What Is Hyper-Automation and How Should Companies Apply It?

Many people believe hyper-automation is the key to taking companies and industries into the future and allowing them to be as efficient as possible. Most individuals are at least somewhat familiar with how automation can make things easier. 

If a manufacturer automates some processes, it could save time, increase output, decrease the likelihood of worker injuries and more. However, hyper-automation takes things to the next level. According to Gartner, “Hyperautomation is a business-driven, disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible.” 

The definition also continues by explaining that people engaging in hyper-automation plan their uses of several advanced technologies, such as artificial intelligence (AI), machine learning, robotic process automation (RPA) and event-driven software architecture. 

In short, it goes beyond company leaders picking a couple of advanced technologies and putting them to work for the good of the organization. Instead, hyper-automation involves highly orchestrated efforts where technologies work together to achieve more benefits than one could alone. 

How Does It Differ From Traditional Automation?

There’s a critical difference between automation and hyper-automation. When people seek to automate something, they typically only focus on one aspect of a process. For example, a company might use mobile robots to restock workstations rather than having workers replenish the items they need. 

Hyper-automation requires taking a holistic approach and optimizing all stages of a process, from beginning to end. That often means it’s necessary to examine the root causes of problems that decision-makers want to solve. 

For example, conventional automation solutions often drastically reduce error rates. Machines excel at repeated processes, and they can perform them for hours on end without breaks. Such industrial automation can also minimize human injury and fatigue. 

However, a hyper-automation approach would ideally aim to find out what causes mistakes or product flaws in the first place. It might include an artificial intelligence data collection system that gathers statistics about the particular processes. By looking at that content, factory managers could use hyper-automation as a springboard for error reduction. 

What Results Has Hyper-Automation Given Early Adopters?

Many company leaders are still at relatively early stages in their digital transformations and technological journeys. So, the idea of even considering how they might apply hyper-automation is too daunting for now. However, they may feel more encouraged by the outcomes of people who adopted it much earlier and have had time to notice the results.

Analytics India conducted a survey to learn more about hyper-automation trends in 2021. One of the main takeaways was that there’s still a relatively small percentage of people that have adopted it. Another thing to keep in mind is that it was a relatively small study, with 320 people participating. 

The results showed that manufacturing has the highest adoption rate, reaching 28%. However, there are large differences in overall usage across industries. In the insurance sector, only 2.3% of companies use it. The health care sector came second after manufacturing, with just over 23% of people using some type of hyper-automation solution. 

When asked to confirm the associated benefits of that decision, 37% of respondents said hyper-automation accelerated complex work. Then, approximately 18% of people reported that it saved them time and money. Nearly 17% of respondents mentioned improved decision-making. Despite noticing those benefits, hyper-automation adoption was not trouble-free. 

Approximately 32% said their main challenges concerned a lack of skills. Then, nearly 27% struggled with the costs to implement hyper-automation. These findings are useful reminders that people interested in using it at their workplaces should perform preliminary assessments. Those examinations could reveal the specific obstacles that company representatives should try to overcome or accommodate.

What Should People Consider Before Using Hyper-Automation?

Most tech-related transformations are less likely to succeed if there’s not enough planning in place at the start. Sabina Amaricai is the founder of Qualinest and a software testing architect there. She explained that a lack of specificity is one of the main reasons why many companies have not implemented hyper-automation. More specifically, she said decision-makers don’t have a handle on their process flows. 

Amaricai recommended that people in charge ask themselves several process flow-related questions before moving ahead. A good start is to determine what need hyper-automation will fill, and what the company must do to achieve that desired result. 

They also must iron out how the process flow happens now. What steps does it involve and which parties or departments handle them? Finally, company leaders must decide what data inputs would help reach the previously identified goals.

Amaricai recognized that the data-input step is the most challenging for a couple of reasons. First, companies have ever-growing amounts of information. The sheer volume of it could make it difficult to narrow down which information is truly relevant and valuable. She also noted that many companies still have legacy systems. Those could make it difficult or impossible to extract the required data. 

Could Companies Hyperautomate Their Contact Centers?

There has been a relatively recent and ongoing push to automate many parts of customer service call centers. That could happen via a chatbot that gets the primary details of a person’s situation, then sends them to the right department or person for further help. Alternatively, a customer might receive a satisfaction survey distributed to them with a RPA product. 

However, a 2020 e-book suggests hyper-automation could take things even further. It explains the potential for breaking out of siloed departments and processes. If that happens, companies could develop centralized, overarching goals to improve their contact centers. 

One scenario mentioned in the e-book was that customers would initially contact companies over the phone or text chat. From there, both robots and humans would handle their requests, depending on the specifics. The tech contains elements of RPA and AI, so it falls under the hyper-automation umbrella. 

However, the content also clarified that hyper-automation does not necessarily mean removing the human element. In the case of a contact center, humans remain at the heart of all the organization’s activities.