In our everyday lives, the information we usually want – news, entertainment listings, restaurant menus, directions, contact details, product facts – seems to be literally at our fingertips thanks to laptops, tablets, smartphones, and other mobile devices. Unfortunately, this instant information access seldom extends to the business environment, which means that organizations often struggle to extract value from the enterprise content they generate.
The question is: Why? In the Big Data age, the obvious culprit seems to be the sheer volume of information that every organization produces – according to Science Daily, at least 90 percent of all of the world’s data has been generated since 2010.
But these huge volumes are not the real challenge for organizations, a new study from MindMetre Research reveals. The survey of nearly 400 senior information professionals at large enterprises across Europe and the U.S. shows that the real hurdle for big corporations, government organizations and other institutions when it comes to tapping into their information assets is the fact that too much enterprise content is unstructured, fragmented and uncategorized – making it unmanageable and inaccessible.
The MindMetre results show that 85 percent of organizations are creating more unstructured data than ever. Undoubtedly, for organizations of all sizes it is becoming critical to harness the unstructured element of Big Data to attain a competitive advantage. Big Content has become the umbrella term to describe this content, which includes emails, plans, presentations, technical descriptions, images, research findings, field notes, management comments, market intelligence, social media messages, and much more. Systematizing this content and transforming it into actionable business knowledge is what is now termed Content Intelligence.
The MindMetre research also confirms that organizations are beginning to understand the power and potential of unstructured data: 89 percent believe that gaining insight into this information – their Big Content – would give their organizations a competitive edge.
Most respondents to the MindMetre survey also make clear that it is not the sheer volume of this information that is problematic when exploiting Big Content. Instead, 71 percent say a major barrier to unlocking the commercial value of enterprise information is the fact that it is dispersed, held in disparate formats, at different sites and by different business units. The next most cited obstacle – identified as a major issue by 56 percent of respondents – is that enterprise information is not effectively categorized and tagged, or this is done in an inconsistent or unworkable way. Only 34 percent see sheer volume as a problem in its own right.
Finding the answers with Content Intelligence
To truly tap into Big Data, organizations need to get to the Big Content component – and to do that they need Content Intelligence, which is all about making the mass of unstructured information within an organization findable and actionable.
As the MindMetre research demonstrates so clearly, however, Content intelligence is not so easy to attain. In too many cases information that could be used to great advantage by a company, government organization or institution is held in a number of databases in different locations or by different business units – or by partner organizations – and there is no practical or consistent system for categorizing each document in a meaningful way.
The result is that finding and making use of enterprise information in a quick, straightforward and precise way is simply unfeasible – and so, in turn, is checking whether work has been done before, or whether it could be easily repurposed, built on, added to or updated.
Fully employing institutional knowledge and experience is essential for organizations aiming to get more value out of their people and assets. Content Intelligence increases work efficiency simply by allowing people to tap into content that informs proposals, new projects, business relationships, collaborations, fresh research, market intelligence, customer analysis, management reporting and regulatory compliance.
Content Intelligence enables organizations to avoid repetition of work, streamline the flow of information, save employees time and ultimately reduce costs. It also enhances strategic planning, risk management, customer insight, and understanding of the marketplace.
Infusing information management with Content Intelligence
The underlying challenge most organizations face when it comes to Content Intelligence is that their existing enterprise information management applications – such as Microsoft SharePoint, Apache Lucene and Solr, Google Search Appliance, Oracle (News - Alert) – don’t have the capabilities needed to organize, find and retrieve unstructured information in a practical timeframe. This capacity has to be imbedded into these systems.
Users of information management systems need have the ability to search contextually – in other words search results need to address the searcher’s intended meaning – so the system has to be able to steer the user more precisely to the strand of meaning they are looking for. For instance, a standard search by a medical organization might show that ‘aids’ can refer to either auto immune deficiency syndrome, or hearing devices, or mobility assistance, or PDA devices – all in the healthcare context. Contextual search allows users to quickly hone in on the area of the search relevant to their enquiry – while including other relevant content.
The information management systems in many organizations are not designed to achieve the level of Content Intelligence required today, having only basic classification and taxonomy management functions while lacking the capability to automatically apply metadata across disparate information sources. Meanwhile, applying the required level of metadata manually is neither affordable nor realistically achievable, given the necessary manpower costs, while the documents being tagged would have to be left in their original locations to avoid the cost of reformatting and transferring large volumes of disparate information into a single database – if this is even possible.
To really achieve a level of Content Intelligence that overcomes the challenges posed by scattered, non-searchable content, organizations need to employ tools that radically improve their ability to find and organize information. These bolt-on applications augment content platforms by imbuing them with more extensive taxonomy management functions and semantic search capability.
Once an information platform has been augmented to enable a greater degree of content intelligence, it should capture the relationships between documents and drive the consistent application of rich metadata through automated meta-tagging – which can be done rapidly and accurately on a massive scale, thus making whole archives searchable, while leaving them in their original locations so that disruption and additional costs are minimized.
The value of unlocking Big Content
The challenges posed by the proliferation of information in the Big Data age certainly can be intimidating, and it often seems the sheer volume prevents organizations from making good on the promise of Big Content. By looking beyond this great wall of information, however, organizations can identify and address the real challenges.
To do this they need Content Intelligence, which makes the vast volumes of unstructured information they generate and hold manageable and findable. This not only enhances search, but drives business workflow, improves workplace collaboration, and enables an organization to create significant information assets that in some cases can be monetized.
Few organizations in either the public or private sector are able to fully realize richness and value of the information they produce and hold – and deploy that knowledge to gain a competitive edge. Unlocking that information, and in turn its value, can help give them a leg up on other organizations and usher in an era of unrivalled efficiency.
About the Author--Jeremy Bentley is founder and chief executive of Smartlogic. An engineer by training, he has spent his entire career in enterprise software, specifically information management systems, including business process workflow, documents and records management, search and now content intelligence. Bentley founded Smartlogic in 2006 on the belief that organizations can outperform others if they fully utilize the huge business value contained in content. Since then, the company’s content intelligence platform, Semaphore – which adds advanced classification and semantic search capabilities to existing information systems – has been implemented at more than 300 organizations worldwide, including NASA, Bank of America and KPMG.