As the world of information continues to grow exponentially, companies today have gone beyond implementing systems to manage documents as part of an effort to go paperless, to adopting enterprise content management systems design to handle the wide range of unstructured digital content that supports a wide range of business processes.
While the shift from managing documents to managing content across the enterprise may seem like semantics, the shift from digitizing paper to getting a handle on a torrent of digital content reflects a growing challenge for most companies.
According to IDC, the explosion of digital content that companies struggle to manage is only going to get worse, without the right systems in place. In fact, IDC predicts that by 2025, the total measure of data globally will increase by a factor of ten—to 180 zettabytes, or 180 billion terabytes.
With massive amounts of data, both structured and unstructured, flowing into and our of organizations and a mind-numbing pace, the biggest question is how will companies and their employees handle all that data, much less be able to DO anything with it.
WHAT to do with it has become the domain of new, emerging technologies like artificial intelligence, where natural language processing may be able to analyze information at a scale that humans simply cannot. By parsing though massive amounts of information to find patterns and trends, AI may have a substantial role to play in how we navigate the future glut of content to sift through to essential information.
Today, however, the biggest hurdle companies face in taking advantage of advance tools and technologies to analyze their data is that most of the intelligence is trapped in these unstructured documents in a way that makes it difficult to get them into the right systems and to extract the information that intelligent process automation systems and applications can leverage.
All too often, companies evaluating enterprise content management systems begin by evaluating what those tools can do for them once the data and documents are in the system. Sales demos for the latest, greatest ECM systems will always focus on the easy of use, convenience and efficiency of working with information that has already been organized, profiled and made available enterprise wide.
They will rarely, however, delve into the details of what it takes to get to that point. That’s where intelligent data capture comes in—and why it is so critical to the success of enterprise content management systems designed to solve today’s most pressing business problems, as well as to future-proofing those systems so that they continue to add value and remain relevant as tools like AI offer affordable, cost effective and practical ways to manage huge amounts of information in the context of a specific process or business problem.
Read any article today about trends in enterprise content management and it’s inevitable that artificial intelligence and machine learning will enter into the equation. Often, predictions related to AI focus on the miraculous things companies can do with the massive amounts of data and documents they are managing within their ERP and/or ECM systems.
AI simulates the human processing of information to identify patterns and trends. But to do so requires massive amounts of information to learn and function meaningfully. That’s all great—assuming your ECM already has the capacity to efficiently and accurately enter documents into the system, profile them with relevant metadata and extract meaningful, structure data from the ‘noise’ inherent to any information source, from email correspondence to vendor invoices.
Read Part 2 of our Blog Series on ECM and intelligent data capture to learn more about how to bvoost ROI from your ECM investment and unlock its true potential.
Ready to take action? Contact your Artsyl account representative.