What Is Tacit Knowledge? Definition, Examples & Uses

Tacit knowledge is expertise built through years of practice that people apply without being able to fully explain it. Michael Polanyi, who named the concept, summed it up as “we can know more than we can tell.”

But tacit knowledge can beome an organizational risk when critical information sits inside the head of one expert. What happens when they’re not available? Transfering that knowledge to others is essential, but if the expert cannot explain it, that’s when you have a problem.

Dorothy Leonard and Walter Swap spent years studying how expertise actually moves between people. They found that it moves when the learner does the work and the expert corrects. If the knowledge transfer is one-directional, then it’s not as effective.

What this means is that simply asking people to document their tacit knowledge is not enough. Instead, have them record themselves working, then get someone else to write it up. Finally, attach the results to the actual task.

We’ll break down the exact process of transferring tacit knowledge in seven steps. We’ll also cover the five mistakes that undo it.

TL;DR: In operations, the ‘Bus Factor’ is the number of team members who can unexpectedly leave (or get hit by a bus) before your company completely stalls. If your daily workflows rely on a few veterans who ‘just know things,’ your Bus Factor is dangerously close to 1.

The fix starts with a sort. Procedural know-how (exceptions, thresholds, workarounds) is capturable this week: record the expert narrating a live run, let a non-expert write the draft, attach it to the recurring task, and assign an owner plus an update trigger. Judgment (reading a client’s tone, pricing ambiguity) never survives as text; it transfers only through shadowing and paired decisions. Sort first. Everything downstream depends on it.

Tacit Knowledge: Definition, Examples & How To Capture It

What Is Tacit Knowledge?

Tacit knowledge is the unwritten, experience-built know-how that people carry in their heads; judgment calls they apply without consulting a document. It survives through conversation, shadowing, and the continued employment of the people who hold it. So when one of these holders of tacit knowledge leaves, it leaves with them.

Tacit knowledge is particularly common in small businesses, with smaller headcounts. For these SMBs, anything that a new hire couldn’t find on their own and would have to interrupt someone to learn is tacit knowledge. That includes the client whose PO number must go in a specific field and the founder’s read on which deals aren’t worth chasing.

Tacit vs. implicit knowledge: What you can actually write down

The PO number rule is not tacit in the strict sense. The account manager can state it in one sentence. Nobody ever asked them to. Knowledge management literature has a separate name for that category: implicit knowledge, meaning writable but not yet written. Polanyi’s tacit knowledge is the harder one, the part that stays out of reach of language, no matter how carefully you ask.

The distinction decides your method:

Implicit knowledge is procedural: exceptions, sequences, thresholds, and workarounds. The expert can articulate it when someone asks. They just never have been asked, or were asked and never got to it
Tacit knowledge in the strict sense is judgment and perception: sensing from a customer’s tone that a renewal is at risk, knowing which projects to decline before scoping them, hearing that a machine sounds wrong before the batch goes bad. No recording gets that onto a page, because the expert can’t state the rule they are following. It transfers through coached practice: shadowing, paired decisions, and guided experience

Tacit knowledge vs. implicit, explicit, and institutional knowledge

These four terms overlap, and usage genuinely varies between the academic literature and everyday business writing, which is why people swap them freely. Here is where each one sits and how it changes your knowledge transfer method.

Type	Where it lives	Can you write it down?	What it looks like in a small business	What to do about it
Tacit knowledge	One person’s experience, partly below conscious awareness	Only partly, never fully	Sensing from a customer’s tone that a renewal is at risk, estimating a job from a quick site visit	Transfer through coached practice: shadowing, paired decisions, guided experience
Implicit knowledge	People who have done the work, never asked to write it up	Yes, it just never has been	The billing exception only one person knows, or the onboarding step that everyone skips	Recorded walkthrough; a non-expert drafts it
Institutional knowledge	Across the whole company, formal and informal	Partly	Why you stopped offering a service line, or the reasoning behind a pricing model	Capture the decision log and the reasoning; accept that some context fades
Explicit knowledge	Documents, systems, and records	Already is	Your published refund policy, your employee handbook	Only needs maintenance

Also Read: How to Create Effective Internal Documentation for Your Team

Tribal Knowledge: What It Means and Why Teams Are Dropping the Term

‘Tribal knowledge’ is the group-held, procedural portion of what your team knows: the undocumented steps a small group shares and passes on by talking. In the table above, it maps to implicit knowledge, named for how it travels rather than for why it resists writing. Many teams now prefer tacit knowledge, institutional knowledge, or know-how instead.

