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Hyperautomation
Quixy Editorial Team
April 2, 2024
Reading Time: 8 minutes

By 2024, organizations will lower operational costs by 30% by combining hyper-automation technologies with redesigned operational processes. – Gartner

But what’s all the fuss about hyperautomation, and why has Gartner classified it as a top strategic technology trend?

To answer these questions, we will have to dig deep, but let’s start from the basics –

What is Hyperautomation?

In simple words, it refers to continuous automation in business. When you keep integrating automation into your operations, you hyper-automate. It is an advanced-level step in the process of digital transformation.

Now, let’s speak the Gartner language and see what their definition of hyperautomation is – Business-driven hyper-automation refers to an approach in which organizations rapidly identify, vet, and automate as many approved business and IT processes as possible through a disciplined approach. Hyperautomation involves the orchestrated use of multiple technologies, tools, or platforms (inclusive of, but not limited to, AI, machine learning, event-driven software architecture, RPA, iPaaS, packaged software, and other types of decision, process, and/or automation tools.)

Business-driven hyperautomation refers to an approach in which organizations rapidly identify, vet, and automate as many approved business and IT processes as possible through a disciplined approach. Hyperautomation involves the orchestrated use of multiple technologies, tools, or platforms, (inclusive of, but not limited to, AI, machine learning, event-driven software architecture, RPA, iPaaS, packaged software, and other types of decision, process and/or automation tools.)

hyperautomation

So, isn’t hyper-automation just like automation? It might feel like it, but there’s a significant difference between the two. Automation is limited to simple optimization. Hyperautomation is advanced because it comes with more intelligence to ensure that the whole process is much smarter than before.

The intelligence may come from AI in different forms, such as optical character recognition and natural language processing.

Also read: A Complete Guide to Workflow Automation Software

Will hyperautomation replace human jobs?

We will answer this with a simple quote –

Robots aren’t here to take away our jobs. They are here to give us a promotion.

Manjunath Bhat (Research Director, Gartner)

This is a looming fear among all individuals. Hyperautomation utilizes AI for smart operation. So, does that mean that it will take away human jobs? Absolutely not. It will only optimize human ability. It is not here to replace it.

Getting started with hyperautomation

Hyperautomation is an unavoidable market state in which organizations must rapidly identify and automate all possible business processes

Gartner

So, the sooner we start, the better. But how?

Businesses must first start investing in the right tools and technologies because, at the crux, this is what hyper-automation is all about. Which tools you select will determine how the entire process goes. So, we suggest that you pick something scalable, easy to integrate, seamless, and easy to use.

Also Read: 2022: A Promising Year for No-Code and Hyperautomation

Key elements of hyperautomation

Let’s expand on the aforementioned point of choosing the right tools and speak in detail about the must-dos for hyper-automation. The key elements, according to us, are:

1. Artificial intelligence (AI)

hyperautomation ai

AI includes machine learning, natural language processing, intelligent optical character recognition, and similar processes. They work to augment the entire supply chain. With the help of AI, businesses can automate all time-consuming, tedious, and repetitive processes. Because AI is smart enough to recognize voices and faces, you can use it for numerous tasks.

Integration of AI is one of the most crucial steps for hyper-automation.

2. Event-driven software such as RPA, iPaaS, iBPMS

This includes robotic process automation, iPaaS, iBPMS, etc. This software will handle data migration even when the APIs are not compatible. RPA, for example, will manipulate data. iBPMS, on the other hand, empowers citizen developers to collaborate with machines and successfully form a technological infrastructure.

3. Conversational process automation

Chatbots use cognitive intelligence and respond to users based on their emotional state. When integrated with RPA, this form of automation can be powerful enough to resolve most issues without human intervention.

Expect that everything that can and should be automated will be automated, rightly or wrongly

Gartner

Using the aforementioned technologies, we are positive you will be able to do it rightly.

Also read: BPM and BPA: What’s the difference, and which do you need?

Why Is Hyper-automation Important?

Hyperautomation is crucial because it empowers organizations to achieve unprecedented levels of operational efficiency, agility, and innovation. By combining advanced technologies like RPA, AI, ML, and no-code/low-code platforms, hyper-automation streamlines processes, reduces errors, and frees employees from repetitive tasks. It enhances decision-making through data analytics and accelerates digital transformation efforts. In an increasingly competitive and fast-paced business landscape, hyper-automation is essential for staying competitive, improving customer experiences, and adapting to rapidly evolving market demands.

