What is Hyperautomation? Everything You Need to Know

We live in a world where extremes are the new normal. Everything from technology to nature has evolved to be more specialized, more precise, and more powerful than ever before. As these hyperspecific attributes shape every aspect of our lives, the way we work and interact with the world around us is also undergoing a radical transformation.  

 

This shift is most evident in the rise of hyperautomation where advanced technologies come together to streamline business operations and enhance productivity.

 

So, what is hyperautomation?

Hyperautomation is the use of advanced technologies to automate complex business processes in an effort to minimize manual intervention and drive digital growth. 

 

To discover what hyperautomation is built from and why it's crucial to your business, keep reading. 

What Advanced Technologies are Used in Hyperautomation?

 

1. Robotic Process Automation (RPA)

Let's start with the definition: What is RPA? RPA is a critical part of hyperautomation tools as it enables the workflow automation of day-to-day repetitive tasks. In large enterprises, implementing RPA can autonomously handle hundreds of minor to mid-level priority processes, significantly saving time and human resources. 

 

RPA uses "robots" to mimic what a person does on a computer, like filling out forms, moving files, or processing invoices. It doesn't involve physical robots but smart programs that take over routine computer tasks, freeing up people to focus on more creative and important tasks. 

 

Another key aspect is that RPA enhances compliance and security levels in business operations. It ensures that processes are executed consistently according to predefined standards and regulations. This is particularly relevant in finance, healthcare, and insurance, where compliance is non-negotiable. Additionally, the risk of data breaches and human errors are brought to a minimum through RPA. 

2.  Artificial Intelligence (AI) and Machine Learning (ML)

AI and ML are foundational technologies driving hyperautomation to the next level. They make automation systems highly adaptable and equipped to learn from data, make decisions, and continuously improve performance. 

 

AI fosters the implementation of intelligent automation by bringing natural language processing (NLP), image recognition, and predictive analytics into the picture. ML, on the other hand, completes the package of AI benefits by enabling automation systems to act based on past data and evolving patterns. 

 

An AI chatbot is one of the most common tools that best portrays the successful combination of AI and ML in workflow automation. It perfectly understands and responds to user queries through AI and then leverages ML algorithms to improve the quality of communication by learning from previous interactions.

3. Business Process Management (BPM) Tools

BPM tools enable businesses to map, analyze, and optimize their existing processes, ensuring stronger alignment with strategic goals. Two key components of BPM tools are process mining and task mining. 

 

Process mining uses the extracted data to visualize and analyze how business processes are actually performed, helping companies identify bottlenecks and inefficiencies from the desired workflows. On the other hand, task mining focuses on understanding the micro-level tasks that employees perform to complete specific processes, offering insights into repetitive tasks and areas for automation. 

 

Together, process and task mining provide a comprehensive view of both macro and micro workflows, enabling them to make data-driven decisions for automation and process optimization. 

4. Cloud Computing

Cloud computing provides the scalable infrastructure necessary to support the rapid deployment and integration of automation technologies. With cloud platforms, businesses can access vast computing resources and storage without significant upfront investment in hardware. 

 

Additionally, the cloud enables real-time collaboration, faster processing, and continuous updates, ensuring that automation systems stay up-to-date and perform optimally.

 

5. Usage of Low-Code or No-Code Platforms

Low-code and no-code platforms are practical tools that automate specific processes with minimal technical effort. For example, a marketing team can use a no-code platform to automate the lead generation process by creating a workflow that captures contact information from forms, sends follow-up emails, and updates the CRM - all without writing a single line of code. 

 

These platforms help businesses quickly build and deploy automation solutions that integrate with existing systems, reducing the need for costly custom development and enabling faster time-to-market. 

 

What is Hyperautomation Used for?

To understand what hyperautomation is used for, let's take a look at an example from the travel and tourism industry. 

 

 

 

Hyperautomation vs Automation

At first glance, hyperautomation might seem like a more advanced version of automation, but in reality, they differ greatly in their scope of application, resource demands, and impact on businesses.

 

Automation refers to the technology of automating repetitive tasks, like sending out emails, generating reports, or processing invoices. So, it's typically rule-based, which means it follows specific instructions to complete a task effectively.

 

Hyperautomation, on the other hand, takes this concept much further. It combines traditional and emerging technologies like artificial intelligence, machine learning, and robotic process automation to not only automate tasks but also make smarter decisions, adapt to new situations, and handle complex processes. For example, instead of just sending out an email, hyperautomation technology can analyze data, decide which emails to send, and even personalize them based on customer preferences. It's about creating a connected, intelligent system that automates as much as possible across an entire organization. 

 

Cons of Hyperautomation

Although not many, hyperautomation still has disadvantages. Here are some of them:

 

• Risk of data privacy

• Potentially biased approach from AI

• Large upfront investment 

• High maintenance costs

• Dependence on technology

• Job displacement concerns
  
  

   

Last Words

Hyperautomation holds immense potential, but it's not a magic fix. It's a journey of blending technology with human expertise to create something better. When used thoughtfully, it's a powerful ally in simplifying the complex and giving people more freedom to tackle real challenges!