The term remains standard in manufacturing and engineering, where it has been in use for decades. The objection is to the word itself: it borrows the anthropological sense of ‘tribe,’ and applying it to corporate ignorance strikes some people as dismissive of Indigenous peoples. Enough teams have raised it that the most common follow-up question is what to say instead.

If it does not sit well at your company, these alternatives describe the same thing:

Undocumented knowledge: The most literal and least ambiguous option
Tacit knowledge: The umbrella term most teams use, and the one this guide leads with
Implicit knowledge: The most technically accurate swap, though almost nobody says it in a meeting
Institutional memory: Better when the worry is loss over time
Unwritten rules: Good for norms rather than procedures
Single points of knowledge failure: The phrasing that gets a leadership team to act
Know-how gaps: Neutral and easy to say in a meeting

The idea does not depend on the label. If swapping the phrase gets your team to engage, swap it.

Why Capturing Tacit Knowledge Pays Off Faster for Small Teams

Capturing what your team knows gives a small business six things it cannot get any other way: the option to step away from the business entirely, recovered expert time, continuity when someone is absent, consistent output on repeatable work, the ability to automate, and onboarding measured in weeks instead of months.

Five of the six come from the writable portion, which is why capturing that first pays back fastest.

The option to scale, sell, or step away. A business where a single person can disappear for two weeks without revenue slowing can grow independently. A business where you cannot take a vacation without the phone ringing is a business that owns you. Documentation converts the first kind from aspiration into fact
Recovered expert time. Your best person spends hours each week answering the same questions. Coveo’s survey found that workers lose about three hours a day searching for information they need. In a small team, most of that hunting ends at one person’s desk, and their day absorbs the interruption. Documenting it gets that time back permanently
Continuity when someone is absent. The turnover math is unforgiving. Approximately 3.2 million people in the US quit their jobs voluntarily in a single month, according to the Bureau of Labor Statistics. If any of them hold undocumented knowledge, it leaves with them. But you do not need a resignation to feel this. A two-week vacation, a sick day, or a parental leave opens the same gap. Documented process closes it
Consistent output on repeatable work. When two people produce different results from the same brief, the standard is unwritten. Documented knowledge eliminates that lottery on anything procedural. Judgment-heavy work still varies by who does it, and no document changes that: a precedent log narrows the spread, but it will not close it
The prerequisite for any automation. An AI agent can only act on knowledge it can read. You cannot hand a workflow to an LLM while the workflow lives in someone’s memory. So the gap between what you expect and what the agent produces is usually a documentation gap. Capture first, automate second, and expect the boundary between the two to sit exactly where your documentation stops
Onboarding measured in weeks. A new hire in an undocumented team learns by interrupting people or by making mistakes nobody warned them about. That takes months and runs on the expert’s patience. A new hire with access to the documented exceptions reaches unsupervised output on procedural work in weeks

Why do documentation projects stall?

Documentation projects stall because the person who holds the knowledge is the worst person to document it. The standard advice tells you to build a knowledge base and have your experts fill it. That advice skips two things. First, writing a procedure is a separate skill from performing one. Second, the expert has to describe steps they no longer think about consciously.

Dorothy Leonard, Professor Emerita at Harvard Business School, studied this transfer problem for years with Walter Swap.

They called it ‘deep smarts’: experience-built judgment, developed over decades, that shows up as pattern recognition rather than recall. Their transfer hierarchy runs from directives and lectures at the bottom to learning by doing at the top, which is inconvenient for anyone planning a documentation sprint.

