Hyperautomation

By combining technologies like artificial intelligence (AI) and machine learning (ML) to automate business processes, hyperautomation can lead to increased efficiency, cost savings, and improved customer service.

But what is hyperautomation and how can you implement it within your business?

What is Hyperautomation?

According to Gartner, hyperautomation involves the disciplined use of relevant automation technologies to automate all business processes that can or should be automated.¹ These technologies include a range of tools, such as machine learning, intelligent document processing, robotic process automation, and optical character recognition, to automate end-to-end business processes.

In recent years, hyperautomation has been adopted by more and more companies globally. In fact, Gartner estimates that more than 56% of organizations have an average of four or more concurrent hyperautomation initiatives underway.²

Benefits of Hyperautomation

Hyperautomation is a powerful strategy that can help organizations stay competitive, increase efficiency, and improve customer satisfaction. Here are some of the benefits offered by adopting such a strategy.

1. Increased Efficiency
   Hyperautomation focuses on automating manual and repetitive tasks, freeing up employees to focus on higher value work and improving operational efficiency.
2. Improved Accuracy
   Automating processes reduces the risk of human error and improves decision-making accuracy.
3. Enhanced Customer Experiences
   Automating customer-facing processes such as service delivery and complaint resolution can improve customer experience and increase satisfaction.
4. Cost Savings
   Automating manual and repetitive tasks can reduce operational costs and increase cost savings.
5. Better Decision-making
   Hyperautomation can provide organizations with real-time data insights, enabling more informed decision-making.
6. Increased Agility
   Hyperautomation enables organizations to quickly respond to changing business needs and market conditions.

Hyperautomation has become an essential tool for modern organizations looking to increase efficiency and productivity while reducing costs. By combining various automation technologies, hyperautomation streamlines complex business processes and enables faster decision-making.

Examples of Hyperautomation

Hyperautomation can be used to automate a wide range of business tasks. This includes repetitive tasks like data entry, customer service, and financial analysis, as well as more complex tasks, such as analyzing large amounts of data and making business decisions based on that data. Because the application of hyperautomation is so broad, it can be used in many industries.

Hyperautomation in Banking

Hyperautomation can be used by banks to automate fraud detection and prevention, onboard customers, process loan applications, process payments, and more.

• Customer Service Automation: Automating customer service functions such as account opening, loan processing, and claim submissions can improve customer experience and reduce wait times.
• Fraud Detection: Hyperautomation can use machine learning algorithms to identify and prevent fraud, reducing the risk of financial losses.
• Risk Management: Hyperautomation can automate risk assessment processes, enabling financial services companies to make informed decisions and minimize potential losses.
• Operations Optimization: Automating manual and repetitive tasks such as data entry and reconciliation can reduce operational costs and improve efficiency.

In an industry critically involved with an individual’s financial wellbeing, hyperautomation has the potential to deliver transformational results.

Hyperautomation in Insurance

By automating tasks such as policy management, premium calculation, claims processing, customer service, and fraud detection, insurers can provide faster and more accurate service to their customers.

Hyperautomation can be used in the insurance industry in several ways:

• Claims Processing: Automating claims processing can reduce the time it takes to process a claim, improve accuracy, and enhance customer experience.
• Underwriting: Hyperautomation can automate the underwriting process, allowing insurance companies to quickly assess risks and make informed decisions.
• Policy Administration: Automating policy administration tasks such as premium calculation and policy renewals, can improve operational efficiency and reduce costs.
• Fraud Detection: Machine learning algorithms can be used to identify fraudulent insurance claims, minimizing financial losses.
• Customer Service: Automating customer service functions, such as policy inquiries and claims submissions, can improve customer experience and reduce wait times.

From these few examples, it’s easy to see that Hyperautomation offers numerous benefits for the insurance industry, making it a critical tool for insurers looking to thrive in today’s fast-paced and competitive business environment.

Hyperautomation in Public Sector and Government Agencies

Public sector agencies are often process heavy, presenting many opportunities for hyperautomation to increase efficiency.

• Service Delivery: Automating service delivery processes, such as benefits processing and license renewals, can improve citizen experience and reduce wait times.
• Compliance: Automating compliance processes can help public sector and government agencies stay current with regulatory requirements and minimize the risk of penalties.
• Decision-making: Automating decision-making processes, such as budget allocation and resource allocation, can improve accuracy and increase efficiency.
• Citizen Engagement: Hyperautomation can automate citizen engagement processes, such as feedback management and complaint resolution, improving transparency and accountability.

It’s clear that the benefits of hyperautomation in government agencies are significant, ranging from improved efficiency and productivity to better decision-making and enhanced citizen services.

Hyperautomation In Healthcare

By automating processes like record-keeping, patient follow-ups, and more, healthcare organizations can reduce the risk of human error. This can lead to more accurate diagnoses and treatments, and improve patient outcomes.

• Clinical Workflows: Automating clinical workflows, such as patient data management, appointment scheduling, and electronic health record (EHR) management can improve operational efficiency and reduce costs.
• Claims Processing: Automating claims processing can reduce the time it takes to process a claim and improve accuracy.
• Clinical Decision-making: Automating decision-making processes, such as diagnosis and treatment planning, can improve accuracy and patient outcomes.
• Supply Chain Management: Automating supply chain management processes, such as inventory management and purchase orders, can improve operational efficiency and reduce costs.
• Patient Engagement: Hyperautomation can automate patient engagement processes, such as appointment scheduling and follow-up care, vastly improving patient experience.

