Category: Radical KM

Radical Knowledge Management

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ABIs Are Your Tools. They’re Not About Creating Art

(This post was originally shared on my LinkedIn Profile.)

For years (I’ve been working on this idea for 15+ years), when I mention arts-based interventions in KM conversations, I watch the same response play out. Eyes light up. Then — a gentle retreat. “That sounds lovely,” they say, “but we’re not really an arty organisation,” or “I work with a bunch of lawyers/engineers/accountants, they will never do this stuff”.

I understand the hesitation. We’ve been conditioned to think of arts-based work as something separate from serious business — creative indulgence rather than strategic leverage. But that’s not what ABIs are.

ABIs are tools. Specifically, they’re tools for doing the thing KM practitioners struggle with most: getting people to think.

In a world drowning in information and increasingly suspicious of what we’re told, our core challenge isn’t capturing knowledge, storing it better, or finding it when it’s needed. It’s reactivating the curiosity, critical thinking, and continuous learning that so many organisations have accidentally designed out of their cultures.

Here’s the paradox: you can’t mandate creativity. You can’t drive critical thinking with a policy. And you certainly can’t build psychological safety — the actual foundation of knowledge sharing — through process and conversation. These things live in the human layer, and they respond to something more subtle than corporate edicts.

That’s where creativity becomes a tool rather than a luxury.

When you ask someone to paint their response to “What does trust look like in our team?” you’ve created a constraint that forces novel thinking. They can’t fall back on corporate-speak. They can’t hide behind jargon. The unfamiliar medium — the act of making something — bypasses the rational filters and surfaces what people actually think and feel.

You’re not running an art class. You’re creating conditions for knowing to emerge.

ABIs work because they:

  • Disrupt habitual thinking. Familiar formats produce familiar responses. A different medium invites different pathways.
  • Create psychological safety through ambiguity. There’s no “correct” answer to a painting or a collage. That removes the performance anxiety that stifles honesty.
  • Make the tacit visible. The patterns in how someone uses colour, composition, or materials often reveal assumptions and thinking they hadn’t consciously articulated.
  • Invite full-system engagement. The hand, the eye, and the brain working together create a different quality of attention than sitting in a meeting watching slides.
  • Generate genuine conversation. When artefacts are at the centre — not abstractions — dialogue becomes richer, more grounded, and more memorable.

I’m not asking you to turn your people into artists. I’m asking you to consider: what if the tool you’re looking for to unlock knowing isn’t another platform, another framework, or another consultant-led workshop? What if it’s permission to engage your people’s creativity as a capacity rather than a personality trait?

Because here’s what I’ve learned: people don’t lose their creativity in organisations. They’re just trained not to use it where it matters most.

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The Automation Paradox: Why AI Makes Human Capacity More Valuable (Not Less)

(This post was originally shared on my LinkedIn Profile.)

We’re told AI will handle routine work, freeing humans for creativity and critical thinking. Sounds great. So why do leaders I speak with say their organisations feel less creative, not more? (Some have said they feel like AI is making them dumb.)

The problem isn’t AI. It’s that we’ve been systematically dismantling the conditions humans need to think, create, and judge well—and we did it before AI arrived.

The Post-mortem of Lost Capacity

Over the last 15+ years, organisations have optimised for efficiency: fewer meetings (no, we added more), faster decision-making (no, we added layers of approval), knowledge capture (no, we built systems nobody uses). The net result? Cognitive exhaustion. People are too busy processing information to actually think with it.

Add AI to this picture, and something shifts. Organisations realise they can automate tasks, but they can’t automate the parts of work that matter: understanding what problem actually needs solving, sensing when the data is misleading you, creating something genuinely new, making judgements that hold human values.

Suddenly, the capacity for critical thinking, intuition, and creativity isn’t a nice-to-have. It’s everything.

But here’s the trap: you can’t generate that capacity on demand. It requires conditions. Uninterrupted thinking time. Psychological safety to challenge ideas. Exposure to perspectives that collide with your own. Reflection. Sense and meaning-making.

Most organisations have actively eliminated these conditions in the name of efficiency.

