Knowledge management (KM) is a key concept in today’s business world. While there is an element of fashion in its appearance toward the end of the 1990s (Swan et al. 1999), many of the world’s most successful corporations, businesses, and organizations are investing considerable resources in this enterprise (Alvesson & Karreman 2001). These knowledge projects include setting up intranets, using collaborative or workflow software, mentoring, and sharing information on best practices. Deeply rooted in practicality and typically tied to organizational objectives, these practices seek to identify, create, represent, and distribute knowledge throughout the organization.
A number of considerations motivate organizations to embark on a KM program. Perhaps first among these is to gain and maintain the competitive advantage that comes with improved or faster learning and new knowledge creation. In a business environment characterized by radical and discontinuous change, successful companies are those that anticipate changes, consistently create new knowledge, disseminate it widely throughout the organization, and quickly embody it in new processes and products. Potential benefits of KM programs include: managing the proliferation of data and information in complex environments; allowing employees rapid access to useful and relevant knowledge resources; greater innovation; shorter product development life cycles; leveraging the expertise of people across the organization and thus benefiting from “network effects” (as the number of productive connections between employees increases); facilitating organizational learning; and increasing the responsiveness or resilience of organizations to environmental change.
Defining Knowledge Management
One aspect of KM, knowledge transfer, has always existed in one form or another. The actual study of KM is much more recent, however, and has its roots in areas such as business, management, sociology, and economics. Most working definitions suggest that KM is about identifying and harnessing intellectual assets, either in the form of explicit knowledge held in artifacts or as possessed by individuals or communities. A recurrent theme is that KM provides a framework that builds on past experiences and creates new mechanisms for exchanging and creating knowledge. Implicit is the recognition that knowledge, and not simply information, is the primary source of an organization’s innovative potential.
In considering KM, it is important to distinguish between knowledge and information. Generally, information becomes knowledge when it is seen in context or interpreted. A more process-oriented view of knowledge focuses on knowing and anchors it as a social accomplishment. Orlikowski (2002), for example, refers to knowledge as procuring the “capacity to act.” As the KM field has matured, there has been increasing academic debate on epistemological questions of this type and the emergence of a critical perspective on what began as a practical, management-based movement (e.g., Styhre 2003).
There are three general perspectives on KM: the cognitive perspective, the networking perspective, and the social, community-based perspective. The dominant perspective is the cognitive perspective, in which knowledge is a commodity and an asset, something that can be accounted for and managed. Typically, there are a number of processes involved: knowledge identification, capture or acquisition, generation, validation, diffusion, storage, retrieval, and use or reuse. 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 described later (Nonaka & Takeuchi 1995) and discussions of intellectual capital, the intangible assets that contribute to an organization’s value (Bontis 1999). Some scholars argue that the cognitive model of KM may be most applicable to the reutilization of knowledge. From this perspective, IT tools are used to codify, store, retrieve, and transfer knowledge.
Networking perspectives on KM emerge parallel with the theories of the network organization. From this perspective, knowledge acquisition and sharing is a primary lever for organizational learning, which enables organizations to choose and adopt new practices where relevant. The network perspective acknowledges that individuals have social as well as economic motives, and that their actions are influenced by networks of relationships in which they are embedded. Information technologies are extremely important as facilitating tools for maintaining and building knowledge sharing and transfer networks. In practice, network models of KM try to integrate collaboration patterns and IT networks in order to control the flow of information and forge strategic alliances both within and across organizations (Contractor & Monge 2002).
Both the cognitive and network perspectives on KM suppose a high degree of planning and formalization. An alternative strategy to encoding and retrieving knowledge from knowledge repositories such as databases is for individuals to ask their knowledgeable coworkers questions as needed. This social, community-based perspective to KM has much in common with communities of practice and narrative or storytelling approaches in organizational communication. The community perspective builds on the notion that knowledge and practice are inseparable. Community members work together to re-create and apply transferred information in locally situated, appropriate ways. The response from the expert individual is highly contextualized to the particular problem being addressed and personalized to the questioner. Knowledge is generated locally and collectively, through the social construction of new meanings and understandings. In this perspective, IT-based solutions play a secondary role. The challenge for organizations approaching KM from this perspective is to encourage enabling organizational practices, such as providing spaces for exchange and a nurturing environment (Cook & Brown 1999; Iverson & McPhee 2002).
