Before the technological revolution, most of the tasks were carried out manually. A product packaging firm, for example, used to have large workshops where daily wage employees stood in line with a live system, folding and taping your packing boxes and stamping with corporate logos. Then came a tide of automated equipment that folded and sealed your boxes automatically, followed by the most recent forms of machinery that folded, taped, stamped, and wrapped your boxes all by itself.
This is exactly how we define and differentiate Manual, Automation, and Hyperautomation.
Hyperautomation is nothing but automating everything that you possibly can. In IT terms Hyperautomation can be referred to as:
“The idea is that anything that can be automated in an organization should be automated. Hyperautomation is driven by organizations having legacy business processes that are not streamlined, creating immensely expensive and extensive issues for organizations.”
It’s a combination of multiple AI, machine learning, and packaged software and automation tools that help deliver tasks along with the application of similar advanced technologies to help automated processes and augment humans.
Hyperautomation can be considered as an extension of automation both horizontally and vertically.
The Key Components of Hyperautomation
- Robotic process automation (RPA)
- Business process management (BPM)
- Artificial intelligence (AI) and/or Machine learning (ML)
- Advanced analytics
As a shift in technology, you need to expand your horizon of thinking of automation beyond RPA and task automation to a highly sophisticated AI-process automation process.
So, to summarise everything we mentioned above, Hyperautomation is nothing but a perfect blend of the latest automation technologies and AI resulting in augmenting human capabilities by allowing them to complete daily processes with increased efficiency and effectiveness ultimately moving towards a new era of digital transformations.
Dig Deeper Into Automation And How Is It Different From Hyperautomation
Before moving forward, let’s define a basic rule. The automation referred to henceforth is IT process automation and not automated machines or robots used in production plants.
Here the automation we come across can further be divided into two parts: Test automation and Robotic process automation, a significant contributor towards enterprise test automation. Both these concepts, though separate, offer the same advantages that any other automation process would do: complete processes faster, with increased efficiency and higher accuracy ultimately contributing to higher productivity, lower risks, and increased ROI.
General Use Cases or Examples of Hyperautomation
- Understanding emails using NLP (Natural Language Processing)
- Understanding documents using OCR (Optical Character Recognition) capabilities
- Improving automation flows using ML/ AI (Machine Learning/Artificial Intelligence)
- Stock forecasting and automate restocking
Can you be a ’Digital First’ with Hyperautomation?
Though surviving for a couple of years, as this technology will grow and become more sophisticated, numerous benefits can be derived out of it for enterprises.
Intelligent bots set in the process can help effectively help become a ‘digital first’ organization by determining critical areas that need improvement and identifying how to provide an unrivaled customer experience.
Let’s take a closer look at how hyper-automation can help you be a ‘digital-first organization” by analyzing its major benefits.
1. Flexibility
Hyperautomation can help enterprises achieve greater scalability and flexibility in operations as they are not limited to a single digital technology anymore.
2. Improved productivity
Automating redundant, time-consuming tasks allow employees to serve more valuable roles in an organization and focus on human sensitive areas that improve overall productivity and efficiency.
3. Integration
You get the liberty to integrate digital technologies across processes and legacy systems that promote the smooth transfer of data across departments and promote better communication.
4. Improved ROI
Hyperautomation helped increase revenue and reduces costs. With the help of analytical tools, organizations can optimize the deployment of their resources as and when required.
5. Faster delivery with increased product quality
With the automation first trend in the market, businesses are increasingly focussing on the need to release products at the DevOps speed and ensuring a delightful user experience that can be supplemented by hyperautomation.
Hyperautomation in Quality Assurance
Hyperautomation in quality assurance automation would typically mean taking a step beyond test case-based automation. It’s about a scenario where the entire IT Life Cycle has been optimized with zero human intrusion in the process. More like creating a digital worker.
Till now, automation in QA is limited to the test execution phase with a significant amount of human intervention throughout the cycle. QA team is limited to developing a strategy to automate requirement analysis, unable to reach the final reporting layer.
Hyperautomation on the other hand helps to eliminate that limitation. It helps to deploy digital testers that are supported by many test pipelines. The intention here is to reduce human intervention as much as you can, going beyond automating repetitive tasks and automating the entire decision-making process using advanced technology like RPA, Business Process Automation, and AI.
But how to achieve it?
But how would you achieve that?
Few key features must be adopted here:
- Automate more frequently
- Take a technology-agnostic approach towards automation at the granular level
- Deploy smart automation techniques
- Adopt orchestrators
What Makes Hyperautomation Possible?
Usually, Intelligent process automation harnesses both artificial intelligence and RPA along with underlying Technologies including computer vision, machine learning, and natural language processing.
While RPA can easily handle algorithm-based automation along with mimicking human actions, the walk-in by AI has proved to be a game-changer. The biggest advantage AI brought with itself was the ability to automate the processing of unstructured data that previously required countless hours of human effort and a data scientist supervising the entire process.
Once AI is done processing the data, RPA walks in proving IPA to be the most useful intervention for automating data-intensive, highly repetitive processes.
Final Say
Hyper-automation improves operational efficiency, which is something that cannot be neglected. Streamlining and optimizing process stages becomes more of a requirement than a choice when using IPA methodologies.
As a result, there is a two-fold improvement.
Faster time-to-market, greater efficiency, and increased scalability are all benefits of a well-optimized process and technology that automates segments. Software testing companies play an important role in ensuring all these factors without a fail. Get in touch with a reliable testing partner to safeguard and track your hyperautomation journey.
