The construction of Robotic Process Automation (RPA) is similar to that of employees’ digital assistants. It can simplify business operations, reduce costs, and reduce human errors. However, due to content incompatibility, Robot Process Automation (RPA) software has pitfalls in content processing. Companies need to find ways to overcome the shortcomings of robotic process automation (RPA) content processing.
As industry experts have pointed out, there are some ways to overcome these shortcomings. One way to overcome the shortcomings of robotic process automation (RPA) content processing is by combining other intelligent technologies and integrating them into the system.
Gopal Ramasubramanian, Senior Director of Intelligent Automation and Technology at Cognizant explained, “Robotic Process Automation (RPA) technology is mainly used to automate rule-based processes and imitate manual operations, such as processing invoices and inputting data from Microsoft Excel spreadsheets to SAP or Oracle. System. However, when processing the content of the document, it is necessary to combine optical character recognition (OCR), natural language processing (NLP) and machine learning (ML) with other intelligent entry technologies to be able to extract metadata from the document. And automatically processed.
The content can be of different types, such as structured/printed, structured/handwritten, unstructured/printed, and unstructured/handwritten content. It is very easy to extract structured content using standard optical character recognition (OCR) technology. However, the extraction of unstructured content faces challenges, and there will be more and more unstructured content, so natural language processing (NLP) and machine learning technologies are needed to solve it. ”
Delaware Robotic Process Automation (RPA) expert Arpit Oberoi added: “The biggest challenge facing Robotic Process Automation (RPA) technology today is that it is still often difficult to handle unstructured content and data. To overcome this persistence The problem is that companies can try to transform their data into a clearer structure of data sets, and where possible, can also use artificial intelligence and robotic process automation (RPA) to optimize or automate content.
Third party participation
Andrew Rayner, vice president of professional services for UiPath Europe, Middle East and Africa, explained the necessity of using third-party applications in conjunction with Robotic Process Automation (RPA).
Rayner said. “Historically, robotic process automation (RPA) technology has been able to integrate with third-party applications to assist content processing. For example, many OCR vendors (such as Abbyy and IBM, etc.) provide directly integrated functions, which can be half Structured or structured documents are classified and identified.
UiPath has invested a lot of money in document understanding for development, providing customers with a “ready-to-use” solution that can flexibly apply various technologies (such as pattern matching, templating, and machine learning) to deal with unstructured And semi-structured documents.
As we consider content processing methods more widely, which has played a good role in automated processing, we now adopt this workflow to allow robots and workers to seamlessly process transactions.
There has been tremendous progress in connecting applications that process content through user interfaces or APIs, and with the introduction of robotic process automation (RPA) and machine learning, robots can now classify unstructured content and understand emotions And proceed to the next best operation. ”
Use tools carefully
Although the help of other tools and software is needed, companies must invest and adopt tools carefully, and ensure that the tools they use are used for a specific purpose.
Chris Porter, CEO of Nex Botix, said: “Enterprises may have unstructured data in many different formats, whether it is documents, emails, and unstructured system-based data. This gives the application of robotic process automation (RPA). Brings a problem, it can only deal with rule-based structured digital processes.
Companies can overcome these shortcomings in several different ways. One is to purchase tailor-made solutions like quasi-optical character recognition (OCR) tools, which can extract data from documents, or they can use workflow tools to help orchestrate the work of robots and workers, or You can buy Google’s machine learning tools to try to extract insights from their data. These tools are designed to solve very difficult problems within strict parameters.
However, every tool faces technical challenges. In carrying out these projects, companies will face more expenditures. In addition, companies need the right skills and technology to support each plan. Each use case should be treated as a separate project, because it can effectively meet specific needs, and if the enterprise has many different types of data, then many different processes have this unstructured content. You need to start again every time and adopt the right solution to solve each individual problem.
The key is to apply the right technology to solve the right problem, but in a scalable way that focuses on business value. For example, an invoice processing program can use reusable components within the enterprise and automatically execute end-to-end business processes in accounts payable.
Increase cognitive function
The last way to overcome the content processing deficiencies of Robotic Process Automation (RPA) is to provide additional functions.
Neil Murphy, Global Vice President of ABBYY explained: “The biggest challenge for Robotic Process Automation (RPA) is the inability to handle unstructured content, such as invoices, emails, forms, receipts or communications. However, companies can overcome this problem. .
What companies need to do is to make robotic process automation (RPA) robots smarter by adding cognitive functions (such as analyzing, understanding, and processing unstructured content). Organizations can deploy this content using easy-to-use no-code or low-code solutions, allowing employees to build robotic process automation (RPA) robots that can handle large volumes of documents.
We have seen many companies adopt this approach, which promotes innovation, and some companies use this approach to combine relevant skills to provide advanced cognitive understanding of complex use cases. The application of the human resources department is a good example. From identification documents and employee entry forms to bank statements and address proofs, a large number of documents need to be processed. “