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The Road to Hyper-automation; Overcoming its Greatest Challenges

As automated systems become commonplace throughout businesses, there is a natural progression to integrate these systems to achieve even higher productivity levels. Often referred to as hyper- automation, this is one of those terms that is less of a technology and more of a methodology or a goal. Laying the groundwork for a “Connected Enterprise”, hyper-automation is the strategic orchestration and integration of various automation technologies, creating an interconnected business model with heightened productivity. Industry experts describe hyper-automation as “a discipline that helps to combine several technologies in an orchestrated manner to deliver end-to-end, intelligent, event-driven automation.” The goal of that approach is aimed at reducing manual efforts and errors, improving efficiency, and increasing the speed of business operations through the integration of various automation technologies, including automation, robotic process automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), and other advanced solutions to automate business processes end-to-end.

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Hyper-automation enables departments across the enterprise to automate workflows – from data extraction and processing to decision-making and analysis, without human intervention. This can reduce the time and cost associated with business operations while improving accuracy and consistency.

The foundational technological elements for hyper-automation are already available to businesses in all sectors and functions.

Leading analyst firm Gartner recently predicted just last year that “By 2024, 90% of integration-platform-as-a-service vendors will enable process automation, while almost all RPA vendors will offer integration via APIs.” However, integrating advanced automated systems poses significant obstacles for entire enterprises. Challenges include complexity, technical expertise, data compatibility, security, scalability, and cost. Despite these challenges, integrating multiple automation technologies can significantly benefit efficiency, accuracy, and cost savings. By addressing these challenges, organizations can create a connected enterprise that unites technology, processes, and people, driving a more intelligent and efficient business environment.


First and foremost, organizations as a whole need to be prepared to tackle the complexity of implementing these technologies. The complexity of implementing hyper-automation can be immense, especially when envisioning it as the key to a Connected Enterprise. To give a sense of how complex this process can be, let’s use a hypothetical example of a large financial institution that has decided to implement hyper-automation to enhance its loan approval process. To achieve this goal, they needs to integrate multiple tools and technologies, such as RPA, AI, ML, natural language processing (NLP), and advanced analytics. That’s assuming that the organization already has these solutions in place to begin with.

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What’s more, the technology implementation team must manage the cultural and organizational changes that come with implementing hyper-automation. They need to collaborate with different departments, provide training and support, and address any concerns or resistance from employees.

Taken together, these elements present a significant challenge. Gartner again provides two key steps to take prior to any actual work. First, “Create a hyper-automation capability map by working with your business peers to identify all capabilities required to achieve task automation, process automation and augmentation goals.”

And second, “Select technologies by prioritizing the key hyper-automation capabilities required to deliver the identified use cases and by following a decision framework to determine the right combination of technologies.” Following these two steps will lay the groundwork for any successful implementation. Technical expertise

Teams across the enterprise must ensure seamless integration of these diverse technologies, which can be challenging as each tool may have different requirements, architecture, and protocols. The team must create a unified platform that allows these tools to work together efficiently. In order to achieve this goal, organizations need to make sure they have the right personnel for the job before taking this next step.

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Data compatibility, consistency, and quality 

With data being gathered from multiple sources, it’s essential for the entire enterprise to ensure data consistency and quality. In a Connected Enterprise, data compatibility, consistency, and quality are of paramount importance.  They need to establish processes for data cleansing, validation, and integration to avoid inconsistencies and inaccuracies that could compromise the automation process.

For example, data management team can standardize data formats and structures to ensure that data is consistent across different systems and applications. This can be achieved by defining a set of data standards, such as data type, format, and length, and enforcing them across the organization.

Similarly, data management team can also leverage data integration tools to extract, transform, and load data from various sources into a unified data model. This can help to ensure that data is consistent, accurate, and up to date across different systems and applications.

Establishing data governance policies will also be important. Solid data governance policies ensure high-quality data that is managed and used in a consistent and secure manner across the organization. This can include defining data ownership, access, security, and privacy policies, as well as establishing data stewardship roles and responsibilities.

Finally, it’s the responsibility of the data stewardship division to continuously monitor data quality to implement quality checks and to ID and resolve issues before they arise. This can be done by implementing data quality metrics and dashboards, as well as establishing data quality management processes and procedures.

Security and compliance

While secure systems are a priority for just about every organization, hyper-automation brings new wrinkles to this issue given the lack of human involvement, particularly with often sensitive financial, personal, or healthcare data being processed.  As the enterprise becomes more connected and automated, the security and compliance aspects gain higher importance. Robust access control, data encryption, and auditing mechanisms are critical tools to ensuring your automated systems are safe from attack.


As the organization grows and transforms into a more Connected Enterprise, it’s vital for the whole enterprise to ensure that the hyper-automation platform can scale to accommodate increasing workloads and adapt to changing business needs. This requires constant monitoring, updates, and optimization of the automation infrastructure. Selecting vendors and technologies at the outset that are capable of growing as your implementation grows is also very important.

Overall, tackling the challenges of hyper-automation will, in the end, deliver a raft of important benefits to the enterprise. Successfully implemented hyper-automation paves the way for a Connected Enterprise, eliminating bottlenecks across all operations, optimizing processes, eliminating the need for time-consuming manual tasks, and fostering a more productive, driven, and motivated workforce. The journey toward a Connected Enterprise may be complex, but the benefits it brings make it worth the effort. Once implemented, it’s the responsibility of the entire organization to regularly evaluate the effectiveness of the hyper-automation solution and fine-tune it to ensure maximum efficiency and return on investment. This may involve monitoring performance metrics, identifying bottlenecks, and implementing improvements. Organizations must plan carefully, involve stakeholders, and continually optimize their hyper-automation strategies.

However, when successfully implemented, enterprises can expect significant benefits; bottlenecks eliminated across all operations, optimized processes, obviating the need for time-consuming manual tasks, and a more productive, driven, and motivated workforce.

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