Auditing process using “Process Mining” and “Process analytics” keeps RPA on Track.
The last decade was dedicated to Automation where Robotic Process Automation moved to mainstream reality through multiple phases and finally got matured to a level of Intelligent Automation that we have today. Initial expertise focused product services and support on automating repetitive and mundane jobs; also, intelligent aspects of automation also got uncovered, which had Artificial Intelligence as a rider.
Now with the changed market strategy, automation is not a one-time activity for a process or operations, it is something which should happen periodically and changes to any of the factors should be assessed and audited properly to tweak automation and avail maximum benefits.
The real question is how to asses the operating environment and get insights that can give enough pointers to mature existing automation or provide insights to initiate a new process for understanding the following differentiation:
- Process Mining” sets a link by discovering information systems logs, operational software, platforms data to information and converts it into insights to evaluate the need for automation, also helps to understand the automation potential of process or subprocesses.
Once identified, automation is up and running; there is a scope for future improvement and “Process Analytics” aids to achieve the same.
- Process Analytics” uses data circulated through the automation workflow to analyze friction points in the current automation and helps to understand where existing workflow needs focus or changes.
Some benefits which can be seen immediately as a part of the process mining and analytics approach are:
- Immediate ROI – Analyze more data and learn more quickly than humans
- Process Visibility – Analyze all possible process variants, including the most common or least possible variants
- Accelerate Automation Development – Insights provide a quick decision on which process to automate
- Continuous Process Optimization – Bot Data Analysis provide insights on what improvement needs to be done on the existing automation
Automation support best practices was initially about automating activities and taking business process discovery (surveys, interviews, etc.) as a base of analysis, which is hard to scale, but the 2020 approach should be more holistic and data-driven along with the traditional process exploration techniques.
Altran is assisting companies right from process mining to automation using RPA sublimated with AI and then keeping automation on track by conducting process analytics.
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