What is Hyperautomation? A Comprehensive Overview

Automation helps to rapidly identify and automate the business and IT processes. In a complex business structure, legacy automation tools may find it difficult to automate all business use cases. Hyperautomation provides the solutions to modern complex problems. Hyperautomation orchestrates multiple technologies, tools, or platforms, thus helping to automate any complex business process. Hyperautomation can provide 90% accuracy along with quality. It can also help to reduce the 60% of operational costs.

What is Hyperautomation?

Hyperautomation is a technique to streamline every possible business process using a combination of technologies such as artificial intelligence, robotic process automation, machine learning, business process management systems, and other advanced technologies.

Technology Used in Hyperautomation

Hyperautomation is a combination of multiple advanced technologies. It is invented to overcome the challenges in legacy automation techniques. Hyperautomation is the  next-generation automation technique. Below are some of the important technologies mainly used in hyperautomation.

• Artificial Intelligence (AI)
• Machine Learning (ML)
• Business Process Management System (BPMS)
• Business Process Management System (BPMS)
• Protocols used are TCP/IP, HTTP, SMTP, and SOAP

How does Hyperautomation work?

Hyperautomation is an extension of legacy business process automation. It uses the power of AI and ML to revolutionize business process automation. The goal of hyperautomation is to mimic the user or employee’s interaction with the application. The good news about hyperautomation is as it uses AI; it can adapt and learn the new business process on its own. The hyperautomation process can be broadly split into below steps.

• Discover business process: This is the first step of hyperautomation. In this phase, the repetitive and time-consuming business process will be identified. Frontline workers can help to make a list of repetitive tasks. Business process experts should help to make decisions on automation. The task’s nature can vary based on the requirements such as repetitive, time-consuming, high-volume transactions, rule-based transactions, etc. 
• Choose the automation technologies: The RPA tools in combination with AI and ML can be used to automate the tasks. The simple tasks can be automated using the RPA tools. If tasks involve logical thinking and decision-making steps then AI and ML can help. 
• Implement hyperautomation: You have identified the process and decided on the right tool sets. The next step is to build the bots and execute them as per the requirement. Furthermore, the organization might have IT infrastructure and compliance to be followed. Hyperautomation bots should be developed considering all these things in mind. Based on the need, one might choose to enable the hyperautomation for selected regions or carry out the pilot testing. Once satisfied with the results the automation will be enabled for broader users.
• Monitoring and Insights: Once the implementation is done, the team should monitor infrastructure and automation tasks. Insights or monitoring dashboard needs to be integrated to get the alerts as and when critical issues pop up. 

What are the benefits of Hyperautomation?

• Reduced operational cost: Hyperautomation reduces the operational cost by 60% by eliminating human intervention. 
• Improved efficiency: Hyperautomation can handle repetitive tasks with great accuracy. This results in increased efficiency and productivity.
• Scalability: Hyperautomation uses modern technologies such as AI, ML, cloud, etc. This helps to scale up or down easily as per requirements.
• Compliance and risk management: Hyperautomation can ensure the processes comply with the regulations and policies, which reduces the risk of legal and compliance issues. Furthermore, it can also help in fraud detection.
• Task complexity: Hyperautomation can handle complex tasks efficiently. Some tasks may be difficult to handle for humans with accuracy, however, these tasks can be carried out by hyperautomation with ease.
• Customer experience: Hyperautomation completes the tasks with high accuracy. Chatbot assistance can help to resolve problems instantly, which increases customer satisfaction.
• Monitoring and insights: Hyperautomation can be integrated with modern monitoring tools, and can be monitored with fewer human resources. It is intelligent enough to provide valuable business insights using AI.
• Flexibility: Hyperautomation can adapt to changing market conditions and business requirements more quickly. With fully integrated AI, hyperautomation can learn new processes.
• Innovation: By automating the repetitive and time-consuming tasks employees can focus on the strategic initiatives and plan for continuous growth.
• Environmental impact: It can be configured to use less resources and scalability helps to add the resources on demand. This in turn helps to reduce the waste and enables minimal use of energy.

Why Is Hyperautomation Important?

Hyperautomation is no longer an option, it is a necessity. In fact, modern start-ups adopt it in the initial phase itself. Larger organizations are swiftly shifting towards automation. Let’s understand the importance of hyperautomation.

