A framework for aligning knowledge management theory and practice [Forum special series]

This article is part of a special series of summaries of keynotes and presentations from the KM Triversary Forum 2025.

For decades, we’ve talked big about knowledge management (KM), but in most organizations, it’s still a disappointment. We have bookshelves full of academic research and a graveyard of expensive, failed projects and under-used applications to prove it.

We need to ask ourselves why this situation is so bleak. The reason might be in our fundamentally wrong approach to knowledge. We treat knowledge like a collection of artifacts, documents to be filed away in a digital cabinet. This “library mindset” is detrimental to KM. Practitioners are drowning in real-world problems like repeating old mistakes and watching expert knowledge walk out the door, while academics are busy perfecting elegant models that never touch ground.

This isn’t just a gap; it’s a failure of imagination!

The heart of the problem: we’re managing the wrong thing

The classic approach, what I call the “Stock-and-File” method, is obsessed with capturing knowledge and stuffing it into repositories. It focuses almost entirely on explicit knowledge (the stuff we can write down) and ignores the messy, human, and social engine where knowledge actually lives and creates value. The result? The “paradox of the empty repository”: a perfectly organized, meticulously curated database that nobody ever uses.

A different lens: knowledge as a living system

What if we stopped treating knowledge as a static artifact and started treating it as a dynamic action? To do that, we need to see it as a system of four dimensions, four interconnected gears. If one gear seizes up, the whole system stops.

1. The human gear (tacit): This is the know-how in people’s heads. The intuition, the experience, the “gut feel.” It’s fragile. When someone leaves, this gear stops turning.
   The real challenge:How do we help it flow? Not through databases, but through mentorship, storytelling, and actual conversation.
2. The explicit gear (codified): This is the knowledge that’s been written down. It’s the manual, the report, the procedure. It’s necessary, but it’s not sufficient.
   The real challenge: Making it easy to find, trustworthy, and alive, not just a PDF buried on a shared drive.
3. The embedded gear (procedural): This is “the way we do things here,” incorporated into workflows and applications. It’s the checklist in our project management tool, the approval routing in our ERP system.
   The real challenge: Keeping it from becoming a rigid cage. How do we build in feedback loops so the procedure can be modified or changed?
4. The collective gear (cultural): This is the social fabric of knowledge. It’s the trust that lets people ask “dumb” questions, the shared norms that enable collaboration, the water-cooler conversation that solves a problem.
   The real challenge: Breaking down silos and fostering psychological safety. No tool can fix a broken culture.

The necessary shift: from librarian to ecosystem architect

This framework forces a radical change in strategy. We must move from “Stock-and-File” management to “Flow-and-Relationship” management.

This means:

• Stop just managing documents. Start managing conversations. The real gold is in the dialogue that creates the document. Prioritize forums, peer assists, and communities of practice where knowledge is co-created.
• Stop just building repositories. Start building context. A document is useless without its story. Link it to the expert who wrote it, the project it served, and the team that debates it.
• Stop managing silos. Start managing the connections between them. Our goal is to make these four gears turn together. How does a collective practice (like a community of practice) help convert human tacit knowledge into explicit guidance? How does a new explicit procedure get woven into the embedded workflow and embraced by the collective culture?

The KM manager’s role is no longer to be a curator, but a designer, an architect of an ecosystem where knowledge can flow freely between people, processes, and content.

A practical compass, not just a theory

So how do we bridge the gap between KM theory and practice? We use this model as a diagnostic tool.

• For the practitioners in the companies: Use this to run an audit. Where are our weak spots? Do we have great documentation (Explicit) but a culture of hoarding (Collective)? That’s our misalignment. Now we know what to fix.
• For the thinkers in academia: Use this as a framework for relevant research. Test these connections in the real world. Develop metrics that matter, not just “number of documents uploaded,” but “reduction in project cycle time” or “increase in cross-team problem-solving.”

The bottom line is this: We can’t fix KM with better taxonomies or another software license. We fix it by recognizing that knowledge is a human system, first and foremost. By managing the flow and the relationships between these four dimensions, we can finally transform KM from a theoretical promise into a tangible driver of performance.

Making it real: from diagnosis to action

Alright, the model of the Four Gears, four dimensions, is available but it requires managing. We still face the real question: What do we do on Monday morning? How does this model actually change anything?

We should not launch another “KM initiative.” That language is part of the problem. Instead, we should start with a series of focused, diagnostic conversations. Our first goal is to listen and map, not to build and deploy.

Step 1: The knowledge ecosystem audit (the “Where does it hurt?” conversation)

Gather a team that’s actually doing the work. Don’t talk to managers in a closed room. Get the engineers, the salespeople, the customer service reps, the people whose daily grind depends on finding and using knowledge.

