Hyperautomation Changing Business

Hyperautomation has the potential to disrupt and accelerate business all over the world. It is necessary to be prepared.

There is automation, and there is hyperautomation. Buckle up!

Before we get to hyperautomation, we should start with automation within the enterprise in the context of business process automation. Or as it is often called, robotic process automation (RPA). First of all, RPA is a software solution to automate repetitive tasks in the organization like calculations, record-keeping, making reports, filling forms, and much more. RPA typically handles digital data that must be worked on or transformed in some way. If a human employee must click, drag-n-drop, copy and paste, etc. with mind-numbing repetition, that is a great indicator of if a task could be automated with RPA.

What is Hyperautomation?

RPA is a software “robot” that imitates the actions of a human users – keystrokes, mouse movements, and applications used. Once automated, these tasks take place in the background while the human employee is doing other tasks, working in parallel. An important observation to make here is that RPA “robots” do not know what they are doing; they are programmed to mimic the actions of a human user click for click. There is no flexibility for non-typical cases.

Hyperautomation integrates AI/ML in order to automate enterprise automation. In a nutshell – automate the automation. This can achieve enterprise-level scalability for automation that uses methodical processes to identify processes and tasks that could be automated, as well as increasing the capabilities and flexibility of the automation “bots” that carry out those tasks.

The underlying technologies

Hyperautomation is a concept, not a single technology. Take a look under the hood at the tech making it work.

RPA is a foundational part of hyperautomation since it delivered a lot of the groundwork for business process automation. It made great progress into no and low code development options and many useful integrations. These capabilities are carried over into hyperautomation for better usability for business users.

But of course hyperautomation doesn’t just automate the tasks, but it automates the process of automating tasks. This requires discovering processes and tasks that could be automated with what is called process and task mining. This uses data from an event log to identify and assess processes from the backend.

But most notable of all is the incorporation of AI/ML for more dynamic automation, using natural language processing (NLP) to better handle unstructured data, machine learning models for computer vision, continuous learning and improvement, and much more.

Hyperautomation synergy with future technologies (machine learning, AI)

Automation and AI/ML are a great match. Here is why:

AI/ML thrives on data-rich tasks that are repetitive because at its core it is a mathematical model that ingests data and returns a prediction based on its previous training. It requires extensive training on tasks that are all similar to each other, and after the model is trained is only suitable to continue tackling tasks like those it handled in training.

A more existential quality of AI/ML is its ability to disrupt business as usual. Concepts of autonomous vehicles will change the landscape of cities as well as the logistics industry with uncalculatable legal implications, AI is a tool that will escalate the cybersecurity conflict between defenders and attackers, and its contribution to digital identities will change how humans interact online and in the real world. Hyperautomation (with the help of AI/ML) is changing the approach to enterprise process automation by removing active human participation more and more. The human is shifting into an oversight position while the day-to-day tasks of running the business are handled automatically which will change the work landscape in years to come.

Curse and blessing of Hyperautomation

Hyperautomation is a disruptive concept. And like any disruption, it can help and it can harm.

Efficiency and reducing repetitive work for human employees should be a familiar theme when considering AI/ML, and it is definitely the case here with hyperautomation. Overall, it is relieving the workload of human employees that manage time-consuming tasks. With the implementation of hyperautomation, many tasks are removed from human employee’s workloads to free up their time for more demanding and creative work.

But it is also very likely that many human roles in the organization will be made redundant, causing job loss for many individuals. And since hyperautomation is likely to see widespread adoption across most industries, human employees with similar skills will be eliminated from their roles across all industries and making it unlikely that they will be rehired elsewhere without significant upskilling. Implementing hyperautomation comes with a responsibility to train employees for other types of work, or to offer compensation for upskilling when they are let go.

Security must also be integrated into hyperautomation initiatives. Connected data and systems provides a larger threat surface and potentially more damaging data breaches if the organization is attacked. Data governance that is adapted for automated tasks must be in place, especially for sensitive data that may be part of the automated process. Appropriate access management for both humans and bots must be in place, along with constant monitoring for vulnerabilities.

Hyperautomation practices taking over business

Hyperautomation isn’t about automating exact tasks, but about reshaping the way the organization approaches tasks. Here are some common use cases:

Goal-oriented hyperautomation: The organization may define a goal to improve a particular KPI, like time needed to process invoices. Although the task may belong to a particular department, it could pull data from different departmental siloes, require communication between different team members, or an approval from a manager. Begin with a key metric to determine were to focus your hyperautomation initiative. Examples include focusing on accounts payable, ordering, document processing, customer service, and much more.

Vendor map: Guidance for you

This is a dynamic vendor space with many new entrants. Here are a few vendors to get you started:

UiPath, Automation Anywhere, Blue Prism, Celonis, Microsoft, Kryon, WorkFusion, ABBYY, Pegasystems, and many more.

Conclusion  

Think carefully about how you approach hyperautomation. It has great potential to serve your organization if managed in a strategic and intentional way.

Hyperautomation is a tool for the digitally transformed organization. Organizations that are successfully operating digitally have critically examined and adapted their business and operating model to fit the changing world and its expectations for user experience, sustainability, ubiquitous connection, and global scalability. Digital transformation does not follow a single recipe, but is unique to each organization, its mission, and its existing and future IT architecture. Hyperautomation better serves the digitally transformed organization by benefiting from connected cross-organizational data, well-architected security and identity management systems and clear business goals that automation helps to achieve.

Be critical of implementing a hyperautomation initiative. Question how it fits with your organization’s digital transformation plan. Does widespread automation of internal processes really help accomplish your business goals, or is it just a cost-cutting measure? Account for the human cost on your organization, including the changing demographics of consumers as more and more are made redundant and will make different buying choices as a result. And build accountability into the individual tasks being automated, with visibility into why a task was handled the way it was. In light of the massive scalability that hyperautomation brings, the individual should not be lost.