Why Is Hyperautomation Important?

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Hyperautomation is the combination of automation technologies and artificial intelligence that, when combined, make human workers more productive, more efficient, and free from errors.

The limitations of one technology no longer restrict businesses.

They can now digitize and automate full lines of business processes and others that have a complete organizational reach.

Hyperautomation forces enterprises to think about the types and maturity of the technologies and processes required to scale automation initiatives.

Instead of streamlining payment reconciliation, the business can automate the entire process — from the moment a customer asks for a quote to the moment it’s fulfilled — and retrieve data to understand inefficiencies.

As automation of various processes is being adopted at high volumes across global industries without any signs of slowing down, the need to automate more complex tasks is becoming more apparent.

So what exactly is hyperautomation, and what are its benefits?

What Is Hyperautomation?

Hyperautomation is the digital destination where you improve customer and employee satisfaction while delivering at scale an optimized enterprise business model under your control.

Intelligent process automation lets you control these business processes by creating a hyper-automated client-centric organization.

So, if your company has already automated processes and tasks leveraging RPA, then hyperautomation is the next step in your automation journey.

Hyperautomation brings together several process automation components along with tools and technology integration to amplify automation and unlock the maximum potential of automation.

For this, innovative technologies such as robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), and intelligent business process management (IBPM) combine to automate tasks.

Therefore, instead of adopting just one technology such as AI in automation, hyperautomation utilizes the synergy of capabilities from all these technologies.

How Does Gartner Define Hyperautomation?

Gartner, who coined the term in 2019, defines “hyperautomation” as “the combination of multiple machine learning, packaged software and automation tools to deliver work […] that deals with the application of advanced technologies including AI and machine learning to increasingly automate processes and augment humans.”

The term can also be called digital process automation.

What's The Purpose of Hyperautomation Technologies?

Hyperautomation initiatives coordinate through a center of excellence (CoE) that helps to drive automation efforts.

Hyperautomation aims to save costs, boost productivity, and gain efficiencies through automating automation and capitalize on the data collected and generated by digitized processes.

Organizations can plumb that data to make better and timelier business decisions.

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Benefits of Hyperautomation

As with all emerging technologies, hyperautomation builds upon what came before it: RPA.

Hyperautomation facilitates connecting various business applications and operations with structured and unstructured data.

It simplifies data analysis and process discovery as well as new automation opportunities.

It empowers organizations to make informed decisions based on data gathered and analyzed by the automation systems. It directly shows which decisions to make.

It complements human intelligence for better business decisions. Here’s how hyperautomation is taking business automation to new, unprecedented heights.

Improved ROI

The reward of leveraging hyperautomation in business processes directly boosts ROI as each department runs smoothly and efficiently, reducing costs across the board without human error.

With hyperautomation’s impressive analytical capabilities, businesses can optimize resource deployment from granular and holistic perspectives.

Deployment of Digital Workers

Marrying RPA with cognitive intelligence helps create an intelligent digital workforce. Such a combination can automate repetitive tasks to augment employee performance.

These digital workers act as the change agents of hyperautomation with the ability to connect to various business applications, work with unstructured and structured data, analyze data to make smart decisions, and discover new automation opportunities.

Flexibility & Scalability

Since hyperautomation incorporates and works on many automation technologies, organizations are not limited to relying on the limited benefits of a single digital technology.

This allows organizations to achieve scalability and flexibility in their business operations.

Easy Integration

Hyperautomation allows businesses to easily integrate their digital technologies and assets across their entire processes and legacy systems.

This means that teams can gain access to data easily, but most importantly, it allows for simple and efficient interdepartmental communication across entire organizations.

A Dash of Artificial Intelligence

RPA+AI makes the essential ingredients of hyperautomation.

Leveraging an evolving set of Al technologies, hyperautomation can rapidly identify and automate all possible business processes.

From managing the full automation cycle on a large scale to discovering automation opportunities and measuring the ROI, the integration of AI differentiates digital workers from others who follow standard automation approaches.

