Knowledge Concepts
Tacit knowledge is expertise held in people's heads — hard to articulate, learned through experience. Explicit knowledge is documented, shareable, and searchable. The distinction is the foundation of knowledge management.
Tacit knowledge is the expertise you carry in your head — the intuitions, skills, and judgment you've developed through experience but struggle to fully explain. Explicit knowledge is knowledge that has been articulated, documented, and made shareable. Tacit knowledge is "knowing how"; explicit knowledge is "knowing that." The difference is the difference between an expert who can do something and a document that describes how it's done — and the gap between them is the central challenge of knowledge management.
Every organization's most valuable knowledge is mostly tacit. Converting it to explicit is hard — and essential.
The tacit vs. explicit knowledge distinction is rooted in the philosophy of Michael Polanyi, whose 1966 book "The Tacit Dimension" coined the memorable phrase: "we can know more than we can tell." Polanyi used the example of facial recognition — you can recognize a face instantly but cannot describe the process you use in sufficient detail for someone else to replicate it.
Ikujiro Nonaka and Hirotaka Takeuchi formalized the distinction for organizational management in "The Knowledge-Creating Company" (1995), introducing the SECI model for how knowledge converts between tacit and explicit forms. Their framework became foundational in business knowledge management theory.
More recent work by Dave Snowden (the Cynefin framework, 1999) further refined the idea by distinguishing different types of complexity — recognizing that tacit knowledge is especially important in complex and uncertain domains where explicit rules are insufficient.
Characteristics of tacit knowledge:
Examples:
Why tacit knowledge matters: In most organizations, the most valuable knowledge is tacit. Explicit knowledge (documentation, procedures) represents a fraction of what experienced employees actually know and do. When an expert leaves, they take years of tacit knowledge with them. This is the core knowledge management risk.
Characteristics of explicit knowledge:
Examples:
Why explicit knowledge scales: Explicit knowledge can be accessed by anyone, at any time, without requiring the original expert to be present. It can be searched, updated, and combined. A new hire who reads a well-written runbook gains explicit knowledge that would take months to develop tacitly. This is why documentation multiplies expertise across teams.
A customer success manager at a software company has worked with enterprise clients for 5 years.
Her tacit knowledge: She knows within the first 10 minutes of a quarterly business review whether the account is at risk — she can't explain exactly how, but it's something about the language executives use, the questions asked, and subtle signals in engagement patterns. She's never missed an at-risk renewal. Her colleagues with 6 months of experience miss most of them.
Attempting to make it explicit: Her manager asks her to document how she identifies at-risk accounts. She tries:
This captures some of her judgment — but not the full intuition. A colleague following the checklist identifies at-risk accounts better than before, but still misses some that she would catch.
The gap: The checklist is valuable — it transfers some of her tacit knowledge to explicit. But the complete transfer requires time: a junior colleague who shadows her on 20 QBRs will develop tacit knowledge the checklist alone can't convey.
This is the fundamental limitation of tacit→explicit conversion: you can transfer some, but not all. The remainder requires experience.
1. Ask experts to narrate their decisions in real time: "What are you looking at right now?" "Why did you choose that?" "What would have made you do something different?" Real-time narration captures reasoning that retrospective documentation often misses.
2. After-action reviews: Post-project debriefs where teams discuss what happened, what worked, what failed, and why. The "why" is where tacit knowledge surfaces — experienced participants explain their reasoning in ways that can be documented.
3. Shadowing and observation: Have an expert perform a task while narrating, with a documentarian capturing the process. The documentarian's questions ("why did you do that?") surface knowledge the expert would otherwise not articulate.
4. Structured knowledge capture interviews: Deliberate interviews with experts before they leave or transition roles, focused on: "What do you know that isn't written down? What would take a successor years to figure out?" These are most effective when asked specifically and concretely, not generally.
5. Example-based documentation: Rather than articulating principles (which often stay abstract), document specific examples — "here's a real situation and what I did and why." Examples transfer tacit reasoning more effectively than abstracted principles.
For remote teams and distributed organizations, the tacit/explicit distinction is especially acute:
What's typically already explicit: HR policies, product documentation, meeting notes, financial reports, project briefs.
What's typically still tacit: How to navigate the organization politically. How to tell when a project is actually in trouble. How the best performers think about their work. Why certain decisions were made. Who to call when something breaks.
The knowledge silo problem: In co-located teams, tacit knowledge transfers through proximity — overhearing conversations, observing colleagues, hallway exchanges. In distributed teams, these informal channels are absent. Tacit knowledge accumulates in individuals and doesn't flow to others unless deliberately captured and made explicit.
WebSnips and knowledge capture: For individual contributors, the annotation habit — capturing not just what you found but why it matters and how you'd apply it — converts personal tacit knowledge into documented explicit knowledge. A WebSnips collection with detailed notes is more valuable than one without, because the notes externalize reasoning that would otherwise stay tacit.
"Explicit is better than tacit." Neither is inherently better. Explicit knowledge scales; tacit knowledge handles complexity and nuance that explicit cannot fully capture. Organizations need both — and the conversion between them is an ongoing process, not a one-time project.
"You can fully convert tacit to explicit." You can convert some tacit knowledge to explicit. Polanyi's "we can know more than we can tell" is a fundamental constraint: there will always be a residue of tacit knowledge that resists full articulation. Documentation captures the explicitly expressible part; the rest requires experience.
"Young employees don't have tacit knowledge." Everyone has domain-specific tacit knowledge in areas where they have experience. A junior engineer with 2 years of experience has tacit knowledge about debugging the systems they work on. A senior executive with 20 years has vastly more — but the category applies at all career stages.
Knowledge base: The primary tool for storing and retrieving explicit knowledge within organizations.
Enterprise knowledge management: The organizational discipline of systematically managing the conversion between tacit and explicit knowledge.
Communities of practice: Social structures that facilitate tacit knowledge transfer through shared experience and conversation — the social equivalent of the SECI model's socialization mode.
Can AI transfer tacit knowledge? AI can help convert tacit to explicit by processing large volumes of examples, decisions, and outcomes to identify patterns that experts use intuitively. But AI output is explicit (it produces text and predictions); the tacit judgment that underlies expert performance involves embodied, contextual factors that remain difficult to fully capture. AI is a tool for supporting tacit→explicit conversion, not a substitute for it.
Is procedural memory the same as tacit knowledge? Procedural memory (how to ride a bike, how to type) is one type of tacit knowledge. Tacit knowledge also includes cognitive patterns, social judgment, and domain intuition that don't fit the "procedural memory" category. The overlap is significant but not complete.
How do you know what tacit knowledge an expert has? Often you can't know directly — the expert may not know themselves. The most effective discovery approach is observation under realistic conditions: watch the expert work, ask them to narrate, note the moments when they make decisions they don't fully explain. Those unexplained moments are where tacit knowledge lives.
The tacit vs. explicit knowledge distinction explains why documentation alone never fully preserves institutional memory, and why organizations that invest in converting tacit to explicit still experience knowledge loss when experienced people leave. The goal is not to eliminate tacit knowledge — it's to make the most critical tacit knowledge explicit enough to transfer without requiring years of experience to discover. Every after-action review, every carefully annotated note, every time someone writes "why I made this decision" instead of just "what I decided" is a small act of tacit-to-explicit conversion. These acts compound into organizational learning.
More WebSnips articles that pair well with this topic.
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A KWL chart is a three-column learning organizer: K (What I Know), W (What I Want to Know), L (What I Learned). It activates prior knowledge before learning, sets specific goals, and documents what you actually learned — making the learning process active and self-directed.