The Future of RPA: Cognitive Automation and the Future of Robotic Process Automation
September 30, 2019
Improving work efficiency has always been one of the main goals of companies. Efficiency is key to a more productive and successful business. One of the best ways to ensure this is by streamlining processes through automation.
Implemented in places like manufacturing industries, e-commerce businesses, IT companies in the Philippines and worldwide, and other businesses, process automation has helped create faster and more efficient processes.
Today’s process automation can trace its roots to early programmable software and machinery that helped automate the early manufacturing and computing industries. This development eventually led to the creation of software that specializes in analyzing and learning various patterns and procedures.
This type of automation is referred to as Robotic Process Automation (RPA). Aside from its successful implementation at present, RPA has shown that it has a massive potential to develop into something even better in the near future. One of these developments is called Cognitive Automation.
Cognitive Automation and RPA
Some people see Cognitive Automation and Robotic Process Automation as two different systems. The reality is that Cognitive Automation is a system that is able to complement and optimize the processes of RPA.
RPA copies and automates repetitive human tasks. These can include sending large numbers of emails, accounting, storing and organizing data, calculating benefits and compensations, conducting transactions, and more. Automating these simple and repetitive tasks helps employees focus on more important work. It is also a comprehensive system that is able to provide a more accurate and refined process.
The continued use of RPA has also pushed towards a more refined and intelligent system that has the ability to learn and provide a wider range of automated functionality. This has led to the development of Cognitive Automation. This is a system designed to learn, analyze, compute, and process data in order to create decisions and develop processes independently.
Cognitive Automation provides RPA systems with the ability to learn and analyze data through a process called machine learning. This helps the system decipher and study data in order for robots to understand their functions. Another process used by Cognitive Automation is deep learning. This is when a system executes decisions based on the data it has.
The functions that Cognitive Automation can perform are due to the advanced set of technologies that it is able to use. These technologies include text analysis, language processing, data analysis, and data acquisition. This allows the systems to mimic human-like decision-making and understand more complex processes. Using Cognitive Automation helps overcome the limitations of RPA and implement a more refined process that adds more capabilities to the existing system.
Robotic Process Automation and Cognitive Automation are two technologies that help optimize the workplace. By making use of both technologies, you will be able to have a system of automated processes that can execute a wide range of functions with little to no human supervision.
Automation in Business and Industry
The use of automated systems has revolutionized the workplace of companies and industries across the world. When it comes to picking which one to utilize, there is no clear answer. You would eventually need both systems to work together to have the best work efficiency. Here are a number of notable examples where their functionality can be applied.
One of the busiest industries today, e-commerce stores are required to handle the requests and transactions of thousands of customers on a regular basis. This is why RPA and Cognitive Automation are systems that would be able to help. RPA would be able to handle basic tasks such as sending customers emails and tracking personal data. Meanwhile, Cognitive Automation has the ability to respond to customer inquiries and guide customers to the intended product or service.
Automation is also useful in the telecommunications industry. Call centers have become one of the most automated industries around the world. Call center agents are equipped with tools that help them respond to customer and service inquiries. RPA helps call center agents lessen the workload of repetitive tasks like responding to emails and acquiring data. Cognitive Automation provides customers with a system that is able to respond to unique and complex inquiries and messages. This can assist call center agents in leading customers to the right services.
One of the first industries that have embraced automation, manufacturing companies have greatly benefited from the use of automated systems. RPA and Cognitive Automation provides benefits such as improved processes, comprehensive data acquisition and analysis, and faster client response systems.
The Future of Automation and IPA
The future of automation does not end with the use of RPA and Cognitive Automation. New technologies like Intelligent Process Automation are being introduced to businesses and industries. Intelligent Process Automation, or IPA, is an automated system that makes full use of artificial intelligence technology. It uses both RPA and machine learning to create and perform complex functions and tasks.
IPA learns tasks and actions through data analysis but aims to develop new methods and more efficient processes. This is another step towards increased automation, as utilizing this system would provide better work efficiency and effectiveness through the use of advanced Artificial Intelligence systems.
Automation is increasingly becoming more widespread and commonplace in businesses and industries across the world. Through the use of systems like Robotic Process Automation and Cognitive Automation, a wide range of simple and complex work tasks can now be done independently. This will help improve work and service efficiency across the board. While automation still has many ways to go in the future, its next systems will continue setting new benchmarks.
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