Benefits of Hyper-automation

It all seems great in theory, but what are the real benefits organizations can enjoy through hyper-automation? List below is the advantages of hyperautomation:

1. Workforce empowerment

When all repetitive and tedious tasks are automated, employees are free to work on productive tasks without worrying about mundane tasks. The workforce will be completely focused on the super-important tasks while hyper-automation takes care of the rest of the processes.

  • Example: A customer service department uses AI-powered chatbots to handle routine inquiries. This frees up human agents to focus on complex customer issues and provide a more personalized experience, leading to higher customer satisfaction scores.

2. ROI

Hyperautomation gives organizations access to analytics data, which is very important for ROI. Businesses can learn from the data and find out which initiatives are making money. They can then iterate and optimize to get a better ROI.

  • Example: A retail company utilizes a No-Code app builder to develop a custom inventory management system. By integrating the app with their existing sales and supply chain software, they streamline inventory tracking and order fulfillment processes. This results in improved inventory accuracy, reduced stockouts, and enhanced customer satisfaction due to faster order processing and delivery times.

3. Business agility

hyperautomation agility

When businesses are agile, they scale and grow without constraints. Hyperautomation enables such agility through AI.

  • Example: A manufacturing company implements hyperautomation in its supply chain management. This allows them to react more quickly to disruptions and optimize inventory levels, leading to increased responsiveness and improved customer delivery times.

4. Upskilling

Through hyper-automation, you can create a culture of upskilling and expert-level support. With all mundane tasks being taken off their to-do list, employees can handle various activities and upskill in the process.

  • Example: A hyperautomation initiative requires employees to learn new skills in working with AI and automation tools. This upskilling process creates a more adaptable workforce and fosters a culture of innovation.

5. Integrations

Seamless integration between cloud and on-premise infrastructure improves communication and reduces lag. All systems will be able to access the centralized data, which means that they will be on the same page. This will help them improve their efficiency.

  • Example: A retail company uses hyperautomation to seamlessly integrate their point-of-sale system, inventory management software, and marketing automation platform. This allows them to personalize customer offers in real-time based on purchase history and preferences, leading to increased sales and customer loyalty.

Also read: What Processes Every Business Must Automate?

The two most common challenges of Hyperautomation

Any new approach introduced in the regular working of business face challenges in the beginning, and hyper-automation is no exception. Some of the challenges of hyper-automation includes

  • Poor quality of data and lack of resources/technical skill shortage prevents businesses from tackling automation efforts.
  • There are n number of automation software available in the marker. It becomes difficult for businesses to choose the one that fits the best. For example, a no-code tool can be helpful if businesses have customized processes.

Difference between Automation vs. Hyperautomation

Think of automation as a helpful robot that can take care of specific tasks for you. It’s like having a little assistant that follows a set of instructions to do things without you having to do them manually. For example, if you have a robot vacuum that cleans your floors on its own, that’s automation in action.

Now, hyperautomation takes this idea and supercharges it. Imagine your helpful robot not only doing one task, but it’s also able to learn, adapt, and take care of a whole bunch of different tasks, even the really complex ones. It’s like upgrading that robot vacuum to not just clean, but also organize your stuff, water your plants, and even remind you when you’re low on groceries.

In simpler terms, automation is like a focused task-doer, while hyperautomation is like having a super-smart multitasker that can handle a bunch of things at once. It uses advanced technologies like artificial intelligence and machine learning to make it happen.

Hyperautomation is the #1 Gartner Top 10 Strategic Technology Trends for the year 2020. Hyperautomation will take automation to the next level, enabling organizations to function faster, better, and smarter. Make sure you choose the right tools to establish it in your organization because its success heavily depends on the choices you make.