Key Concepts In Knowledge Management
Nonaka and Takeuchi’s (1995) widely cited model of knowledge creation and dissemination distinguishes between tacit and explicit knowledge. If “tacit,” knowledge is unarticulated, and thus indescribable. Polanyi’s (1967) famous example of bicycle riding is a case in point: the ability to ride is demonstrated not through explanation, but through presentation. “Explicit” knowledge, on the other hand, can be expressed linguistically in artifacts (through writing, drawing, programming). In its explicit form, knowledge lends itself to recombination and thus becomes accessible to others. Only when it is externalized can tacit knowledge become useful to the group.
Nonaka’s model of knowledge creation and management has served as a foundation for much of the research in KM (Nonaka 1994; Nonaka & Takeuchi 1995). Nonaka and Takeuchi (1995) argue that a successful KM program must, on the one hand, convert internalized tacit knowledge into explicit codified knowledge in order to share it, but also enable individuals and groups to internalize and make codified knowledge personally meaningful once it is retrieved from a KM system. The model describes a continuous process of dynamic interaction between tacit and explicit knowledge through a sequence of four modes of knowledge conversion. In the first mode, “socialization,” tacit knowledge is shared through interaction between individuals. Because tacit knowledge cannot be articulated, the key to acquiring it is experience. Apprenticeships are one example. The second mode, “externalization,” involves developing ways to embed this shared tacit knowledge, and enable its communication. “Combination,” the third mode, involves reconfiguring different elements of externalized information through sorting, categorizing, adding, and recontextualizing it in new ways. Finally, “internalization” occurs when explicit knowledge is integrated into and becomes part of the individual’s knowledge base (a mental model). This sequence of steps from socialization, to externalization, to combination, to internalization is known as the SECI process.
According to the model, various triggers, such as interaction, dialogue, the use of metaphors, or experimentation, induce shifts between modes. The result is a dynamic spiral, which widens as it moves from individual to group to organization levels, explaining how individual knowledge is transformed into organizational knowledge and vice versa. The successful organization is one that best enables the knowledge creation spiral from socialization (tacit-to-tacit) to externalization (tacit-to-explicit) to combination (explicit-to-explicit) to internalization (explicit-to-tacit), thus capitalizing on the intellectual capital of individual employees (Bontis 1999).
Technological Aspects Of Knowledge Management
Information technology is a key enabler of KM programs. The earliest KM technologies were online corporate yellow pages (expertise locators) and document management systems. With the development of collaborative technologies such as Lotus Notes in the mid-1990s, KM systems expanded rapidly. Workflow systems and status tracking tools also added impetus to the movement, as did semantic technologies for search and retrieval and content management.
Several issues cloud the application of technological tools to KM. IT tends to reduce the complexity or richness of knowledge in order to be able to code it. Organizations sometimes store large quantities of information or data and mistakenly think they are fostering the flow of knowledge. There is a tendency to focus on individuals as the source of knowledge. Finally, existing KM systems have difficulty dealing with tacit knowledge.
As technologies gain in sophistication, they are progressively more capable of providing meaningful support for knowledge sharing in organizations. For example, discussion forums and the scaffolding structures they provide can be seen as KM tools. Intelligent information filtering and extraction (such as recommender systems) have become commonplace in the past five years. Social computing tools such as blogs and wikis provide a more unstructured approach to knowledge transfer and knowledge creation. Such tools are still primarily text based, however. Developments in visualization techniques such as concept mapping and image indexing provide new opportunities for distilling meaningful, reusable knowledge from their content.
As the KM field has matured, it has become apparent that advanced technologies cannot solve all KM problems, however. Database entries in knowledge repositories are only valuable if they correspond with users’ sense-giving processes. Constructing an information technology infrastructure for knowledge does not, in itself, guarantee that organization members will use the system. The literature on best practices in KM suggests that fostering an environment conducive to knowledge sharing and open communication is vital in any KM strategy. Other considerations are a shared vision, committed leadership, and a strong link to business priorities.
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