What Is Hyperautomation?

Hyperautomation is the use of a combination of automation technologies to automate and streamline business processes. It involves automating as many tasks as possible, including those that were previously performed by humans. Although it is often associated with automating repetitive tasks, it can also be applied to more complex business processes.

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Hyperautomation and Low-Code

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What are the benefits of hyperautomation?

hyperautomation strategy 

Benefits of a solid, well-executed hyperautomation strategy include:

  • Increased efficiency: Hyperautomation enables organizations to automate repetitive and manual tasks, increasing operational efficiency. By automating these tasks, employees can focus on higher-value activities that require creativity, critical thinking, and problem-solving.
  • Improved productivity: Automation reduces the time and effort required to complete tasks, resulting in improved productivity. With hyperautomation, organizations can streamline and optimize end-to-end business processes, eliminating bottlenecks and reducing manual errors. This allows employees to accomplish more in less time.
  • Cost savings: By automating tasks and processes, organizations can reduce costs associated with manual labor, human errors, and rework. Hyperautomation eliminates the need for repetitive, time-consuming activities and minimizes the likelihood of errors, leading to cost savings in the long run.
  • Enhanced accuracy and quality: Automation ensures consistency and accuracy in performing tasks. By minimizing human intervention, hyperautomation reduces the potential for errors caused by fatigue, distractions, or lack of attention. This leads to improved quality, precision, and reliability in business processes.
  • Scalability and agility: Hyperautomation enables organizations to scale their automation initiatives across departments and functions. It provides the flexibility to handle increased volumes of work without a proportional increase in resources. Additionally, as hyperautomation leverages a combination of technologies, organizations can adapt and evolve their automation capabilities to meet changing business needs and market demands.
  • Data-driven insights: Automation generates large amounts of data that can be analyzed to gain valuable insights. Hyperautomation can leverage AI and ML technologies to extract meaningful patterns, trends, and insights from the data collected during the automation process. These insights can be used to drive informed decision-making, optimize processes further, and identify opportunities for improvement.
  • Improved customer experience: Organizations can enhance the overall customer experience by automating processes. Automation enables faster response times, reduces errors, and ensures consistency in customer interactions. This leads to improved customer satisfaction, loyalty, and retention.

Examples of technology that supports hyperautomation

Common hyperautomation technology includes:

hyperautomation technology examples 

Many, if not most, of these technologies, are fortified with or connected to tools with artificial intelligence (AI) and machine learning (ML) algorithms that can automate next steps in processes and perform intelligent analysis.

What are some hyperautomation use cases?

High-volume, repetitive processes that still involve manual work by several people across departments are good candidates for hyperautomation.

It is also beneficial to focus on processes that are time-sensitive (i.e., faster for machines), require audit trails, or would not even be possible without automation due to data volume, especially those that benefit from AI and ML analysis.

Here are a few examples of hyperautomated processes:

  • Data extraction: OCR can extract and convert data into a machine-readable format from scanned or photographed documents and PDFs. That data can then be validated and enriched against internal and third-party databases by machine learning tools and submitted to the proper systems, such as CRM and ERP. Hyperautomated data processing can be used by accounting departments, supply chain, insurance companies, legal firms, and any others that handle large amounts of documents with both structured and unstructured data.
  • Customer service: A customer call center may automate the transcription of service calls and then use NLP to correct the transcriptions. The company can then use NLP to look for patterns in these transcriptions – along with chatbot records — to uncover trending issues, measure sentiment, inform better self-service topics for the website or automated telephony options, help with agent training, and improve chatbot performance.

What are the key steps in the journey to hyperautomation?

Hyperautomation is often managed by Chief Information Officers (CIOs) or Chief Digital Officers (CDOs). Optimally, these executives should work with fusion teams to identify processes ripe for automation, as well as to vet the tools and technologies to be implemented and integrated into workflows.

While each fusion team can be responsible for implementing technologies for their function, it is crucial to have a holistic overview of all hyperautomation initiatives to identify overlap where automation tools can be used across functions and departments, spot opportunities for collaboration, and minimize doubling of efforts and wasted resources.

Organizations should start with process discovery to identify all processes that need automation. To determine prioritization of projects, that list should be analyzed in terms of alignment with key business goals, available resources and budget, and breadth of use across the company.

Fusion teams can then take responsibility to vet and implement the technologies and integrate the automated processes within existing systems and workflows. This process will be iterative, as the teams evaluate, refine, and optimize the automation technologies and find new opportunities for use.

What are some hyperautomation best practices?

Gartner advises that fusion teams engender the best results for hyperautomation efforts.

In a recent survey, Gartner found that the three top ways to increase likelihood of success of hyperautomation initiatives involved taking the work of business technologists (aka citizen developers, who are key members of fusion teams) seriously, ensuring responsiveness to business technologists’ needs, and brokering connections and communities of practice.

Other best practices include:

  • Use fusion teams to work on concurrent initiatives to speed automation efforts
  • Holistically map all initiatives, so there aren’t siloed efforts
  • Involve fusion teams throughout the lifecycle of all projects, including the overall hyperautomation roadmap and governance, to ensure optimal results and agility for future business model changes.

Why should you invest in low-code to support your hyperautomation strategy?

In its latest Magic Quadrant for Low-Code Platforms, Gartner identified low-code platforms as a key component for a successful hyperautomation strategy.

Quotting Varsha Mehta, Senior Market Research Specialist at Gartner,

“Organizations are increasingly turning to low-code development technologies to fulfill growing demands for speed application delivery and highly customized automation workflows. Equipping both professional IT developers and non-IT personas — business technologists — with diverse low-code tools enables organizations to reach the level of digital competency and speed of delivery required for the modern agile environment.”

Low-code development provides a rapid application development framework that can be used to build applications that incorporate and orchestrate the various automation technologies involved in hyperautomation. It enables organizations to implement automation solutions more efficiently and empowers non-technical stakeholders to participate in the automation process.

A high-performance, low-code application development platform like OutSystems allows you to deliver brilliant web and mobile workforce apps, employee portals, and operational dashboards. It offers a best-in-class user experience and superior integration with third-party systems of record. It is, therefore, a great tool for building custom applications that automate and orchestrate your unique cross-functional workflows.

These allow for greater productivity and operational efficiency. OutSystems’ AI-powered, automated impact and dependency analysis also allows you to take an adaptive and iterative approach to process improvement.

To learn more about it, visit our Process Automation page or watch our webinar Streamlining Business Operations with Intelligent Automation.