The healthcare industry stands to gain immensely from hyperautomation, as it can streamline administrative tasks, improve patient outcomes, increase data accuracy, and enhance overall operational efficiency.

A Real-World Hyperautomation Use Case

In this example of hyperautomation, we’ll cover how hyperautomation can revolutionize the insurance claims process by automating tasks that were previously done manually, resulting in faster claims processing, reduced costs, and better customer experience.

When a customer files an insurance claim, a traditional process would require a claims adjuster to manually review and process the claim by sifting through piles of documents and data, which can be time-consuming and prone to errors.

With hyperautomation, an insurance company automates the entire process, from claim submission to payout, using several different technologies:

1. A digital assistant or a chatbot interacting with the customer, collects all the necessary details for the claim, then hands it off to an IDP solution
2. IDP software classifies, reads and extracts data from the claim form, including policy numbers, coverage details, and damages incurred
3. After data extraction, machine learning analyzes the data, and makes suggestions based on the information
4. Generative AI drafts a personalized email to the applicant, informing them their claim has been processed, and when they can expect to receive their payout
5. A robotic process automation solution updates the customer’s record in all the necessary systems (CRM, ERP, etc.)

This example shows how hyperautomation involves several different technologies working together. In the next section, we’ll cover some of the most common technologies used in hyperautomation.

Hyperautomation Applications & Technologies

There are multiple types of software and tools involved in hyperautomation. Some of the more common technologies include:

1. Intelligent Document Processing (IDP): Technology that uses artificial intelligence and machine learning to extract and process data from structured and unstructured documents.
2. Robotic Process Automation (RPA): RPA automates repetitive manual tasks, such as data entry and document management, to improve efficiency and reduce costs.
3. Artificial Intelligence (AI): AI refers to the simulation of human intelligence in machines, enabling advanced decision-making, natural language processing, and predictive analytics.
4. Generative AI: Generative AI is a type of artificial intelligence that can create new and original content, such as images, text, or music, without direct human input. In the context of hyperautomation, generative AI could be used to draft email responses based on customer data.
5. Machine Learning (ML): ML is a subset of AI that enables machines to learn and make predictions based on data inputs.
6. Natural Language Processing (NLP): NLP is a form of AI that enables computers to understand, interpret, and generate human language.
7. Optical Character Recognition (OCR): OCR is a form of AI that enables computers to recognize and extract text from images and scanned documents.
8. Intelligent Process Automation (IPA): IPA combines RPA, AI, and other technologies to automate end-to-end business processes, improving accuracy and efficiency.

These technologies work together to create a comprehensive hyperautomation solution, enabling organizations to automate manual and repetitive tasks, improve decision-making, and reduce costs.

How IDP Enhances Other Hyperautomation Technologies

IDP is a critical component of hyperautomation, as it enhances the functionality of many traditional automation tools. Without IDP, businesses are limited to applying the benefits of those technologies to structured data, which, according to Gartner, accounts for as much as 80% of an enterprise’s total data.³

This means that a significant portion of information is still trapped in documents, both physical and digital. Before it can be handled or analyzed by any automation software, it needs to be structured by a human, a machine, or both.

With documents still playing a huge role in business processes, extracting accurate, usable data from them is the critical first step. Mistakes and errors in this initial step often cascade down to the rest of the process and become more and more costly to fix the further they go downstream.

By supporting other hyperautomation technologies with data previously trapped in millions of documents, IDP increases the return of investment in hyperautomation software and helps organizations accelerate their digital transformation initiatives.

The Hyperautomation Journey

Although implementing the right hyperautomation tool for your business involves a considerable commitment of time and resources, the benefits are numerous. But it is important that the setup is done correctly involving careful planning and execution.

1. Create a Hyperautomation Capability Map
   Identify all capabilities required to achieve task automation, process automation and augmentation goals.
2. Select Technologies
   Prioritizing the tools and technology available to you based on the most important features for your business. Include everything from price to after care.
3. Develop a Roadmap for Your Hyperautomation Project
   Outline the steps and milestones necessary, considering the resources and budget you have available.
4. Implement the Tools
   Ensure that the tools are properly integrated with each other and with your existing systems.
5. Monitor and Review
   You will need to evaluate the results for your implementation and adjust the project as necessary to ensure that it meets your goals.

As with most business strategies, the work isn’t finished when you reach the final step. Hyperautomation is an ongoing journey, but it’s a process that provides numerous opportunities.

Hyperautomation: More than Just a Trend

Hyperautomation is a transformative combination of technologies that is changing the way organizations operate. Through automating manual tasks, improving accuracy, and enabling informed decision-making, hyperautomation can help organizations increase efficiency, reduce costs, and improve customer experience.

As the pace of digital transformation accelerates, hyperautomation will continue to play a critical role in helping businesses stay competitive and adapt to changing market conditions, making it imperative for organizations looking to remain competitive in an increasingly digital world.

1. Gartner: Beyond RPA: Build Your Hyperautomation Technology Portfolio
2. Gartner: Top Strategic Technology Trends for 2022: Hyperautomation
3. Gartner: Organizations Will Need to Tackle Three Challenges to Curb Unstrucuted Data Glut and Neglect.

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