Abstract Today the world has more and more of free flow of information leading to transfer of knowledge from a person or an organization to others. Whereas this invariably leads to faster development, it also impacts the competitive advantage held by the innovators of processes or technology. It has therefore become strategically important for one and all in business to understand the knowledge, processes and controls to effectively manage the system of sharing and transferring the information in the most beneficial fashion. This paper dwells upon definition, types, scope, technology and modeling of knowledge and Knowledge Management while examining its strategic importance for retaining the competitive advantage by the organizations.
What is knowledge? Plato first defined the concept of knowledge as 'justified true belief' in his Meno, Phaedo and Theaetetus. Although not very accurate in terms of logic, this definition has been predominant in Western philosophy (Nonaka and Takeuchi, 1995). Davenport et al. (1998) define knowledge as 'information combined with experience, context, interpretation and reflection'.
The terms 'knowledge' and 'information' are often used inter-changeably in the literature and praxis but a distinction is helpful. The chain of knowledge flow is data-information-knowledge. Information is data to which meaning has been added by being categorized, classified, corrected, and condensed. Information and experience, key components of definitions of knowledge, are put into categories through the process of labeling with abstract symbols. This allows the process of synthesis to occur more efficiently than when dealing with masses of individual bits of information. Information coded into symbols to make it "knowledge" may be stored both inside and outside the individuals.
Thus, knowledge may be stored within a person in his mind or outside the person in books, manuscripts, pictures, and audio and videotapes or discs. However, while only the individual himself may retrieve knowledge stored within his mind, knowledge stored outside can be retrieved by anybody familiar with the storage systems. In organizations, knowledge is often embedded not only in documents and presentations but also in "organizational routines, processes, practices, and norms", and through person-to-person contacts. Even the simplest information about the environment requires the use of rules for interpreting it. This means that for information to become knowledge, people make interpretations, apply rules, and create knowledge. "People with different values 'see' different things in the same situation" and organize information so as to create different kinds of knowledge (Davenport and Prusak, 1998).
Types of Knowledge Systemic knowledge Systemic knowledge is a sort of knowing how we know. Systemic knowledge is both a process and a product. As a process it is expressed by Matura na and Varela (1987) as - "reflection is a process of knowing how we know". As a product it is knowledge on how we think.
Systemic knowledge has bearing on the perspectives of individuals, i.e. what is seen and how this is perceived. In this way, systemic knowledge directly influences the people's perception as to what type of explicit knowledge is relevant and meaningful for the organization. The more uniform this perspective is among the most important actors of the organization, the more influential this perspective will be as to what knowledge type (e.g. explicit versus tacit) is critical to the competitive position of the organization. Explicit knowledge Explicit knowledge is the part of the knowledge base that can be easily communicated to others as information. Explicit knowledge involves knowing facts (Sveiby, 1997). Explicit knowledge can be objective and inter-subjective.
Bunge (1983) defines objective knowledge in the following way: "Let p be a piece of explicit knowledge. Then p is objective if and only if (a) p is public (intersubjective) in some society, and (b) p is testable (checkable) either conceptually or empirically". Tacit knowledge Tacit knowledge (Polanyi, 1962) is a form of skill, ability or 'tech ne', i.e. know how, which is difficult to communicate to others as information, but "much of what Michael Polanyi has called tacit knowledge is expressible - in so far as it is expressible at all - in metaphor" (Nisbet, 1969). In the context of tacit knowledge, Drucker (1993) opines, "the only way to learn tech ne was through apprenticeship and experience". David and Foray (1995) also stress that no knowledge is tacit by nature, what has to be done is to create incentives to make tacit knowledge communicable. Polanyi (1962) says that this sort of knowledge also can be regarded as connoisseurship.
Such knowledge is deeply rooted in employee experience or in company culture making it more valuable in sustaining the competitive advantage because it is much harder for competitors to imitate. Hidden knowledge Hidden knowledge influences the way we think and act, as a sort of personal paradigm, or the technical-economic paradigm in the business world, a trajectory which leads our way of thinking and acting when expressing and interpreting, among other things, new ideas. Hidden knowledge organizes the development of mental models, the nature of the abstraction we make, the choice of variables, problems or phenomena, the facts we choose to focus on, our underlying metaphysical positions, our theoretical 'tastes' etc. Support for the concept 'hidden knowledge' is found in Schutz' (1990, Vols.