Walter Swap, professor of psychology emeritus at Tufts University and co-author of Deep Smarts, put it this way in an interview with ACM Ubiquity:

Rather than thinking about transferring the knowledge out of the head of an expert and into the head of a novice, we talk more about re-creating knowledge through guided experience… The coach has to guide the protégé’s practice, engage in joint problem-solving, and provide opportunities for guided observation.

Walter Swap, Professor and Author

The practical translation for a small business: a recorded walkthrough where the expert narrates the process is closer to guided observation than a blank-page writing assignment.

Leonard also proposed ‘dual-purpose projects,’ in which the work itself becomes the learning environment. That principle carries directly into how you store what you capture. A document attached to the recurring task describes updates as the work changes. A document filed in a separate wiki drifts from day one.

The fix for both problems is the same: treat documentation as a byproduct of how work already gets discussed, not as a separate project with a finish line. Record the conversation instead of requesting the document. Attach the result to the task instead of filing it in a folder. Then the work and the record stay together, and updating one updates the other.

Which Capture Method Fits Your Knowledge Type

Four methods move knowledge out of someone’s head: recorded walkthroughs, reverse shadowing, structured interviews, and written documentation sprints. Three of them capture writable processes. Structured interviews are the only one that reaches judgment.

Pick based on one question: is the knowledge procedural or judgment-based? Procedural work responds to recording and live correction. Judgment responds to questions, and only partially.

Approach	Strength	Weak spot	Best for
Recorded walkthrough	Lowest friction for the expert; captures rare scenarios they forget when writing	Raw output needs heavy editing before it’s usable	Processes done on a screen or workbench that can be narrated live
Reverse shadowing	Surfaces gaps the expert doesn’t know they’re skipping	Requires a real task to arrive; you can’t schedule curveballs	Exception-heavy workflows where the expert corrects on instinct
Structured interview	Targeted; you control what gets covered and in what order	The expert summarizes instead of demonstrating, so the steps get compressed	Judgment and decision-making knowledge, where the reasoning is worth capturing even though the instinct isn’t transferable in text
Written documentation sprint	Produces a polished document directly	Highest friction; the expert avoids the task for weeks	Simple, short procedures that the expert can write in under 30 minutes

Also Read: How to Write Procedures in 7 Clear Steps

How to Capture Tacit Knowledge in 7 Steps

Capturing the writable portion takes seven steps: identify the single points of failure, pick one process, record the expert’s work, run a reverse shadowing session, have someone else write the draft, attach the document to the work, and assign an owner with a trigger.

The sequence is tool-agnostic. A voice memo app, a screen recorder, and a shared document will get you through all seven.

1. Name the single points of knowledge failure

List two things: which process stops, and whose absence stops it. Keep the list to five or fewer. Then mark each item as procedural or judgment. Procedural items follow the six steps below.

This list is your Bus Factor inventory: every name on it is a 1.

You are looking for three signals:

Work stops when they are on leave, or there’s panic because of their resignation
Quality varies by who does it, and the standard exists only as an abstraction in one person’s head
One person consistently addresses repetitive queries

Teams skip this step and start with whatever is easiest to write, which is usually half-documented already. Resist that instinct. The uncomfortable items carry the real risk. For example, how pricing exceptions actually get approved, or which clients need a call before the invoice goes out.

Pro Tip: Frame it as a vulnerability exercise, not a documentation project. Ask: ‘If this person quits with no notice on Friday, what breaks on Monday?’ The answers write your list for you.

2. Pick one process, not the whole company

Choose the highest-consequence item from your list and document only that. One finished, trusted, used document changes more behavior than a half-built wiki with 40 empty pages.

The first document you complete has a second job beyond its own content: it proves that the knowledge base is worth checking. That proof only works if the document is correct, complete, and actually used the first time someone relies on it.

3. Record the expert working instead of asking them to write

Have the expert perform the process while narrating what they are doing and why. Screen recording covers anything on a computer. A phone camera covers anything physical. Talking while working adds roughly five minutes to a task they were doing anyway, which is why this beats the writing assignment that never gets started.

