In the current modern business world, organizations are dealing with a higher volume of digital data. It is estimated that 97 zettabytes were generated in the year 2022, and it is projected that the total amount of data generated worldwide to reach 175 zettabytes (1 zettabyte = 1 billion terabytes) by the year 2025 from individuals, businesses, organizations, and machines. Imagine that a fraction of the data is emails, PDF files, scanned documents, images, etc that are required for daily business operations, and that is still a tremendous amount of data to deal with. To deal with the data more efficiently, businesses are always looking for advanced technology that can support such requirements, like, for example, Robotic Process Automation (RPA) and Intelligent Document Processing (IDP).
What is Robotic Process Automation (RPA)?
Robotic Process Automation, or RPA in short, is a well-known technology that uses software robots or “bots” to automate routine, mundane rule-based tasks. The software robots are designed to mimic human interaction with digital systems and can be programmed to follow specific rules and instructions. RPA is commonly used in businesses to streamline and optimize processes that are time-consuming, manual, and prone to human errors. The technologies are designed in a way that is only highly effective when dealing with structured data. It lacks effectiveness when dealing with unstructured data and requires other technologies to complement the process; for example, Intelligent Data Processing technology when it comes to processing unstructured data like texts, PDF documents, emails, and others.
What is Intelligent Document Processing (IDP)?
Intelligent Document Processing, or IDP in short, is a technology solution that enhances the reading and data extraction capabilities. IDP uses combination of AI technologies like Optical Character Recognition (OCR), Machine Learning (ML) and Natural Language Processing (NLP) to read, classify, extract, validate, and processing of information from unstructured documents. Unstructured documents refer to files that do not have a predefined or standardized structure, such as invoices, contracts, emails, forms, repots, and various types of textual documents.
To put it into simpler term, IDP simply takes in unstructured data like a scanned document in PDF format, ingest and understand it, and then extract information from the document for further processing or utilization for data analysis, reporting, data entry, or feeding into other automated processes. Processing and extracting such documents traditionally require manual efforts and can be time-consuming and error-prone. IDP shares a similar goal to RPA in automating, streamlining, and optimizing efficiency, particularly in document processing. Automating document processing with IDP can help streamline business processes, improve data accuracy, reduce manual labor, and enable faster decision-making.
Differences between RPA and IDP
In the automation world, RPA is commonly known as “the hands”, which do all the work, and AI as “the brains”, which do all the thinking and processing. One of the biggest differences between RPA and IDP is that RPA does not have AI intelligence by itself as a technology. RPA cannot read, understand, or interpret data on its own, and it only performs actions as per the given instructions, like repeatable actions on computer screens or applications.
As for Intelligent Data Processing, it is the AI technology that brings automation to the next level. IDP not only automates document processing, but it also ingests and understands documents and then converts it into structured data, a data format that is acceptable by RPA and makes it possible for end-to-end automation for document-centric business processes. Ultimately, RPA needs intelligence to reach its full potential, and AI, too, needs automation to scale. Hence, it is ideal that combine both RPA and IDP as both technologies complement each other in boosting efficiency and productivity in document-centric business processes.
How does IDP work with RPA?
Both RPA and IDP serve in the form of automation, but each technology focuses on a different forte. It is not possible to achieve end-to-end automation with IDP or RPA to work individually. RPA can extract data from any data source like email attachments, file servers, and other sources, but it has no capability to process unstructured data. On the other hand, IDP has the capability to process unstructured data, but the technology itself is unable to automate the data extraction from the source and is unable to do further processing after data is converted from IDP.
