RST Software
Editorial Team
Magdalena Jackiewicz
Reviewed by a tech expert

Introduction to hyperautomation, its benefits and best practices

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Even with the relentless push for digital transformation, many businesses today are still bogged down by manual processes, which impede productivity and agility. According to Gartner, the future lies in the inevitability that all processes that can and should be automated, will indeed be automated.

Rather than settling for basic automation, there is a shift towards hyperautomation, anticipated to provide much-needed efficiency. This advanced approach intelligently automates business functions by integrating technologies such as robotic process automation, artificial intelligence, and machine learning. So, what exactly sets hyperautomation apart from merely enhanced automation on steroids?

What is hyperautomation?

Hyperautomation refers to the enterprise-wide coordination of automated systems: enabling end-to-end process automation by seamlessly connecting technologies. Unlike simple, standalone automation, hyperautomation takes a holistic approach – analyzing entire workflows to determine optimal integration of automation at each touchpoint.

The concept involves continuously discovering automation opportunities through process mining, then implementing the most effective solution – whether RPA bots, AI assistants, APIs, or more. These components interoperate through central orchestration, optimizing for efficiency while allowing seamless scalability.

With hyperautomation, organizations can automate at unprecedented scale, freeing workers for higher-value responsibilities and unlocking new levels of productivity.

Key hyperautomation technologies

Hyperautomation integrates various technologies, with core components including:

Robotic Process Automation (RPA)

Robotic Process Automation refers to software bots mimicking human clicks and keystrokes, automating rules-based, repetitive tasks like data entry, form filling, and report generation.

For example, an RPA bot can automatically process purchase orders at scale.

Artificial Intelligence (AI)

Natural Language Processing (NLP) makes computers understand text, Machine Learning (ML) allows them to perform new tasks and adapt, and Computer Vision (CV) empowers them to see and interpret the world around them. Their combined power lets computers understand unstructured data, learn, and make decisions.

An AI-powered system can analyze customer emails and automatically route them to the appropriate teams, ensuring faster and more efficient resolution.

Application Programming Interfaces (APIs)

APIs act as messengers, allowing different systems and applications to share data and seamlessly work together. In other words, Application Programming Interfaces enable system interoperability.

For instance, an API can connect an automated scheduling system with a calendar app, ensuring appointments are automatically booked and synced across platforms.


Orchestration tools oversee the entire automation ecosystem, ensuring smooth integration, flexible scaling, and efficient workflow management across components.

An orchestration platform can monitor automated processes, trigger actions based on real-time data, and ensure seamless transitions between different automation components.

While these core components form the foundation of hyperautomation, additional technologies further expand its capabilities:

Process mining

It discovers and analyzes existing processes, identifying automation opportunities.

Intelligent Document Processing (IDP)

IDP extracts data from unstructured documents like invoices and emails.


Chatbot applications and solutions allow to engage with customers and employees, automating simple interactions and freeing up human resources for complex tasks.

Supplementary technologies expand hyperautomation capabilities for discovering and implementing automation. Let’s have a look at how this complex structure is expected to work.

How does hyperautomation work?

Hyperautomation applies process mining to discover automation opportunities within workflows, determine optimal solutions, and track outcomes. Key steps include:

Step 1: Process discovery

Analyzing systems and employee tasks to map processes and identify pain points, this step involves scrutinizing existing workflows and systems to detect inefficiencies or areas that would benefit from automation.

Step 2. Automation planning

This stage focuses on selecting the right mix of technologies for each part of the process, ensuring that automation is both effective and efficient, as well as reviewing processes to determine appropriate integration of RPA, AI, APIs, and other tools at each touchpoint.

Step 3. Development & testing

In this phase, the chosen automation solutions are developed and rigorously tested to ensure they meet the required standards and can handle real-world scenarios effectively.

Step 4. Orchestrated deployment

Launching hyperautomated workflow through a central platform enabling seamless interoperation and governance. It involves ensuring that different technologies work harmoniously and are governed effectively.

Step 5. Insights and iteration

Post-deployment, the performance of the automation solutions is continuously monitored, and adjustments are made to optimize the system based on real-time data and insights.

This lifecycle of discovery, planning, building, orchestrating, and optimizing drives exponential efficiency gains compared to disjointed automation efforts. By following this structured approach, organizations can not only automate individual tasks but also transform entire business processes, leading to significant improvements in efficiency, accuracy, and customer satisfaction. This strategic approach to automation ensures that businesses can adapt quickly to changing market demands and maintain a competitive edge.

What are the benefits of hyperautomation?

Hyperautomation significantly enhances throughput by coordinating various automation technologies, allowing for the handling of higher volumes at a much faster rate. This is particularly evident in scenarios requiring 24/7 operations, where human labor is either impractical or cost-prohibitive.

For example, in a logistics company, hyperautomation can manage and track shipments around the clock, ensuring continuous movement of goods and reducing downtime.