Keep the instruction loose: ‘Do the job, talk through it, include the parts you would normally skip.’ The exceptions an expert handles on autopilot are the highest-value content in the finished document. They are also exactly what disappears when someone writes from memory.

How to run it:

One process per recording. A 20-minute recording covering one workflow is usable. A 90-minute recording covering four is not
Do not rehearse. A polished second take loses the hesitations and workarounds that are the actual content
Record a normal instance, not the cleanest one. The tidy version is the one already in the SOP

Skip it if: The knowledge is judgment-based rather than procedural. ‘How I decide which projects to decline’ produces a rambling monologue. Use a structured interview instead.

4. Run a reverse shadowing session

Hand the work to the newer person, have the expert watch, and log every correction as it happens. Traditional shadowing has the novice observe. Reverse shadowing inverts it, and the inversion is what surfaces the gaps.

Every correction the expert makes is a piece of undocumented knowledge announcing itself. A specific instruction can look like this: ‘No, not that field; that client needs the PO number in the description line.’

Interviews cannot produce that. Asked to describe the same process, the expert compresses six steps into two sentences because they have done it a thousand times. Watching someone do it wrong triggers the corrective instinct instead of the summary instinct.

How to run it:

Use a real task. You cannot reverse-shadow a hypothetical, so wait for an actual invoice or an actual order
Have a third person log the corrections, or record the session. The expert is watching, and the novice is working, so neither can take notes
Log the correction and the reason, not just the correction. ‘Use the description line’ is a rule. ‘Use the description line because their AP system rejects the PO field’ is a rule that survives a system change
Run a second session on a different instance if the first task ran clean. One tidy run means you captured the standard path and none of the exceptions

Stop when the novice can complete the task with only minor corrections. That signals the captured material is close to complete, and it doubles as a test of the document you are about to write.

Skip it if: No novice is available, or the cost of an error during the session is too high. You would not reverse-shadow a live financial reconciliation with a first-week hire. Record a walkthrough instead.

5. Have someone else write the first draft

The person who does not know the process writes the document from the recordings. They produce clearer instructions than the expert would, precisely because they have to translate rather than summarize. Every step that confuses them will confuse the next new hire.

This person’s job is to notice the gaps. The unexplained jumps, the assumptions, and the steps that are not obvious to anyone outside the expert’s head. Those gaps become questions back to the expert, and the answers fill the document.

The expert’s role shrinks to reviewing and correcting, which takes minutes.

For the first pass:

AI transcription tools convert a recording into a transcript. Treat that output as raw material with errors, not a finished draft
A standard operating procedure (SOP) template prevents an argument about format and gives the writer a container to fill

Pro Tip: Make the first draft testable. Hand it to someone who has never done the process and ask them to follow it. Every point where they get stuck is a gap in the document.

6. Attach the document to the work it describes

Put the finished document where the work happens, not in a separate documentation tool. This curbs context sprawl and avoids wasting your team’s time that otherwise would be spent connecting scattered dots.

A procedure linked to the recurring task that runs it gets opened every cycle. On the other hand, a procedure filed in a documentation folder gets opened when someone remembers it exists, which is almost never when it actually matters.

The placement test: If finding the document takes more effort than asking a colleague, the colleague wins. Position it so the path of least resistance leads through the document, not around it.

Where to attach and organize SOPs:

On the recurring task that executes the process, so whoever picks it up sees the instructions without searching
In the checklist for the workflow, following the process and reading the document are the same action
Linked from the chat channel where questions about it get asked, so the answer and the source sit in the same conversation

7. Give it an owner and a trigger

Assign one named owner and define the event that forces an update. Instead of a calendar block, shape it as an event.

‘Review annually’ is a date nobody honors. It arrives, the owner glances at the document, decides it looks fine, and marks it complete. ‘Update this when we change the payment process’ triggers when accuracy matters, because the process just changed, and the document is now wrong.

Two triggers that keep the document alive:

Process-change trigger: When the work itself changes, the document updates as part of the change
Question trigger: When someone asks a question that the internal knowledge base should have answered, the person who answers adds the answer to the document immediately. That turns interruptions into upkeep instead of letting them accumulate into a rewrite project

At higher volumes, the same habit makes a knowledge management system worth running.