Combining both RPA and IDP makes it possible for end-to-end automated document processing. RPA can be utilized in automating the process of getting input data from upstream, whether it requires access to email, login to FTP server, access to CRM or finance system, it can be automated with RPA, and it is also possible to program the bots to follow specific rules and instructions, like for example, only get the data if it fulfills the naming conventions or the file format. IDP comes into the picture once there are unstructured data available to process. IDP can be used to extract relevant data from unstructured documents such as invoices, purchase orders, or forms. IDP can do the document recognition and classification and then determine what data to be extracted from the document. If required, it can also do the data validation and verification with predefined rules. Once data are extracted, verified, and validated, it can then transform into a structured format that the bots support or can consume in downstream processes. The data transforming steps may involve formatting, standardization, or data mapping.
Once data are transformed, they can then be consumed by the downstream automated processes, whether it is to store into databases, calculation, data analysis, data entry into backend or enterprise solutions, reporting, and many other business processes. These are the steps that required interactions of keyboard and mouse with the workstations and applications, and these are definitely the strength of RPA bots.
There is no IDP solution that can guarantee 100% accuracy. That is why it should include exception handling in the automated document processes. In the case of IDP systems encountering documents with low confidence or requiring manual intervention, the system can flag these as exceptions, and RPA bots enroute these exceptions to human operators to review, validate, or further processing. The strength of IDP is that the machine learning (ML) algorithms allow learning and improving over time. As the system processes more documents and receives user feedback, it can enhance performance and accuracy, leading to continuous improvement in the data recognition and extraction capabilities.
There are plenty of benefits for Intelligent Document Processing to work with Robotic Process Automation, including:
Automation of unstructured data: With the digital transformation, growth of IoT and social media usage, the number of data growing each year, it is safe to assume that the volume of unstructured data is growing, and automation of unstructured data is becoming one of the important elements for business to grow.
Improved Data Accuracy: IDP ensures high accuracy by leveraging advanced technologies, such as OCR, NLP, and machine learning. By providing accurate data inputs to RPA bots, the combined solution reduces the risks associated with manual data entry and improves the overall accuracy of automated processes.
Increase Process Efficiency: By combining RPA and IDP, organizations can achieve higher levels of process efficiency and productivity. RPA bots can handle repetitive, rule-based tasks, while IDPs take care of document processing, data extraction, and verification. This eliminates manual efforts, reduces processing time, and speeds up overall process completion.
Flexibility and Scalability: The combination of RPA and IDP offers flexibility and scalability in handling document-centric processes. IDP can adapt to various document types, formats, and languages, while RPA bots can be scaled to accommodate growing document volumes and expanding business needs.
Auditability and Compliance: The automated nature of RPA and IDP allows for accurate and consistent data handling and reduces the chances of errors and non-compliance. The integration also enables the tracking and logging of document processing activities for audit and compliance purposes.
Streamline Document Processing: Automating Document Processing allows organizations to reduce the reliance on human resources in document processing, thus allowing them to streamline the processes and greatly eliminate errors from manual processing.
Cost and Resources Savings: The combination of RPA and IDP can help organizations achieve cost and resource savings. By automating document processing, organizations can reduce the need for manual labor and free up human resources for more strategic or high-value tasks.
Robotic Process Automation and Intelligent Document Processing are proven to be great pair of automation solution that brings plenty of benefits to organizations. Most organizations require certain amounts of document processing, whether it is transactional documents, legal documents, HR documents, or forms. With the combination of RPA and IDP, it can greatly support organizations in achieving a higher level of operational efficiency and productivity, and thus improving customer service and employee satisfaction.
Cybiant’s RPA Services
Cybiant is an expert in leading digital platforms that enable digital transformation through Service Automation and RPA. Our founders were involved in developing the Service Automation Framework, which today is the leading publication for service automation and RPA. Our firm offers RPA consulting and implementation services that assist companies in their every phase of their RPA implementation journey:
Cybiant is an organization that specializes in the development, delivery, and execution of organizational Best Practices – proven methodologies that improve quality and efficiency in modern organizations. Our expertise includes Digital Transformation, Big Data, Automation, Cybersecurity, IT service management and asset management. If you wish to learn more about our services or know how we can help you in your RPA journey, please contact us at firstname.lastname@example.org.