Artificial Intelligence vs. Traditional Automation Tools

Traditional approaches to enterprise automation focused on the best way to implement automation within a particular context.

These automations were highly specific to a particular piece of software. For example, workload automation uses scripts to automate many highly repetitive processes.

BPM tools can automate tasks within the context of a specific workflow.

AI extends traditional automation to take on more tasks, such as using OCR to read documents, natural language processing to understand them, or natural language generation to provide summaries to humans.

Hyperautomation vs. Regular Automation

Hyperautomation goes beyond just automating tasks.

It creates a backbone for automation tools by harnessing the power of multiple technologies like artificial intelligence (AI) and machine learning (ML) with robotic process automation (RPA).

Simply put, RPA only automates predefined and repetitive tasks.

Creating A Digital Twin

By automating and uncovering inaccessible data and processes, hyperautomation helps create a digital twin of the organization (DTO).

The DTO can help organizations assess how new automation drive value, enable new opportunities, or create new bottlenecks that need addressing.

AI and machine learning components enable automation to interact with the world in more ways.

For example, OCR allows automation to process text or numbers from paper or PDF documents.

Intelligent Business Management Software (iBPMS)

An iBPMS is an integrated set of technologies that coordinates people and machines in process delivery.

An iBPMS enables companies to model, implement, and execute sets of interrelated processes by applying business rules.

Though it is less popular with the emergence of RPA, it is still a useful tool for process automation.

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Hyperautomation Takeover

As a key strategic technology trend, hyperautomation is the driving force of global digital transformation to streamline processes to create higher efficiency, accuracy, and output.

The usual narrative we hear is that hyperautomation will augment rather than replace humans, but the reality is that automation eliminates jobs once done by humans.

The recent developments in robotics, artificial intelligence (AI), and machine learning (ML) have put businesses across every domain on the cusp of digital transformation.

This digital transformation, also known as intelligent automation, has empowered robots and computerized machines to perform routine virtual and physical activities better, faster, and cheaper than humans.

Workers need convincing that the robots will not take their jobs for these efforts to take off.

Many industrial environments also use legacy systems and processes that could benefit from optimization.

The financial services industry involves many calculations, transactions, and communications with customers, buyers, fund managers, and other entities.

Also, the various monitoring tools used in hyperautomation projects might prompt a backlash from knowledge workers worried about the potential misuse of that data.

The next inevitable questions are how the hyperautomation trend will affect your job or business and what you can achieve if you gear your business with hyperautomation technology today.

We need to answer these questions to understand the potential return on investing in hyperautomation.

Here, it’s important to establish that the point of automation is to augment human capabilities, not to replace them.

It is attractive to vendors since it is short something companies aspire to vague, so any vendor can claim to enable it.

Hyperautomation includes most automation technologies in the definition so that any emerging technology can be associated with hyperautomation.

Machine Learning Capabilities

Machine learning enables businesses that have implemented hyperautomation to learn from the processes without human intervention.

It then determines which AI process or algorithm is the most effective and which processes marketers should eliminate.

This innovative approach to automation has empowered businesses to eliminate individual tasks and implement knowledge-based inputs that drive better business outcomes.

With machine learning, hyperautomation enables organizations to learn from the processes themselves.

It determines, for example, which route is the most efficient and which steps marketers can eliminate. It goes beyond the simple use of RPA to reproduce human tasks.

It fixes the gaps left by RPA and allows organizations to automate even complex processes where tasks previously needed human input.

What Is Task Mining?

Task mining uses machine vision software running on each user’s desktop to construct a view of processes that span multiple applications.

Process mining and task mining tools can automatically generate a DTO, enabling organizations to visualize how functions, processes, and key performance indicators interact to drive value.

Optical Character Recognition (OCR)

Optical character recognition (OCR) can eliminate manual labor for certain tasks. OCR can extract data from documents and convert it into machine-readable characters.

When combined with AI and RPA, businesses can automate the processes where human interaction is needed to capture data from documents, analyze it and take action to handle the task.

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