Where Knowledge Management Has Failed (And Why It Can Recover)

Traditional KM treated knowledge like widgets: capture it, store it, retrieve it. The assumption was that better information architecture = better decisions. It didn’t account for the human dimension.

We lost the messy, generative stuff: the conversations where ideas collide, the storytelling that embeds wisdom, the reflection that turns experience into judgement. We built systems, not cultures.

So, when AI arrived, organisations had already stripped away the human conditions for thinking. The software wasn’t the problem. The culture was.

Radical KM: People-First, Not Technology-First

This is where the work shifts. If human capacity for creation, critical thinking, and judgement is the competitive advantage in an AI world, then KM isn’t about technology adoption. It’s about designing the conditions that allow humans to do what humans do best.

That means:

  1. Making space for thinking. Not as something to aspire to, something that is structurally embedded in the systems. Protected time. Simplified information. Reduction of noise.
  2. Reactivating curiosity through exposure. Cross-sector conversations. Diverse perspectives. Learning that isn’t bounded by function. This is where intuition develops—through pattern recognition across domains.
  3. Creating safety for dissent and iteration. Humans refine judgement through being challenged. Organisations that treat disagreement as a threat lose their smartest people.
  4. Embodying knowledge differently. Not everything knowable fits in a database. Wisdom about how to navigate ambiguity, where to apply intuition, when the data is lying to you—these are often learned through story, conversation, and shared sense-making.

Using arts-based approaches to do all of this.

I know that last line raises eyebrows. But arts-based interventions—guided visualisations, drawing, painting, storytelling, reflection practices—aren’t luxuries. They work because they interrupt the efficiency mindset, create psychological safety, and make knowledge shareable in ways that pure information architecture can’t reach.

A facilitated drawing exercise doesn’t seem like “knowledge work.” But it’s creating the conditions where people actually think together instead of just exchanging information.

The Choice

You can treat AI as a threat to human work, and race to automate more. Or you can treat it as a signal: the human work matters now more than ever. Which means investing in the conditions that allow humans to create, think critically, and exercise sound judgement.

That investment starts with culture, not code. With people, not platforms. With how you design the rhythm and psychology of work itself.

Organisations that get this right won’t lose to AI. They’ll use it to do what it does—handle volume, pattern-match, optimise routine—while reclaiming the uniquely human work their people are actually capable of.

The question for your leadership team: Are the conditions in your organisation supporting human capacity, or eroding it?

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Why Your Knowledge Management Strategy Needs the Arts

(This post was originally shared on my LinkedIn Profile.)

Most knowledge management strategies focus on systems, processes, and technology. But what if the missing piece is a scribble drawing?

Knowledge Work Has a Creativity Problem

We have built our organisations around efficiency metrics and linear processes — get from A to B to C in the most direct line possible. But knowledge work does not actually work that way. It requires curiosity, reflection, and iteration. It demands that people make unexpected connections, ask uncomfortable questions, and see the bigger picture.

Those capacities are not switched on by yet another technology upgrade.

This is the premise of Radical Knowledge Management — a framework developed to bring creativity and arts-based interventions (ABIs) deliberately into KM practice. The definition of KM at the heart of this approach is broader than the traditional one: rather than merely connecting people to documented knowledge, it focuses on enabling people to find and create the knowledge they need to do their jobs — including through continuous learning and new ways of thinking.

What Are Arts-Based Interventions?

Arts-based interventions are activities that use an artistic medium or discipline to improve a process or situation. In organisational settings, the most common artistic modalities include drawing, painting, photography, theatre, music, poetry, improvisation, and storytelling.

These are not team-building novelties bolted on to the end of a strategy day. Used deliberately, they are instruments for culture change, innovation, leadership development, problem-solving, and organisational transformation.

There are at least twelve use cases for ABIs in organisations:

  1. Culture change
  2. Innovation
  3. Wellness
  4. Getting unstuck
  5. Sustainable leadership
  6. Team building
  7. Collaboration
  8. Problem-solving
  9. Amplifying learning
  10. Transformation
  11. Creating community
  12. Employee engagement

Because of the interconnected nature of these activities, focusing on ABIs for one use case tends to positively affect the others as well.

