Knowledge Management Technologies

The early Knowledge Management technologies were online corporate yellow pages (expertise locators) and document management systems. Combined with the early development of collaborative technologies (in particular Lotus Notes), KM technologies expanded in the mid 1990s. Subsequently it followed developments in technology in use in Information Management. In particular the use of semantic technologies for search and retrieval and the development of knowledge management specific tools such as those for communities of practice.

More recently social computing tools (such as blogs and wikis) have developed to provide a more unstructured, self-governing approach to the transfer, capture and creation of knowledge through the development of new forms of community, network or matrix.

However, such tools for the most part are still based on text and code, and thus represent explicit knowledge transfer. These tools face challenges in distilling meaningful re-usable knowledge and intelligible information and ensuring that their content is transmissible through diverse channels, platforms and forums. Let us briefly understand the some of the technologies that are currently associated with the field of knowledge management:

Some Key Technologies are as follows:

The impact of each technology varies enormously from situation to situation. Several technologies recur in many knowledge management programs, partly because they are generic and pervade many core activities and processes. Let us briefly review some of the main technologies used in KM programs.

(a) Intranet, Internet

The ubiquitous Internet protocols make it easy for users to access “any information, any where, at any time”. Further, browsers and client software can act as front-ends to

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information in many formats and many of the other knowledge tools such as document management or decision support. Remember too, that the basic functions of email, discussion lists and private newsgroups often have the biggest short term impact.

(b) Groupware - Lotus Notes

What groupware products like Lotus Notes add over and above Intranets are discussion databases. Users such as Thomas Miller, a London based manager of insurance mutuals, access their ‘organizational memory’, as well as current news feeds in areas of interest, through one of Lotus’s key features, its multiple ‘views’. When writing new insurance proposals, existing explicit knowledge can be assembled from the archive, guided by expert systems front-end, while tacit knowledge is added through discussion databases.

(c) Intelligent Agents

The problem of information overload is becoming acute for many professionals.

Intelligent agents can be trained to roam networks to select and alert users of new relevant information. Additionally they can be used to filter out less relevant information from information feeds. However, in practice it seems that a well run knowledge center, such as those at Price Waterhouse, the best intelligent agent is still a human being!

A related technology is that of text summarizing, which British Telecom have found can summarize large documents, retaining over 90 per cent of the relevant meaning with less than a quarter of the original text.

(d) Mapping Tools

There are an increasing number of tools, such as COPE and IDONS, that help individuals and teams develop cognitive maps or ‘shared mental models’. These have been used by companies such as Shell to develop future scenarios and resolve conflicting stakeholder requirements. In addition, other mapping tools, such as those found in Knowledge X, can represent conceptual linkages between different source documents.

(e) Document Management

Documents, and especially structured documents, are the form in which much explicit knowledge is shared. With annotation and redlining facilities, they can become active

KM Viewpoint 1.5

Booz Allen & Hamilton’s Knowledge Online is an Intranet that provides a wealth of information (e.g. best practice, industry trends, database of experts) to their consultants world-wide. Through active information management by knowledge editors (subject experts and librarians) the information remains well structured and relevant.

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knowledge repositories, where the latest version and thinking is readily shared amongst project eams.

(f) Expert systems

Knowledge-based expert systems, or simply expert systems, use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Books and manuals have a tremendous amount of knowledge but a human has to read and interpret the knowledge for it to be used. Conventional computer programs perform tasks using conventional decision-making logic — containing little knowledge other than the basic algorithm for solving that specific problem and the necessary boundary conditions. This program knowledge is often embedded as part of the programming code, so that as the knowledge changes, the program has to be changed and then rebuilt. Knowledge-based systems collect the small fragments of human know-how into a knowledge-base which is used to reason through a problem, using the knowledge that is appropriate. A different problem, within the domain of the knowledge-base, can be solved using the same program without reprogramming. The ability of these systems to explain the reasoning process through back-traces and to handle levels of confidence and uncertainty provides an additional feature that conventional programming doesn’t handle.

KM Viewpoint 1.6

By using a document management system for the construction of the Thelma North Sea oil platform, AGIP reduced construction time by 9 months and reduced document handling costs by 60 per cent. Suppliers like Dataware are repositioning their products as knowledge management products and are also adding ‘knowledge enriching’ functionality.

KM Viewpoint 1.7

Most expert systems are developed via specialized software tools called shells. These shells come equipped with an inference mechanism (backward chaining, forward chaining, or both), and require knowledge to be entered according to a specified format. They typically come with a number of other features, such as tools for writing hypertext, for constructing friendly user interfaces, for manipulating lists, strings, and objects, and for interfacing with external programs and databases.

