公司规模
Large Corporate
地区
- Pacific
国家
- Australia
产品
- Prometheus ETL tools
- YellowfinBI analytics and visualisation platform
- HAMBS insurance operating software system
技术栈
- ETL tools
- Data visualization
- Data manipulation
实施规模
- Enterprise-wide Deployment
影响指标
- Employee Satisfaction
- Productivity Improvements
- Cost Savings
技术
- 应用基础设施与中间件 - 数据可视化
- 分析与建模 - 预测分析
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 医疗保健和医院
适用功能
- 商业运营
- 质量保证
用例
- 过程控制与优化
- 质量预测分析
- 远程资产管理
服务
- 系统集成
- 数据科学服务
关于客户
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.
挑战
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.
解决方案
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.
运营影响
数量效益
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