Knowledge Management
Ask your best performer how they do the thing they do best, and watch them struggle to answer. That struggle isn’t a communication problem. It’s a knowledge management problem and it’s costing your business more than you think.
Every organisation has a handful of people who just seem to know. They spot the problem before it escalates, sense which client is about to churn, or fix the machine nobody else can. Ask them to explain how, and most will shrug: “I just know it when I see it.” That’s implicit knowledge and because it can’t be written down the way a process or a policy can, it’s one of the hardest kinds of expertise for any L&D or knowledge management function to capture. This guide breaks down what implicit knowledge actually is, why even your most articulate experts struggle to explain it, and what a practical approach to drawing it out looks like.
Implicit knowledge: the short answer
Implicit knowledge (also called tacit knowledge) is know-how that someone has internalised so deeply that it operates below conscious thought — judgement, instinct, and pattern recognition built through repeated experience.
Unlike explicit knowledge, which lives in manuals and slide decks, implicit knowledge can’t simply be transcribed. The person holding it often isn’t consciously aware of every step they’re taking, which is exactly why “just write it down” doesn’t work.
The risk isn’t that this knowledge exists. The risk is that most organisations have no process for surfacing it before the person holding it walks out the door.
What implicit knowledge actually is
The philosopher Michael Polanyi coined the phrase that still best describes the problem: “we can know more than we can tell.” A skilled cyclist doesn’t consciously calculate the physics of balance. A veteran recruiter doesn’t run through a checklist to sense a candidate is wrong for a role. The knowledge is real, it’s reliable, and it’s genuinely useful, it just isn’t stored in a form the person can hand over in a sentence.
This is different from institutional knowledge in one important way. Institutional knowledge is often knowable but undocumented — a process that exists but was never written down. Implicit knowledge is knowable but unspeakable — even if you sat the expert down for a week, they might not be able to fully articulate it, because a large part of expertise becomes automatic and unconscious the longer someone practises it.
Researchers sometimes call this “unconscious competence” — the fourth and final stage in the classic four-stage model of skill acquisition, where a skill has been practised so much it no longer requires conscious thought to perform. It’s a hallmark of genuine expertise. It’s also precisely what makes that expertise so hard to transfer.
Why your experts can’t explain what they know
This is sometimes called the expertise paradox, or “Polanyi’s paradox”: the more skilled someone becomes, the less able they typically are to describe the mechanics of that skill. It isn’t reluctance or poor communication, it’s a genuine feature of how expertise develops in the brain.
As a task becomes automatic, the deliberate, step-by-step reasoning that once accompanied it fades into the background, replaced by fast, intuitive pattern recognition.
A few things make this especially difficult for L&D and knowledge teams to work around:
Experts underestimate their own expertise. Because a skill feels effortless to them, they often assume everyone else finds it just as intuitive so they don’t think to explain the parts that took them years to learn.
Standard interviews and manuals ask the wrong question. “How do you do this?” invites a generic answer. Implicit knowledge only surfaces when someone is asked to walk through a specific, recent example in detail.
There’s no natural moment to capture it. Like institutional knowledge more broadly, implicit knowledge only becomes visible once the person holding it has already left, by which point there’s nobody left to ask.
Examples of implicit knowledge at work
Implicit knowledge rarely announces itself. It shows up as a “gut feeling” or a “knack” — language that makes it sound unteachable, when really it’s just undocumented.
Sales
A top performer who can sense a deal is stalling from the tone of a client’s email, three exchanges before anyone else would notice.
Engineering
The engineer who knows instantly which of five plausible causes is actually behind a bug, without being able to say exactly how they knew.
Operations
The supervisor who can hear that a machine is about to fail from a change in its noise, long before a sensor would flag it.
Management
The manager who reads a room in seconds and adjusts their approach, drawing on hundreds of past conversations they couldn’t individually recall.
The cost of losing implicit knowledge
Because implicit knowledge is invisible while it’s still in the building, its loss tends to get bundled into the general cost of turnover e.g. recruiter fees, interview time, a signing bonus. That’s the visible cost. It’s rarely the real one.
is the average cost of replacing a single employee earning above £25,000, across sectors including IT, accounting, legal, media, and retail. Roughly 82% of that comes from lost productivity, not recruitment — the exact category implicit knowledge loss falls into.
is roughly how long a replacement needs before they’re operating at the level of the person they replaced — much of that gap is judgement and instinct that simply can’t be handed over in a two-week notice period.
a week is roughly what knowledge workers spend searching for information or tracking down colleagues who hold it, according to McKinsey’s research into workplace productivity — much of it chasing judgement calls nobody thought to document.
None of this shows up as a single line item. It shows up as slower decisions, quietly repeated mistakes, and new hires who take longer than expected to reach full speed — for reasons nobody can quite name, because the thing that’s missing was never named in the first place.
Why the usual fixes don’t work
Most L&D teams reach for the same three tools when trying to capture expert knowledge, and all three tend to fall short with implicit knowledge specifically:
Process documentation — captures the steps an expert takes, but not the judgement calls between the steps, which is usually where the real skill lives.
Generic training courses — teach the theory behind a skill, but theory rarely transfers the instinct that only comes from repeated, real-world exposure.
One-off shadowing — puts a junior colleague next to an expert, but without structured prompts, most experts still won’t narrate the parts they’ve stopped consciously noticing.
How to draw out implicit knowledge: a practical framework
Knowledge management researchers Nonaka and Takeuchi described this transfer as a cycle — tacit knowledge becomes explicit through conversation, observation, and shared practice, then gets re-absorbed as tacit skill by the next person. In practice, that cycle needs a bit of structure behind it to actually happen.
Ask about a specific moment, not a general process
“How do you handle difficult clients?” invites a vague answer. “Walk me through the last time a client got difficult — what did you notice first?” invites a real one.
Pair experts with a curious outsider, not another expert
Two experts skip past the obvious because it’s obvious to both of them. A newer team member will ask “wait, why did you do that?” at exactly the moments that matter most.
Capture it in the moment, not months later
Implicit knowledge is easiest to describe right after it’s been used — while the specific decision is still fresh — not when someone’s asked to reconstruct it from memory for a handover document.
Give it a searchable, permanent home
A single anecdote captured once is a nice artefact. A library of them, tagged and searchable by situation, is what actually helps the next person facing a similar judgement call.
This is exactly the gap Thirst is built to close. Instead of relying on formal, one-off documentation projects, Thirst makes it easy for people to capture what they know as they’re doing the work — turning fleeting, in-the-moment judgement calls into a structured, searchable knowledge base the whole team can draw on.
See how Thirst helps teams capture the knowledge that’s hardest to write down
What good looks like in practice
Organisations that get this right rarely describe it as a single dramatic change. It shows up in a series of small, everyday shifts:
Onboarding
New hires reach full competence faster because the “gut feeling” moments are captured as real examples, not left for them to rediscover the hard way.
Resilience
Losing a top performer stings less, because their judgement has already been partly captured and shared before they walk out the door.
Confidence
Teams make faster calls because they’ve absorbed real examples of expert judgement, not just the theory behind it.
Compounding
Every judgement call captured makes the next person’s decision a little easier — expertise builds on itself instead of resetting with every departure.
Implicit knowledge will never be fully documentable — that’s the nature of instinct built through experience. But “impossible to fully capture” isn’t the same as “not worth trying to capture.” The goal isn’t a perfect manual for every gut feeling your best people have.
It’s a habit of asking the right questions, at the right moment, so that even a fraction of that instinct gets passed on instead of walking out the door with the person who built it.
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For more expert insights and tips, check out the Thirst blog.
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