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kBOS Applied Knowledge Engineering Methodologyknowledge management

kBOS Applied Knowledge Engineering Methodology

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Knowledge Management Overview

Defining Knowledge and Knowledge Management

There is no universal definition of Knowledge Management, just as there is no agreement as to what constitutes knowledge in the first place.


The distinction between the three terms – data, information and knowledge is relevant to establish a common understanding of terms and concepts used in knowledge management. First, data represents facts, parameters or statistics that can be analysed to produce information. Information is data related to a particular context which creates meaning. In other words data represent facts and becomes information when embedded in a context of relevance to a recipient.  In contrast to data that can be characterised as a property of things, knowledge is a property of agents (people or computer systems) predisposing them to act in particular way in circumstances defined by the context. 


In contrast to information, knowledge can not be directly observed; its existence can only be inferred from the actions of agents. Importantly, knowledge involves the mental processes of comprehension, understanding and learning and involves interaction of individuals with their environment.  Some experts include wisdom and insight in their definitions of knowledge.


Knowledge Management is about the protection development and exploitation of knowledge assets. KM encompasses theories, models, processes and tools that support the efficient and effective evaluation, acquisition, dissemination, development and exploitation of knowledge resources in business processes and business decision making.

Knowledge assets

The fundamental principle of the Knowledge Economy is to regard knowledge as assets and indeed possibly the most valuable assets the organisation posses. Knowledge Assets (also referred as Intellectual Assets) are the organisation's intangible assets that relate to knowledge including intellectual property.

Knowledge assets are the knowledge regarding markets, customers, products and technologies, that a business owns (or needs to develop as part of its strategic plan) and use to implement business processes efficiently and effectively.

Explicit and tacit knowledge

Knowledge-based assets are often categorised as explicit or tacit. Explicit knowledge consists of anything that can be documented, archived and codified (e.g. knowledge held by designs, manuals etc often referred to as corporate memory).


Much harder to manage is tacit knowledge, or the personal know-how which cannot be described and is primarily manifested through the results of actions. Tacit knowledge resides in relationships, usually complex social relationships, and is implicit in the organisational culture.

In traditional perceptions of the role of knowledge in business organizations, tacit knowledge is often viewed as the real key to getting things done and creating new value. Thus, we often encounter an emphasis on the "learning organization" and other approaches that stress learning by doing through experience and action and generation of new knowledge through managed interaction.

Knowledge networks

Organisations store in computers (in the form of processes, instructions and data bases) only a small fraction of the knowledge needed to run an enterprise. A figure of 10%-30% is the estimated range. The rest is the tacit knowledge in people's heads which is the key to an organisation's ability to innovate and respond in a flexible and timely manner to dynamic challenges. The role of knowledge networks is to facilitate tacit knowledge growth.


Knowledge networks provide the means for local or global knowledge diffusion. Diffusion occurs through interaction which is influenced by the network structure. Both empirical and theoretical studies have shown that network characteristics have a significant impact on how fast knowledge grows.


A key feature of a knowledge network is the ‘capacity for knowledge absorption’ by the members of the knowledge network. Knowledge diffusion works better if the knowledge level of sender and receiver of knowledge is similar.

The second important factor in knowledge diffusion is the knowledge base associated with a specific industrial sector.


Spatial clustering generates high knowledge growth rates in industries characterised by highly tacit knowledge and high potential for technological innovation. The opposite is true in industries where codified knowledge is important and in such cases special knowledge clustering could have a negative effect.


Knowledge networking IT systems provide the means of combining individuals’ knowledge in the pursuit of personal and organizational objectives. In the simplest form knowledge networking supports person-to-person communications resulting in the development of new knowledge. More advanced computer conferences (forums, bulletin boards, reviews) can create a level and quality of debate not normally achievable within the conventional work environment.


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