Since the introduction of the term Robotic Process Automation (RPA) in 2012, hype has been on the rise. And followed at least in part by disappointed expectations. Is RPA dead? Is hyperautomation “only” new hype? We think not. Learn what the Gartner term hyperautomation is really about. And what automation will be important in the future.

HfS Research, an international tech analyst, published a provocative title back in Spring 2019: "RPA is dead". HfS was referring to the initially rather narrow, basic definition of RPA. In the beginning, it focused mainly on the automation of only small, piecemeal tasks, often in the form of attended automation. This means that an RPA bot does not execute a process completely automatically; instead, it operates only in cooperation with and under “supervision” of humans. The analyst's request? Look at automation as integrated automation. Essentially, it’s not about having many individual technologies such as RPA, artificial intelligence (AI), or analytics. It’s about the integrated deployment of RPA AND artificial intelligence AND analytics.

Integrated Automation

In short, RPA makes digital processes faster and better. In a first step, these are rule-based, repetitive processes and activities, which aim to kick start fast results right from the beginning. Gartner coined the term "hyperautomation" with the publication of the “Top 10 Strategic Technology Trends 2020”.

Gartner definition |
“Hyperautomation deals with the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans.”

What is hyperautomation?

Hyperautomation goes beyond the automation of purely standard tasks: What can be automated is automated. Gartner uses hyperautomation to describe the approach of automating even complex and long processes as extensively as possible with the help of various modern technologies. While this process can start with RPA as the core, it also extends to other tools and technologies. For example, intelligent business process management software (iBPMS) and artificial intelligence (AI) can be expressed in the form of process mining, machine learning, natural language processing (NLP), etc. This enables organizations to increasingly automate knowledge work.

People who systematically pursue hyperautomation create a digital (virtual) twin of an organization (DTO) in the process. This digital twin makes it possible to visualize processes, procedures, key performance indicators and how these interact. This holistic view with continuously generated information in real time can open up new business opportunities.

Gartner describes three steps on the way to hyperautomation:

  1. Define business goals (for example in terms of costs, revenue, risk)
  2. Optimize processes (including industrialization and scaling)
  3. Select and combine appropriate tools and technologies (with AI, RPA, etc.)


Benefits of hyperautomation

  • Fast (automated) identification of automatable processes
  • Efficient automation using artificial intelligence components
  • Enabling the entire organization to automate
  • End-to-end automation: automation of complex, long processes as completely as possible
  • Management of the complete lifecycle of automation


Intelligent Process Automation versus Hyperautomation?

Intelligent Process Automation (IPA) - also called Cognitive Process Automation - describes how RPA is linked to intelligent components. This can include computer vision – the intelligent vision and recognition of texts, images, and signs – as well as machine learning or NLP. The Capgemini Research Institute estimates that large organizations will achieve cost savings of around USD 500 billion through IPA in 2022.

IPA describes the combination of RPA with intelligent technologies. This is the case with hyperautomation, too. However, hyperautomation takes it even further: Hyperautomation is the comprehensive approach with the goal of automating to the greatest possible extent. This is not limited to RPA and AI.

Gartner regards hyperautomation as a state that companies need in order to maintain their future competitiveness. Hyperautomation has several implications, including the following:

  • a higher scope of automation. The scope of process automation will grow and shift from simple tasks to knowledge work.

  • the use of numerous tools and technologies. RPA alone is not enough. It requires different technologies and, above all, machine learning. The art will lie in selecting, orchestrating, and controlling the “right” technologies.

  • high agility and agile process management. Organizations must be able to quickly reconfigure and optimize processes. This requires agility.

  • employee commitment. Employees must question, optimize, and reinvent their work processes. To do so, they must understand and actively use automation. They can achieve still greater effects through cross-departmental initiatives.


Whether intelligent, integrated, or hyper – process automation is the future

One thing is certain: Robotic Process Automation is not dead. On the contrary, appearances can be deceiving. Indeed, RPA is increasingly being combined with artificial intelligence, or already equipped with it by suppliers. While the terms “integrated automation” or “intelligent process automation” refer primarily to the integration of intelligent components, hyperautomation goes much further. Hyperautomation is not a technology or a state; it is an approach, an endeavor to automate as comprehensively as possible.

Automation is thus likely to become an integral part of our future. In other words, the future is automation. Those who might overlook it or not take it seriously should take a look at the companies that have overslept digitization (like Kodak, one of the big losers of digitization). 

Servicetrace's goal from the very beginning has been to develop an automation platform that enables organizations to successfully manage all aspects of RPA. On the one hand, this includes the complete lifecycle of RPA including all parties involved. On the other hand, the platform is designed to introduce RPA as comprehensively as possible in accordance with the hyperautomation approach:

  • Thanks to a highly dynamic, unique RPA scaling technology, companies can scale RPA quickly, while remaining cost-efficient.
  • The intuitive usability and user guidance of the X1 RPA platform quickly enables all employees to automate the process on their own in good quality, which is, in turn, major leverage for rolling out RPA across the entire organization.
  • The platform enables simple, seamless integration of AI components and automation of complex and the most comprehensive processes.

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