Is hyperautomation in your organization's future?

Enterprises can take their automation efforts to the next level by combining technologies such as robotic process engineering, artificial intelligence, and machine learning.

gears orange large efficient automated machine learning automation

If you asked IT and business executives to name some of the items on their lists of priorities for this year, there's a good chance "add more automation" would be one of them.

Automating processes to complete tasks more quickly and accurately and at the same time reduce costs, has taken on even greater significance during the Covid-19 pandemic. Technologies such as robotic process engineering (RPA), artificial intelligence (AI), machine learning (ML), and others are gaining traction in many enterprises as they look to achieve their automation goals.

An emerging concept that combines these tools to help organizations create broader automation capabilities, called hyperautomation, might just end up being one of the more significant technology trends this year.

What is hyperautomation?

The term was coined by research firm Gartner, which defines hyperautomation as the application of advanced technologies, AI and ML, to increasingly automate processes and augment humans. Hyperautomation extends across a range of tools that can be automated, the firms says, but it also refers to the sophistication of the automation.

"Business-driven hyperautomation is a disciplined approach that organizations use to rapidly identify, vet, and automate as many business and IT processes as possible," the firm says in a December 2020 report on hyperautomation. "Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms."

In addition, to AI, ML, and RPA, hyperautomation might also encompass an event-driven software architecture, intelligent business process management suite, integration platform as a service, natural language processing, low-code tools, and other types of decision, process, and task automation tools. It can also involve established enterprise applications such as enterprise resource planning (ERP).

Among the common use cases for hyperautomation are customer onboarding, order taking, payments, and customer data updates, which are typically highly manual, Gartner says. Other common uses might include regulatory compliance, employee onboarding, product tracking across supply chain systems for retail and manufacturing, and tracking for transportation and logistics.

Hyperautomation has been "trending at an unrelenting pace" over the past few years, Gartner says, mainly because of a pent-up demand for operationally resilient business processes. Organizations have a tremendous amount of "collective" debt—technical, process, data, architecture, talent, and social—that significantly affects their value proposition and brand, it says. "The cause is an extensive and expensive set of business processes underpinned by a patchwork of technologies that are often not optimized, lean, connected, consistent, or explicit," the firms says.

Senior business executives want a path to digital operational excellence, which creates demand for speed, efficacy, and democratization of process automation and data integration, Gartner says, and this has triggered an enormous backlog of requests from business stakeholders for automation using one or more technologies.

The pandemic has accelerated a "default is digital" requirement, the firm says, with many employees needing to work from home and digital customer service becoming a necessity. Companies today need resilience, efficiency, agility, and productivity, and the digital transformations that deliver these capabilities rely on automation.

An example of the concept in action might be a hyperautomation platform that helps a bank better manage cash on hand that was previously measured manually daily or weekly, says Kevin Martelon, consultant and automation partnership manager at Saggezza, a global IT consultancy. This would increase the scope and quality of financial measures that reach executives and inform decisions, potentially uncovering a market opportunity that may have been inaccessible before, he says.

"This can be applied in much the same way to assess loan default risk with more dynamic and time-relevant inputs," Martelon says. "Imagine a world where most if not all loan offerings are priced or approved—and expected to be—at more or less real-time. That's progress."

While the most mature use of hyperautomation is in a growth stage today, the concept is well understood and highly visible mostly across industrial and commercial sectors, Martelon says.

"It is safe to say that hyperautomation is on the rise on the basis of strategic value, but the true realization of this concept has yet to be seen," Martelon says. "It is also important to note that organizations at the leading edge of their respective domain, whether in terms of market capitalization or product development, will be the first to realize the full benefits of this approach."

Gartner's affinity for the concept has spurred increased interest in hyperautomation outside of "best fit" industry such as financial services, logistics, and manufacturing, Martelon says.

Saggezza sees that the organizations adopting hyperautomation as a strategic approach, regardless of their maturity level in terms of the related technologies, are mainly doing so to gain the ability to make progressively faster business decisions with higher quality data.

They also want to increase their use of existing IT investments in AI, ML, and automation platforms including business process management systems. And they want to create a "future-forward" enterprise where IT and the business both see positive results, Martelon says.

Gartner, which listed hyperautomation as the number one strategic technology trend for 2020, estimates that more than 70% of large commercial organizations have dozens of hyperautomation initiatives underway.

What can hyperautomation do for organizations?

Hyperautomation can lead to enhanced processes through more effective automation, which in turn can lead to reduced costs. Gartner predicts that by 2024, organizations will lower their operational costs by 30% by combining hyperautomation technologies with redesigned operational processes.

Hyperautomation can bring organizations a number of other benefits.

Particularly for organizations that are new to the concept, Martelon says, it can help deliver a tangible, documented understanding of current organizational processes. And it can create a working environment where essential human resources have digital "helpers" to perform manual and tedious work.

One of the more intriguing benefits is the possibility of having digital twins to test organizational changes. Organizations create digital twins, virtual representations of entities such as assets, systems, devices, processes, and people, to support business objectives.