By automating repetitive and time-consuming tasks, hyperautomation frees up employees to concentrate on higher-value activities. This shift not only boosts overall productivity but also enhances job satisfaction and innovation.

An instance of this is in customer service, where automation of routine inquiries enables staff to focus on more complex and rewarding customer interactions.

Hyperautomation optimizes the integration of disparate systems, preventing duplication of efforts and streamlining operations. Dynamic orchestration of these systems ensures scalability and adaptability to changing business needs.

For example, in manufacturing, hyperautomation can synchronize supply chain and production line operations, reducing bottlenecks and improving efficiency.

Leveraging predictive analytics and AI, hyperautomation enables businesses to offer hyper-personalized experiences to customers. This can transform customer engagement, as seen in retail, where personalized shopping experiences are created based on customer behavior and preferences, significantly enhancing customer satisfaction.

The deployment of bots for high-volume, rules-based transactions reduces operating costs, as they perform these tasks more efficiently and at a fraction of the cost of human labor.

In sectors like banking, bots can handle routine transactions like account inquiries and transaction processing, reducing staffing costs.

Automation minimizes the risk of human error and ensures consistency in tasks. Additionally, machine learning algorithms continuously improve systems and processes.

In healthcare, for example, automated systems can enhance the accuracy of patient record handling and reduce errors in medication dispensing.

Hyperautomation facilitates faster iteration and adaptation of business processes through advanced discovery and orchestration tooling. This agility is crucial in rapidly changing market environments, where companies can quickly adapt and deploy new solutions.

The integration of embedded analytics, such as process mining, provides unprecedented visibility into operations and processes. This visibility enables businesses to identify inefficiencies and areas for improvement.

Finally, one of the most desired benefits of hyperautomation, rapidly emerging as its crucial aspect, is automated decision-making. Decision intelligence (DI) stands out by directing the need for:

  • precise information,
  • collaborative efforts, and
  • effective feedback loops.

It finds application in various sectors, such as optimizing portfolios in financial services, setting dynamic pricing in retail and pharmaceuticals, and implementing predictive and prescriptive maintenance in manufacturing. Central to DI is the integration of machine learning techniques, transcending the limitations of traditional rule-based systems to address more complex decision-making scenarios.

Where can hyperautomation make an impact?

Numerous business functions contain subprocesses that are ideal candidates for automation, with key areas of application being:

  • Onboarding – this involves automating document processing and data transfers across HR, payroll, and IT systems. Automating these tasks ensures a seamless and efficient onboarding experience, reducing manual errors and saving time.
  • Order management – automation in this area includes data entry, conducting inventory checks, and coordinating fulfillment. This enhances the speed and accuracy of order processing, leading to improved customer satisfaction and reduced operational delays.
  • IT service operations – involves automating ticket classification and executing basic troubleshooting steps. This speeds up response times and allows IT personnel to focus on more complex issues, improving overall service quality.
  • Finance – comprises automating transaction processing and report generation. By automating these tasks, businesses can ensure greater accuracy in financial operations and timely reporting, aiding in better financial decision-making.
  • Customer service – includes the use of chatbots for handling basic inquiries before escalating to human agents. This reduces wait times for customers and allows service agents to concentrate on more complex queries, enhancing overall customer service efficiency.

Through the lens of process mining, businesses can identify and capitalize on automation opportunities within their fragmented enterprise systems. This approach fosters significant efficiency gains that are unattainable with piecemeal automation strategies, streamlining operations and boosting overall organizational productivity.

Hyperautomation best practices

To optimize the implementation of hyperautomation in your organization, consider these enhanced hyperautomation best practices:

Start small with scalable technologies

Begin your hyperautomation journey by targeting simpler, well-defined workflows. Use technologies like basic robotic process automation (RPA) to automate routine tasks, demonstrating tangible hyperautomation benefits before progressing to more intricate processes. This initial step not only provides valuable learning but also establishes a foundation for scaling up.

Choose the right processes with AI and ML integration

Focus on high-volume, transactional activities that involve repetitive human tasks. Utilize advanced technologies like artificial intelligence (AI) and machine learning (ML) to identify patterns and optimize these processes. This approach ensures that the chosen processes are ideal for automation and can benefit significantly from hyperautomation technologies.

Take a human-centered approach with cognitive automation

Hyperautomation should aim to enhance human capabilities, fostering a synergistic collaboration between humans and bots. Incorporate cognitive automation technologies, such as natural language processing and intelligent decision support systems, to ensure that automation supplements human work rather than replacing it. This approach enhances employee satisfaction and efficiency.

Maintain governance with advanced analytics

It is crucial to audit and monitor your hyperautomation efforts continuously. Utilize orchestration tools and process mining to enable dynamic refinements and adjustments. Advanced analytics and real-time monitoring systems can provide insights into the performance of automated processes, ensuring compliance and facilitating ongoing improvements.