1 and 2) 'epoch e' concept. Relationship knowledge Relationship knowledge "involves the social capability to establish relationships to specialized groups in order to draw upon their expertise" (Lundvall, 1995). In a time where turbulence, change and hyper competition, are accelerating it is crucial for organizational survival to invest in relationship knowledge. The type of relationship knowledge which is relatively easy to communicate, may be classified as explicit knowledge. Knowledge management [KM] A business discipline called Knowledge Management emerged that identifies captures, organizes, and processes information to create knowledge. Knowledge Management is a conscious effort to get the right knowledge to the right people at the right time so that people can share and put information into action in ways that improve an organization's performance.
Knowledge is crucial to the operation of businesses, to predicting outcomes of events, to understanding how and why things function, and to appreciating things that are happening around us. With the rising importance of knowledge in our global economy, knowledge management has gained worldwide attention. Individuals including Sveiby (1997), Stewart (1997), Davenport and Prusak (1998), Allee (1997) and Nonaka (1991) have worked in the area to discover the opportunities, practices and benefits of knowledge management. Companies such as Buckman Laboratories, Dow Chemicals, Skandia, Hewlett-Packard, C elemi, and IBM to name a few, have made use of knowledge management in order to more effectively manage and utilize the knowledge and expertise in their organizations.
A number of disciplines have influenced the field of KM thinking - the important ones being philosophy (in defining knowledge); cognitive science (in understanding knowledge workers); social science (understanding motivation, people, interactions, culture, environment); management science (optimizing operations and integrating them within the enterprise); information science (building knowledge-related capabilities); knowledge engineering (eliciting and codifying knowledge); artificial intelligence (automating routine and knowledge-intensive work) and economics (determining priorities). This naturally leads to a host of working definitions of KM. Some of the definitions of KM are: o "Conscious strategy of getting the right knowledge to the right people at the right time and helping people share and put information into action in ways that strive to improve organizational performance' (O'Dell and Jackson, 1998). o 'Formalization of, and access to, experience, knowledge and expertise that create new capabilities, enable superior performance, encourage innovation and enhance customer value' (Beckman, 1997). o 'Collection of processes that govern the creation, dissemination and utilization of knowledge to fulfill organizational objectives' (Murray and Myers, 1997). o Knowledge management is the process of creating, capturing, and using knowledge to enhance organizational performance (Bassi e, 1997). o Knowledge management is the management of the information, knowledge and experience available to an organization, "its creation, capture, storage, availability and utilization" in order that organizational activities build on what is already known and extend it further (Mayo, 1998). o Knowledge management is the process of capturing a company's collective expertise wherever it resides, and distributing it to wherever it can help produce the biggest payoffs (Blake, 1998). o Knowledge management is about encouraging individuals to communicate their knowledge by creating environments and systems for capturing, organizing, and sharing knowledge throughout the company (Martinez, 1998). o Beckman (1999) asserts that KM concerns the formalization of and access to experience, knowledge, and expertise that create new capabilities, enable superior performance, encourage innovation, and enhance customer value. o Coleman (1999) defines KM as an umbrella term for a wide variety of interdependent and interlocking functions, including knowledge creation; knowledge valuation and metrics; knowledge mapping and indexing; knowledge transport, storage, and distribution; and knowledge sharing. Most of the definitions imply that KM can incorporate any or all of the following four components: business processes, information technologies, knowledge repositories and individual behaviors (Eschenfelder et al., 1998). A consistent theme in all espoused definitions of KM is that it provides a framework that builds on past experiences and creates new mechanisms for exchanging and creating knowledge.
Influence of Organizational Relationships and Processes on KM Knowledge management may be severely affected by the relationships and processes of the organization. Relationships are the arrangements of a system's parts at a moment in three-dimensional space. Processes are the dynamic changes of a system over time. For knowledge to be useful in the future, it must be stored in some memory system. Ways of doing things or procedures are maintained and stored within routines that different people perform in the organization. Thus, organizational processes not only record knowledge, but also shape the way in which knowledge is retrieved for use in the future.
