When businesses can utilize a convenient set of tools to automate, connect, integrate and translate the many different apps and software in their toolbox into a cohesive unit that works well together, that’s hyperautomation. 

The COVID-19 pandemic motivated the sudden drive for hyperautomation as organizations looked to evolve their business and drive automation to all facets of their new reality. Employee shortages, the need for application access and the speed at which all important data can be available are driving businesses to embrace the use of hyperautomation. 

What Technology Does Hyperautomation Use?

When it comes to enabling hyperautomation, there are many technologies and toolsets required. If you think about each of the processes and tasks that you touch every day, each portion of those step-by-step human-led tasks needs a technical counterpart to mimic and work to completion. The hyperautomation toolkit requires a broad technology base to help in automating business workflows and decision-making. It is a way to take these formerly isolated, semi-automated or unautomated tasks and make them fully integrated and seamlessly automated to become something more: a cohesive hyperautomated unit.

1. Robotic Process Automation (RPA) & iPaaS

Robotic processes are the very essence of hyperautomation. Robots or bots excel at repetitive, rules-based tasks. Automating such tasks reduces the workload on humans by 70% to 80%, so your human labor force can concentrate on more value-added tasks. Many of your day-to-day business processes can be automated using RPA, such as processing applications, procure-to-pay, reporting preparation and data transfer. An Ephesoft poll at a webinar in July 2021 revealed that 42% of attendees rated RPA systems as their top hyperautomation tool.  

Taking RPA to the next level, iPaaS, or integration Platform as a Service, provides a deeper and robust integration capability through simple and easy-to-use no-code interfaces.

2. Intelligent Business Process Management Suites (iBPMS)

Simply put, iBPMS enables the creation of physical, real-world processes in the virtual realm.  They allow the creation, operations and monitoring of these processes and provide a means for strategic management of automation. This creates more effective workflow experiences from start to finish through the use of cloud-based platforms and low-code/no-code tools. 

3. Process Mining

A new and highly innovative software, process mining, gives businesses the ability to study their current “processes,” identify the flow of the process and summarize how those processes are running on a day-to-day basis. It provides detailed and data-driven logs about each process, including function, timeliness, operator, and how that data compares to the average. Process mining can identify repetitive tasks given to people and allow companies to transfer those tasks to automation tools. 

4. APIs

Application Programming Interfaces (APIs) are the meet and greet of the software world. They are the middleman that lets two different software types talk to each other. Using APIs, developers can harness data from different software types into a single interface or application, and provide an integration layer that ties hyperautomation elements together. 

5. Artificial Intelligence (AI) and Machine Learning

AI today goes beyond just collecting data – it has morphed, through business needs, into a deep understanding of data. Artificial Intelligence and Machine Learning are similar disciplines, but their differences lie in automatic learning. AI can mimic human responses, while machine learning adapts from human responses and enhances this intelligence. AI is paramount to raising the level of automation to levels humans could never achieve.

6. Natural Language Processing (NLP)

Natural Language Processing is a subset of artificial intelligence that deals with a computer’s ability to learn spoken and written language. It takes the real-world input of language and converts it into a code that a computer can understand. It is necessary for automating complex use cases where sentiment and key text must be analyzed.

7. Intelligent Document Processing

OCR technology can scan and digitize documents but it has its limits. When OCR is taken to the next level using AI or machine learning, it is called intelligent document processing (IDP). Any form or document can be parsed, read classified and data extracted using this technology. IDP takes unstructured or unsearchable information and transforms it into structured, actionable data.

For example, Agnico Eagle Mines used Ephesoft integration to process handwritten invoices that had been previously manually entered. With intelligent document processing technology, like Ephesoft Transact, the invoices are automatically captured, extracted and exported into their ERP solution. With this implementation, the accounting staff can process 20,000 more invoices per year.

How Can You Put Hyperautomation to Work?

Most of the fundamental processes of a business can be hyperautomated. Here are just a few examples of how hyper and intelligent automation can help your business.

  • Chatbots can assist many customer service applications 
  • Unstructured documents can be automatically read by IDP, simplifying and accelerating data retrieval 
  • AI and machine learning can ease the burden on customer support using conversational AI and RPA
  • RPA can analyze financial transactions, find pertinent information and scan and assess for fraudulent activity
  • iBPMS combined with RPA assists enterprises to analyze their business and procedures

Cost Savings and ROI Using Hyperautomation

Many businesses report 80% cost and time savings from their automation projects, and your savings will depend on the level of implementation you choose. 

The desire for hyperautomation hit hyperdrive during the pandemic, while the landscape showed some room for improvement and exposed technology gaps. Businesses realized that they needed to ensure that all nodes in the process talk to each other in the same manner. As you plan your hyperautomation strategy, be sure to discuss how your needs align with your existing technology stack.  

Also, consider the ROI of reallocating your staff away from data input and toward operations within your company that require human interactions. For example, the time saved travels downstream as managers no longer need to approve documents weeks and months later because the process has been hyperautomated. 

With more remote workers — or even workers distanced within an office — hyperautomation propels businesses as feature enhancements have reached new departments that hadn’t previously realized the need. Because of this shift, the next layer of hyperautomation will reach all departments working in harmony.