Take them through the four gears, one by one, with brutally simple questions:

• Human (tacit): “What’s the one thing we know how to do that isn’t written down anywhere? What happens when someone critical goes on vacation? Where is our expertise most fragile?”
• Explicit (codified): “When we need a specific answer, where do we look? How many places do we have to search? Do we trust what we find, or is it usually outdated?”
• Embedded (procedural): “Where do our tools and processes make our job harder? What workarounds have we built that the official procedure doesn’t know about? Where is the system fighting us, taking away our time, making our work less productive?”
• Collective (cultural): “Who outside your immediate team would we feel comfortable asking for help? Is it safe to admit we don’t know something? Do we share our failures or just our successes?”

We’re not collecting data for a report; we’re looking for the critical friction points. We’ll quickly find our “hot spots”, places where one gear is grinding to a halt because another is broken.

Step 2: Align and prioritize (the “So what?” conversation)

After the first step is completed, take that friction and frame it as a misalignment. This is where the framework gives us a powerful common language.

For example, that complaint about “nobody updating the project documentation” isn’t just a lazy team. It’s a classic Explicit-Collective misalignment. The explicit gear (documentation) is failing because the collective gear (culture, incentives) doesn’t reward sharing or punish hoarding. The solution isn’t to buy a better wiki, it’s to fix the cultural incentives.

Or, the complaint that “the new Enterprise Resource Planning (ERP) system is clunky and nobody uses it right” is a misalignment between Embedded and Human dimensions. The embedded gear (the ERP system) is fighting against the human gear (how people actually work). The solution is to redesign the workflow with the users, not just mandate more training.

By diagnosing the problem this way, we stop applying generic “KM solutions” and start designing targeted interventions that address the root cause.

Step 3: Co-create and experiment (the “Let’s try this” conversation)

This is the death of the “big bang” KM roll-out. Instead of a two-year, million-dollar software implementation, we can run a series of small, fast experiments.

• Problem: The engineering team’s “tribal knowledge” (Human) is a massive risk.
• Hypothesis: If we create a lightweight, peer-to-peer “Lesson Learned” session (strengthening the collective gear) right after project milestones, we can capture key insights and build a habit of sharing.
• Experiment: Run it for one month with one team. See what happens. Did people show up? Did they talk? Was anything useful captured? Tweak it and try again.

This experimental, co-creative approach does two things:

1. It builds solutions with practitioners, not for them, ensuring they actually fit the work.
2. It generates quick, tangible proof of value. A single, solved problem is worth a thousand theoretical PowerPoint slides.

A call to action for researchers and practitioners

This gap between KM theory and practice won’t be bridged by one side crossing over to the other. It requires a new meeting place. The Four-Dimensional Framework can be that place.

For practitioners: Stop asking researchers for “the answer.” They don’t have it. Instead, invite them into your specific, messy context. Use this framework to show them the real problems you’re facing. Challenge them to help you design and measure the small experiments. Your reality is their most valuable data set.

For researchers: Leave the ivory tower. Your models are elegant, but are they useful? Engage in “action research” where your study is the intervention. Partner with a company to diagnose their knowledge friction using this framework and co-design a solution. The outcome of your research shouldn’t just be a paper; it should be a measurable improvement in that organization’s performance. That’s impact.

Conclusion: it’s about the flow

We’ve spent too long building libraries when we should have been tending gardens. Knowledge isn’t a thing to be stored; it’s a living process to be nurtured.

The persistent gap between KM theory and practice isn’t a fact of life. It’s a symptom of our collective failure to see the whole picture. By shifting our focus from static assets to the dynamic flow between Human, Explicit, Embedded, and Collective knowledge, we stop being librarians and start being ecosystem architects.

This isn’t just an academic exercise. It’s the key to building organizations that are resilient, adaptable, and genuinely intelligent. The potential is all there, trapped in the conversations we’re not having and the connections we’re not making. Let’s stop managing knowledge and start enabling knowing.

Biography:

Dr Dobrica (Dobie) Savić is an experienced manager and consultant specializing in knowledge and information management, grey literature, and the application of artificial intelligence. He is also a renowned communicator, known internationally as a conference speaker, lecturer, moderator, and author. With a career spanning over 35 years, primarily within the United Nations system across three continents, Dobie has developed a deep expertise in managing information and fostering innovation on a global scale. His academic credentials, including a Doctorate (Middlesex University), an MPhil in Library and Information Science (Loughborough University), and an MA in International Relations (University of Belgrade), underscore his commitment to continuous learning. Dobie has authored 16 books and published over 100 professional articles. As a sought-after thought leader, he has presented his insights at more than 60 international conferences. Beyond his professional work, he produces educational YouTube content focused on the history of the First World War. He is guided by the principle: “Strange how much you’ve got to know before you know how little you know.”

Presentation resources: PowerPoint slides and video recording (coming soon).

Header image source: Author provided.

AI statement: AI was used to identify references and proofread the final text.

References:

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