Knowledge acquisition is the starting point of the organizational knowledge cycle (Wickramasinghe et al., 2003). Knowledge acquisition is the capture of the exist- ing knowledge through activities such as knowledge transfer, knowledge sharing, observation, interaction, and self-study. The knowledge acquisition activity is responsible for ensuring that the knowledge base required for intelligent problem solving is continually updated and recognizes the relevance of information in the knowledge base for the current problem-solving activity. As such, knowledge ac- quisition is akin to the act of learning. Knowledge creation/generation, which can be thought of as a sub-set of knowledge acquisition, is concerned with yielding new knowledge from previously existing knowledge. After individuals acquire existing Figure 5. The knowledge life cycle (Adapted from Wickramasinghe, 2005)
knowledge, this knowledge is then used as a foundation for creating new knowl- edge. Whether this new organizational knowledge is in the form of innovations, improvements in existing processes, new product designs, or market intelligence and strategic guidelines for the future, it is built on knowledge generated in the knowledge acquisition process.
As distinct from knowledge acquisition, the knowledge creation process focuses only on the formation of new knowledge. In their theory of organizational knowl- edge creation, Nonaka and Takeuchi (1995) presented a major perspective of the knowledge creation process where the knowledge spiral is created through specific knowledge transfers between organizational members. Nonaka and Takeuchi’s (1995) knowledge spiral centers around tacit and explicit types of knowledge. Tacit knowledge is a personal, context specific knowledge that is difficult to formalize and communicate. It includes cognitive patterning, such as mental models and technical knowledge, which is concrete and skill-related, and subjective insights. In contrast to tacit knowledge, explicit, or codified knowledge, suitable for technology and computer manipulation, is transmittable in formal, systematic language expressed in symbols, words, and/or numbers. Tacit knowledge is experientially based and is difficult to communicate. This suggests that tacit knowledge is implicitly learned through the personal interpretation and processing of information based on beliefs, experience, emotions, and all of the subsets of the aspects of human consciousness.
Tacit knowledge, as a principal component of knowledge creation, is imperative to the functioning of the knowledge creation process.
In the internalization process, explicit knowledge is converted to tacit knowledge through experiential learning. Experiential learning involves using the senses to interpret the environmental stimuli and create an individual sense of knowledge to respond to the presented reality (Popper & Lipshitz, 2000; Simon, 1999). Interest- ingly, since sensual learning is essentially neural in nature, technological attempts to simulate our sensual nature include the creation of robots that are embodied, situated agents.
Knowledge creation is central to the organizational knowledge activity cycle. With a reciprocal relationship to knowledge application, it is an essential activity in the innovation process of an organization. Based mainly on the conversion of tacit knowledge, knowledge creation, like knowledge acquisition, is a human based activity set in sociological- and psychological-based tasks. Therefore, information technology is not a vehicle upon which the knowledge creation process is based (Silver, 2000).
Knowledge Representation/Storage
In order for knowledge to be used efficiently and effectively in an organization, it must be represented and stored. In many ways, knowledge representation is
closely linked to knowledge creation. However, it is only possible to represent explicit knowledge in databases and knowledge bases. Thus, tacit knowledge that has been created must first be transformed into explicit knowledge before it can be represented. As well as storing the particular knowledge itself it is important to develop knowledge cartographies of where what type of knowledge is stored. We shall elaborate upon this point when we discuss the knowledge architecture and key technologies that facilitate this process in later chapters.
Knowledge Distribution/Use and Re-Use
Knowledge distribution is the third and central activity in the organizational knowl- edge cycle. In the literature relating to knowledge management and its organiza- tional components, much attention is devoted to knowledge acquisition, knowledge creation, and knowledge application. Although it is important for organizations to acquire existing knowledge and create new knowledge, in order for knowledge to be applied in the quest for competitive advantage, it must be made actionable: it must be distributed through the organization to the individuals responsible for tasks such as innovation, product/process design, or innovation.
The knowledge distribution component interacts with each of the other organizational knowledge activities to optimize and complete the knowledge activity structure within an organization. Similar to the two components that were previously discussed, knowledge distribution is largely a human-based process, although technology plays a major role in facilitating organizational knowledge distribution. Swan et al. (1999) emphasize that organizational knowledge distribution is both social and technical, composed through the interaction between aspects of organizational culture and organizational technology capabilities.
Social processes, such as organizational procedures, hierarchical structure, and social networks affect member interaction within an organization: they are capable of directly enabling or hindering the functions of the knowledge distribution process of an organization. Technological facilitation of knowledge distribution by means of e-mail, bulletin boards, intranets, newsgroups, teleconferencing, data conferencing, and videoconferencing plays the supporting role within the knowledge distribution component. Although designed to support interaction, without interaction itself these technologies are useless. Thus, if organizational members are not encouraged to interact either through individual motivation or deliberate design of organiza- tional culture, interaction will be limited and consequently mitigate organizational distribution of knowledge. Unquestionably, technology is central in the knowledge distribution process. Nonetheless, social processes within the organization are the catalyst for the dissemination of knowledge throughout its internal channels. The success of the organizational distribution of knowledge is directly related to the organizational culture that serves as the framework for interaction.
Knowledge Application
Knowledge application constitutes the last activity in the organizational activity cycle and is predominantly concerned with the utilization and management of knowledge that has been acquired and created by the organization. Most of the literature re- lating to knowledge management addresses concerns related to the application of knowledge within organizations. The focus of knowledge application relates to how knowledge should be utilized in order to add value to the organization and create an advantageous position. Knowledge application is contextual and perceptive in nature. In order to effectively apply knowledge, one must understand the underlying contexts and operational boundaries, and use the knowledge to create an acceptable answer to the perceived reality of the situation.
Within the business context, computers that possess knowledge in the form of input from human users cannot, at least at present, engage in the knowledge application process in the true form, because they lack the ability to create context and perceive the situation based on their experiences and their interpretation of the external en- vironment. The assessment of the external environment and the creation of a reality are based on a potentially infinite number of combinations of inputs that are based on social, historical, psychological, and cultural. At the moment, computers are best used in the knowledge application process as tools assisting human operators in making value-added decisions.