• Reduces manual labor: Hyperautomation starts by identifying the repetitive and time-consuming tasks, once it is automated, there is no need for manual labor to execute a set of tasks.
• Eliminates the automation restrictions: Legacy automation has certain restrictions. It might be difficult to automate complex tasks or tasks that involve decision-making. Hyperautomation eliminates all barriers by incorporating AI and ML. Even decision-making tasks can be efficiently automated.
• Improved usage of data: Data is a great asset in the modern world, the hyperautomation stores the data in a structured way and it can be used for further process. Certain decisions can be derived from the past data.
• Valuable insights: Hyperautomation intelligently provides insights using historical data. Insights can be configured and used as and when required. Insights help businesses to make strategic plans and critical decisions with less effort.
• Improved team collaboration: Hyperautomation is not a single team responsibility. From beginning to end it has to go through multiple phases. It clearly defines the steps and process which helps to delegate the responsibility for each team and increases team collaboration.
• Increases business agility: It may be difficult to adapt to rapidly changing market demands without hyperautomation. Furthermore, it creates a competitive and collaborative environment which amplifies productivity.
• Ready for the future: Hyperautomation is not just an automation technique, rather it also focuses on business processes and compliance. It understands them and provides feedback on improvement. It is the next-generation automation framework to adopt any future changes.

Challenges of Hyperautomation

Business process are often complex and time-consuming. Hyperautomation focuses on automating the business process as much as possible to lower operational costs and increase efficiency. Many organizations may not be ready to integrate changes right away, it may be because of the technology they are using, their process standards, regulatory compliance, etc. However, to survive in the digital world it is necessary to step into automation by understanding the challenges. Here are some key challenges of hyperautomation.

• Requires skilled resources: Hyperautomation is not a tool, rather it is an approach to building future automation. It uses many technologies, and these technologies and approaches may vary based on organization. Hence it requires an innovative mindset and highly skilled resources. Often these resources may be expensive.
• Business process re-engineering:  Bringing business into line is a prerequisite for hyperautomation. Though it looks simple, it requires a lot of investment, effort for planning, and strategic execution.
• Technology upgrades:  To enable hyperautomation organization might need to undergo certain technology upgrades such as changing architecture styles and data storage etc. Furthermore, adopting the cloud, AI and ML is necessary. All these result in higher investment in technology upgrades.
• Analytics: Along with new technology adoption, organizations are required to integrate analytics and monitoring tools across the business process and platforms. This helps to measure the effectiveness of the hyperautomation. This may incur additional investment and effort.
• Security: Hyperautomation touches many parts of systems in the organization. Furthermore, it is configured to extract data in real-time from many different channels. Security of infrastructure and data leakage is the major concern of hyperautomation. Hence, It should be thoroughly tested before you enable the customer.

Hyperautomation Use Cases

Hyperautomation fits almost every industry that carries out business processes. As it encourages innovation, you can always build one that fits your needs. Considering the current market trend below are some of the key domains that efficiently incorporate hyperautomation and witnessing the benefits.

Banking And Financial Services

The KYC process in banking is the most complex and time-consuming. Hyperautomation can easily be incorporated into the KYC process. It can efficiently read KYC documents using the OCR, map the manual forms into the electronic fields, provide feedback, and re-verify them. Apart from KYC, there are many processes that hyperautomation can handle efficiently such as regulatory compliance, reporting, marketing, sales distribution network, payment operations, etc.

Insurance

The insurance domain has the most complex process and compared to any other industry it has more processes. Unlike other domains, the insurance domain has to collect the data from multiple sources. Because of all these complications, it takes a lot of time to process insurance claims. Customer satisfaction is comparatively low. Hyperautomation is capable enough to automate all these processes. It can efficiently fetch data from various departments or sources, convert the manual format to digital format, and identify fraud based on historical data. Once all the required data is in place the hyperautomation can deliver the output with high accuracy. Interestingly all these things can be done without any manual intervention.

Medical and Healthcare

Though the healthcare industry is rapidly adopting the digital experience because of its huge data processing, manual data formats, and interdepartmental dependencies there are still a lot of opportunities for automation. Accuracy of clinical results, and identifying the root cause for the illness is still a challenge. By utilizing the potential of AI, hyperautomation can accurately provide clinical results, and based on the historical data it can provide valuable feedback related to the illness. Similarly, the process involved in appointment, admission, bed allocation, payments, and many other processes can be automated using a hyperautomation approach.

Retail

The retail industry can benefit from hyperautomation right from warehouse management. It can be extended to order management, payments, transactions, transportation, inventory, supply management, risk management, etc. It can efficiently handle various consumer-facing processes such as order fulfillment, return process, replacement process, etc. The hyperautomation bots can help customers get product clarifications, get suggestions for what they are looking for, and finally, bots can resolve issues immediately.