Note: The owner is not necessarily the expert. It is whoever is closest to the work daily and notices when the document drifts. Often, that is the person who took over the process after it was documented, not the person who originally held the knowledge.

Examples of Documenting Tacit Knowledge Across Three Scenarios

Tacit knowledge looks different at every company, and so does the artifact you produce when you capture it. A returns team needs a decision table, a founder’s judgment needs a precedent log, and a production line needs a card taped to the machine.

The three scenarios below are composites, built from patterns that repeat across small businesses in every industry.

1. Exception rules in a 30-person ecommerce returns team

One supervisor handles every return exception. The team processes normal returns fine. Out-of-the-box scenarios pile up until the supervisor returns to their desk.

Threshold rules: Refund amounts that get auto-approved versus escalated
Supplier exceptions: Three suppliers accept returns outside policy. The rest do not
Fraud patterns: Repeat addresses that trigger manual review, undocumented
Judgment calls: When to absorb a cost versus enforce policy to save a relationship

The right method: Reverse shadowing on live returns tickets. The output is a decision table (condition → action → threshold → escalation), attached to the returns workflow.

What makes this one different: Curveballs only surface when real tickets arrive. You cannot document them from memory. Reverse shadowing on live work is the only method that catches the full range.

2. Founder judgment at a nine-person services firm

The founder decides which projects to take, how to price ambiguity, and when to absorb a cost. None of it follows a sequence. Documenting it as a procedure will fail.

Project selection: Which engagements to decline based on past patterns
Pricing logic: How to price work when the scope is deliberately vague
Escalation instinct: When tone means the relationship is at risk versus routine negotiation
Scope defense: When to hold the line and when to give ground

The right method: A structured interview covering five past decisions, plus a running decision log going forward. The log becomes a precedent that the team can reference.

What makes this one different: You are building a library of precedent, not a procedure. The team stops asking ‘should we take this?’ and starts asking ‘is this similar to the one we turned down in March?’

3. Machine and shift handoff knowledge at a 40-person contract manufacturer

Two operators have run the same line for eleven years. The machine has quirks that appear in no manual. The second shift learns them by breaking things.

Startup sequence: The line needs a specific warm-up order that the OEM documentation does not mention
Failure precursors: A change in sound or vibration that precedes a bad batch, caught before scrap accumulates
Real tolerances: Which spec numbers hold in practice and which get adjusted for a known material variance
Handoff context: What the second shift needs to know about the run in progress, currently passed verbally or not at all

The right method: A recorded walkthrough on the physical machine using a phone camera, paired with a structured interview on the failure precursors. The output is a one-page startup and handoff card posted at the station. Plus, it includes a short video library linked from the shift-change task.

What makes this one different: Some of this knowledge is sensory, so it does not survive as text. ‘It sounds different’ cannot be written into a procedure, but it can be recorded. Capture the audio and video, then let the text handle the sequence and the thresholds. It is also the one scenario where the document has to be readable in 30 seconds while standing up.

Five Mistakes That Dilute a Documentation Effort

Five things kill documentation efforts that otherwise look healthy: building structure before content, documenting everything at once, making the expert the author, storing documents away from the work, and selling documentation as insurance. Each one produces visible activity and zero adoption.

Building the structure before the content. Someone spends a week setting up a wiki with a category tree, naming conventions, and a folder for every department. Then nothing gets written. The structure sits there, clean and empty, teaching your team that the knowledge base is not where answers live. Every empty visit reinforces the habit of asking a colleague instead.

The fix: Write three documents people actually use. Then organize what you have. Structure should follow volume, not precede it.

Documenting everything at once. A ‘documentation sprint’ produces 40 thin pages in two weeks. Nobody knows which ones were verified. One bad experience and the team concludes that ‘the docs are unreliable’. Trust is earned per document, not per project.

The fix: Finish one process, use it, then move to the next. Sequence by consequence, not by ease. A single document that is right the first time someone relies on it does more for adoption than a library that nobody has tested.

