Maxime Vermeir, Senior Director, Technology Marketing at ABBYY
For most companies, documents and the data they contain form the basic framework of their business model. It is therefore crucial to their success that even large volumes of documents are processed effectively and quickly.
While companies have jumped on the bandwagon to automate their processes as part of their digital transformation, the question of automated document processing is increasingly arising. The biggest challenge: automation platforms often only process digitized and structured data. However, unstructured content makes up a large proportion of corporate data. A current approach, therefore, leverages existing automation tools such as Robotic Process Automation (RPA) and equips them with AI-based cognitive skills to be able to process semi-structured and unstructured data. In this way, data from a wide variety of document types becomes easily accessible and can be further processed quickly.
Since the dawn of the digital age, companies have pursued the goal of true process automation, allowing machines to take over entire processes and relieving human workers to focus on more demanding, value-added activities. For a while, RPA seemed to be the answer, but it never took the advantage of its potential to become a standalone solution. There is no question that robotic process automation has paved the way for intelligent process automation, and it remains a viable, albeit limited, solution. Today, companies looking for true process automation are finding the answer in an approach that is both simpler and more complex. Complex in its multi-layered nature, but simple for people to implement and manage: Intelligent Process Automation (IPA).
Processing content from documents intelligently
In companies that already use automation solutions, RPA robots are often used for manual document processing. However, these robots alone are not yet able to recognize unstructured data and process it accordingly. The solution is to equip digital software robots with cognitive skills based on Artificial Intelligence, Machine Learning, and Natural Language Processing, thus providing them with content-related skills and knowledge. It solves the challenge of business-critical data being locked within enterprise documents and enables the digital workforce to learn how to turn content in any form into actionable information. This enables organizations to gain more value out of their content-centric processes to make business decisions faster and smarter. Intelligent Document Processing (IDP) enables straight-through processing of documents by automatically capturing, extracting, and processing data embedded in business documents, in just about any process in any industry.
Emerging no-code/low-code platforms go one step further, allowing automation without specific technical knowledge of the platform. It comes with a set of core AI skills that provide the foundation for processing documents of any kind—structured, semi-structured, or unstructured, and all types of data including machine printed, hand printed, barcodes, signatures, checkboxes, and 200+ different languages. Trained skills can be quickly designed to understand and extract information from all types of documents. In addition to these platforms, providers such as ABBYY already make pre-trained and ready-to-use AI skills available on an online marketplace such as invoices, purchase orders, receipts, tax forms, utility bills, or insurance claims to save development time and gain quicker ROI. These skills can be selected and merged via drag & drop. The advantage: even non-technical employees without extensive programming expertise can easily use these platforms. Easy no-code skill designer allows citizen developers to design, train, and publish document skills for all types of structured and unstructured documents. The result: putting your information to work so organizations can make better business decisions faster.
With IDP solutions, documents can be automatically split into a specific classification, depending on whether it is an invoice, an insurance document, a delivery bill, or another document type. It is also easy to automatically combine pages into a single document file or to categorize each document as a separate type, as well as to read tables. Incoming invoices, for example, can be processed in seconds, and content can be classified and further processed depending on the tax rate or local requirements. Since cognitive skills can also be adapted at any time, employees can react quickly and flexibly to changes in their processes or legal requirements.
Understand your processes correctly
Intelligent process automation is based on the recognition that business processes have two main dimensions: the process itself and the data (usually in documents) that underlie it. On the process side, it is critical to understand how processes work, not just how they should work. And any successful approach to process automation would be incomplete without considering the documents that carry information from one step to the next. That’s why IPA combines process intelligence with intelligent document processing (IDP), enabling organizations to gain more control over business operations and automate and optimize processes and decision-making in a much simpler way.
Process intelligence, a combination of process mining and task mining, uses advanced algorithms to capture and analyze timestamps in business applications to create visual models of processes. It enables businesses to automatically build an interactive digital twin of their processes, analyze them in real-time to identify bottlenecks, and predict future outcomes to facilitate decision-making of technology investments. These models make it easy to identify deviations from ideal process flows that could cost time or money, impact customer satisfaction, or cause regulatory compliance issues.
Companies need to understand their processes before they can successfully implement process automation, and process intelligence provides them with the real-world insights they need to do so. They can eliminate inefficiencies before committing resources to automation, avoiding the common mistake of automating processes that don’t work. They can also compare processes to determine which ones are likely to generate the greatest return on investment (ROI) from automation. Once automated, process intelligence enables continuous monitoring to identify deviations or inefficiencies as they occur. This allows companies to address small issues before they become large ones.
In today’s world where companies are more reliant on data than ever before, they should no longer rely on outdated methods of data and document processing. For the success of companies, it is essential to familiarize themselves with intelligent and automated document processing and integrate it into their business processes. The use of new AI technology not only helps companies relieve employees of time-consuming, monotonous tasks, allowing them to invest valuable time in customer service and enhancing the customer experience but also to make faster, higher-quality business decisions that further drive the company’s success.