Levels of automation can be complex to understand, as very few organisations if any have reached a level of automation where computers have complete control of tasks. Organisations who have started to implement RPA within their business have already experienced a positive impact regardless of the level of automation. A report published by Everest Group (2017), shown in figure 2, suggests that the level of automation can be spilt into four distinct categories as outlined below:

  • RPA 1.0: The objective of the first category is to improve the workers productivity with the help of automated tools. The robot does not perform the tasks but assists the human workforce with their effort. At a very basic level, a calculator will not perform complex analysis but can be used to accelerate addition, subtraction or multiplication within a process.

Figure 2: Levels of Robotic Process Automation (Everest, 2017)

  • RPA 2.0: In this category, RPA is deployed to carry out end-to-end tasks. The robot is no longer helping the human workforce but replacing it. However, the objective is far from straight forward and the human workforce still has a key role to play in supporting the deployment and scale of the new digital workforce. At this stage organisations will have a centralised robot management system in place, with the retrained human workforce analysing robot performance and orchestrating scheduling and queuing.
  • RPA 3.0: By the time an organisation is operating in this category, end-to-end tasks will be fully automated, and the human workforce will be focusing their efforts on exception handling. As processes age, new exceptions occur which require resolution. In this instance the task of resolving the exception falls to the human workforce. This is often referred to as “human-in-the-loop”. However, over time the digital workforce will start to learn by studying patterns and recalling how the exception was previously resolved. At this stage in an organisation’s journey they will have a Cloud / SaaS (VMs) & on-premises deployment. Features will include, advanced analytics and workflows, auto-scaling, dynamic load balancing and context awareness.
  • RPA 4.0: The final category sees RPA integrated with AI technologies such as Machine Learning, voice recognition, computer vision, text analytics, natural language processing and natural language generation. These enhanced capabilities provide the organisation with a whole series of digital interactions, for example; object connectivity on the screen, voice and visual interfaces, processing of unstructured data, predictive and prescriptive analytics, automation of tasks that involve cognitive decision making and diagnostics that enable your robots to self-manage and selfheal. At this stage, the objective for the human workforce is to increase the scope of automaton and simplify the development and management of the digital workforce.

These levels of automation do not need to be achieved in a step by step manner. The scalability of each level depends on the organisation’s capability and the resources it has at its disposal to invest in its automation journey. Much of the initial hype about RPA has been related to RPA 1.0. The future potential is an order of magnitude larger as organisations address solutions in the later stages. Not all processes can be improved by applying full automation. Much will depend on a specific problem or opportunities the organisation faces.

It is worth noting that the term RPA is sometimes used to broadly refer to a range of available technologies. RPA stage 1.0 would refer to the basic scripting available in traditional RPA tools. For RPA stage 4.0, a wider range of the tools would be required covering a range of other automation capabilities. This is shown in the automation ecosystem model in figure 3, depicting RPA as a satellite function, including other technologies such as; Artificial Intelligence (AI), Optical Character Recognition (OCR) and Robots as a Service (RaaS), also incorporating data analytics and the enablement and empowerment of people. This ecosystem is underpinned with BPM as the foundation of its core.

Figure 3: Automation Ecosystem

All this makes RPA look like a pragmatic and powerful solution, a big business opportunity. Value-driven RPA has to realise those opportunities systematically.


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