Different Models of KM Different practitioners have given different models for KM. Some of the models are - the cognitive model of KM (Swan and Newell, 2000), the network, community (Swan and Newell, 2000), philosophical, and quantum. Each model treats knowledge in its own particular way; thus, has different KM approaches (Swan and Newell, 2000). Philosophy-based model of KMThe philosophical model is concerned with what constitutes knowledge. Its main concern is how one gathers information about social and organizational reality and is focused on objectives, concepts, with the relationship of knowledge to other notions such as certainty, belief justification, causation, doubt and. The philosophical model of KM is an attempt to think deeper on how one thinks and acts by posing deep-knowledge questions about knowledge within organizations (Murray, 2000).
The model provides a high-level strategic overview and creates a valuable framework of understanding, which informs later knowledge initiatives. This model is built along the lines of Polanyi's (1966) argument that 'We can know more than we can tell and we can tell nothing without relying upon our awareness of things we may not be able to tell'. The philosophy-based KM model is based on interactive dialogues within a strategic context. Numbers of international research studies conducted by the Cranfield School of Management (Murray and Myers, 1997; Kakabadse and Kakabadse, 1999) show that the philosophy-based model of KM is practiced by top teams in learning organizations; where the environment is conducive to an open, quality dialogue.
The model holds that KM need not be technology intensive and should not be technology driven - rather, it is actor intensive and actor centered. It is based on the Socratic definition of knowledge and a search for the highest knowledge - wisdom (Plato, 1953). Cognitive model of KM Leading management and organizational theorists have suggested that for an organization to remain competitive it must effectively and efficiently create, locate, capture and share knowledge and expertise to solve problems and exploit opportunities (Winter, 1987; Drucker, 1991; Kou got and Zander, 1992). The model is deeply embedded in positivistic science as the tool for understanding a mechanical universe driven by single cause effect relationships (Skolimowski, 1994). For knowledge-based industries, knowledge itself is the commodity traded (Gibbons et al., 2000). For the cognitive model of KM, knowledge is an asset; it is something that needs to be accounted for and a number of efforts are being made to develop procedures for measuring it (Sveiby, 1997; Swan and Newell, 2000).
Knowledge is seen as something that needs to be managed (Dodgson, 2000). This model builds particularly on definition of knowledge by Shank and Abelson (1977), Holliday and Chandler (1986), and Edvinsson and Malone (1997). Variations of the cognitive model of KM are practiced by most organizations with formal KM processes in place. Some prominent cognitive models of KM are the SECI model (Nonaka and Takeuchi, 1995; Nonaka and Konno, 1998); state of knowledge (Earl, 1998), organization knowledge networks model (Cara yannis, 1999), pillars and functions of knowledge management model of intellectual capital (Wing, 1993; Edvinsson and Malone, 1997); intellectual capital management model (Van Buren, 1999); and the knowledge management model based on cognitive science, semiotics and epistemological pragmatism (Snowden, 1998). Cognitive models of KM are integrative or controlling in approach, operating predominately at the operational level (McKinlay, 2000). The focus of many cognitive models is on repetitive action, replication and standardization or of knowledge and its replication (Swan and Newell, 2000).
An important point to be noted is that this model can become an obstacle for change and new knowledge as changing static routines is difficult. In today's environment of rapid change and technological discontinuity, even knowledge and expertise that can be shared often and quickly becomes obsolete (Zack, 1999). Establishing a dynamic balance is the fine line between exploration and exploitation proposed by the SECI model (Nonaka and Konno, 1998) and has been achieved only by a few organizations. Network model of KMThe networking perspectives of KM emerge parallel with the theories of the network organization and focus on acquisition, sharing and knowledge transfers. Network organizations are thought of to be characterized by horizontal patterns of exchange, interdependent flow of resources and reciprocal lines of communication (Powell, 1990). From the network perspective, the idea of knowledge acquisition and sharing is seen as a primary lever for organizational learning in order for an organization to choose and adopt new practices where relevant (Everett, 1995).
