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New Directions for Knowledge Management Software

  • October 01 1999, 1:00am EDT

Technological advancements in knowledge management software over the past few years tend to fall into two strong, complementary trends:

  • From manual to automatic information categorization, and
  • From document- centricity to people-centricity.

These two trends provide a context for understanding directions in knowledge management software, whether judging the recent past or extrapolating into the near future. Figure 1 charts these trends and places in their context some of the common functionality of knowledge management software. Note that time flows through the chart from lower-left to upper-right corners.

Shifting from Manual to Automatic

Knowledge management software (like most categories of software) has been achieving ever higher levels of automation. With the number of information sources and the volume of information both increasing rapidly, knowledge management software can help users survive "information glut" by automatically categorizing and routing documents, as well as automatically building relationships between information objects.

For example, a text mining tool parses one or more documents, semantically understands content and builds a catalog of topics covered by the document(s). The automatically generated topic catalog (sometimes called a taxonomy) provides a content- oriented interpretation of documents that ­ in an organization with a very large body of documents ­ could require thousands of person-hours to build manually.

Figure 1: Trends for Knowledge Management Software Capabilities

Similar technologies for automatic cataloging are now being adapted for use with other types of knowledge management software. In document management systems, automatic cataloging promises to enhance document routing and other workflow capabilities. In collaborative knowledge management systems, automatic user profiling catalogs people according to their interests and ranks them by level of expertise. After all, many knowledge workers are more interested in identifying experts than in searching and reading documents online.

Some software vendors have already merged all cataloging into a central repository that can hold knowledge objects as diverse as documents, topics and knowledge worker profiles. The next step is to fully automate and integrate the processes of cataloging documents, deducing topics and capturing user interests and expertise.

The People Versus Documents

A traditional assumption behind knowledge management software is that documents contain much of an organization's explicit knowledge. In fact, most knowledge management systems are actually document management systems at heart. Even so, this assumption has been challenged by the growing realization that an organization can develop knowledge by providing a collaborative environment where knowledge workers share tacit knowledge. Document-centric functions will always be central to knowledge management, but they have acceded their exclusive hegemony to make room for people-centric collaborative functions.

Collaboration can, of course, be document-centric. Knowledge workers share explicit information and solutions by publishing documents and adding value to them in the form of comments, new content or new versions of a document.

Even so, collaboration in knowledge management is progressively becoming more people-centric. People-centric collaboration software typically involves integrated e-mail (or sometimes a dedicated client application) through which knowledge workers communicate information and requests for information.

Automation is always an issue, even with collaboration. Capturing and cataloging collaborative messages between knowledge workers can be a manual task, or it may be automated to some degree with collaborative filtering software. In many organizations, online collaborations have the goal of producing explicit solutions or decisions; to document the decision-making process, the evolution of a solution may be recorded automatically as a collaborative thread. If an organization has reengineered its processes appropriately, all transmissions of or requests for information travel through the collaborative software environment, which is an ideal opportunity for automatically generating and dynamically updating knowledge worker profiles.

On the cutting edge of collaborative environments, software for virtual work spaces provides project management, electronic engineering, online courses and other capabilities for virtual teams that are dispersed across geographic or organizational boundaries. In the near future, knowledge management software will support so-called "innovation spaces" that bring to bear real-time collaboration (synchronous or asynchronous), automated cataloging and virtual teaming to help creative knowledge workers brainstorm while the software records and adds value to their ideas.

Riding the Knowledge Management Life Cycle

The many capabilities of knowledge management software are in a variety of stages in their respective life cycles. The dotted lines in Figure 1 divide knowledge management capabilities into three life cycle stages: maturing, evolving and emerging.

Maturing. The capabilities of knowledge management software that are currently entering maturity mostly involve document-centric functions provided by document databases and document management systems. Although the core of these systems is mature, they will continue to improve as evolving and emerging technologies are retrofitted to them.

