Most organizations are looking forward to automating business processes to reduce cost and to improve efficiency; RPA platforms have been traditionally driving this transformation. Global companies depend on technology to add value-creating differentiators to their products and find newer ways to enhance their customer experience. With the increasing demand for a variety of use cases, organizations are increasingly hitting a roadblock with RPA tools and seeking to add intelligence to automation. Therefore, Hyperautomation has become one of the most talked-about buzzword these days, and discussions around it are expected to be a key focus area across digital strategy plans in 2022 and beyond.
According to Gartner Research – “Hyperautomation is defined a business-driven, disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms.”
Hyperautomation is one top trend on the Gartner Top Strategic Technology Trends for 2022.
What is Hyperautomation?
Hyperautomation is defined as the combination of various cutting-edge Artificial Intelligence (AI) technologies with automation – such process modernization approach acts as catalysts for organizations seeking to achieve operational excellence and positively impact profits. Hyperautomation is not simply an extension of robotic process automation (RPA). RPA was only the first step in the direction. Hyperautomation brings intelligence to bear upon automation. This helps in calibrating collaboration and decision-making across businesses. Technology major Accenture refers to this collaborative intelligence, were humans and technology work not just side by side but together. Gartner predicts: By 2025 the market for software that enables hyperautomation will reach nearly $860 billion, with a CAGR of 12.3%.
Hyperautomation definition also revolves around Automation, being is at the core of a Hyperautomation platform. This core is flanked by artificial intelligence (AI), machine learning, process mining, data analytics as part of the broader umbrella of Hyperautomation. This concept has different names: Gartner refers to it as Hyperautomation, Forrester calls it Digital Process Automation (DPA), and IDC calls it Intelligent Process Automation (IPA).
According to a McKinsey study, businesses that adopted Hyperautomation tools were able to:
- Automate approximately 50–70 percent of tasks.
- Cut down data processing time by 50 to 60 percent.
- Decrease annual labor expenditure by 20–30%
- Achieve triple-digit ROI
What does Hyperautomation mean for businesses
Organizations are often dragged down by “Operational Debt,” the intrinsic issue can be traced back to legacy systems, suboptimal processes and bottlenecks, unstructured data residing in silos, lack of centralized data architecture, and security gaps. Business processes are usually operational using a patchwork of technologies and are not optimized, coherent, or consistent. Collectively, they hamper operational capabilities and dampen value propositions to customers.
Technology tools or products are designed to fulfill an individual purpose. However, the benefits of Hyperautomation lie in the fact that it combines multiple cutting-edge technologies, that helps organizations to develop strategic advantages irrespective of the existing operational environment. It focuses on adding progressive intelligence across workflows than traditional automation solutions. Each of the technology components is designed to enhance an organization’s ability to intelligently automate processes.
Hyperautomation approaches are more impactful solution than traditional automation solutions. It brings intelligence to process cores to optimize costs and delivers on the promised ROI. Hyperautomation mindset helps organizations to achieve operational excellence and ensure operational resiliency across business processes.
Key Technology Examples encompassing Hyperautomation
Since by now, we have understood the what associated with Hyperautomation, now let us look at the how. Hyperautomation approaches includes multiple examples incorporated by enterprises that power automation and cognitive decision making across business process. It exclusively includes data mining, text analysis, natural language processing, machine learning model, AI, - just to name a few.
Learn from Dr. Akhil Sahai (Chief Product Officer, Founding member Kanverse.ai) Published on Forbes - About Using AI To Automate Enterprise Document Processing Workflows.
- Optical Character Recognition: OCR Technology extracts the data from documents and the extracted data is often translated into a machine-readable format and made accessible to teams for editing, future referencing, or searching purposes. Learn more about What is Optical Character Recognition Software?
- Machine Learning: It improves a system's performance (positively impacts straight through processing rate) and document extraction accuracy through continuous learning based on real-time data; it eliminates the need to explicitly hard code instructions
- Data Mining: Data is mined from documents and simultaneously checked for meaningful patterns, trends, or correlations based on existing data warehouses/repositories, often using advanced statistical and mathematical modules
- Natural Language Processing: NLP is the system's ability to understand and process native human languages and perform necessary actions.
- Cognitive Reasoning: It is when a system successfully develops real-time decision-making capability often exhibited by a human operator
Also learn about How Kanverse Hyperautomation Platform combines multiple AI technologies (Computer vision, ML, NLP, fuzzy logic) with OCR to delivers high extraction accuracy while processing documents. In addition, process owners can achieve a touchless document processing experience, agnostic of inbound document type with Kanverse.
Hyperautomation benefits for enterprises?
Enterprises handles various documents daily bearing different formats and structure. These documents are manually processed by humans, and the relevant data is then manually entered into the enterprise application systems.
Natively data capture solutions extract data from incoming documents powered. Hyperautomation platform identifies and extracts the critical information from the incoming documents (paper and electronic versions) without any human agent's guidance. It also can process documents coming from multiple channels in the enterprise. This data is then verified and validated based on custom business logic and automatically exported to downstream applications.
Learn from Dr. Akhil Sahai (Chief Product Officer, Founding member Kanverse.ai) about The Strategic Advantage of Hyperautomation
Using an intelligent document processing automation software – fusing AI components with automation helps organizations to achieve complete process transformation. It is an ideal state when automation can be seamlessly scaled across multiple business processes and seamlessly handle the increasing volumes of semi-structured and unstructured information.
Hyperautomation builds efficiencies to every business process core by improving the quality of operations and does it at scale. Digital transformation officers are keen on keeping Hyperautomation at the center of their digital transformation plans for global business processes.
- Add decisioning to automation: Businesses can now leverage AI to automate decision making and take live data-driven decisions just as any human operator would do.
- Enable your workforce like never before: Minimizing time-consuming and repetitive tasks and capturing their tribal knowledge to undertake such tasks will enable them to focus more on business-critical activities.
- Collaboration on tasks across the organization: Process operators can intuitively automate cross-functional activities which involves collaboration among multiple stakeholders; it reduces cycle time and boosts productivity
- Seamless system integrations: Hyperautomation unites distributed technology and data storage systems. These systems can now communicate seamlessly with the power of smart integrations.
- Developing a strategic edge: Hyperautomation prompts all technology components to function in tandem with business needs and requirements. It will help organizations to achieve a state of true digital agility and flexibility.
- Return on Investments (RoI): Business can now track to optimize the ROI based on processes automated, optimized workflows, and time and costs saved.
Make your Accounts Payable (AP) workflows future ready with Kanverse AP Invoice Automation. Combining AI with automation gives much needed decisioning and analytics capabilities to reason and complete tasks seamlessly. Automate high-volume, repetitive manual invoice processing tasks and improve overall process efficiency and organizational productivity! Learn More about the Top 5 Advantages of Accounts Payable (AP) Invoice Automation powered by Hyperautomation.
About Kanverse.ai
Kanverse brings you the best optical character recognition software to automate Accounts Payable (AP) Invoice processing for enterprises right from ingestion, classification, extraction, validation to filing. Extract data from a wide gamut of documents with up to 99.5% accuracy using its multi-stage AI engine. Say goodbye to manual entry, reduce cycle time to seconds, optimize cost by up to 80%, minimize human error, and turbocharge productivity of your team.
AP automation software like Kanverse APIA (AP Invoice Automation) is built to do the heavy lifting across your AP cost centers while your staff can focus on productive and business-critical activities.
Kanverse can also automate insurance submission workflows and seamlessly process ACORD and supplemental forms.
Schedule a demo with us today to find out more.
About the Author
Aritro Chatterjee, Product Marketing, Kanverse.ai