Leveraging Process Discovery for Workload Management

Most large enterprises operating globally have a huge number of processes across all the functions. Digitization and process automation are key initiatives taken to reduce the cost of operations and also to meet the SLAs. It is important to understand and choose the right processes for automation and get the benefits and savings as per the goals set. The Chief Automation Officer (CAO) is responsible and accountable for driving the Automation programs successfully. He has the challenge to get the ROI fast and show the benefits of automation to the management. However, to realize the benefits of automation, apart from the prioritization of the processes, the critical requirement is also on the workload management of the digital workers.

How does process discovery help in workload management?

The first step towards workload management is identifying and prioritizing high-value tasks and processes which can be taken up for automation. The expectation is to run this tool across processes and figure out the Manual Operations Index (MOI) as we call it. The MOI for each process is calculated by calibrating 30 steps and measuring the manual efforts. For example, a process with 30 steps has 15 manual steps then the MOI (Total Steps / Manual Steps) is 2.0. A process with MOI > 1.5 qualifies for Automation. Process Transaction Index (PTI) is the transaction volume for a particular process. The PTI gives the cost-benefit analysis for a process to be automated. The Range of PTI is between 1 to 80,000 per day. For example, a process having a volume of 300 transactions per day with an execution time of 30 secs per transaction, it has a PTI of 9000.

While the designs are required to consider the MOI and PTI, it also depends on the target application’s execution and response speed on which the processes are running. For example, the SAP application is one of the target applications from where the data is fetched and updated, and if that is running on slow computing infrastructure, then the maximum robot efficiency will be restricted by the underneath SAP application. Based on the MOI and PTI, the design has to take into account the number of profiles to be used for robots, which drives the number of robots required. RPA products that support multi-skilled robot usage, are easy for optimization and maximize the utilization of robot licenses purchased.

The selection of processes is a key requirement for planning automation of processes. The CAO must work on the plan with all the parameters to achieve his goals.

Process Discovery tools such as AssistEdge Discover help in process mining resulting in prioritizing tasks leading to workload management.

How an American corporation & a global healthcare company based in Europe leveraged AssistEdge Discover for workload management – A case study

There are some excellent case studies where enterprises were able to leverage the AssistEdge Discover and realize the ROI fast. AE Discover is AI-enabled and uses Machine Learning for process discovery.

One of the clients, an American corporation manufacturing agriculture, construction, lawn care, and forestry machinery, leveraged AssistEdge Discover and RPA. The client wanted an outcome-based deal and EdgeVerve successfully delivered the automation benefits to the client using AssistEdge Discover, RPA, and Engage products.

EdgeVerve has successfully implemented the AaaS model for the outcome-based deal with significant savings delivered within 6 months – automating 22 complex processes across the supply chain, finance, and loan processes giving an annual savings of $ 2 Mn, which is 60 FTEs savings. The plan is to provide an annual savings of $ 15 Mn with 200+ processes automated. The Automation Factory concept applied helps in continuously churning out automation processes in a highly optimal way.

Similarly, EdgeVerve has also successfully delivered RPA at scale automating 200+ processes for a global health technology leader in Europe operating in 100+ countries. The processes are Finance and Accounting processes which were automated in the first phase, giving almost $40+Mn savings to date, with 200+ automation use cases, using 500+ bots.

Conclusion

To enable workload management of the digital workforce, it is very important to categorize the processes into complex, moderate, and simple complexity in conjuncture with business criticality. Once the processes are categorized, the MOI and PTI are applied for prioritizing the processes. As part of the Automation Center of Excellence, EdgeVerve has laid very standard processes to ensure Workload Management and process prioritization. There is also monitoring of processes after automation, to further optimize the same. My recommendation is, enterprises must embark on the Automation journey and use all the industry-standard tools like Process mining, process discovery, RPA, and Engage for getting the maximum ROI in a short period. The enterprises that go with the structured approach to Automation, benefit more, and grow much faster than their peers.