This model builds on conception of knowledge as defined by Samuel Johnson (quoted in Boswell, 1979), and Frantz ich (1983) where the important knowledge concerned resides within networks of actors. With the proliferation of Web-based technology, IT-based tools gained increased importance in the network perspective of KM as a facilitating tool for maintaining and building networks for knowledge sharing and transfer (Hayes, 2001; Swan and Newell, 2000). Network models of KM are integrative in approach as they try to develop networks structures and a way to control flow of information. It has the strategic intention of tapping across levels within organization and industry (Swan and Newell, 2000). Community of practice model of KM Perhaps one of the oldest models of KM, community of practice (CP), is receiving revival and recognition within contemporary organizations. The CP model of KM builds on the sociological and historical perspective.
Kuhn (1970) argued that scientific knowledge is 'intrinsically the common property of a group or else nothing at all'. This assertion was supported and expanded among others by Rorty, 1979; Barabas, 1990. Barabas (1990) opines that 'there is no universal foundation for knowledge, only the agreement and consensus of the community'. Knowledge has been traditionally passed from generation to generation by means of stories. Storytelling is a well-known technique for conveying complicated meaning in a simplified format to handle complex situations. The term 'community of practice' was coined in the context of studies of traditional apprenticeship (Lave and Wenger, 1991).
A CP model is widely distributed and can be found at work, at home or amongst recreational activities. The model proposes the coming together of members, relationships of mutual engagement that bind members together into a social entity and the shared repertoire of communal resources that members have developed over time through mutual engagement (Wagner, 2000). In organizations, community of practice arises as people address recurring sets of problems together. Since membership is based on participation rather than on official status, community of practice is not bound by organizational affiliation. Models of community of practice have a variety of relations to the organization in which they exist, ranging from completely unrecognized to largely institutionalized (Wagner, 2000). The CP model builds on the concept of knowledge defined by Heron (1996) and Nonaka and Takeuchi (1995) that holds that one cannot separate knowledge from practice.
CP models can retain knowledge in 'living' ways rather than in the form of a database or manual. Quantum model of KMThe quantum perspective of KM assumes that current information and communication technology will fundamentally change when built using quantum principles. Quantum computing will be able to make rational assessment of an almost infinite complexity and will provide knowledge that will largely make sense to people (Tissen et al., 2000). In order to cope with new levels of complexity and decision-making, actors will not just need knowledge but meaningful knowledge that is not fact driven, but scenario driven (Tissen et al., 2000). Quantum models of KM are highly dependent on quantum computing and assume that most intellectual work will be performed by IT-based tools which will provide simultaneous and virtual scenarios of decision outcomes, while actors will prioritize value systems and select desired futures (Tissen et al., 2000).
The quantum model of KM is simultaneously integrative and interactive of operations at all levels of organization thereby solving complex, conflicting and paradoxical problems in a way that is beneficial to shareholders, stakeholders and society. SECI Model Figure 1: The SECI process The SECI process given by Nonaka and Takeuchi (1995) depicts four modes of knowledge conversion with the underlying understanding that an organization creates knowledge through the interactions between explicit knowledge and tacit knowledge [Fig. 1]. The process is viewed as a spiral, operating at the individual, group, organization, and inter-organizational levels. The model assumes that tacit knowledge can be transferred through a process of socialization into tacit knowledge and then become explicit knowledge through a process of externalization. Also, the model assumes that explicit knowledge can be transferred into tacit knowledge through a process of internalization, and that explicit knowledge can be transferred to others, through a process of combination. It is to be noted that knowledge created through each of the four modes of knowledge conversion interacts in the spiral of knowledge creation.
The spiral becomes larger in scale as it moves up through the ontological levels. Knowledge created through the SECI process can trigger a new spiral of knowledge creation, expanding horizontally and vertically across organizations. Socialization Socialization is the process of converting new tacit knowledge through shared experiences. Socialization typically occurs in a traditional apprenticeship or in informal social meetings outside of the workplace where tacit knowledge can be learned through hands-on experience or sharing of worldviews, mental models and mutual trust. Socialization also occurs beyond organizational boundaries. Externalization Externalization is the process of articulating tacit knowledge into explicit knowledge.
When tacit knowledge is made explicit, knowledge is crystallized, thus allowing it to be shared by others relatively easily, and it becomes the basis of new knowledge. The successful conversion of tacit knowledge into explicit knowledge depends on the sequential use of metaphor, analogy and model. Combination Combination is the process of converting explicit knowledge into more complex and systematic sets of explicit knowledge through a process of combining, editing or processing thereby forming new knowledge. It is new knowledge in the sense that it synthesizes knowledge from many different sources in one context. This new explicit knowledge is then disseminated among the members of the organization.
