The international professional services firm Mazars used Task Mining & RPA to optimize back-off ice processes at the health insurance company Dôvera, who have over 1.5m
Mazars delivered a project to the biggest private health insurance company in Slovakia, Dôvera. Thanks to UltimateSuite Task Mining software, Mazars was able to identify opportunities for optimization with up to 30 % cost savings potential in the back office department. The identified savings included automating processes by implementing RPA and other process improvements. After the successful Proof of Concept, benefits were high enough to motivate Dôvera to a long-term engagement with Mazars and UltimateSuite. During the next two years, Mazars will be conducting task mining across Dôvera's organisation to identify further task improvement and automation opportunities.
Dôvera is the biggest private health insurance company in Slovakia. As in most countries, rules for health care financing, reimbursement of health care, and payment collection are very complex. Processes require manual execution of a large number of administrative transactions related to payers and providers. Dôvera's back-office processes are stable and have undergone several optimisations during the last few years by using conventional methods (business process improvement). However, Dôvera continues to strive to achieve operational excellence.
Dôvera decided to run this project with their trusted consulting partner Mazars and chose UltimateSuite as the tooling for mapping back-office tasks related to the processes involving health insurance payers and health care providers. The first phase of measurements and analysis took 2 months.
Mazars and Dôvera focused on following tasks:
Handling of faulty monthly reports from payers and providers
Invoice processing in the hospital segment
Invoice processing in the outpatient specialised care segment
UltimateSuite software was deployed on workstations within two departments to cover the full scope of processes being undertaken by their employees with a focus on measuring tasks to cover how the employees are performing the work on a continuous basis. The data captured were analysed to uncover potential bottlenecks and workarounds used by employees while executing individual tasks.
After one month of data collection, Mazars identified up to 30% savings potential from analysing the selected tasks identified by the task analysis. By using Task Mining, the need for analysis workshops was decreased to a minimum. Data about how users conduct their activities was collected automatically from their computers, while their daily work was not affected in any way.
As a result of Task Mining, Mazars was able to quickly formulate hypotheses and validate them with the business stakeholders. Mazars suggested 5 areas for potential savings with cumulative saving potential of up to 30 % and an ROI of 7 months. The measures leading to these savings include training, user interface changes, process redesign and process automation.