Starting the Hyperautomation Process

For a business process to undergo hyperautomation it takes commitment and collaboration from many people and teams. Based on the current business data storage model and process, organizations may have to go refinement of data and process. Here are the high-level steps to the hyperautomation process.

Identify the automation needs and opportunities

Gather the information from the current business process, rules, and conditions and compare that with industry-standard practices. Reach out to frontline workers to understand the bottlenecks, complexity, and repetitive process. Find the best suitable automation tasks that may already exist and have a plan to enhance using the hyper-automation.

Prepare your data

Hyperautomation requires structured data to get stable and accurate resources. Understand how data is stored in the current process and refine them to align with the hyperautomation process. Storing the data in ML format can help in the future to achieve seamless adoption.

Identify your tools

As we discussed earlier, hyperautomation encourages innovation. Hyperautomation is highly customizable and adaptable. Based on the business process you need to identify the tools that are required for your organization. The tool may include RPA tools, ML tools, data sources, cloud technologies, IoT sensors, etc. Once the tool is identified, the next step is to map these tools into the business use cases.

Organize your personnel

Clearly define the responsibilities to execute the tasks. Have a detailed plan to carry out the tasks. This includes identifying the project leads, and sign-off personnel. All the processes and plans should be clear. Since there is a transition from manual to automation the staff should not get confused.

Implement, measure and iterate

Once everything is ready, you are ready to implement the hyperautomation. Start with the useful and standard process. Implement the insights and monitoring. Keep your communication channel open. Receive the feedback and act on it. Never forget to measure the outcome periodically. Adopt the changes and repeat until all stakeholders are satisfied.

Hyperautomation vs. automation

The hyperautomation and automation both look similar. It can create a lot of confusion in your mind. Often we hear the same words in both automation and hyperautomation. Let’s compare hyperautomation and automation, to clear out all our confusion. Below are the key differences between hyperautomation and automation

Key pointers	Automation	Hyperautomation
Definition	It streamlines the repetitive tasks, reducing the need for human intervention	An approach uses a combination of technologies that helps businesses scale automation efforts and extract more value from it
Technologies	Standard automation tools	Uses multiple tools and technologies such as RPA, ML, AI, BPMS, etc.
Sophistication of technology	RPA and simple task-oriented automation	Sophisticated AI-based process automation
Outcome	Efficient operations	Smart, flexible, and efficient operations
Degree of coverage	Requires to identify the tasks that can be automated. Might have to do a feasibility study.	Everything that can be automated will be automated. As it encourages innovation, if it doesn’t exist already you can build one.
Scope	It is  conducted from one platform	It is an ecosystem of platforms, systems, and technologies
Accuracy	Average accuracy	High accuracy
Decision-making tasks automation	Not supported	Supported using AI
Insights and monitoring	Limited insights and monitoring	Customizable insights and monitoring with a high degree of granularity

Learn more about test automation here

Hyperautomation can help the organization to achieve lower operational costs, increase efficiency, and reduce manual labor. It can also help in achieving higher accuracy. Hyperautomation removes all restrictions that exist in the legacy automation approach. It helps the organization to speed up the process. As it integrates AI and ML any complex process that involves a decision-making process can also be automated. Hyperautomation is not a tool or technology it is an approach that encourages innovation and customization. It is a future automation practice that many industries are shifting towards.

Frequently asked questions

What are the key components of hyperautomation?

Hyperautomation uses many technologies or components, AI, ML, Business Process Management Systems, RPA tools, monitoring tools, and other advanced automation tools are key components of hyperautomation.

What is an example of hyper-automation?

Below are the some of the examples of hyperautomation

• Extracting and understanding the emails using Natural Language Processing (NLP)
• Forecasting stocks and automating restocking. Implementing hyperautomation requires a strategic approach, decision-making skills, and the right toolbox to deliver value.
• Understanding documents using OCR (Optical Character Recognition)

Why do businesses need to scale to hyperautomation?

In a digitalization race, hyperautomation is no longer an option, it’s a necessity. In recent years, operational costs have increased considerably. Hyperautomation reduces the operational cost by 60% and it can deliver the result with a high degree of quality and accuracy.

Is Hyperautomation the same as intelligent automation?

Intelligent automation is a subset of hyperautomation. Intelligent automation has limited scope to use technologies in automation such as RPA, AI, and NLP. Whereas hyperautomation scope is much broader, it focuses on automating the business process as much as possible using any technologies.