Internalization Internalization is the process of embodying explicit knowledge into tacit knowledge. Through internalization, explicit knowledge created is shared throughout an organization and converted into tacit knowledge by individuals. Internalizati on is closely related to 'learning by doing'. Explicit knowledge has to be actualized through action and practice. When knowledge is internalized to become part of individuals' tacit knowledge bases in the form of shared mental models or technical know-how, it becomes a valuable asset. This tacit knowledge accumulated at the individual level can then set off a new spiral of knowledge creation when it is shared with others through socialization.
Figure 2: Three elements of the knowledge-creating process Nonaka et al. (2000) extended the SECI model to include three elements of knowledge creation: the SECI process, Ba, and the moderator of the knowledge creating process. The first element of the model is the SECI process which, as explained above, places an emphasis on 'knowledge conversion', that is the creation of knowledge through explicit and tacit knowledge interactions [Fig. 2]. The second element of the model, Ba, refers to the context for knowledge creation 'a shared context in which knowledge is shared, created and utilized'. The last element of the model is knowledge assets that are 'firm-specific resources that are indispensable to create values for the firm'. These knowledge assets are the inputs, outputs, and moderator of the knowledge-creating process.
The three elements of knowledge creation have to interact with each other to form the knowledge spiral that creates knowledge The central focus of Nonaka et al.'s (2000) work is the processes of conversion between tacit and explicit knowledge and the cultural context within which this knowledge creation occurs. According to this knowledge-creating process, knowledge creation is a continuous, self-transcending process. Knowledge is created through the interactions amongst individuals or between individuals and their environment. In knowledge creation, micro and macro interact with each other, and changes occur at both the micro and the macro level: an individual (micro) influences and is influenced by the environment (macro) with which he or she interacts. The first element of the knowledge creating process - the SECI model has already been discussed above in detail.
The second element of the model - Ba - is the shared context for knowledge creation. Knowledge needs a context to be created in terms of who participates and how they participate. Knowledge also needs a physical context to be created: 'there is no creation without place'. 'Ba' (which roughly means 'place') offers such a context. Based on the concepts proposed by Kit aro Nishida and Shimizu, ba is defined as a shared context in which knowledge is shared, created and utilized.
It is a concept that unifies physical space such as an office space, virtual space such as e-mail, and mental space such as shared ideals. It thus provides the energy, quality and place to perform the individual conversions and to move along the knowledge spiral. These contexts provide the basis for one to interpret information to create meanings, as in the words of Friedrich Nietzsche, 'there are no facts, only interpretations'. Ba lets participants share time and space, and yet it transcends time and space. In knowledge creation, especially in socialization and externalization, it is important for participants to share time and space. A close physical interaction is important in sharing the context and forming a common language among participants.
There are four types of ba - originating ba, ba, systemizing ba and exercising ba. These four types of Ba are defined by two dimensions of interactions - the type of interaction (whether the interaction takes place individually or collectively) and the media used in such interactions (whether the interaction is through face-to-face contact or virtual media such as books, manuals, memos, e-mails or teleconferences). Each ba offers a context for a specific step in the knowledge-creating process, though the respective relationships between each single ba and conversion modes are by no means exclusive. Building, maintaining and utilizing ba is important to facilitate organizational knowledge creation. Knowledge Development Cycle Model Bhatt (2000) provides a model that conceptualizes some discrete phases of a knowledge development cycle as: (1) knowledge creation (Nonaka, 1994); (2) knowledge adoption (Alder, 1989; Alder et al., 1999); (3) knowledge distribution (Praha lad and Hamel, 1990); and (4) knowledge review and revision (Cross an et al., 1999). Because creating the required knowledge (the first phase) for competitive advantage is difficult many organizations adopt knowledge (the second phase) to fulfill their needs.
Knowledge adoption minimizes the commitment of organizational resources by adopting knowledge from leading organizations. However, caution has to be taken in this approach, as it is highly unlikely that the institutional and contextual variables of both companies will remain constant to permit the transfer of practice from one organization to another. In other words, knowledge adoption is risky without the appropriate adaptation to the specific organizational context. The third phase of knowledge development cycle is knowledge distribution. The organizational structure plays an important role in distributing knowledge. Where the organizational structure is centralized or has formal authority, knowledge sharing and distribution is difficult (Huber, 1991; Savary, 1999).
