Task mining helps us to better understand where can we further improve our operations by providing unique insights into how our people conduct their daily activities. When it was introduced to me by Mazars, it immediately caught my attention, as these data had not been available in this level of detail and structure to us before.
Martin Troják CFO, Dôvera
Optimisation of back-office processes at the biggest Slovak private health insurance company
Optimisation of back-office processes
Challenge
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.
Approach
Dôvera decided to engage Mazars to analyze back-office tasks related to the processes involving health insurance payers and health care providers.
Mazars and Dôvera focused on the following tasks:
- Handling of faulty monthly reports from payers and providers
- Invoice processing in the hospital segment
- Invoice processing in the outpatient specialised care
- Support case resolution in the contact centre
Task mining software was deployed on workstations at five departments to cover the full agenda of 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.
Results
The measurements took one month each (2-3 departments in parallel, 38 FTEs in total), after which Mazars identified 5 % to 37 % savings potential from analysing the selected tasks, taking over majority of the work effort of the analysed employees.
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, Mazars was able to quickly formulate hypotheses and validate them with the business stakeholders. Mazars suggested multiple areas for potential savings with cumulative saving potential of up to 37 % and an average ROI of 8 months. The measures leading to these savings include training and learning from best-in-class users, user interface changes, process redesign and process automation.
Breakdown of results | |||
Faulty monthly reports by payers & providers | Invoice processing in the hospital segment | Invoice processing in the outpatient care | Support case resolution in the contact centre |
- 5 %Handling of faulty monthly reports from payers and providers optimised by process redesign results in 5 % of cost savings in the department. | -10 %Invoice processing in the hospital segment optimised by the implementation of robotic process automation results in 10 % of cost savings in the department. | -15 %Invoice processing in the outpatient specialised care automated by robotic process automation results in 15 % of costs savings in the department. | - 37 %Support case resolution in the contact centre has a potential to be automated by robotics process automation in combination with intelligent automation to gain 37% in cost saving in the department. |