Consulting firm Deloitte has projected that the global market for digital twin technology will see a compound annual growth rate of 38 percent, reaching $16 billion by 2023.

The rise of digital twins coincides with the rise of the Internet of Things (IoT), according to Gartner. It says many organizations that either have IoT solutions in production or projects in progress already use digital twins or plan to use them within the next few years. Digital twins are becoming more popular because they have capabilities that significantly decrease the complexity of IoT ecosystems while increasing efficiency, the firm says.

Although it's not the main goal of hyperautomation, it often results in the creation of a digital twin of the organization (DTO), which enables the organization to visualize how functions, processes, and key performance indicators interact to drive value, according to Gartner. The DTO then becomes a vital part of the hyperautomation process, providing real-time, continuous intelligence about the organization and driving significant business opportunities, it says.

AIMultiple, a research firm focused on AI issues, cites numerous potential use cases for digital twin applications in various industries.

For example, in manufacturing digital twins can help engineers test the feasibility of emerging products before they are launched; or enable companies to design various permutations of products so that they can offer personalized versions to customers. Manufacturers can also use digital twins to predict potential downtimes of machinery and improve the overall efficiency of machines.

In healthcare, digital twins can help providers virtualize the healthcare experience to optimize patient care, reduce cost, and increase performance, the firm says. They can improve the operational efficiency of healthcare operations by creating a digital twin of a hospital, operational strategies, staffing, and care models to help examine the operational performance of the organization; or improve personalized care by enabling providers and pharmaceuticals companies to model the genome code, physiological characteristics, and lifestyle of patients, so that healthcare companies can provide personalized care such as unique drugs for each patient.

In retail, merchants can create digital twins of customer personas to improve the customer experience delivered in stores or online. They can provide ideal clothing products to customers based on their digital twin models, for instance.

Companies should plan to incorporate digital twins into their product development strategies, especially if they deal with asset-intensive industries or work in IoT, or risk losing clear business opportunities in their markets, Gartner says.

They should build maps of how digital twins can contribute to short-term and long-term revenue strategies, and use these maps to monetize the full revenue potential of digital twins, the firm says.

Overcoming the hurdles

Organizations interested in deploying hyperautomation need to be aware of and address challenges and requirements they might face as they plan out and execute their strategies.

Before even starting the move, they need to know exactly where they stand in terms of existing automation solutions. "Engage with [a] hyperautomation strategy specific to your level of automation maturity," Martelon says. "We need to know but also assess or confirm our level of automation maturity before reasonably engaging in a hyperautomation journey."

IT and business executives need to understand that hyperautomation involves considerable effort for organizations that have lots of manual processes, Martelon says. "Consider taking a 'step' on your hyperautomation journey before a 'leap'; you will get there," he says. To that end, organizations should consider approaching hyperautomation in phases to better capture return on investment. 

Stakeholders, whether in IT or the lines of business, need to work together as they map out the strategy. "Automation project or program work requires a high level of alignment to succeed," Martelon says.

Once hyperautomation tools and processes are in place, it's important to measure initial outputs to better understand whether the projects are working as expected and pivot if needed. "This is an inherently positive way to address change, and will allow you to create an effective and visible way to approach your hyperautomation journey," Martelon says.

These are all "critically important" steps for any organization looking to succeed with hyperautomation, Martelon says. "These practices are structured in much the same way as a project or piece of work is delivered, and this is intentional as they capture a holistic approach" to hyperautomation," he says.

Gartner has several recommendations for organizations looking to succeed with hyperautomation. These include planning for a mandate that everything that can be automated will be; using automation to optimize and accelerate experimentation of new value streams; demanding holistic mapping of collective initiatives, rather than islands of task automation; prioritizing IT investments based on an iterative multi-year journey involving many business-driven hyperautomation initiatives; architecting and planning for multiple concurrent initiatives to drive operational resiliency, efficiency, agility and productivity; and using fusion teams throughout the iterative process of designing, building, scaling, and governing a hyperautomation roadmap.

For many companies, the effort put into hyperautomation will be well worth it, given the possible benefits. It seems to be a natural progression for organizations deploying tools such as AI and RPA.

"Hyperautomation is irreversible and inevitable," Gartner states in its report on the market. "Everything that can be automated will be automated. Competitive pressures for efficiency, efficacy, and business agility are forcing organizations to address back-, middle- and front-office operations. Organizations that resist the pressures will struggle to remain competitive or to differentiate."

And the sense of urgency in building more automation into business models might increase as organizational look to improve processes further and take advantage of post-COVID-19 opportunities in digital business. Consumers are more open to buying products and services online, or making their purchases at physical locations via contactless technology. Employees have adjusted to working from remote locations. Supply chains need to be more agile than ever. Automation can support all of these areas as well as others.

As IoT and edge computing become bigger components of IT strategies, automation can also play a big role. Businesses that ignore opportunities to automate might find themselves losing out to competitors that take automation to the highest levels.