The Rationale for Using Process Mining Tools with RPA Projects
Business process mining and process discovery software are not new as these platforms/tools have been around for a while, including the current development of new tools. Process Mining tools use the event, transaction and/or audit logs generated by many IT system of records to apply data mining techniques to identify trends, patterns, and in the case of Robotic Process Automation, create process models and maps. Think of them like a Navigation system for the car; millions of data points are used for creating maps (cartography), the GPS system is used to find the current position of the car, and algorithms are used to determine a route for getting from point A to point B. For example, process mining tools can take event data from an ERP system and generate a process map or even the entire workflow. These tools can also be used to monitor processes and process changes on an ongoing basis which can be used to proactively manage changes and potential failures with some of the already deployed RPA robots.
Types of Process Mining
There are several different types of Process Mining. The first one is “Discovery”; the tool may use the logs to determine the existing process model, business rules or the organization models. The second one is “Conformance”; the tool checks if the process conforms to an existing process model or if there are deviations from the desired process model. The third one is “Extension”; the tool takes an existing log data and merges some new information or insights (correlations, decision rules, etc.) and suggests enhancements to the process model. Process Mining is a heavily researched area within academics and commercial organizations, and many Open Source tool kits are available such as ProM, PMLab, BupaR, etc. However, for the scope of this article, we will keep things very simple.
Many enterprise software vendors have their own process designer/analyzer tools that come as a part of their product suite, however, some of the focused vendors in this space are solely focused on creating offerings which are designed with RPA and Business Process Managmenet based automations in mind. These vendors include Minit, Celonis, TimelinePI and QPR.
Evaluation and Implementation of Process Mining Tools
From the above information, it would seem that such Process Mining tools should be considered a must have for most enterprise RPA programs. Although these tools are immensely powerful and can be possibly utilized for existing process discovery, process suitability for RPA automations, process optimization and monitoring, one must consider not only the cost, but also the implementation complexities involved with them. In simple cases, where the processes in question are performed on IT systems with excellent logging capabilities, these logs can be quickly consumed by the Process Mining tools and a lot of useful process information can be made visually available very quickly. However, if a process involves multiple systems where logging might be erratic and not readily available, there may be more work involved to get those IT systems ready for Process Mining.
Since the entire premise of RPA is speed to market, introducing more work may prolong the Proof of Value or Proof of Concept life cycle. The pros and cons of introducing the Process Mining tools must be considered before introducing them in any RPA program.
At Accelirate, we constantly evaluate the feasibility of RPA platforms and the ecosystem that is evolving around them. We see lots of Client Use Cases where introducing Process Mining tools can not only make the process discovery and selection simpler but also helps transform the RPA programs for long term success.