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Hyperautomation – The Next Milestone Towards Complete Digital Transformation

Hyperautomation, Robotic Process Automation, Intelligent Process Automation, Digital Transformation

“Hyperautomation” sounds like something borrowed from a sci-fi film script. The first thought that comes to the mind is a robotic overthrow of humans. Fight scenes where the bots are winning, workplaces becoming cold and grey, humans losing jobs – okay, this might be an exaggeration.

However, if you have read our overview of RPA, you might have seen a mention of Hyperautomation. In this overview, we also stressed the fact that “Robotic Process Automation, amongst other similar technology, is meant to function as an aid to a workforce and not to replace it.
This claim remains true even in the wake of progressive solutions like Hyperautomation.

So, before we jump to any conclusions, what is Hyperautomation?

To answer this question, we started a discussion with an analyst at Quadrant Knowledge Solutions, and this is what they had to say – “Hyperautomation, also known as digital automation/ smart automation, when compared with RPA, appears as a more polished, comprehensive, end-to-end solution. The avenues of automation continue to grow, and hyperautomation allows complex, unorthodox processes, to be automated. With a strong RPA-based foundation, and infusions from AI, ML, OCR and NLP, even unstructured and legacy data can be processed and digitized.”

As we understand it, 

Hyperautomation relies on a collective suite of robotic process automation, process mining, analytical and decision management tools, as well as disruptive technology like artificial intelligence, machine learning, optical character recognition, and natural language processing to magnify the scale of process automation.

Some features of Hyperautomation include –
  • Automated Process Discovery – Process discovery, or process mining allows you to understand the effect of automation efforts and decide what and how your further automation efforts should be after highlighting places of improvement.
  • Workforce Engagement – Hyperautomation ensures ease-of-function. It aims at involving non-technical workforce in the folds of digitalization by incorporating automation into daily tasks.
  • Advanced Analytics – Business insights and advanced analytics spanning over various departments and aspects of operations contribute to the overall growth of business intelligence.
  • Application Management – Integrated AI capabilities make applications easy to understand and manage. Tech solutions like LCAP make app development and maintenance less complex.
  • Logical Workflow – Predictive analysis and workflow management abilities allow the formation of logical process maps.
  • Human-bot collaboration – Just like RPA and other automation solutions, the ultimate goal is to smoothen human-bot interaction. Hyperautomation aims at making the collaboration seamless and in turn, increase productivity, efficiency, and accuracy.
By this point, you’re probably wondering – But where does Robotic Process Automation fit in?

We’re calling hyperautomation the ‘next milestone’ – but where did the journey begin?
At Robotic Process Automation!

RPA is the conceptual foundation that the future of the digital era is based on. RPA is the ultimate automation solution when dealing with mundane, repetitive tasks. It is exceptional at handling structured data but falls short in handling undefined tasks and unstructured data.
Hence, while RPA is limited to specific tasks, hyperautomation aims at automating every process that can be automated to support wider sections of organizational operations.

To learn more about RPA and its contribution to mobilizing hyperautomation, read this overview of RPA or this blog about process mining and RPA.

All this surely sounds very rosy. Be that as it may, it is impossible to ignore the drawbacks that hyperautomation introduces to business management.

There are a number of necessary changes that organizations will have to undergo before they can reach this milestone.
  • Preparing for disruptive technology – The addition of AI, ML, NLP, and OCR will, without a doubt, ease the work of employees. However, organizations will need to take steps towards changing the work environment and mindset as well as the existing data management and business management systems.
  • Un-learning and relearning – The organizational ecosystem will have to transform. Every employee will have to go back in time, erase certain ideas and inculcate new ones. This will pose a major challenge for industry veterans – since they have been used to certain procedures for many years, making way for automation might become extremely challenging.
  • The learning curve – Even if a mental acceptance occurs amongst workers, learning to interact and cooperate with bots and AI won’t come quickly. Like any other skill, this one will also have a learning curve, and it will vary for each individual.
  • Interoperability – Once an enterprise turns towards automation, they will have to ensure that any solutions they utilize in the future are integrable and compatible with the existing technology. This will definitely narrow their choices down until the reach of AI expands.
  • Elimination of fear – The biggest obstacle businesses are bound to face is the hesitation of employees to allow automation. This hesitation, stemming from the fear that robots will make human workers redundant, is deeply rooted and will have to gradually be eliminated.
But can bots take away human jobs? Probably not.

Industry leaders constantly stress that robots will not be replacing humans. The statistical and analytical capabilities of the human mind are irreplaceable. However, at a business management level, instilling the confidence within employees that hyperautomation is here to help, will remain a major challenge.

While vendors like UiPath and Celonis have already begun treading the path towards complete automation, the bitter reality remains that achieving this milestone globally is a fair bit away in the future. Nevertheless, many organizations have made the initial switch towards IPA and will soon begin considering the adoption of hyperautomation.

Meanwhile, research and advancement continue, solutions become smarter, tech becomes more affordable and organizations continue to be reformed to suit the digital age.