Hyperautomation Exponentially Advances Data Processing and Accelerates Business Workflows

Hyperautomation Exponentially Advances Data Processing and Accelerates Business Workflows

Bringing as many automation tools as possible to accelerate data analysis and intelligence

Rich Dugdell

In 1936, Alan Turing birthed computer science when he presented a hypothetical machine that could compute any problem that could be described by encoded instructions on a paper tape.

Before this breakthrough, computers were people. They spent hours compiling tables, crunching calculations, and postulating probabilities. The first computer could perform the same calculations in seconds, which some say helped turn the tide of World War II.

When we compare this automation to processes today, we still look for tasks that robots and computers simply do better than humans, whether that’s crunching data, testing substances or chemicals, and lifting heavy objects. And by automating these processes and embedding capabilities like business process management, analytics, artificial intelligence (AI) and machine learning (ML), you take things to the next level with what is known as hyperautomation.

An emerging, explosive capability

Many assume hyperautomation is the next major evolution of automation technologies. Think of it as a Turing machine cranked up to 11. In fact, Fabrizio Biscotti, research vice president at Gartner, said hyperautomation is a “condition of survival” for organizations. Gartner also named hyperautomation the top strategic technology trend of 2021. Needless to say, this is a significant mover and shaker for the future of digital transformation.

Hyperautomation is a methodology that enables organizations to rapidly automate as many processes as possible using robotic process automation (RPA), AI, and other emerging technologies. One of the technologies we use specifically at SAIC to enable hyperautomation is called MetaSift. MetaSift processes and manages customer data, from capture through to archiving, by using AI and ML capabilities, thus accelerating data analysis. This enables companies to get real-time intelligence and analysis of their data. My colleague Jim Tuson leads SAIC’s hyperautomation domain to utilize RPA, business intelligence (BI), business process modeling and notation (BPMN) and user experience (UX) methodologies with DevOps teams to rapidly deliver solutions to our customers.

Organizational change

It’s common for skeptics of RPA or hyperautomation to assume that these technologies will result in scaling back the workforce. There may not be as many number-crunchers as there were back in Turing’s day, but today, there are problem-solvers and decision-makers who use data to move their organizations forward.

Analysts shouldn’t be wasting their valuable time and energy on processing data that a machine can do. They should be studying those data outputs to discover trends and nuances that machines can’t identify.


SAIC's hyperautomation experts leverage AI to process and manage data for analysis, accelerating the insight-creation process for customers.

I’ll give a quick example. Analysts at a microbrewing company were reviewing data from the previous year’s sales and noticed periodic spikes in the Northeast. They analyzed the dates, crosschecked it with some analytics, and uncovered that more beer was sold, and even stocked out, when there was severe weather. Because of that analysis, the company was able to prepare its supply chain for higher demand during forecasted storms, thus increasing profits and satisfying more customers.

Today’s analysts have to be trained to find trends and shifts in data to move in the direction of actualizing hyperautomation. Obviously, someone has to input all that data into the system, but once those automated processes come into play, hyperautomation creates those analytics, not people.

Hyperautomation is ultimately a companion to top-rate analysts who can interpret and infer analytics to change how their organizations operate. Hyperautomation transforms business processes just as much as it augments repetitive tasks.

Redirecting resources

One of our customers had a seemingly routine bookkeeping issue and found itself unable to process invoices as fast as it was receiving them. This customer almost hired $1 million worth of contract bookkeepers. Instead, we built four programs that processed invoices at the speed of automation. This customer saved millions, which allowed them to divert funds to other arms of the organization that were facing budgetary constraints.

The opportunity costs of hyperautomation are not always as easy to put into picture as this use case. But as hyperautomation reengineers processes, the organization can focus on improving decisions, saving money and, in many cases, lives.

Hyperautomation's future and applications

What really excites me about the components of hyperautomation is that they’re all proven technologies. There’s no need to do a proof-of-concept, and there’s no ongoing research, which means that the next step is finding applications for the technology.

Hyperautomation is the future because of how the automation industry has advanced to a transformational point. Multiple tools working together are brought in to improve an entire system, which improves multiple aspects of both the processes and data simultaneously. That naturally leads to improved efficiency, productivity and most importantly decision-making. The nature of hyperautomation is to enable and encourage teams to collaborate and work together, by providing transparency and near real-time feedback that enhances workforce communication and knowledge-sharing.

The biggest advancement in hyperautomation will be the continuous, gradual integration of AI. By introducing AI incrementally into our customers' mission processes, hyperautomation helps solve mission problems that our customers are not able to focus on today, allowing them to transform their mission goals and outcomes.

To learn more, contact me at richard.t.dugdell@saic.com.

Written with Jim Tuson, Solutions Architect Master

Posted by: Rich Dugdell

Software Engineer Director / SAIC Fellow

Rich Dugdell is a software engineer director and SAIC Fellow in SAIC’s Strategy, Growth, and Innovation Group.

Dugdell specializes in information management and applied analytics, working on hyperautomation research, and is the lead for SAIC’s MetaSift product. He is also a technical lead on several programs across SAIC’s National Security and Space Sector and Defense and Civilian Sector, developing and deploying mission-critical customer solutions.

Dugdell came to SAIC in 2005 as a senior systems engineer, delivering commercial multimedia exploitation techniques for a digital audio and video enterprise program. He later became the technical lead on several intelligence community programs.

Prior to joining SAIC, Dugdell worked with many Fortune 100 companies to create enterprise solutions that addressed the impacts of digital convergence and the ever-increasing need to move capabilities to the cloud. He was also the professional services lead architect for Open Text, where he led more than 50 enterprise engagements with both large and small teams.

Dugdell received a Vanguard Award in 2015 for mission excellence and innovation in his work on multimedia analysis and forensics programs. He was also recognized for his work on MetaSift with the 2018 Washington Technology Industry Innovator Award. Dugdell is a member of IEEE and AIIM, focused on cloud-based information systems technologies and content analytics and processing techniques.

Dugdell earned his bachelor’s degree in management information systems from Ashford University.

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