Making the expert the author. A task lands on your busiest person: ‘Please document the returns process.’ It sits open for six weeks. They are not procrastinating. They are busy completing the work they were hired for, while this seemingly ‘low-priority’ task sits in their queue.

The fix: Take the writing off their plate. Their job is 15 minutes of red ink on a draft.

Storing documents away from the work. The document exists with accurate information. People still ask the question anyway, because finding it requires opening another tool and hoping the search works. Asking a colleague seems easier than encountering tool sprawl.

The fix: Link the document to the task, list, or workflow it governs.

Selling documentation as insurance. You pitch the project as ‘what if Sarah leaves?’ The project gets approved, but nobody feels urgency because Sarah has not left. If you sell documentation as just a safety net for “what ifs,” it’ll lose to today’s house fires every single time.

The fix: Justify it by what it unlocks this quarter. The expert stops fielding the same five questions every week. The team runs the process without interrupting anyone. You can automate the workflow because it is finally written down. The ‘what if they leave’ benefit still exists. It is just not what gets people to do the work.

How to Capture Tacit Knowledge in ClickUp Small Business Suite

*Search your Docs, tasks, and Chat history to answer questions, freeing the expert using ClickUp Brain*

ClickUp brings together capture tools, documentation, and work in a single workspace. That directly addresses the two failure modes this article covers: the writing tax on experts and the gap between the document and the job it describes.

As a small business assembling this workflow from separate tools, you would pay for a meeting recorder, a documentation platform, a chat tool, and an AI subscription. Then maintain the connections between them. ClickUp bundles all of those natively for teams of 5 to 100 through its Small Business Suite.

What works well for tacit knowledge capture specifically:

Remove the writing tax. Record, transcribe, and generate summaries with action items from your Zoom, Teams, or Google Meet calls using the ClickUp AI Notetaker. For the reverse-shadowing session, the expert talks and corrects while the Notetaker captures everything. The transcript and action items become raw material for whoever writes the first draft

This walkthrough shows how AI turns a single meeting into tasks, Docs, and follow-ups without manual note-taking:

Handle the solo capture. Have someone narrate the process out loud instead of typing, using ClickUp Talk to Text. AI converts the spoken walkthrough into structured text, which feeds directly into a Doc without anyone transcribing manually
Record answers in Docs in one click. When someone answers a complex question in ClickUp Chat, that answer can become a part of ClickUp Docs. They sit in the same workspace. This closes the leak most small teams have: a good explanation gets written once in a thread and then vanishes. Because Docs attach directly to Lists, tasks, and recurring workflows, the ‘store it where the work happens’ principle stops being a problem
Answer repeated questions without burdening one person. The built-in contextual AI pulls answers from your Docs, tasks, and Chat history using ClickUp Brain. Once you have documented the billing exception or the returns threshold, Brain can answer the question instead of the expert
Run documented workflows without prompting. Take documented processes and execute them on a schedule or trigger with ClickUp Super Agents. They operate 24/7 alongside your team, scaling output without scaling headcount. For example, set up an Agent to prepare a meeting brief from your Docs and past notes 30 minutes before the call.

What this looks like at scale: MTM Logix, a logistics company moving thousands of shipments across Mexico and Latin America. It built its entire operation on ClickUp Small Business Suite.

Founder Mario Veraldo used ClickUp’s flexible data architecture to build 78 specialized Super Agents.

Every shipment used to require someone typing, copying, and relaying data between systems. We now connect internal platforms and external data sources to one command layer, then let specialized agents interpret the signals and execute within defined controls. Today 95% of our recurring shipment activities are automated or agent-orchestrated, from intake to delivery.

Mario Veraldo, Founder, MTM Logix

Each agent has a defined role:

One reads incoming bills of lading and extracts structured data
Another audits invoiced amounts against costs to catch billing errors
The other one runs daily team briefs and surfaces blockers

The result: Shipment volume tripled with no headcount increase, and output improved 5x.

