapping and finance tasks
Historical data retention and enhanced cost pool granularity (e.g., pathology, therapies, radiology)
Automated data pipelines replacing manual Excel-based ingestion
Power BI dashboards for finance, commercial, and operational reporting
Role-based access control and versioning for governance
Results that speak volumes
Improved cost allocation accuracy across key business services
Strengthened governance and security with role-based access and audit trails
Enabled real-time financial insights through Power BI dashboards
Increased stakeholder engagement through co-designed dashboards and training
By the numbers
80% reduction in manual effort for data ingestion and transformation
Improved cost allocation accuracy across 30+ cost pools
50% faster model refresh cycles, moving from annual to monthly updates
£250K+ estimated savings through automation