Evolving. Collaborative functions in knowledge management software are already established, but they are still evolving. For example, there is still plenty of room for improvement with knowledge worker profiles and the functions that depend on them, such as mechanisms for push/pull and publish/subscribe.

Emerging. The most recent innovations in knowledge management software are exploring the extremes of the trends toward automation and people-centricity. Automatic cataloging and online collaboration come together at the cutting edge with automatically generated and maintained catalogs of experts.

Show Me the Taxonomy

Automated catalogs are a great leap forward for knowledge management software, but the next step is to represent the catalogs with advanced visualization techniques. One goal of knowledge management visualization is to summarize information. For example, with a glance at a visualization, a knowledge worker can see the prominent clusters of topics of an organization's knowledge base or the clusters of expertise among fellow knowledge workers. Many visualizations also show how clusters relate. As the amount of input information increases, the importance of visualization as a summarization technique increases, since it is very difficult to browse a catalog of thousands of documents or to contact hundreds of knowledge workers looking for an expert with the right solution.

But visualizations are not just for viewing. The user interacts with the visualization, such that it becomes a navigational tool. By clicking on a visual clue that represents a cluster of information, a knowledge worker should be able to move from a summary view to a more detailed view of a topic. The knowledge worker should be able to drill through into source documents or document summaries.

Advanced data visualization is already an important component in data mining tools, OLAP tools, performance management applications and other types of business intelligence software. In knowledge management software segments, visualization is emerging with the new generation of text mining tools that provide creative visualizations of topic taxonomies. Similar visualization techniques should soon be applied to other types of automated catalogs, such as document and expert catalogs.

Driving Knowledge Management Down the Road

The two trends identified in this article ­ ever-increasing automation of catalogs and a shift of focus from documents to people ­ will continue to drive innovation in knowledge management software for several years to come. However, these are not the only influences on future directions for knowledge management software.

Many customer-facing business tasks (such as sales, service and support) tend to be collaborative in nature. Therefore, applications that automate these tasks benefit from having knowledge management techniques embedded in them. For instance, help desk applications have a long history of embedded knowledge management capabilities (such as document-oriented knowledge bases and collaborative environments for sharing solutions), whereas some applications for sales force automation and telemarketing are now incorporating these capabilities.

Many corporations are currently debating how best to implement electronic business, which requires an IT infrastructure that integrates information across stovepiped systems. A corporate portal is one way to accomplish this infrastructure. As corporations work on the specifications for their corporate portals, many realize that document management and word-index search are base requirements, whereas advanced requirements include text mining and automatic catalog creation. Many organizations will become electronic businesses and many will deploy corporate portals over the next few years, which will drive sales of many types of knowledge management software.

In May 1999, Microsoft Corporation announced its intentions to update Exchange Server and Site Server to make them serious contenders for the general knowledge management market currently dominated by Lotus/IBM. Although it will be a long while before Microsoft releases its updated product offerings, Microsoft will actively promote the cause of knowledge management in the meantime. It is unlikely Microsoft will catch up with Lotus' rich, mature and ever-expanding product set, but Microsoft may be successful in offering a low-cost, low-maintenance alternative that appeals to low- and middle-market users.

XML is rapidly becoming the lingua franca of knowledge management. It is an important technology driver whose obvious benefits will force software vendors and IT departments to retrofit existing systems to support it, as well as to develop new products that capitalize on it. As knowledge management software products become "XML-ized," there will be ample opportunity for software vendors to reposition themselves and exploit XML support as a competitive advantage.

For instance, applying XML tags to text documents is a tedious and time- consuming task when done manually. As text mining technology evolves, one of its emerging capabilities will be to automatically add XML tags describing content as it parses a document. No doubt, authoring tools and document management systems will soon add similar XML tagging capabilities. When documents and collaborative messages are stored with XML descriptions, most knowledge management software functions improve enormously in efficiency and accuracy.

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