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Glossary for Knowledge-based Organization

For Both Executives and Information Technology Managers
A collaborative effort with Teresa Di Cairano of Intervista and Michael Kull of Lighthouse Consulting Group, this uniquely organized glossary helps to define significant concepts and terms in organizational knowledge. A handy guide to navigate the most current of management models.

We are also inviting contributions to this glossary. Do you have a contribution? Accepted contributors receive a complimentary wall poster illustrating the Zachman Framework for Enterprise Architecture. To make a contribution to the Glossary, please use the Online Form below.

This glossary of terms has been conceptually structured in four broad categories. These include:

1. General Knowledge Concepts
2. Explicit Enterprise Knowledge
(including some information technology related terms)
3. Tacit & Implicit Knowledge
4. Knowledge Practices & Knowledge Creation



enterprise architecture1. General Knowledge Concepts
Knowledge: Justified belief. Knowledge is the generalized interpretation of the complex network of ideas and understandings that apply in a given environment and which fit the general experience of a community of practitioners.

Knowledge in business environments includes those experience, facts, rules, assertions, and concepts about process and subject areas that are crucial to the business. It is the key resource in tasks such as decision making, assessment, forecasting, design, planning, diagnosis, synthesis and analysis. It can be explicit and represented in various media (such as in information systems), implicit in the social context and not necessarily formally articulated or codified, or tacit and resident in people. s minds as insight, intuition, and expertise.

Individual Knowledge: The accumulation of personal history, skills, education and experience that informs the judgment of the individual in a given situation.

Collective Knowledge: The aggregation of the personal knowledge of the members of the collective, as well as the shared knowledge as manifested in the artifacts and tools, normative behavior and value system of the culture.

Knowledge Ecology: A way of looking at organizations that emphasizes the interplay by the actors in a system of knowledge by focusing on the flow and transformation of knowledge processes. It is a network that constitutes a kind of ecosystem of ideas.

Knowledge Management: An emerging management discipline that embraces knowledge as the core organizational asset that drives sustainable business advantage. It embodies organizational processes that seek the synergistic combination of data and information processing of technology with the creative and innovative capacity of people.

Knowledge Organization: "A social community specializing in the speed and efficiency in the creation and transfer of knowledge." (Kogut & Zander 1996)

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enterprise architecture2. Explicit Enterprise Knowledge
Relates to the codified, recorded, externally visible knowledge of an organization. usually includes classified, quantified and documented enterprise events, descriptions and business processes. It is often but not necessarily housed in an enterprise. s information system and stored in a computerized medium or document. It also includes the processes relating to the management of information systems.

Examples of coded enterprise events include, but are not limited to, sales ordering, accounts payable, payroll, customer support, performance reviews, blueprints, schematics, transcripts, and so forth. Sometimes also referred to as data objects, artifacts or formal business rules.

Analytical Processing Systems: Represents those information systems that are optimized for the process of analysis and decision support such as trend analysis, demographic analysis, etc. Sometimes referred to as OLAP (On-line Analytical Processing) which indicates real-time processing.

Data: Observed and recorded experience and events including the measurement of events.

Database: A collection of interrelated data stored according to a schema or data model.

Data Model: The conceptual data structures (i.e. the classification system), including operations and constraints provided by a database management system for effective database processing.

Datawarehouse: A collection of integrated subject-oriented databases designed to support the decision-support function.

Data mart: Contains data from the Data Warehouse tailored to support the specific analytical requirements of a given business unit.

Decision Support System (DSS): An information technology system optimized to support managerial decisions. Usually DSS involves the analysis of many units of data in a heuristic fashion.

Domain: A group of related systems, programs, processes, or activities which are linked through a common set of problems and solutions, disciplines, existing systems, and to one degree or another, shared purpose. A simpler, more colloquial term for domain (especially in enterprises) is "subject matter". A person proficient and knowlegable in a domain is called a "domain expert", and is oftern the source fo expertise for developing knowledge-based or expert systems.
(contributed by Atul Bhatt)

Domain Analysis: The process of building a conceptual framework for understanding the nature of systems in a domain.
(contributed by Atul Bhatt)

Information: The aggregation of data. Data in which salient features have been rendered into digestible form. Saliency and interpretation is determined by the context and values of the group or organizational culture, reflective of the knowledge that underlies it.

Information engineering: The discipline of creating a data-driven development environment. (I.e. as opposed to an operational process-driven development environment).

Information retrieval: The techniques of storing and recovering and often disseminating recorded data especially through the use of a computerized system. (Webster, 1950)

Measurement: The act of interpreting, qualifying and quantifying observations.

News (i.e. mass media): The process of interpreting, qualifying and reporting of current events. The popularization and simplification of events or knowledge.

Operations Automation/Processing: Represents those information systems that are optimized to run the day-to-day business operations. These systems have traditionally made up the legacy environment and provided a competitive advantage by automating the manual business process to gain economies of scale or speed to market. Systems that exemplify business operations include accounts payable, accounts receivable, billing, order processing, etc.

Project Management (as defined in the Project Management Institute Body of Knowledge): Project Management is the application of knowledge skills, tools, and techniques to project activities in order to meet or exceed stakeholder needs and expectations from a project.

Technology: The application and embodiment of knowledge. Any tool that amplifies human intelligence and purpose, including all tangible and intangible manifestations, e.g. manufacturing tools as well as software tools.

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enterprise architecture3. Tacit and Implicit Knowledge
Tacit knowledge reflects the "ways of doing" practiced by individuals and communities and cannot be fully articulated, if at all. Examples include knowing how to ride a bicycle, when to close a deal in a sales situation, what an expression means on a customer. s face, how to deal with a difficult colleague, when to end negotiations so that all participants feel they have contributed, how to make a medical diagnosis under uncertainty, how much is enough, and so on.

