Process and models of KM cycle(CONTD)

Wiig’s KM cycle frames knowledge management around two linked problems: where knowledge is built and used (individual, team, organization) and how knowledge moves through an organization (building, holding, pooling, and applying). The core insight is that knowledge isn’t just “stored” or “shared”—it must be created from experience and learning, converted between tacit and explicit forms, coordinated across social units, and then applied in real work contexts where resources and constraints determine whether it actually delivers value.

At the individual level, knowledge grows through both explicit sources—manuals, guidelines, books—and tacit learning gained through interaction with experts and collaboration. That mix drives two complementary strategies: codification (turning know-how into documented, explicit form) and personalization (using direct relationships and collaboration to transfer tacit insight). The cycle then shifts to the team level, where effectiveness depends on group dynamics such as cohesiveness, active dialogue, and full participation. Cross-functional project teams—people from different functional areas like R&D, marketing, and product—pool resources and knowledge to generate shared best practices, often using benchmarks or more standardized community approaches.

At the organizational level, knowledge becomes “organizational capital”: practices and assets like trademarks, patterns, and copyrights that are not owned by any single person or team. This is where knowledge bases and repositories matter, because they allow knowledge to persist beyond individual tenure and become part of the organization’s competitive advantage.

The process side of Wiig’s model runs through four stages that are distinct yet interdependent and can operate in parallel. Building knowledge starts with learning from tangible and intangible sources—books, videos, people, experts, and documented materials—followed by analysis and synthesis to reconstruct knowledge for a specific context. That reconstruction may be codified into steps and procedures, modeled into testable representations, and then applied in new contexts.

Holding knowledge focuses on where it resides: tacit knowledge in people’s minds and explicit knowledge in documents, books, or computerized systems such as search engines and other repositories. Internalization is the bridge—knowledge becomes “owned” when it is applied in context, not merely read. After internalization, knowledge can be encoded back into tacit form or documented into explicit form, then archived in knowledge centers, libraries, or digitized repositories for easier access and lower storage cost.

Pooling knowledge is especially important for tacit know-how. It happens through dialogue, expert networks, collaboration across teams, and coordinated sharing so that lessons from one group can inform others. Accessing and retrieving knowledge requires evaluation mechanisms—expert judgment, peer review, and second opinions—because tacit knowledge can’t be inspected directly. Concrete examples include troubleshooting recurring equipment failures by consulting experts, checking manuals and guidelines, and validating what was learned in the specific shop-floor context.

Finally, applying knowledge turns options into action. Knowledge leads to action only when the organization and the worker can apply it within a relevant work context. That means ranking alternatives, weighing advantages and disadvantages, assessing feasibility and acceptability, and using heuristics when problems are non-routine and lack a fixed diagnostic rule.

The cycle closes by emphasizing critical KM functions tied to knowledge value: capturing and sharing knowledge, developing successors to prevent loss when experts retire, eliciting and encoding expertise so it remains retrievable, and continuously updating the knowledge base so creation, assessment, dissemination, application, and revision keep repeating.