Those agents work only because someone first wrote the rules down: what counts as a valid bill of lading, which cost signals mean a billing error. 78 of them run alongside 12 people, doing what used to take a team four times the size. You cannot hand an agent a rule that only exists in a person’s memory.

ClickUp’s limitations:

There is a learning curve. Teams coming from a plain document tool like Google Docs or Notion need to learn how ClickUp connects Docs, tasks, and owners. Most teams take a week or two to settle into the structure that fits
It is more tool than a very small project needs. If you need to document one process and never touch it again, a shared Google Doc is faster to set up and easier to hand off. ClickUp earns its place when documentation has to stay current across recurring work and more than a handful of people

Skip it if: Your team is two people with a single procedure to capture. A shared document gets you there faster.

Best for: Small teams (5-100) where multiple processes need to stay documented, current, and connected to the recurring tasks they govern. Also, if the goal is to eventually automate those processes with AI.

What to Do This Week

Pick one person on your team whose absence would stop operations. Ask them to do that process out loud this week while you record it. Have a teammate draft it. Attach it to the recurring task. Give it an owner and a trigger.

Then test it. The next time that person is out, does the work continue without them? If yes, you just converted tacit knowledge into an operational asset. Do the next one.

In ClickUp, the recording becomes a Doc, the Doc attaches to the task, and the process eventually runs itself through a Super Agent. Try ClickUp for free.

Frequently Asked Questions About Tacit Knowledge

Can AI actually capture tacit knowledge for you?

AI can capture tacit knowledge for you, but only partially. AI transcription and drafting tools turn a recorded walkthrough into a rough first draft. A human then corrects it, which removes most of the ‘writing tax.’ But AI can only act on knowledge it can read. Capture first, automate second. Tools like ClickUp Brain answer from documented content, but the documentation has to exist before any agent can run the workflow.

Is tacit knowledge good or bad?

Tacit knowledge is valuable expertise, and the risk comes from it being undocumented rather than from the knowledge itself. The workarounds and exceptions exist because they solve real problems. This is why deleting them in favor of a clean process usually reintroduces old failures. The danger is concentration: when know-how sits with one or two people, work stops when they are away, quality varies by who does the task, and onboarding stretches into months. The goal is to capture it, not eliminate it.

What is tacit knowledge in manufacturing?

In manufacturing, tacit knowledge is the undocumented machine and process know-how held by long-tenured operators. It can include the startup sequence a temperamental line actually needs, or the tolerance the spec sheet doesn’t mention. It matters more on the factory floor than in most functions because the knowledge is sensory and shift-based, so it never makes it into a written SOP.

Who usually holds tacit knowledge?

Long-tenured employees in operational roles hold the most tacit knowledge, and the clearest signal is whoever colleagues interrupt most often. In small businesses, that is usually the founder, the office manager, the senior technician, or whoever originally set up the current systems. Tenure matters more than seniority: a five-year coordinator typically holds more undocumented process detail than a recently hired director.

Is tacit knowledge the same as intuition?

No, though they overlap. Intuition is the felt experience of knowing without conscious reasoning; tacit knowledge is the underlying expertise that produces it, built through years of pattern exposure. Per Polanyi, tacit knowledge also includes learnable components, like procedural shortcuts and workarounds, that can be articulated when prompted. Intuition can’t be documented; the procedural layer of tacit knowledge can.

What is the difference between tacit knowledge and an SOP?

An SOP is the documented, approved version of a process. Tacit knowledge is the unwritten version people actually follow, including the exceptions the SOP never captured. Most teams have both, and the gap between them is where errors live. The SOP describes the standard path while tacit knowledge covers the deviations. A useful test is to hand your SOP to a new hire and log every question they still have. Those questions are your tacit knowledge inventory.

Everything you need to stay organized and get work done.

Contact Sales

What Is Tacit Knowledge? Definition, Benefits and Examples

What Is Tacit Knowledge?

Tacit vs. implicit knowledge: What you can actually write down

Tacit knowledge vs. implicit, explicit, and institutional knowledge

Tribal Knowledge: What It Means and Why Teams Are Dropping the Term