In the first part of this 2-part blog series, we explored how technologies to eliminate manual processes, once commonly known as ‘advanced data capture’ have evolved into more intelligent, flexible and cost effective solutions that are suitable for more than just high-volume, high-velocity document handling.
With all the industry hype around machine learning and artificial intelligence, wouldn’t it be nice if there was a clear, simple, broadly-applicable use case that makes sense?
There is. One of the biggest challenges when it comes to applying intelligent data capture to large volumes of documents is that those documents can be very different from one another. Unlike structured or semi-structured forms, details like a vendor name, invoice number or order number can’t be found by knowing were to look for it on the page. Advanced algorithms that rely on context within the document can help improve the accuracy of intelligent data capture systems. But sometimes, these systems need a little help from a clever human operator.
In the ideal world, we want that clever human to be a process owner who understands what they are looking at—rather than a coder, developer or technician who can just write more rules for the system to follow. And that’s where machine learning comes in.
Today’s intelligent data capture tools, unlike advanced capture software, relies on machine learning to allow the system to learn in real time, from human operators who are tasked by the system to manually address an identified error or exception. Rather than coding for every variable and exception (which is costly and inefficient), the system modifies its algorithms based on user input and continues to learn as it goes.
By applying intelligent to the challenge of quickly and accurately finding the right information in a huge number of documents, solution providers like Artsyl are working towards a much bigger goal. Beyond minimizing keystrokes and mouse clicks, the bigger goal is the make it easy to create intelligent, automated processes that are flexible and cost-effective enough to apply to even lower volume, higher-value processes within an organization.
In the past, it was only high-volume, document-dependent transactional processes that could cost justify the effort and expense of automation. With intelligent data capture solutions, however, intelligent process automation can be applied to any process, in any department, where documents/data slow down the flow of information.
Stay tuned for our next Blog on Intelligent Process Automation and discover how to connect the dots from your data and documents to the decisions and desired outcomes that matter most to your organization.