What is hyperautomation?

Many financial organizations use hyperautomation to increase the speed of their business operations. One example of hyperautomation is the automated credit card approval process. Financial institutions get thousands of credit card applications every day. While traditional automation helps with pre-filling forms and validating fields, hyperautomation takes it to the next level. The hyperautomation framework communicates with different systems and retrieves customer data such as credit balance and debt. It automatically performs background checks on the customer. Then the hyperautomation framework approves or rejects the application based on the data it retrieved and the pre-set rules. Thus, hyperautomation makes the credit card issue incredibly faster.

Customer service is another real-life example where hyperautomation augments the human workforce. When a customer service executive gets a call, the hyperautomation pulls up various details about the customer from different systems and makes the task of the customer service executive easier.

Why should organizations embrace hyperautomation?

Hyperautomation is a top strategic technology trend of 2020. While automation is a familiar term, hyperautomation is still a new concept for many organizations.

Establishing a hyperautomation system is a challenging task, but it has a multitude of benefits, such as increasing the efficiency of the workforce by automating repetitive tasks. Hyperautomation helps employees to concentrate on more interesting and challenging tasks. It also reduces the chances of human error and biases in decision making.

Highly competitive sectors like finance have already embraced hyperautomation strategies. Organizations that use remote process automation are just a few steps away from hyperautomation, so they should look towards integrating artificial intelligence and machine learning into the automation framework to reap the benefits of hyperautomation.

Technologies that facilitate hyperautomation

Hyperautomation is a complex process that combines many cutting-edge technologies. Here are different technologies facilitating hyperautomation:

Robotic process automation (RPA)

Robotic process automation uses computer programs known as software robots to automate structured and repetitive tasks. For example, in manual data entry, an employee looks at the forms submitted by customers and types in that data into a spreadsheet. If the input forms are standardized, a software program can mimic the actions of the employee by retrieving information from the relevant fields in the form and filling out the spreadsheet. This is an example of robotic process automation. Robotic process automation is not as simple as writing a piece of code to accomplish a simple task. It uses technologies like artificial intelligence to understand external events and change accordingly.

Artificial intelligence and machine learning

Artificial intelligence and machine learning are widely understood technologies in their classic context. In hyperautomation, robotic process automation is used in conjunction with artificial intelligence and machine learning techniques. When an organization ventures to implement hyperautomation, it has to deal with large volumes of unstructured data, such as emails, chats, text messages, and purchase orders. Artificial intelligence techniques are used to process unstructured data.

Another application of artificial intelligence in hyperautomation is pattern recognition. Hyperautomation analyses the data and makes decisions without manual intervention. For example, hyperautomation uses artificial intelligence to analyze insurance claims and, based on the models, detect fraudulent claims.

How does hyperautomation work?

Implementing a hyperautomation ecosystem in an organization is a complex task as there is no single workflow for hyperautomation. Instead, it combines many processes, including intelligent document processing, automated business process discovery, and robotic process automation.

Automated business process discovery

A hyperautomation system detects which business processes can be automated instead of organizations. Hyperautomation deploys software bots to identify these processes, and the ecosystem creates software robots to perform those processes. Hyperautomation looks through the enterprise processes that are structured and repetitive, then it records how an employee performs this task and creates a systematic workflow. Based on this, the hyperautomation platform creates software bots that can perform this workflow.

Intelligent document processing

Organizations spend a lot of time analyzing their unstructured and semi-structured data. Semi-structured documents include weblogs, sensor data, XML data, activity logs, and customer forms. Emails, text messages, customer reviews, images, and videos are unstructured data.

In an organization with traditional automation, employees examine these documents and convert them into a structured format then automated processing happens on this structured output. This manual processing of unstructured data is time-consuming, error-prone, and mundane. It might lead to human errors and employee dissatisfaction.

