ECM Briefs

History has taught us that in an enterprise setting there are many diverse needs and expectations related to search for different types of content at different phases of the information lifecycle and for different user contexts.

The volume of data in organizations continues to increase at unprecedented rates. And while enterprise information systems control access to some of this large quantity of data, there is so much information that it results in overwhelmed end users. The information noise that attacks users on an hourly basis is causing new forms of inefficiency throughout the enterprise. Governments and corporations are investing heavily in creating and archiving information and that data is underutilized and yet that data must still be both discoverable and made available to users who need it. Unfortunately, most information quickly becomes buried in information silos.

The problem with enterprise search was recently exposed in an AIIM Market IQ on Findability, which asked users about their experiences finding information within their enterprise. The study found that fully 50 percent of respondents believe that "Findability" in their organization is "worse" to "much worse" than their own organization's consumer-facing Web sites. Of course, finding publicly available information is much easier on the Web because information is in browser-ready, standards based formats. In contrast, company data lives in a morass of database formats and file structures, and faces the complexity of user permissions and sign-ons.

Given this complexity, applying consumer-style search to enterprises is unlikely to provide a satisfying experience for users. Or for companies, for that matter: does a company really want its users to spend time combing through millions of results per query? A better approach is to build intelligent enterprise search into users' daily context. This involves making full use of the user's context and behaviors to deliver task-related intelligence that enhances the user experience, with the ultimate goal being what we call "find before search. Current examples of this in Open Text applications today include:

• Records being automatically categorized and filed according to their content when added to the system
• Aggregating related information into documents being viewed, such as automatically providing links to subsequent procurement documents when a contract is viewed within the repository.

These are capabilities that are here today and utilize search and information access technology "behind the scenes" to provide users with important information and context around the document or process that they're working with. We have customers who have seen big gains in productivity and customer service because workers have the information they need gathered and accessible just by opening an email from a customer, for example.

Future advances in search "intelligence" will also become embedded in a modular fashion into enterprise applications, such as business intelligence and litigation support. The concept will be expanded to include many other user-centric applications that can provide even more details about the user's task at hand.

When talking to vendors about these solutions, be sure they are taking a modular approach to providing all the technologies necessary to deliver full spectrum information access and discovery. This is achieved through the application of search as an integrated set of technologies that can adapt to the diverse and constantly changing landscape of content repositories and native indices from many different vendors. By continuing to align information access with enterprise content management capabilities, companies can move to the point where they have a joined-up content and access strategy across the enterprise. The key isn't just search, it's search with context.