On the other hand, when the organizational structure is decentralized or has informal authority, the sharing and distribution of knowledge would be enabled (Broadbent and Lofgren, 1993; Savary, 1999). Thus, the structure of the organization therefore plays a key role in the successful distribution of knowledge within the firm. Knowledge review and revision is the last phase of the cycle and is especially important for organizations. Adopted or created knowledge needs to be evaluated to establish its appropriateness within a particular organizational context.
However, a drawback of Bhatt's (2000) model is that it does not determine a specific direction for the knowledge development phases. Different Perspectives on Knowledge Management There are at least four distinct perspectives on knowledge management that must be integrated to implement any long-term strategy. These four perspectives are: o Strategy / leadership perspective - Senior executives see knowledge management primarily in terms of how it supports strategic business objectives, and the capital market's perception of related intangible assets. o Knowledge content / practice perspective - This view is held by line managers who are more concerned with what knowledge is to be managed and how it is actually applied in practice. In contrast to the CEO's strategic view, the manager of a regional office is more likely to be concerned with what practical knowledge another regional office has that makes it a better performer. o Technology perspective - As would be expected, this view is taken by those in information technology (IT) roles, who view knowledge management as a product of applying information and communication technologies. o Change management / re engineering perspective - This view is taken by OD and HR specialists, or internal experts on business process re engineering and emphasizes the changes in work design, organizational structure, and culture necessary to leverage knowledge. Thus, in practice, the meaning of "knowledge management" for the organization becomes multifaceted and subject to a broad range of interpretations. Failure to recognize and legitimize these different views when trying to communicate with others is an important source of the conceptual confusion that undermines attempts to use knowledge more effectively.
Steps In Managing Knowledge The management of knowledge usually involves five basic steps: (1) Capturing knowledge - Recording steps involved in solving a particular problem. (2) Storing knowledge - Storing the captured information in, may be, a production system, a data warehouse, or a groupware application. (3) Processing knowledge - This may involve sorting, filtering, organizing, analyzing, comparing, correlating, mining, labeling the knowledge or analyzing it with sophisticated, complex, statistical methods to discover relationships and insights. (4) Sharing knowledge - Knowledge can be shared through information systems or by face-to-face interactions. (5) Using knowledge - The ultimate use of knowledge is to solve problems and advance the goals and objectives of the organization. Technologies For Knowledge ManagementSchultze and Boland Jr.
(2000) state that 'Organizations seeking ways to manage their knowledge assets are increasingly turning to information technology for solutions'. Gray (2000) also views knowledge management systems (KMS) as a class of information system that enables the identification of 'knowledgeable individuals' within an organization. Further, Zack (1999) acknowledges that there is a recognized role for information technologies (IT) in a KM program. Thus, it is seen that knowledge management inherently uses technological support as a facilitator for effective KM in an organization. Various technologies support the capturing, storing, sharing, and use of information, know-how, and insights within and across communities of people and organizations in order to create knowledge. Although technology is essential for knowledge management, it should not be over emphasized.
Technology helps in transforming knowledge management from a concept to a business reality that solves problems and exploits opportunities. Technologies that are more pervasive in knowledge management implementations are highlighted below: Network knowledge infrastructure According to Huang et al. (1999), one of the key objectives of using technology for knowledge management is to provide access to valuable information and codified knowledge on a timely basis. Many technology options are available for knowledge management namely, knowledge representation, document management, data mining, data warehousing, knowledge bases, expert systems, artificial intelligence, enterprise resource planning, legacy systems, decision support, groupware, the Internet, intranets, network computing, e-mail, web conferencing, and multimedia. Selection of the technology depends upon the problems that one is trying to solve, the information and knowledge needed, the number of locations one needs to link to, etc. Today, most large organizations have some form of corporate intranet and extra net in place.