What if an organization can automate the conversion of unstructured data in structured data? Hyperautomation uses remote process automation powered by artificial intelligence to achieve this. Hyperautomation uses natural language processing, computer vision, fuzzy logic, and pattern detection to read, classify, analyze, and extract information from unstructured data.

Advanced analytics

We have seen that hyperautomation can add structure to unstructured data and automate the business processes. Another main component of hyperautomation is the advanced analytics of unstructured data. Every organization has a vast volume of data at its disposal, such as customer data, reviews, surveys, and social media interactions. Most of this is unstructured data, and organizations may find it challenging to analyze this data. With hyperautomation and its advanced technologies, organizations can now derive insights from this data. Most of the software bots not only perform their designated task but collect and analyze a plethora of data while they do it. When an employee does the same task, they might easily overlook this process-level data.

What are the benefits of hyperautomation?

Increased efficiency

Automation increases the efficiency of the workforce. Organizations who still use manual processes may create bottlenecks, even when using simple automation. For example, in an automated business process, if at any stage, an employee should manually validate the results, it creates a bottleneck; hyperautomation removes this bottleneck by entirely eliminating the need for manual intervention.

Employee satisfaction

In many organizations, employees need to perform repetitive, legacy tasks that could be easily automated. Employees might feel underwhelmed doing such tasks that do not offer intellectual stimulation. Hyperautomation takes away the stress of having to do repetitive, structured tasks, so employees can find time to do more valuable jobs, leading to better employee satisfaction.

Create a digital twin of the organization

A digital twin of an organization is the digital replica of its business processes. Take, for example, the case of a supplier who gets a request for a quote via mail. An employee manually creates the quote and sends it to the customer then the customer sends a purchase order, which the supplier fulfills. With hyperautomation, all these processes are automated, and the automated pipeline behaves just like a particular business process. With a digital replica, organizations can derive real-time, continuous insights about their business processes, opening up a huge opportunity for the business and process streamlining.

Elimination of human error

When an employee performs repetitive tasks like filling a spreadsheet with financial data, there is a high chance of error. The software bots installed by the hyperautomation doesn’t make human errors. Once deployed, they perform as expected in normal scenarios.

What are the challenges in implementing hyperautomation?

While hyperautomation comes with a multitude of benefits, its implementation can be a challenging task for organizations.

Hyperautomation is complex and diverse

Hyperautomation doesn’t just automate a handful of processes--it creates a new ecosystem based on automation. It is a complex process that demands expertise in various technologies and business processes and a collective effort from different departments of an organization.

Solution: Collaboration is key to implementing an effective hyperautomation ecosystem. Many teams in the organization should come together and share information about the business process. They should cooperate to leverage technologies that are spread across the organization. Teams should share their expertise and insights for the success of hyperautomation.

Employees might be skeptical

While hyperautomation improves the efficiency of the workforce by performing mundane tasks, employees might be skeptical about it. They may fear that the hyperautomation ecosystem will gradually take away their jobs. So, any attempt to implement hyperautomation in an organization may meet with resistance from employees.

Solution: Revolutionary technologies are always met with certain friction from people. For example, when personal computers came out, many were worried about the loss of manual jobs. However, it only created more job opportunities. Hyperautomation is similar. While it takes away the repetitive, mundane tasks, it also opens up new avenues for innovation. Organizations should encourage employees about new opportunities. The organization should explain to employees the problems that hyperautomation solves that will assist them. There should be a clear roadmap for hyperautomation.

Creating more complexities

Hyperautomation aims at simplifying the business process, but if used incorrectly, it might complicate and add more processes to the workflow.

Solution: Automating every business process may not be required or not even advisable. Don’t use hyperautomation to create more processes; instead, carefully evaluate the current business processes and identify which needs to be automated first and slowly progress towards more coverage. When it comes to hyperautomation, organizations shouldn’t rush. They should spend enough time to draw up an implementation plan, identify a process to automate first, then set up teams to participate in hyperautomation efforts.