I’ve heard that Hyperautomation is the next step after RPA. How does it specifically change the way we handle project status reports and risk dashboards? Does it require a different set of tools than the standard Blue Prism or UiPath setups we currently use?
3 answers
Hyperautomation isn't a single tool; it's a strategy that combines RPA with AI, Machine Learning, and Process Mining. Traditional RPA is "do" (repetitive tasks), while Hyperautomation is "think and do." For project reporting, instead of just pulling data from Jira into a spreadsheet, Hyperautomation uses Natural Language Processing to read the developer comments, sentiment analysis to gauge team morale, and predictive analytics to flag a project as "at risk" before the milestones are even missed. It essentially turns your static dashboard into a proactive advisory system for the PMO.
This sounds like it would require a complete overhaul of our data strategy. Is it possible to implement Hyperautomation incrementally? What is the first "intelligent" layer we should add to our existing RPA bots to start moving in this direction without breaking our current reporting?
Think of Hyperautomation as RPA with a brain. It uses process mining to find the bottlenecks you didn't even know existed, then automates the fix.
Exactly, Barbara. The "Process Mining" part is key. It helps you see where the reporting process itself is broken before you try to automate it, which prevents you from just doing a bad process faster.
Larry, start with "Intelligent Document Processing" (IDP). If your bots currently just move files, add an AI layer that can actually extract meaning from unstructured PDFs or emails. That's the easiest entry point into hyperautomation that delivers immediate value to project stakeholders.