Quite recently, Gartner shared a reprint on the necessity for the enterprise architecture and technology innovation leaders to look beyond Robotic process automation (RPA) and target on delivering end-to-end automation. This is more of a strategically defined approach and the focus lies on both the tactical and strategic goals of an Enterprise. This essentially involves following a more integrated approach by augmenting RPA with its counterparts like AI, ML, NLP, ETL. Gartner coined this as ‘Hyperautomation’.
The need to look Beyond RPA
Enterprise architects and technology innovation leaders focus more on tactical automation over a strategic roadmap. Without any doubt, Robotic process automation is great when it involves automating the more functional, tactical, routine needs of an enterprise, however, for the complex processes, it’s just not enough. Thinking of larger, strategic-level business objectives, it needs to be combined with the complimentary technologies to succeed in the strategic output. Gartner states that “By 2022, 65% of organizations that deployed robotic process automation will introduce artificial intelligence, machine learning, and natural language processing algorithms.”The approach, thus, must shift on the end-to-end automation by integrating the functional and process silos.
Three (strategic) Musketeers to enable Hyperautomation
Some still confuse Hyperautomation with IT automation, they are not the same. While Automation is about optimizing a process or a task, Hyperautomation is an additional layer of ‘intelligent’ automation, i.e., adding artificial brains to IT automation.
Hyperautomation is a strategic jump and is here to stay. Let’s understand how does a business gets going with Hyperautomation. Gartner has laid out three key strategies to help enable Hyperautomation in organizations- Planning, Applying, and Augmenting.
- Planning the Hyperautomation journey
A business wouldn’t succeed without a strategic plan in place, so would any idea or a process, same applies with Hyperautomation. A blueprint is to be put in place at the beginning of it. It is essential to define the business objectives and understand what processes are to be worked upon, in what priority, the scope of it, etc. Digital ambitions can cost you a fortune if gone wrong or make you a fortune if done right. Therefore, a digital vision must be set i.e., understanding whether to transform, optimize, or to leave the process under question uninterrupted. Revenue, cost, and risk play a vital role here. Answering each of these, as an example, the process that you are thinking of optimizing, once optimized would it reduce the cost by improving its efficiency or can redesigning the process be a better option. All the three are to be well defined at the start of it.Next step is to optimize the process. However, a clear understanding of the use cases for optimizing processes is of importance. This can be achieved by focusing on understanding how smart your process can be, scaling the core processes and enhancing these processes with structured and standardized data inputs, and decision intelligence. Once the roadmap is set, it steers the path clear for next steps.
- Applying the right combination of tools and technologies
Once we have had the plan ready, it is time to identify the tools and technologies that are closely aligned to our roadmap and would get us the expected output as per the defined objective. Tools that simplify, measure, and manage the processes are to be put to use. DigitalOps is one such process framework that addresses different stages of process automation. A wide variety of tools is used to discover, analyze, design, monitor, and to enable end-to-end process automation. Identify the optimum combination of these tools that would be required as per the use cases and the business objective.How effectively and seamlessly these tools and technologies are communicating and working with each other needs to be vetted as their good compatibility score would help in a smoother transition.
- Augmenting with intelligence, Artificial Intelligence
Now is the part where “intelligent” automation comes to play, time to augment human capabilities to achieve end-to-end process automation. AI technology has its impeccable imprint across industries like Insurance, banking, retail, media, healthcare, and more. AI technologies are to be deployed as per the business needs and according to each use case. Since AI and ML have low explainability it is imperative to first determine how AI functions will perform along with other components. Identify if there is any chance of hindrance within the automated process. Augmenting with AI, ML, and other processes is tougher than it seems. It involves ensuring optimal augmentation of AI and other applications, assessing the required resources, and all factors, including actors, trigger points, the list goes on. Hyperautomation is the need of the hour, yet it can turn into a failure if all the stages are not addressed properly. It is too much for a business to look into every aspect of Hyperautomation and ensure there is absolutely no gap there. Experts intervention thus play a fundamental role in the smooth shift to Hyperautomation.
- Planning the Hyperautomation journey
AutomationEdge – Your Hyperautomation partner
AutomationEdge is ones such RPA platform with AI and service management capabilities to automate IT and business operations and can ensure swift migration to Hyperautomation. AutomationEdge is one of the first automation tools to hold Hyperautomation capabilities. It comes with inbuilt technologies like RPA, Artificial Intelligence, Machine Learning, Natural Language Processing, iPaaS, data ingestion, technology integrations and is one of the finest Hyperautomation solutions for businesses.
Looking to transition to Hyperautomation? Contact us at email@example.com for a discussion.