Real-world hyperautomation examples

Real-world hyperautomation examples showcase the transformative power of this technology across various industries, demonstrating its capability to overhaul traditional processes and elevate efficiency and customer experience.

The State of California Correctional Healthcare Services exemplifies hyperautomation's transformative impact in healthcare. Managing over 98,000 patients, the organization, led by IT Director Cheryl Larson, automated critical pharmacy processes. An advanced bot collects and processes data from medication dispensing machines, streamlining drug reconciliation for controlled substances. This integration of AI, robotic process automation (RPA), and data analytics not only accelerates operations but also enhances accuracy and compliance.

This implementation showcases hyperautomation's ability to refine complex, manual tasks in a regulated environment. The system's dynamic workflow efficiently manages tasks, reducing human error and improving operational efficiency. Such strategic use of hyperautomation underscores its potential in revolutionizing healthcare administration, fostering efficiency and reliability in patient care management.

Heathrow Airport presents an instructive case of hyperautomation driven by its employees. After downsizing its IT department, the airport reduced its IT dependency by transitioning the department to an orchestrator role, encouraging a low-code/no-code approach among employees. This strategy enabled staff to develop their own automation solutions, aligning with Gartner's prediction that 70% of new enterprise applications by 2025 will use low-code/no-code technologies.

This initiative led to the creation of practical tools, including a health and safety app for streamlining employee return-to-work processes and a turnaround audit app that eliminated the need for Excel and paper in audits. The tangible results of Heathrow’s hyperautomation efforts are impressive – savings of approximately £1,980 in potential outsourcing costs, a reduction of 120,000 pages of paperwork, and over 1,170 hours saved in manual data entry. These hyperautomation examples highlight the efficiency and cost benefits of empowering employees in the realm of hyperautomation.

Best hyperautomation tools

For hyperautomation, various specialized tools are used, each serving a different purpose. For instance, Celonis is used for process mining, Camunda Modeler for process modeling, and Automation Anywhere for Robotic Process Automation (RPA). There are also numerous tools for integrations, artificial intelligence (AI), machine learning (ML), front-end solutions, and orchestration, such as Camunda Optimize, which ties all these elements together.

In our discussion, we will focus on three key hyperautomation tools – Celonis, Automation Anywhere, and Camunda Optimize – to provide an overview of leading hyperautomation technologies.

Automation Anywhere is a holistic solution with bots, IQ Bot intelligence layer, process mining, and central Bot Insight dashboard. It offers a dynamic hyperautomation platform with key features. The first is an intelligent automation platform that promises to double automated processes and scale three times faster than legacy systems. It utilizes AI and machine learning to convert document data into digital assets, enhancing process automation. Features the Automation Workspace for, scalable instant automation and deployment of digital assistants, and provides security with ISO27001 and Soc 1 & 2 certifications.

While Automation Anywhere focuses on enabling enterprises to automate processes using AI and cloud-based solutions, Celonis takes a slightly different approach. It is centered around eliminating inefficiencies in enterprise operations using:

  • Execution management system analyzes and improves process efficiency by integrating data from various sources, unlocking enhanced performance.
  • Business applications – tools for optimizing operations in key areas like order management, inventory, and accounts.
  • Celonis Studio – a collaborative environment for creating custom solutions, involving customers, partners, and developers.

Transitioning from Celonis, which focuses on optimizing and streamlining business processes, we encounter Camunda Optimize. While Celonis excels in revealing and addressing inefficiencies in enterprise operations, Camunda Optimize bridges the gap between business and IT, offering transparency in automated workflows and decisions. Here is a brief overview of its features:

  • Expressive dashboards – enables the creation of insightful dashboards using process data, highlighting areas of success and those needing improvement.
  • KPIs & alerts – facilitates setting up key performance indicators and custom alerts for real-time monitoring of process performance, ensuring constant vigilance and responsiveness.
  • Insightful analytics – Provides advanced analytical tools like BPMN heatmaps and branch/outlier analysis for a deeper understanding of processes.
  • Holistic overview – Offers a comprehensive view of the entire process landscape, aiding in effective optimization and decision-making.

Camunda Optimize stands out as a powerful hyperautomation tools for businesses looking to delve into data-driven insights for analyzing and enhancing complex processes. It complements the functionality offered by Celonis by providing a more focused lens on workflow transparency and decision-making processes within automated environments.

How RST can help you with hyperautomation

Let RST guide your hyperautomation initiatives – allowing you to vault past competitors still relying on disjointed bots. Our integrated approach delivers efficiency at scale through seamless human and digital collaboration.

With RST as your guide to expediting hyperautomation maturity, you will rapidly outpace competitors – unlocking new levels of productivity. Let us help you transform operations with hyperautomation while lowering risks – delivering the resilient efficiency demanded in today’s climate. Reach out to us to explore how to get started!

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