They, then, become the main infrastructure to support the new corporate wealth of information and knowledge. Knowledge-sharing intranets Intranets, by their very nature, reflect a knowledge management strategy by providing a centralized approach and a common architecture for managing information and knowledge. Intranets provide a common electronic platform for capturing, storing, and sharing information and knowledge. One popular approach to utilizing the firm's intranet facility for knowledge sharing is the corporate knowledge portal. This portal basically consists of a browser-based application that allows knowledge workers to gain access to, collaborate with, make decisions about, and take action on a wide variety of business-related problems, regardless of the staff location or departmental affiliation, the location of the information, or the format in which the information is captured and stored. Extranets and external knowledge sharing With the internal needs being satisfied by the organization's intranets, there is an urgent need to find better ways of external knowledge sharing with customers and business partners.
Extranets are extremely powerful systems that meet these needs of solving problems and streamlining processes in areas such as marketing, sales and distribution, finance, engineering and customer service, thereby creating operational efficiencies for both the organization and its external constituents (Huang et al., 1999). Groupware technologies and collaboration Groupware is a system designed to support and accelerate joint work group activities by enabling communication, and the sharing and coordination of information using computers and networks. Among the several groupware applications available, the more popular ones are Lotus Notes, Domino, Microsoft Exchange, and Office 2000. The objective would be to enable the organization to make or save money. The process of achieving this goal should be documented and placed in the organization's knowledge memory. Dow Chemical saved more than $4 million through better management of patents alone.
Knowledge sharing strategies of Buckman Laboratories led to big sales that would not have happened without employing new knowledge management ideas. Intra-firm knowledge management Knowledge management and strategic management writers tend to emphasize monolithic "firms" (e.g. Barney, 1991). A key concern of this literature is the transfer of knowledge within the firm (Goh, 2002). Lam, amongst others, suggests that tacit knowledge is of central concern, thereby pointing to the significance of spatial proximity in the development and diffusion of tacit knowledge. This assumes considerable significance considering that "knowledge" is one that is locally obtained and unevenly distributed. Further, a site or facility provides the unique context for interaction and diffusion through unusually rich face-to-face interaction, allowing tacit knowledge development and diffusion.
This is particularly important in operations, where advances are often minute and incremental and where "learning" and "innovation" are often indistinguishable from "normal operations" (Johnsen, 1992; Eckert, 2000). Ferdows' (1999) model suggests a contingency relationship between the rate of change of operational knowledge, the extent to which it is, and the roles of facilities within an intra-firm network. But, although examining the intra-firm issues, Ferdows does not link them to inter-firm knowledge management. Inter-firm knowledge management vital aspect of firms' knowledge assets are those that are developed and reproduced in network relationships (Dyer and Singh, 1998). Furthermore, following Cohen (1990), it can be suggested that a firm's 'absorptive capacity' - its ability to take on new knowledge - varies depending on the particular counterpart with whom it is interacting. The IMP interaction model (Hakansson, 1982) provides a way of considering the relationship between actors (firms, plants, or individuals, depending on the focus).
Briefly, interaction is characterized as a series of episodes, involving product / service, social, information and financial exchange. It is suggested that the ability to transfer knowledge between firms - their mutual 'absorptive capacity' - changes over time, and that face-to-face relationships brought about by proximity of facilities promotes tacit knowledge between firms. Combining the issues of single- and multi-site, and inter- and intra-firm knowledge then, with the now questionable distinction between explicit and tacit knowledge types, presents a new challenge. KM And Competitive Advantage Knowledge is fast becoming a key asset and a potential source of competitive advantage. As an example physical assets accounted for 62.8% of the total market value of U.S. manufacturing firms in 1980 but only 37.9% in 1991. The remainder of the market value is composed of intangible assets primarily in form of intellectual capital.
It is to be understood that knowledge is tantamount to power and members in an organization possessing key skills can secure for themselves a base of practical power. Managers must therefore accept it as an integral part of their jobs and must control how to use it (while preventing its misuse) to further their own and organizational goals. The competitive opportunity enabled by knowledge management (KM) is potentially of great magnitude and strategic importance for organizations. Toff ler (1990) suggests that today's society has been distinguished by, and rapidly changed into, a 'knowledge-based society'.
Nonaka et al. (2000) point out that 'management scholars today consider knowledge and the capability to create and utilize knowledge to be the most important source of a firm's sustainable competitive advantage'. In fact effective KM can make and sustain the organizations whereas lack of it may as well ruin them.