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RPA versus Hyper Automation

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RPA versus Hyper Automation

Blog
  • April 26, 2022
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RPA versus Hyper Automation

 

The Gartner’s Top Strategic Technology Trends for 2022 report says that technology trends will deliver solutions and capabilities to boost growth, digitalization, and efficiency as force multipliers of innovation.

Essentially, the proliferation of automation has caused the shift from repetitive, rule-based, process-focused, legacy systems to more data-focused processes that generate high-value insights. The adoption of Robotic Process Automation(RPA) and Hyperautomation has been gaining significant traction in driving digital transformation and supporting new delivery models. Organizations are now merging, acquiring, and divesting at record levels to help with their transformation strategy and gain access to these modern automation technologies so they can be more ‘intelligence-driven’.

What is Robotic Process Automation (RPA)?

Gartner has defined Robotics Process Automation as ‘a noninvasive integration technology used to automate routine, repetitive, and predictable tasks through orchestrated UI interactions that emulate human actions’. With two distinct classes -  Assisted and Unassisted, RPA is a combination of automation tools with several Machine Learning(ML) and packaged software layers on which Hyperautomation is built.

Assisted RPA deploys Bots to the desktop portals or workstations for executing complex and repetitive activities. Assisted technologies increase the users’ accuracy and response time to mitigate operational inefficiencies. High-risk tasks involving complicated decision-making are often handled by assisted RPA.

Unassisted RPA eliminates user intervention and input and automates all back-office workflows such as resource allocation, prioritization of tasks, and channeling of resources to deliver the highest levels of efficiency in business processes.

Use cases of RPA

In the context of digital transformation and improved performance workflows, RPA is useful in the following application areas:

Quote-to-cash automation, where sales operations are completely automated to enable rapid customer service, eliminate anomalies in prices, and standardize processes such as invoice payments and cash flows.

Procure-to-pay transaction automation, where invoice generation and procurement best practices are followed to enable a single touchpoint for all transactions.

Customer onboarding, where the customer onboarding processes are automated using cognitive automation capabilities to deliver a seamless end-user experience to customers in B2C businesses.

The enormous potential of RPA is also realized in other business areas such as data updates, data validation, and Optical Character Recognition (OCR)-based pattern recognition technologies for extracting data from multiple formats.

What is Hyperautomation?

Gartner has endorsed Hyperautomation as one of the top ten technologies to watch for. Hyperautomation is often seen as a ‘superset’ of RPA and drives higher-level functioning from task automation to intelligent orchestration enabling predictive insights, guided recommendations, processing mining, and adaptive decision-making.

Hyperautomation is a blend of emerging technologies and tools such as Artificial Intelligence (AI), ML, RPA, Intelligent Process Automation (IPA), and other decision management systems. Often touted as the ‘ultimate automation toolbox,’ Hyperautomation uses AI to calibrate cognitive functioning for transcending the confines of legacy process automation and individual processes.

Use cases of Hyperautomation

Hyperautomation can be leveraged through two types of processes – document-based and digitally-based.

Document-based processes use ML models that extract and validate machine-readable data from documents. The validated machine-readable data is transferred to the next record system, which is triggered by incoming documents or emails.

Digitally-based processes use structured data for easier automation of internal business functions across industries such as insurance and banking.

Hyperautomation is beneficial to the following digitally-based process areas of finance, sales, marketing, and customer services:

Accounts payable processes, that are automated to minimize errors and processing time through ML and OCR technologies to RPA.

Travel and Expense (T&E) processes and expense policies, that involve manual and repetitive tasks can be automated through hyper automation.

Order management processes, that involves automating the retrieval of customer-specific order data and customer query actions.

How do RPA and Hyperautomation differ?

The fundamental difference between RPA and Hyperautomation is in the area of cross-functional collaboration. Hyperautomation breaks inter-functional barriers and uses intelligence to determine the best strategy for automation.

RPA has eliminated the need for complex coding to drive automation through simplified execution workflows. However, it is limited to the automation of predefined and repetitive tasks. Hyper-automation transcends the limitations of RPA by facilitating adaptable, intelligent, predictive processes that optimize decision-making and help maximize ROI.

Some of the leading-edge Hyperautomation software solutions that help organizations automate and orchestrate their key process workflows are RPA, iBPMS, UiPath, Automation Anywhere, and Blue Prism. Eagle INSIGHT can be easily integrated and deployed with any of these RPA solutions, with on-prem and Cloud variants.

Automation redefines the Future of Work

In an increasingly competitive landscape, technologies such as RPA and Hyperautomation are being seen as business catalysts for driving transformation in the automation space. Business leaders are seeking ways to scale, adapt, accelerate, and deliver growth in their digital transformation journey through a new level of enterprise-wide automation to processes, data, and people.

At Cloudgate, we believe that though the beginning of your automation journey may seem daunting, determining the components and tools that will help build the framework of automation and align with the overall organizational objective is key.

 

 

 

 

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