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According to Gartner, a reference in research and consulting for businesses, the global market for hyper automation software, which involves applications for a massive automation approach, generated US$ 481.6 billion in 2020 and is expected to have exceeded US$ 532.4 billion in 2021. This is a number that will be confirmed in the coming months.
In its forecasts for 2022, Gartner included hyper automation as one of the main technological trends of the year, as the process enables companies to foster accelerated growth and build business resilience by quickly identifying and automating as many processes as possible.
Hyper automation is part of the digital transformation landscape, being achieved through the combination of advanced techniques such as Robotic Process Automation (RPA), Process Mining (PM), Machine Learning (ML), and Artificial Intelligence (AI). To reach this high level of automation, a company will need to utilize several tools, including advanced analytical, discovery, design, measurement, monitoring, and complex automation software. It is important to be aware that hyper automation will bring profound changes to the company, both in structure and mindset.
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To reach the stage of hyper automation, however, companies need to embark on a journey and change their practices to create intelligent work environments. The internal support ecosystem should provide the appropriate IT infrastructure and solutions, support from senior management, financial backing, team training, and continuous evaluation of results.
The first step in this journey for a company involves structuring and organizing the database from various sectors: commercial, operational, financial, and others that make sense for the business. The data will likely be organized in an Enterprise Resource Planning (ERP) system.
It is worth noting that automating a business process without understanding its function or steps can represent wasted investments and efforts. It is also important to understand that hyper automation aims to free employees from repetitive and low-value tasks, reduce operational costs, and increase efficiency.
Is It Scalable and Standardized?
A process mining solution is a relevant tool in this journey, as it allows for data-driven analyses of processes that will reconstruct the actual flow of business processes based on transaction logs in the organization’s main IT systems. Thus, the construction of the flow to be automated will not depend solely on the information provided by employees – sometimes, there may be a gap and bottlenecks between the actual process and the ideally designed one by management.
For the implementation of RPA tools, processes must be scalable, repetitive, and standardized. When a company has complex and non-standardized processes, automation may not be feasible or may require substantial investment initially, leading to the need for review or postponement.
Users participating in a particular process should be mobilized to train the robots in the workflows. During this “training” phase, typically in a pilot project, the processes to be automated can be evaluated using the process mining application. An RPA initiative requires continuous monitoring of results and using these findings for improvements.
The combination of robotic process automation with artificial intelligence technologies should generate more options for processes to be automated. The use of AI solutions is increasing as hyper automation advances, as machine learning generates relevant and original content, further accelerating digital transformation.
Source: Chris Santos:
Text: *Rogério Ferreira is a Solution Architect | Pre Sales at A10 Aanlytics and has a degree in Process Management and Data Science
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