The operations in an enterprise face variations that can be the outcome of factors such as – non-standardization in task execution, iteration of activities due to introduction of errors, regulatory needs of different industries/geographies affecting the processes etc. While enterprises strive to adopt process-enhancing technologies such as automation, the prerequisite is to have a complete knowhow of the variations to make sure processes are holistically analyzed for their automation potential.
Process mining comes in here as an enabler of Robotic Process Automation (RPA). Traditionally, process mining has been an activity of leveraging the event logs generated in enterprise systems such as Enterprise Resource Planning, Customer Relationship Management etc. to analyze process-related information to understand the whole process cycle better and generate process maps. With time, the gamut of process mining activity has expanded, and the new capabilities are able to capture the user’s activities on desktops to construct the whole set of processes involved and then generate process maps - this falls under the class of Desktop Process Mining.
With this expanded repertoire, not only the past knowledge of long running processes is being leveraged to look out for avenues to implement RPA but also the present activities, which might be newly introduced.
The need for process mining before RPA implementation
Although RPA is an excellent tool to help with integration of systems, automating certain repetitive tasks etc., the end goal is still automation for its own sake but not the modification of business outcomes. Thus, it somehow is delinked with the vision related to operational efficiencies of businesses. It has been seen in implementations, that if proper due diligence is not done before RPA implementation, projects tend to fail or the results are ephemeral, rather than giving long term return on investment.
Process mining helps understand business processes holistically, as it helps discover inefficiencies and bottlenecks while also allowing assessment of workers’ performance. Broadly, the capabilities offered fall under the following brackets:
a. Diagnose & Optimize – Process mining tools are designed to identify process enhancing opportunities, which may or may not include possibility of automation. Moreover, study of the existing set of processes and its comparison and assessment against the industry standards help in standardizing those optimally. The document processes can further be used for training purposes, maintenance work, handing over in case of outsourcing etc. Another unique proposition provided is in the case of mergers and acquisitions where the unification and standardization is all the more important to get the new entity in sync.
b. Monitor & Control – Once standards are set, the next set of operations under the process mining purview take note of the worker performance. Here, the aim is not just to look at the efficiencies and mistakes, but also to further study those to design next set of actions aimed at allotting tasks based on the employee capabilities.
These capabilities allow the right set of information for applying RPA as the processes being automated are completely understood throughout the value chain, and benefits of RPA can be truly realized through this holistic viewpoint.