What is Hyperautomation?


What is Hyperautomation?

Hyperautomation is a process in which companies utilise AI, machine learning, event-driven software, robotic process automation, and other types of process automation tools and decision-making tools to automate and augment business processes. Gartner uses Hyper-automation to describe the use of combining digital tools to achieve digital transformation. 

Hyperautomation can be facilitated through DigitalOps, a business process framework designed to simplify, measure and manage the entire or a specific business process. DigitalOps, or digital operations, is the heart of your digital transformation, providing the orchestration of systems and other resources. It incorporates mechanics for sensing and responding while potentially supporting dynamic learning and optimisation.

The DigitalOps toolbox offers more than just RPA (robotic process automation) technologies, including BPM, workflow engines, decision management suites, process mining, low-code application platforms (LCAPs) and more. 

What is the purpose of the DigitalOps toolbox?

The DigitalOps toolbox helps with three critical hyper-automation aspects: process automation, system orchestration, and intelligence.

Process automation refers to a hyper-automation mindset that introduces the world of “automating anything that can be.” If bots or other technologies can handle a process or a task, then it should be carried out by bots.

Orchestration: Hyperautomation adds an orchestration layer to simple automation. Orchestration happens through intelligent technologies such as intelligent business process management.

Intelligence: Machines can automatically perform repetitive tasks, but they lack human decision-making capabilities. We need artificial intelligence to achieve the perfect balance of letting machines “think and act” or attain cognitive abilities. Natural language processing, machine learning, and artificial intelligence algorithms and analysis are combined to promote simple automation to become more cognitive. Technology does not simply follow if-then rules but helps gather insights from data, enabling robots to have decision-making capabilities.

Critical strategies for enabling hyperautomation

Plan your automation journey

A solid plan is a MUST if you want to achieve your business objectives with hyper-automation. Designing the desired business outcome and the processes that need to be optimised before automating and assembling tools from the DigitalOps toolbox is important.

If your goals are clearly defined, the planning process becomes simple. Make sure you have the right experience to handle all the emerging technologies involved in hyper-automation and develop a clear roadmap. 

Implement DigitalOps Tools

Consistent with business model-driven process automation, the DigitalOps toolbox has many options for solving process automation discovery, analysis, design, automation, measurement, monitoring, and re-evaluation. The DigitalOps tools are BPM Platforms, RPA, Low-Code Application Platforms, Process Mining and Discovery and Decision Management Suites (DMSs)/Business Rules Management Systems (BRMSs). 

Ensure to check your use cases and long-term business goals to determine the best combination of these tools and have the necessary infrastructure during the implementation phase. 

Augmentation

To accelerate hyper-automation, an integrated system of intelligence effectively combines DigitalOps tools with Artificial intelligence (AI), Machine learning (ML), Natural language processing (NLP), Optical character recognition (OCR) and Conversational chatbots.

Therefore, to achieve business value, you must implement artificial intelligence technology to provide specific, measurable business outcomes for the targeted use cases. Then you should develop candidate use cases for AI and ML and determine measurable business outcomes from each use case to understand how the built-in AI ​​features works with other components during the automation process. 

Businesses must highly integrate communication channels between these technology stacks to achieve process efficiency. You should also achieve the best improvements among all applications that evaluate their required resources and other related factors.

Want to know more about robotic process automation? Visit here

 

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