Implicit knowledge refers to the contextual surroundings of an organization or community that is imbued with and shapes the collective values, normative behavior, roles, customs, ceremonies and other rituals, expectations of events, expected contributions to the community, and even expected thoughts and conclusions. Examples of implicit knowledge include acceptable holidays, proper ways of dealing with authority, customs for conducting meetings, expectations of performance, expectations of team participation, and so on.

Belief: An idea with emotional or spiritual appeal that has not been tested and/or is not considered accepted knowledge.

Decision: An informed judgment. The point at which an individual feels he or she has accumulated enough evidence to take action. The result of the combination of conscious and unconscious cognitive and emotional processes that filter desired outcomes against existing and presumed evidence.

Emotional intelligence: The ability of an individual to be aware of his or her emotional nature and to behave in ways that are beneficially to his or her long-term success. The exercise of emotionally desired constraints, such as self-control and delayed gratification; motivation. (Goleman) "To be angry with the right person, to the right degree, at the right time, for the right purpose, and in the right way." (Aristotle)

Expertise: A compelling understanding exhibited by one who is presumed to hold or claims to hold deep knowledge in a given domain.

Faith: Belief that is untestable through accepted scientific methods.

Intangible Asset: Valued relationships and knowledge maintained by organizations that are not quantified or cannot be quantified acceptably in the current business environment. Examples include stakeholder relationships such as customer loyalty, supplier reliability, engineering know-how, employee competency, as well as intangibles such as trust, optimism, and experience.

Intellectual Capital: The intangible assets, and the capability to create more of said assets, of an enterprise that include the structural, customer, and human dimensions understood as the knowledge produced and embedded in systems, the relationships and affiliations of the enterprise and its people, and the skills and capabilities of employees.

Intelligence: The cognitive capacity of an entity to leverage knowledge and employ reason in meeting its perceived challenges.

Quality: Value as embedded in a product, service, or knowledge itself; the perceived manifestation of value.

Social Capital: The sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit.

Truth: Knowledge that is highly probabilistic in a given environment.

Value: An intangible good; an end or purpose of organizing.

Value Proposition: Articulates the fundamental business reasons and expected benefits that drive the organization.

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enterprise architecture4. Knowledge Practice and Knowledge Creation
Knowledge practice and knowledge creation deals with the cognitive and organizational processes, structures and environments that lead to enhanced understanding, innovation, and change.

Business modeling: The process of understanding an organization based on cognitive simplifications such as metaphor, simulation, process modeling, or explicit causal mapping. Business models allow organizational members to interpret (through explanation and/or prediction) organizational behavior.

Communities-of-Practice: A group of professionals informally bound to one another through exposure to a common class of problems, common pursuit of solutions, who use a common language and who embody a common store of applicable knowledge. Shared competency and language in a collaborative working group. An anthropological approach to understanding organizations that rests on the idea of community as the central organizing tenet (Brown, 1991).

Development: Obtaining expanded sets of capabilities. Bringing out inner potential. Development may be though of as crossing the threshold between standards or sets of capabilities and moving into a mode of behavior which is qualitatively different.

Experiment: A test based on socially agreed upon research methods.

Hypothesis: An idea that may be tested through accepted scientific methods.

Idea: A causal relationship proposed or supposed to exist.

Learning: The iterative process of knowledge creation and transformation that results in new knowledge, skills, attitudes, and other cognitive, physical, or emotional capabilities.

Learning Environment: The planned or accidental range of development, experiential, and knowledge-sharing opportunities that creates in individuals and organizations new sets of capabilities.

Learning Organization: (1) An organization that facilitates the learning of all its members and continuously transforms itself. (2) An organization that facilitates the learning of all its members and continuously transforms itself in response to changes in its business. A learning organization is one that recognizes knowledge as an organizational resource and focuses not only on individual learning but also on collective or systemic learning.

Organization: A community of purpose. An interdependent social group working together for a purpose. The self-understanding by the group of itself and its reasons for organizing. "An organization is a body of thought thought by thinking thinkers." (Weick).

Organizational Cognition: The meaning and processes for generating knowledge embedded in rich, complex, contextual social interaction.

Organizational Intelligence: "An organization. s capability to process, interpret, encode, manipulate, and access information in a purposeful, goal-directed manner, so it can increase its adaptive potential in the environment in which it operates." (Glynn 1996)

Reasoning: The processes through which ideas are generated and evaluated against existing knowledge.

Sensemaking: The process through which an environment is socially constructed.

Strategy: A course of action, prescribed or descriptive, that is enacted to attain desirable future states or avoid unpleasant ones using existing and anticipated resources. Alternatively, strategy can be defined as a plan, an emergent pattern of behavior over time, a position of an organization in an environment, a perspective of an organization. s fundamental way of doing things, or a ploy designed to outwit an opponent. (Mintzberg)

Test: An accepted process for evaluating ideas and knowledge.

Theory: A set of ideas or propositions that can be tested against observable data.

Wisdom: The ability to discern inner qualities and relationships; insight, good sense, judgement.

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Glossary Credits
This glossary was developed by Teresa Di Cairano of Intervista Inc. and Michael D. Kull of Lighthouse Inc., and reflects an emerging knowledge-based perspective of organizations that introduces new terms and translates existing terms to reflect this perspective. It is not a fully complete or comprehensive list and is in continuous development.
© Copyright by Michael Kull & Teresa Di Cairano, 1999.

Please e-mail any comments or contributions to teresa@intervista-institute.com, or sent us a contribution using the online form below.



 
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