The common denominator for many of those who have already started the journey towards Digital Transformation is the use of Robotic Process Automation (RPA) that enjoy, or will enjoy, Artificial Intelligence services, as a means of achieving the goal of digitization and automation of business processes.
However, in most cases, the potential and benefits of this combination are completely unknown or underestimated in the development of the best strategy for Digital Transformation in business, so, to better understand the combination of such technological solutions, it is necessary to know the basic concepts.
What is Intelligent Process Automation?
RPA is what is called the software ecosystem that provides programming, testing, implementation, and management of the codes delivered to software robots to execute them, constituting the digital workforce, this being able to replicate monotonous activities, due to the high degree of repetition, previously performed by people when interacting with the applications.
Like people, once “taught” and “trained”, software robots will be able to perform the repetitive and low value-added tasks often considered mundane in the daily life of those who work on them, such as understanding what is on a screen, pressing the right keys, navigating through various application windows, identifying and extracting data, and performing a wide range of predefined actions and activities.
In turn, Intelligent Process Automation is the combination of RPA and AI technologies, such as Machine / Deep Learning (ML / DL), Natural Language Processing (NLP), Intelligent Document Processing (IDP), Computer (or Machine) Vision, among others.
In effect, the ability to teach and train the software robots, using Machine Learning techniques, providing significant amounts of samples and/or storing the history of decisions made by people, when necessary, elevate Process Automation to a level where it becomes possible to address levels of high complexity, with the consequent delivery of greater added value to the organization.
Such simplification allows people’s efforts to be redirected to the analysis of results, instead of being occupied with both the execution of the process itself and overcoming intrinsic limitations, either to the process or to the applications inherent to it.
The Intelligent Automation of Processes can also include the use of Virtual Assistants and/or Chatbots with recourse to NLP, automating the communication channels with the outside world, in order to increase the efficiency of these means and, thus, provide faster responses to customer requests.
Moreover, solutions that implement Intelligent Document Processing (IDP), resulting from the evolution of Optical Character Recognition (OCR), from the incorporation of intelligent ML and NLP services, allow organizations with intensive use of physical documents, such as health or financial services, to dematerialize them and automate their digitalization in order to speed up the classification, extraction, and processing of relevant information, providing better and faster decision-making and reducing costs.
When to use Intelligent Process Automation?
- Intelligent Document Processing (IDP) – In the handling of unstructured documents that may contain sensitive information, images, emails with or without attached files;
- Automation discovery via Task or Process Mining – In assisting in the analysis process of the actions most frequently performed by the user at his workstation, or in the steps performed daily in the applications and their work tools, generating “heatmaps” and the script to automate them;
- Agility in workflows – In the analysis of the history of the transactions executed in the existing applications in order to map the flows traveled and make the processes more agile and efficient;
- Supply chain management – In forecasting and readjusting production planning and procurement needs, in order to meet changes in supply and demand.
The best way to define a strategy for the mix of two such powerful technologies is to first understand their role in a potential Digital Transformation process.
RPA provides value in automating processes based on structured data, many of which previously required intensive manual intervention, while Artificial Intelligence collects data from various sources to feed services that provide useful and desirable information to increase the value of RPA.
The successful application of this combination of technologies raises the bar for automatable processes, according to their weight and the role they play in the organization they are part of.
Inevitably, by combining these two technologies there is an addition of strategic value, with the creation of solutions that use a knowledge base to streamline processes and interactions between applications. The subsequent solutions become even faster and more accurate, and contribute to the following efficiency gains:
- Increase in productivity – The Intelligent Automation of Processes from multiple sources of data, structured or not, allows for greater productivity and accuracy in planning cycles;
- Cost reduction – This is the most relevant benefit, since, according to studies, it is estimated that there is an average cost reduction of around 22%;
- Improvement in decision-making precision – the use of structured or unstructured data undoubtedly guarantees greater precision in the outputs generated and, in turn, better decision-making with minimal human intervention;
- Enriches the user/customer experience – By using this technological combination, it is possible to glimpse and better understand customer needs, communicate more effectively and put higher quality products/services to market. Customers, in turn, are typically more satisfied and happier with their overall experience.
Although some misconceptions about Intelligent Automation of Processes still persist, for example, that it will progressively replace people, or that it is something “cute” to implement but not really necessary to the functioning of an organization, or even that the decisions taken by these technologies are intrinsically biased, due to the relatively controlled data collection, among others, we strongly believe that RPA supported by Artificial Intelligence services can significantly improve people’s lives within their organizations.
Based on this belief, we concentrate our efforts on the adequate use of these technologies and, in this way, everything tends to improve in the global functioning of the organizations, starting from inefficient processes that become totally efficient, the good management of people’s time and, thus, decisions are taken based on valid inputs that are very close to the most varied business areas since these technologies are completely transversal and applicable to multiple purposes.