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As the global economy faces unprecedented challenges with the Coronavirus pandemic, most businesses are seen struggling to sustain on multiple frontiers. The common reasons are either demand is slumped or, if they have the demand, they do not have the people ready to meet it. What this crisis has highlighted is that the weakest link in the global supply chain is human beings.
Of course, much of the process in the industry including the supply chain is mostly automated, yet there are huge elements of it that have humans in the loop. Let’s consider the jobs such as keying in data, making simple routing decisions, checking records, answering queries, etc. In “normal” times, all of these activities would be on the ‘to-do’ list of automation, using Robotic Process Automation (RPA) but with the recent disaster, it has highlighted its priority like never before. This means that when the dust settles, and we return to some kind of normal, any industry that has been impacted during this chaotic period will look for ways to make their services and operations more resilient in the face of dynamic and unexpected change. One such major pathbreaker would be ‘Hyper automation‘!
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What does Hyper-automation mean?
Let’s skip the technical lingo, and put it in simple words : Hyper-automation is the combination of automation technologies and artificial intelligence that, when combined, boost human capabilities, allowing them to complete processes faster, more efficiently, and with fewer errors. Hyper-automation could be simply perceived as RPA reinforced with artificial intelligence (AI). While RPA is software robots, or bots, that mimic human actions, AI is concerned with simulating human intelligence by machines. The integration of the two enables end-to-end business process automation and delivers greater impact.
Global automation business leaders at Gartner emphasized the momentum of this tide listing in top 10 emerging trends in 2020. According to Gartner’s report on Top 10 Strategic Technology Trends for 2020, Hyper-automation was describes as “the combination of multiple machine learning, packaged software, and automation tools to deliver work” and it “deals with the application of advanced technologies including AI and machine learning to increasingly automate processes and augment humans.”
How is Hyper-automation different from automation?
Initially, the trend of intelligent automation was kicked off with robotic process automation (RPA). However, RPA alone is not Hyper-automation. Hyper-automation requires a combination of various tools to help support replicating pieces of where the human is involved in a task.
Where RPA can be the simple optimization of repetitive tasks in the process (where you set up a bot to perform a series of jobs), Hyper-automation has an extra layer of robotic ‘intelligence’ that makes the processes even smarter. Metaphorically, automation is the robot’s arms to perform tasks quicker while Hyper-automation is the robot’s brain that performs those tasks in a smarter way. This ‘intelligent’ layer can include AI technologies in various forms. For example, natural language processing (NLP), which lets bots interpret human speech, optical character recognition (OCR), which lets bots convert images to readable text, and machine learning (ML), which lets bots identify patterns in data. When these technologies combine with any RPA automation software, the automation possibilities get multiplied manifold,
You must have got the idea by now: It’s the idea of an all-in-one solution that combines RPA, AI, machine learning, Process Mining, decision management, and natural-language processing, all for the purpose of making automation smarter! To the business that hasn’t yet invested, it may seem like the expensive icing on the cake that they can live without. But once they find out that all the other businesses are putting the icing on their cakes, they’ll lose their competitive advantage.
How can enterprises start with Hyper-automation?
Since Hyperautomation by definition implies the blend of various technologies, it’s important for businesses investing in it to select the right tools. Thus, the ease at which the tools and technologies can communicate with one another, also called interoperability, is more critical than ever.
If you’re looking for a new tool or platform to operate with, a good starting point is to search for one that is easy to use, scalable, works across platforms and systems. Acquiring a highly sophisticated yet entirely alienated system that doesn’t adapt to your organization’s existing systems instantly, will cost you. Since most teams today are built up of people with diverse skills and backgrounds, you need to find a tool that can be easily used by all and collaborated within. Unfortunately, most automation platforms today require their users to be able to write and read code. Choosing a tool that eliminates this barrier can give businesses an immense head start in the automation race.
Which industries are Hyper-automation relevant to?
Hyper-automation is relevant in many industries such as logistics, finance, banking and insurance. There are virtually no limits to where Hyper-automation can be leveraged. It’s more a matter of where the largest ROI on implementing Hyper-automation can be found. Hence, it’s more relevant to look at specific use cases for Hyper-automation rather than the industry, as well as which underlying technologies it utilizes to deliver its value. Let’s see a few of such use-cases solved with Hyper-automation:
- Understanding documents to extract structured data using Intelligent Data Capture technique
- Extracting structured data from invoices, sales orders, receipts, etc.
- Parsing domain-specific information from emails using NLP (Natural Language Processing)
- Forecast stocks and automate restocking
- Enhancing automation flows using AI/ML (Artificial Intelligence/Machine Learning)
- Reducing fraudulent expense claims by employees in the organization
KlearStack: How does this Intelligent Document Processing platform makes Hyper-automation possible?
KlearStack is an AI-based platform that turns clients’ unstructured documents into a competitive advantage by automating data extraction from various financial documents without human intervention of drawing templates. Processing invoices, resumes, legal contracts, and other documents manually would be inefficient, non-scalable, complex, and might lead to errors.
However, due to Intelligent Document Processing models in KlearStack which are built using OCR, AI, and ML automate these routine processes, improve efficiency, effectiveness, accuracy, and consistency across various workflows in the organization. Learn more about how KlearStack brings artificial intelligence and automation together in this explainer demo video.
Conclusion :
Concluding from the cases we’ve seen through this troubling and shaky time, automation has only committed to improved productivity and due to this, it will be in ever greater demand once this crisis recedes.
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