Yellowfin > Case Studies > Automated reconciliations deliver over 25% process efficiencies for St. LukesHealth

Automated reconciliations deliver over 25% process efficiencies for St. LukesHealth

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Customer Company Size
Large Corporate
Region
  • Pacific
Country
  • Australia
Product
  • Prometheus ETL tools
  • YellowfinBI analytics and visualisation platform
  • HAMBS insurance operating software system
Tech Stack
  • ETL tools
  • Data visualization
  • Data manipulation
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Employee Satisfaction
  • Productivity Improvements
  • Cost Savings
Technology Category
  • Application Infrastructure & Middleware - Data Visualization
  • Analytics & Modeling - Predictive Analytics
  • Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
  • Healthcare & Hospitals
Applicable Functions
  • Business Operation
  • Quality Assurance
Use Cases
  • Process Control & Optimization
  • Predictive Quality Analytics
  • Remote Asset Management
Services
  • System Integration
  • Data Science Services
About The Customer
St. LukesHealth is a Tasmanian not-for-profit health insurer established in 1952. The organization manages over 30,000 policies covering more than 62,000 people across Australia. As the membership grew steadily, the need to re-evaluate internal processes became apparent. The organization aimed to automate routine tasks to allow their experienced staff to focus on more value-adding activities. The first process identified for automation was payroll group processing, which involved reconciling member payroll deductions with employer remittance advices. This task was previously handled manually by the Member Services team, consuming significant time and resources.
The Challenge
St. LukesHealth, a Tasmanian not-for-profit health insurer, faced inefficiencies in their payroll group processing. The manual reconciliation of member payroll deductions with employer remittance advices was time-consuming and required the attention of their most experienced staff. The process involved comparing employer-provided PDF files with data in the HAMBS insurance operating software system, which was tedious and prone to errors. With 25 payroll groups to manage, the task was ripe for automation to free up staff for more productive work.
The Solution
To address the inefficiencies, St. LukesHealth implemented ETL tools from Prometheus and the Yellowfin platform for data manipulation, visualization, and reporting. The first step was to request employers to provide data in CSV format instead of PDF, making it easier to manipulate and insert into a source CSV file. Sample templates were created for testing and validation, and a report was developed to support faster, more accurate reconciliation of payments. The new system displayed HAMBS system data on one side and the equivalent employer data on the other, allowing for quick identification of discrepancies. The automation process took two months to implement and has since seen incremental improvements, including alerts and broadcasts to further reduce operator intervention.
Operational Impact
  • The automation process has significantly reduced the time required for payroll group processing, with some tasks now taking as little as half an hour compared to an entire afternoon previously.
  • Staff satisfaction has increased as they are now freed from tedious, repetitive tasks and can focus on more productive work.
  • The degree of operator intervention has diminished with each improvement, making the process more efficient and less error-prone.
  • The automated system quickly identifies discrepancies, allowing for faster resolution of errors.
  • The final report is broadcast to the member services task list, and where there are no exceptions, the entire payment process can be completed in minutes.
Quantitative Benefit
  • Processing efficiency gains of between 25% and 33% in payroll group processing.
  • Reduction in time required for reconciling one of the largest payroll groups from an afternoon to around half an hour or less.

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