Hyperautomation: Power and potential
Hyperautomation — whether it’s new jargon, a buzzword, a technology or just another marketing gimmick — it’s something we cannot deny.
It’s a combination of new technologies that empowers businesses to perform tasks efficiently. When independent research analysts recognize technology as a trend, I think it's time to pay attention. According to Gartner, hyperautomation is at the top of the list and features in the top 10 strategic technology trends for 2021. 
You may have heard of intelligent automation before, and some consider it to be a synonym for hyperautomation. However, there are subtle differences between RPA, intelligent automation and hyperautomation. In this four-part blog series, I will discuss the need for hyperautomation and differentiate it from RPA and intelligent automation. I will also delve into the possibilities for using hyperautomation and offer some tips for its implementation.
What is hyperautomation?
Below, I will share Gartner's extremely technical definition of hyperautomation. First, however, let us start with a simple plain text definition.
Hyperautomation is a mindset and approach to automate processes, in which organizations rapidly identify and automate as many business processes as possible. It’s not just about the technologies; it's also the desired business outcomes that drive the use of one or more aspects of the automation. It brings together several process automation components, integrating tools and technologies combined with a human capability that amplifies the ability to automate work.
"Hyper" is the keyword here. The reason why it's called hyper is because it allows rapid automation of use cases. For example, a business user can automate the process by building an intelligent robot rapidly without being a data scientist or a developer. That's the beauty of hyperautomation — you don't need to be an expert or hardcore technical person to automate a process. It is a paradigm shift. As a result, more and more people without technical skills can automate processes.
As you all know, artificial intelligence and machine learning (AI/ML) is a popular technology that is widely used across domains. Today AI is everywhere, be it a toothbrush, home vacuum cleaner or even coffee machines. Hyperautomation is no exception to this. AI/ML is one of its critical elements.
According to Gartner, hyperautomation combines multiple machine learning, packaged software, and automation tools to deliver work. It deals with applying advanced technologies, including AI and machine learning to automate processes and augment humans capabilities. It starts with robotic process automation (RPA) at its core and expands automation capability with artificial intelligence (AI), process mining, analytics, and other advanced tools.
The need for hyperautomation
Today business leaders are expecting digital to help them transform operational excellence. The pandemic is an excellent example of what digital-led operational excellence could do. Digital-ready organizations swiftly adopted a remote, automation-first approach while non-digitized businesses either came to a standstill or were forced to embrace a virtual, remote-anywhere platform. Hyperautomation can help companies become operationally efficient by transforming legacy processes and digitizing technical, data and security debts faster and cost-effectively.
In a typical mid-size to large enterprise, the internal digital team collaborates with external consultants to automate business processes using RPA or BPM. Typically they identify the processes that need to be transformed and determine the ROI before embarking on the automation exercise.
While this is important, it only addresses 10% of the automation needs of the enterprise. Most of the long-tail work is overlooked because ROI for these use cases is not dramatic or falls under the corporate IT-led strategy. This long-tailed work becomes a source of giant spreadsheets, a single point of failure as individuals are forced to determine how they work and potentially the reason for inefficiencies.
More than 40% of these long-tail processes can be automated and outsourced to external service providers who can quickly deploy expert resources and advanced technology to issues.
No single solution, including RPA, can hyperautomate every business process to address various types of debts. The nature of the work is too varied to have one approach or solution. By recognizing the differences in the types of work required to begin zeroing in on the right solution for a particular job, hyperautomation came into existence.
Organizations can utilize hyperautomation to begin their journey of digitizing processes that are mostly overlooked but significantly impact organizational productivity.
In the next installment of this four-part series, we will discuss how hyperautomation is different from other known automation techniques. Stay tuned!
By Yash Malge, Head of Robotic Process Automation, Digital Transformation Office – North America
Posted on July 01