The Knowledge Management Connection   

Knowledge management (KM) is best understood as an umbrella term for a variety of loosely related practices, programs, and technologies associated with leveraging the “knowledge” of organizations for greater performance or competitive advantage.

That’s a pretty big umbrella. But KM means different things to different people, and each of these forms of knowledge management can lay claim to solving important problems of improving organizational performance. There are common elements … but most consultants and technology vendors are pursuing opportunities in specific niches rather than seeking a common denominator.

Common synonyms for knowledge management include managing [corporate] intellectual assets and managing intellectual/knowledge capital. Although some commentators insist that there is a clear distinction between knowledge management and these somewhat older terms, in practice the terms are often used interchangeably today.

Other terms used include managing corporate memory or corporate intelligence.

Subsections:

• Broad-based knowledge management initiatives

• KM programs that focus on specific requirements

• Technologies often associated with knowledge management

• Domains less frequently associated with “knowledge management”

• The perspective of The Knowledge Management Connection

Broad-based knowledge management initiatives

If you think about “managing knowledge” for more than, say, five seconds, you know that every organization needs to do it. After all, in the many different aspects of our business lives, we are  Peter Drucker’s “knowledge workers.”  Failure to manage the knowledge in an organization results in duplication of effort, lost time, and wasted opportunities at every turn. So what do you do?

Knowledge management is, or has been, associated with the following business concerns and associated consulting activities, many of which have broad organization goals:

• The “Learning Organization” and innovation management. Peter Senge’s popular business management theory stresses learning and innovation as key competitive advantages.
• Business process re-engineering. Recoiling from accusations of slash-and-burn business tactics, many BPR consultants have relabeled their offerings as knowledge management, focusing heavily on managing knowledge processes.
• Change management. You have to be smart and adaptive to react to changing market and economic conditions. And what could be smarter than planning, communicating, and implementing methods for dealing with technological and market changes?
• Risk management. Risk management shelters organizational assets — financial, intellectual, human, and physical — from undesirable exposure. Organizational knowledge is both an element and a beneficiary of the process.

KM programs that focus on specific requirements

Knowledge management programs may also focus on specific requirements, and those specific needs may vary substantially from one organization to the next. For example,

• Capturing best practices for use by others with similar requirements. (Related terms: lessons learned, benchmarking, communities of practice.)

  This is a common objective, for example,  in consulting organizations, where consultants may be distributed geographically but meet similar requirements in the field. The American Productivity and Quality Center (APQC), in particular, has a strong focus on sharing best practices and offers frequent conferences and seminars on sharing the experiences of one company with other member companies.

• Building and maintaining competitive intelligence (occasionally referred to as business intelligence; however, business intelligence more frequently includes “digital dashboards” and other forms of viewing multiple forms of organizational knowledge simultaneously under a single, integrated interface.).
• Supporting collaboration and shared development of document content — a requirement often addressed with such tools as Lotus Notes .
• Supporting specific new competences with distributed learning/training environments — often with “eLearning.”
• Supporting customers who have purchased complex products and services in order to reduce support costs and increase customer satisfaction.
• Leveraging existing intellectual assets — for example, mining the untapped reservoirs of knowledge buried in patents.
• Re-using document resources, an activity often supported by document-management or content-management technology.
• Converting specific areas of business-critical knowledge into tools that can be used by less-skilled personnel or into automated tools. This the traditional domain of  expert systems.

And that’s just the short list.

Technologies often associated with knowledge management

Although many gurus rant that “knowledge management is not about technology,” the technologists would certainly beg to differ. Technologies laying claim to important roles in managing organizational knowledge include, in no particular order:

• Expert systems.  “Knowledge engineers” have been around for quite a few years now … and they are often horrified at how KM has expropriated some of their well-established nomenclature.
• Artificial intelligence technology. The “failed promises of AI” is a meaningless cliché used as a strawman. AI is alive and well, providing key components in a variety of KM applications. Closely related domains include informatics, applied informatics, knowledgebase management systems, and qualitative analysis.
• 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.
• 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. Sometimes referred to as competitive analysis or competitive intelligence.
• Corporate portals and knowledge portals. 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.
• 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.
• 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.
• Decision-support systems.  Decision-support systems, according to Daniel Power, “… 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.”  See Power’s Decision Support Systems Resources.
• 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.
• Customer relationship management. Both a strategy and technology applied to that strategy: “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.” (Source: “Customer Relationship Management,” by Robin A. Robinson.)
• 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. (See, for example, The Consortium for Service Innovation.)
• Performance-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.
• 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.)

• 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. (See also, Taxonomies, thesauri, ontologies, and other systems of knowledge organization.)

Domains less frequently associated with “knowledge management”

The following domains seem to have less visibility in the business world as contributors to knowledge management. However, they are directly applicable at times, and solutions coming out these domains are often embedded in technologies and practices more closely associated with KM.

• The classification aspects of library and information science. The library/information science community has vast experience in classification and knowledge organization. Full-text search is insufficient by itself to provide predictable, efficient access to large bodies of electronic information, and tools for thesaurus construction and controlled vocabularies are already being applied in knowledge management efforts in business environments. Members of such organizations as the American Society for Information Science and Technology (ASIS&T) understand the vital connection, but implementers in business are still unconvinced that a liberal arts discipline can provide solutions for business problems.  (See Weaknesses of full-text search.)

  Nevertheless, classification is increasingly seen as an essential foundation on which communities (for example, the medical community with MeSH) and even some business practices (retrieval of re-usable software components) move forward.

  (And, just in case you had not noticed, the library-science oriented Information Today gobbled up KMWorld … not vice versa.)

• The young field of information modeling. Information modeling is concerned primarily with abstract and precise specification of the objects, processes, and rules in business requirements for software solutions — not the “how” of implementation, but the” what” of requirements, functionality, and connections with business objectives.  At its root, perhaps, is the question, “What are we talking about, really?” And how do you turn that precise knowledge more effectively into software solutions?

The perspective of The Knowledge Management Connection

However, nearly every organization has a core of knowledge that could provide immediate, daily benefits to most of its members … if it could be shared effectively. The more useful question may be, “What is the first thing you should do about managing knowledge”?

We describe our viewpoint in What is knowledge management? No one really asked.