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How to Get started with hyper-automation

To kickstart hyper-automation, follow these steps:

  1. Assessment: Identify and prioritize processes for automation, considering complexity and impact.
  2. Define Goals: Clearly state your automation objectives, like cost reduction or efficiency improvement.
  3. Choose Tools: Select automation tools, including no-code platforms, RPA, AI, and ML.
  4. Build a Team: Assemble a skilled team of analysts, developers, and automation specialists.
  5. Analyze Processes: Map existing workflows and identify inefficiencies.
  6. Design Automation: Create a roadmap for implementation, starting with no-code solutions for simple tasks.
  7. Implementation: Deploy no-code, RPA, and AI/ML solutions, ensuring seamless data integration.
  8. Testing: Rigorously test automation solutions.
  9. Training: Train staff to work alongside automation tools.
  10. Monitor and Optimize: Continuously track performance and refine processes.
  11. Scale Up: Expand automation to other areas.
  12. Compliance and Security: Ensure regulatory compliance and robust security.
  13. Continuous Learning: Stay updated with new automation tech and best practices for ongoing success.

Remember that hyper-automation is an ongoing journey, and it’s crucial to adapt and refine your approach as you gain experience and encounter new opportunities for automation within your organization.

Also Read: AI Automation 101: What It Is & How Businesses Are Using It

Industries that can benefit from Hyper-automation

Hyperautomation has the potential to benefit a wide range of industries by enhancing efficiency, reducing costs, and improving decision-making. Here are some industries that can significantly benefit from hyper-automation:

1. Healthcare

  • Automated Patient Intake: Bots can streamline patient registration, appointment scheduling, and insurance verification, reducing administrative burden and improving patient experience.
  • Medical Diagnosis Support: AI-powered tools can analyze medical images and assist doctors in early disease detection and treatment planning.

2. Finance & Banking

  • Fraud Detection and prevention: Machine learning algorithms can analyze transaction patterns to identify and prevent fraudulent activities in real-time.
  • Loan Processing: AI ML automates loan application review, document verification, and credit scoring, leading to faster loan approvals.

3. Retail

  • Demand Forecasting: Predictive analytics can forecast customer demand and optimize inventory levels, reducing stockouts and overstocking.
  • Personalized Customer Recommendations: AI chatbots can recommend products based on customer purchase history and browsing behavior, leading to increased sales and customer satisfaction.

4. Manufacturing

  • Predictive Maintenance: IoT (Internet of Things) sensors and machine learning can predict equipment failures and schedule preventive maintenance, minimizing downtime and production losses.
  • Quality Control Automation: Machine vision systems can automate visual inspection of products, ensuring consistent quality and reducing human error.

5. Insurance

  • Automated Claims Processing: AI ML automates data extraction from claim forms and integrates with insurance systems for faster and more accurate claim settlements.
  • Risk Assessment & Underwriting: Machine learning models can analyze past claims data and customer information to personalize risk assessments and insurance premiums.

6. Customer Service

  • Automated Chatbots & Virtual Assistants: AI-powered chatbots can handle routine customer inquiries, freeing up human agents for complex issues and providing 24/7 customer support.
  • Sentiment Analysis: Text analytics tools can analyze customer feedback and social media conversations to identify satisfaction levels and areas for improvement.

7. Human Resources

  • Recruitment Automation: AI ML automates resume screening and candidate scheduling, streamlining the recruitment process.
  • Onboarding Automation: Automated workflows can handle new employee onboarding tasks like document collection and benefits enrollment, saving time and reducing errors.

These are just a few examples, and hyper-automation applications continue to evolve across various industries. By strategically implementing hyper-automation, businesses can unlock significant improvements in efficiency, accuracy, and customer experience.

Quixy – Your no-code platform to spearhead hyper-automation

Quixy will help you get started with hyper-automation through no-code automation. Quixy is a visual, no-code application platform (hpaPaaS) that helps large enterprises build complex custom software applications faster, with higher quality and lower costs, without writing a single line of code. Get Started Today! Empower your organization with automation and customized app development without coding.

Frequently Asked Questions(FAQs)

How Does Hyperautomation Work?

Hyperautomation combines AI, machine learning, and automation tools to enhance processes. It learns, adapts, and executes tasks with minimal human intervention.

Why Is Hyperautomation Important?

Hyperautomation boosts efficiency by automating complex tasks, freeing up human effort for more strategic work.

What is Hyperautomation used for?

Hyperautomation is used to streamline workflows, integrate data, and improve decision-making across various business areas.

What is an example of Hyperautomation?

An example is using AI to analyze customer data, automate responses, and personalize interactions for better engagement.

What is Hyperautomation vs. automation?

While automation simplifies tasks, hyperautomation goes further by using AI to optimize processes and decision-making, making it smarter and more adaptable.

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