Don't Overlook Document Processing When it Comes to Your Bottom Line
By Karan Yaramada, CEO, Kanverse
The invention of paper created a global revolution in communication. Imagine those first users of papyrus and how that must have felt. It made such an impact that, thousands of years later, it still inspires a strong sense of nostalgia that makes people reluctant to give it up – even if documents are often no longer actually on physical paper. And even many of the digital counterparts have warn out their welcome. It’s time to let go of the PDFs, Word and Excel documents and more that are bogging down businesses with inefficient, manual processes.
It’s taken a while, but most organizations now understand that they need a new approach that involves automation and machine learning to improve the document handling process. It’s admittedly not the flashiest topic, especially not when it comes to artificial intelligence, but the potential benefits to the overall business are anything but mundane.
Down with manual document processing
Some industries, especially healthcare, are still wrestling with reams of physical documents, which introduces multiple inefficiencies. Organizations that continue to use manual methods to process documents experience longer cycle times, increased costs and errors.
Many organizations are still using manual processing for even for digital documents. One of the main drawbacks of manual processing is that it introduces human error. Every time a person has to copy information from one spot to another, you have the potential for error. If you’re lucky, that error will just wind up being an administrative nuisance; at worst, it can result in serious consequences. In the aforementioned healthcare sector, for instance, an error can endanger a patient’s health.
There’s also the issue of reduced productivity. Many organizations have developed unstructured, in-the-moment processes to manage various kinds of documents. This often makes it harder to then connect the documents to other business processes and systems.
Collaboration and correlation of data also suffer due to manual processes. Providing the right information to the right users at the right time helps them to make better decisions. However, data is often distributed across multiple systems, and users are isolated. Conversely, users become very productive when they can collaborate in real time because this eliminates choke points in business process.
The role of artificial intelligence
By eliminating touchpoints that require manual intervention, the right application of automation can help an organization digitize the entire document processing workflow across business processes. However, not all automation is the same; this automation also needs to be intelligent.
Deloitte found in its Automation with Intelligence survey that organizations adopt intelligent automation with the expectation that it will increase productivity, reduce cost and provide greater accuracy. Organizations also need intelligent capture to understand and turn unstructured and semi-structured data into a structured format. And accordingly, the intelligent document processing (IDP) category is quickly arising as businesses look for new ways to extract data from the many documents driving their business – insurance claims, purchase orders, invoices and so on. Consequently, many organizations are investing more resources to deploy IDP capabilities. Everest Group estimates that the IDP market will grow 70-80% over the next two years to $1.1 billion.
IDP uses AI technologies such as Natural Language Processing (NLP), machine learning (ML) and fuzzy logic to process documents. IDP is able to intelligently classify, capture and extract all data from documents entering the workflow. Then, this information can be organized according to business need.
There’s more to IDP than blindly applying AI and automation to document processing.
And there’s more to it than just optical character recognition (OCR). IDP is about the true intelligence of the solution. As noted earlier, organizations can use these emerging technologies to capture, classify and extract the most difficult-to-automate data.
That’s an impressive list of achievements – a list that is difficult to realize. Buyers need to beware, because not all solutions are created equal. A near zero-touch system is possible with a high-quality solution, one in which a human doesn’t need to touch every transaction but does so only by exception.
An important point to make here is that the purpose of IDP is not to reduce staff; its purpose is to provide a tool to do their job better and more effectively without getting mired in inefficient processes.
Focus on the goal
Organizations that rely on a manual, human-based model for document processing can expect
increase in costs, longer cycle times and errors in addition to hindered productivity. How you handle documents shouldn’t hold your business back. New technologies are making it easier for businesses to overcome the challenges of manual document processing. Intelligent document processing happens when the right mix of automation and AI capabilities (including NLP, ML and fuzzy logic) are applied the right way. IDP solutions like this make document processing easier, more efficient and more accurate. They also lower costs and reduce risks by making business processes more resilient to disruptions. With intelligent document processing, you can offload manual tasks so that your employees can focus on the real work of achieving your business goals.
About the author: Karan Yaramada, CEO & Founder
Karan Yaramada founded Kanverse in 2020, and established Jade Global, as the Founder and CEO in 2003 with a vision and passion to deliver excellence to its customers. An alumnus of Harvard Business School, Karan exemplifies the company’s deep rooted culture of maximizing value from the latest technology to address some of the biggest business challenges. Kanverse is Karan’s visionary pursuit to interweave the world with the power of AI, driven by the need for safe and responsible use of this revolutionary technology.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.