Analyst firm Gartner rolled out hyperautomation as one of its key trends in 2020 to describe what happens when companies “rapidly identify and automate as many business processes as possible.”
What is Hyperautomation?
Hyperautomation is an important idea that will separate companies that automate well from those that don’t.
Hyperautomation is here. But it needs to be done right. To truly accelerate business processes and achieve maximum ROI, the hyperautomation journey needs to advance beyond just a collection of tools that solve specific problems and on a wider spectrum of business functions and knowledge work.
Why it’s needed
Automation overlaps with many related areas — process mining, machine learning, analytics, iPAAS, iBMPS, decision modeling and RPA.
While it’s easy to recommend that all these systems work together synchronously, executing on this is a different matter. Each only adds a patchwork solution on top of already existing patchwork solutions. Especially RPA, which is good for automating repetitive screen tasks, not end-to-end business process automation.
Companies are left with a stack of internal systems duct taped together, with simplistic automations running on top of legacy software. This has the indirect effect of cementing the legacy software in place. Instead of digging deep to find out why their tower is leaning, companies just stack another wobbly layer on top.
Leaders must now look far beyond quick fixes and temporary patches. They need a thoughtful, strategic approach to digital transformation, one that takes a more overarching view.
How Automation Hero meets hyperautomation
We believe the fastest path to hyperautomation is an end-to-end and agile platform that takes an iterative and incorporative approach of new information and workflows. Automations are already integrated with:
AI
Explode the automation opportunities with machine learning (ML), natural language processing (NLP), optical character recognition (OCR), and AI computer vision.
iBPMS
Combine business process management (BPM) software with additional capabilities such as AI to help companies dynamically automate more types of start-to-finish experiences.
Ingestion Engines
Bring in data for process mining, decision modeling, machine learning and business process management.
Process Mining
Create a digital clone of your business process to analyze inefficiencies and automation opportunities.
Decision Modeling
Model the logic of a decision that can be used in multiple processes.
RPA
Automate mundane rules-based business processes.
iPAAS
Connect software applications that are deployed in different environments.
Analytics
Measure and demonstrate the ROI of automation and its impact.
UX
Provide a streamlined interaction between automation and the user experience.
Hyperautomation Resources
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