These shells qualify as languages, although certainly with a narrower range of application than most programming languages.

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(g) Knowledge base

A knowledge base is a centralized repository for information: a public library, and a database of related information about a particular subject. In relation to information technology a knowledge base is a machine-readable resource for the dissemination of information, generally online or with the capacity to be put online. An integral component of knowledge management systems, a knowledge base is used to optimize information collection, organization, and retrieval for an organization, or for the general public.

A well-organized knowledge base can save enterprise money by decreasing the amount of employee time spent trying to find information about - among myriad possibilities - tax laws or company policies and procedures. As a customer relationship management (CRM) tool, a knowledge base can give customers easy access to information that would otherwise require contact with an organization’s staff; as a rule, this capacity should make the interaction simpler for both the customer and the organization. A number of software applications are available that allow users to create their own knowledge bases, either separately (these are usually called knowledge management software) or as part of another application, such as a CRM package.

In general, a knowledge base is not a static collection of information, but a dynamic resource that may itself have the capacity to learn, as part of an artificial intelligence (AI) expert system, for example. According to the World Wide Web Consortium (W3C), in the future the Internet may become a vast and complex global knowledge base known as the Semantic Web.

(h) Artificial intelligence technology. AI is providing key components in a variety of KM applications. Closely related domains include informatics, applied informatics, knowledgebase management systems, and qualitative analysis.

(i) Case-based reasoning systems. CBR systems solve new problems by adapting previously successful solutions to similar problems. Meeting customer-support requirements is just one of the applications.

(j) Competitive intelligence applications. Collecting, analyzing, and communicating the best available information about technological trends and developments outside a company’s walls is the purpose of competitive technical intelligence. It is sometimes referred to as competitive analysis or competitive intelligence.

(k) Corporate portals and knowledge portals. It is concerned with gathering the information resources of an organization into a centralized resource. Full-text retrieval and various kinds of taxonomies are applied to provide access to the information. Related terms: corporate portals, knowledge portals, business intelligence, digital dashboards.

(l) Data mining. Many large companies — for example, pharmaceutical and chemical corporations — have major intellectual assets buried in their paper and electronic files.

Extracting them isn’t easy. Related terms: knowledge discovery and automatic discovery.

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(m) Groupware and artifact-based collaboration. The term artifact-based collaboration is often used to describe products like Lotus Notes, because the collaborative activity centers on an artifact — for example, a document authored by many people. See also, Computer-supported collaborative work. Groupware also includes computer applications for organizing meetings and supporting interactions and group decision-making processes-without a substantial shared artifact.

(n) Decision-support systems. Decision-support systems incorporate insights from cognitive science, management science, computer science, operations research, and systems engineering both in order to produce computerized artifacts for helping knowledge workers in their performance of cognitive tasks, and to integrate such artifacts within the decision-making processes of modern organisations.”

(o) Content management and document management. Although document management systems have been with us for many years, many original DM products have been recast as content management systems, whose primary function is to manage the data that goes into corporate Internet and intranet (and extranet) sites.

(p) Customer relationship management. Customer Relationship Management (CRM) strategies have been around since the first bazaar, but products designed to automate CRM efforts are among today’s hottest new computer applications. Companies are rushing to automate and better manage all the ways they deal with customers, including people who might not consider themselves customers yet.

(q) Customer-support technology. Help desk systems and customer-support systems are designed to reduce the heavy labor costs imposed by demands for information from users of increasingly complex products and improve timeliness and quality of support.

“Customers” may be internal or external clients.

(r)support systems and distance-learning technology. Performance-support systems (PSS) and “eLearning” are designed to reduce the skyrocketing costs of classroom training in specific skills while addressing the problems caused by the rapid pace of change. By the time a classroom training program is designed, it is usually out of date.

(s) Hypertext technology. A more recent development or, perhaps more accurately, a return to interest in “hypertext” as a method of representing and providing access to critical organizational knowledge is reflected in the Topic Map standard (ISO/IEC 13250) and in Tim Berners-Lee’s Semantic Web effort. Both are XML-based and are seeking common ground.

(This is not the simple Web hypertext model, but the richer, often proprietary hypertext models that preceded the World Wide Web. The HyTime standard on which the Topic Map standard is based grew in part out of a need for creating a common ground among the hundreds of unique hypertext systems.)

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(t) Semantic networks. A semantic network is a method of representing knowledge often used for critical analysis of literary texts. Similar to hypertext technologies in some ways, but with emphasis on typed links among concepts.

In document DBA 1735 Knowledge Management (Page 46-51)