As philosophical as it may seem, ‘knowledge is power’ is an adage that practically governs today’s business environment. Organizations, irrespective of the industry they belong to, are looking to deploy the newest and the most innovative systems to derive nuggets of ‘knowledge’ from the enormous volumes of structured and unstructured data residing in the enterprise systems. ‘Content’, as we call it, is rapidly growing in volume and diversity across globally-spread businesses. In fact, even the way it is delivered and consumed is undergoing visible changes. While in the past, ‘content’ was static information rendered through a designated set of devices, with limited objectives, and left for human interpretation, today it can be rendered through a multitude of smart devices, and is easily adaptable to changing needs.
Can traditional content management systems, better known as enterprise content management systems, serve the purpose of the game in the wake of these changing realities?
Let us explore what needs to be done for content to become a monetizable asset for organizations, basically, content that is smart.
So, what is smart content? To understand this, let us see this schematic representation of the evolution of content from unstructured static to structured smart content
From the consumption perspective, smart content should be discoverable, interpretable by machines, and structured for contextual publishing.
Let us now see what kind of changes we can bring in to produce smart content.
If we look back a few years, enterprises were satisfied with the enterprise content management system, which provides regular content-centric workflows, metadata management and discover, as part of their digitization transformation program. Is it sufficient today? The answer is no.
Today’s customers need abundant information sources given the high degree of volatility and dynamism in business.
The content management and processing systems should be relooked at from the following perspectives:
• Incorporating steps to extract knowledge leveraging artificial intelligence and building a knowledge graph of related topics or concepts
• Leveraging Big Data concepts to analyze, manage, and store information
• Managing information according to its context and behavior – rather that as static content
Semantic technologies that involve natural language processing and generation and machine learning techniques are being used by enterprises to embed intelligence within content. The content management system should have these components, which will pave the way for the semantic content management system.
If we consider the e-learning industry, there is a high need for effective guided learning that helps learners achieve their goals. Many of the existing learning management systems (LMS) are based on providing a pre-defined learning plan rather than guided and adaptable learning. One of the essential elements for an LMS to provide immersive and adaptable learning is to have content tagged with metadata, classified by topics, and structured and linked with other related topics as a knowledge graph. With this as a use case the process of extraction of metadata, classification, and relatedness should be automated. And the process of building smart content is possible with the adoption of semantic-enabled content management system.
The concept of semantic-enabled content management system is futuristic, and will mature with time as enterprises develop expertise in techniques such as text engineering and mining. Enterprises are still in the process of evaluating the right approach for the adoption of the semantic-enabled content management system, so that it can optimally and efficiently manage global business in the connected world. What’s your take on this subject?