What Is Hyperautomation?
- March 2, 2023
- 7 minute read
Hyperautomation, as defined by Gartner, is a disciplined approach used by enterprises to identify, vet, and automate as many business and IT processes as possible. This requires the use of technologies, tools, or platforms, such as artificial intelligence (AI), machine learning, robotic process automation (RPA), business process management (BPM), and intelligent business process management suites, among other tools. Gartner coined the term ‘Hyperautomation’ in 2020.
Hyperautomation software is key to achieving near-term and long-term operational and business objectives. Hyperautomation has gained a lot of attention over the past two years. Since Gartner’s 2021 report, new research reveals that 80% of companies will include hyperautomation in their technology roadmap by 2024.
“A business-driven, disciplined approach that organizations use to rapidly identify, vet, and automate as many business and IT processes through the orchestrated use of multiple technologies, including AI, machine learning, event-driven software architecture, robotic process automation, business process management suites and other types of decision, process, and task automation tools.”
Gartner estimates that $481.6 billion was spent on “hyperautomation enabling software” in 2020.
By 2024, companies will be able to cut down operational costs by 30% through hyperautomation and redesigned processes, Gartner predicts.
Read More: What is Process Intelligence?
Hyperautomation: How it Works
Hyperautomation combines several components of process automation, integrating tools and other automation technologies. RPA is the core of hyperautomation, including AI, process mining, analytics, and other sophisticated technologies. For instance, hyperautomation uses cognitive technology to make sense of unstructured data, often supported by data lakes for storage.
Key components are:
- RPA: In hyperautomation approach, bots are used to streamline rules-based processes and enable companies achieve business outcomes.
- Cognitive technologies: Hyperautomation software uses technologies such as – artificial intelligence, machine learning, chatbots, optical character recognition, and natural language processing.
- Process mining: Hyperautomation greatly reduces and improves the efficiency and accuracy of business processes such as procurement, invoice management, payroll processing, and scheduling through process mining that analyses existing processes, the bottlenecks, and gaps. By visualizing the as-is state of processes, hyperautomation software identifies areas of improvement and creates cost efficiencies.
Read More: What is Intelligent Process Automation (IPA)?
Hyperautomation vs. Intelligent Automation: What’s the Difference?
Simply put, hyperautomation is an umbrella term that covers intelligent automation, as well as traditional RPA.
3 key differences between hyperautomation vs. intelligent automation:
- Scope: Hyperautomation has a larger, organization-wide scope compared to intelligent automation, which can be applied to individual processes.
- Effort: Hyperautomation requires significantly less effort from users. IT involvement is minimum, and business users can execute automation through an easy-to-use interface.
- Cost: Intelligent automation is more cost-effective in the short term but may be difficult to scale unless you bolster it with strategic tools like process discovery and task mining. Meanwhile, hyperautomation provides greater returns in the long term.
Read More: What Is Business Process Automation?
Getting Started with Hyperautomation
Choosing hyperautomation software can be difficult since it essentially comprises multiple digital elements that work together. Ideally, you need a set of compatible automation tools that you (or your hyperautomation partner) can connect. The ultimate objective is to discover automation candidatesv, redesign processes, build automation scripts, and execute improvements across the organization – through a phased-out and structured pattern.
Today, over 60% of the teams’ workday is spent on unstructured interactions in documents, emails, communications, custom applications, and websites – outside of ERP, CRM, and other systems of record. This massive unstructured and undocumented interaction dataset between people and software is untapped and contains a goldmine of insights that could give a significant competitive edge to enterprises. Traditional task solutions used for identifying and building automation pipelines have significant privacy, accuracy, and scalability issues and fail to capture work done outside the systems of record, such as ERPs and CRMs.
Through Soroco ScoutTM, powered by the world’s first work graph platform, organizations can unlock this data source to discover processes where inefficiencies occur and are prime candidates for intelligent process automation.
Request a demo of Soroco ScoutTM today!