Why ABIs Belong Inside Your KM Strategy

There is a tendency to think of creativity as a bolt-on — something for design or marketing, or perhaps for the occasional off-site. The argument for placing ABIs firmly within KM rests on something more fundamental.

Knowledge is created by people. It is intangible, complex, and deeply social. In our increasingly volatile, uncertain, complex, and ambiguous (VUCA) world, the knowledge we most urgently need cannot be captured in a database. It lives in the capacity of people to think differently, collaborate across silos, and remain curious even under pressure.

ABIs directly support those capacities. They help people tap into skills and behaviours that formal education and career pressures have pushed into dormancy. They encourage people to get out of their comfort zones, see the bigger picture, and ask different questions. In doing so, they create new knowledge — and they shift organisational culture towards one that supports knowledge sharing rather than knowledge hoarding.

As Albert Einstein observed, imagination is more important than knowledge; knowledge is limited, whereas imagination embraces the entire world. Arts-based interventions are one of the most reliable ways to fuel imagination in the workplace.

The MAGIC-SH Framework

For organisations ready to take this seriously, the Radical KM framework provides a practical structure organised around the acronym MAGIC-SH:

S & H — Sustainable and Human. This is the foundation. ABIs make organisations more sustainable because they help people see the interconnectedness of things and develop sustainable leadership behaviours. They also reinforce the humanity of work — critical at a time when technology threatens to crowd out the very qualities that make people valuable.

The Nine Cs. The middle layer of the framework encompasses the concepts that ABIs develop and evolve:

  1. Creativity — producing novel ideas and approaches
  2. Collaboration — building the trust that makes real knowledge sharing possible
  3. Communication — developing empathy and purposeful expression (improv theatre is particularly powerful here)
  4. Content — shaping what knowledge is captured and how
  5. Critical thinking — challenging the “that’s how we’ve always done it” assumption
  6. Conversation — opening new avenues for dialogue and insight
  7. Culture — shifting the organisation towards one that values learning and sharing
  8. Confidence — building the self-belief to ask for help, try new approaches, and share imperfect knowledge
  9. Change management — supporting the cultural shift that ABIs require

A, G, I — ABIs, Ideas, Innovation and the Guerrilla approach. These represent both the outputs sought (fresh ideas and innovation) and the practical approach recommended: starting small, positioning ABIs as experiments, and growing support iteratively.

M — Metrics. Measurement comes last — not because it is unimportant, but because defining metrics too early can constrain the very creative exploration that makes ABIs valuable.

How to Start: Two Practical Pathways

There is no need to overhaul your entire KM programme. Radical KM explicitly recommends starting small and iterating.

The Icebreaker stream begins at the individual or team level with short, low-stakes activities: a guided visualisation at the start of a meeting, a scribble drawing exercise during a workshop, an improvisational warm-up before a strategy session. These take as little as five minutes, but they shift the energy and engagement in the room, build psychological safety, and begin to normalise the idea that creativity belongs at work.

The Studio stream takes a larger, more structured approach — dedicated sessions, longer interventions, and formal integration into KM processes such as knowledge capture workshops, after-action reviews, or communities of practice.

In both cases, the implementation approach is the same: treat it as an experiment, start with early adopters, debrief afterwards, and iterate based on what you learn. Change management is essential — people have often been educated to believe that the arts are wasteful, and that belief takes time and consistent experience to shift.

The Hardest Part

The biggest obstacle to incorporating ABIs into a KM strategy is not logistics. It is the stories we tell ourselves about why we cannot — or should not — do it. What will my colleagues think? Are the benefits really there? Is this really my job?

Those doubts are understandable. Most of us had our creativity criticised or ignored somewhere around adolescence, and we learned to put it away as unprofessional.

But look around your team. Someone is doodling during calls. Someone uses role-play to prepare for difficult conversations. Someone plays an icebreaker game at the start of team stand-ups. The arts and creativity are already finding their way into your workplace — unconsciously. Radical KM simply asks you to be more deliberate about it.

The first time you try a scribble drawing exercise in a knowledge management workshop, you may be pleasantly surprised. The energy and engagement in the room shifts. Responses become more thoughtful and detailed. People make connections they would not otherwise have made. The knowledge that flows is richer.

A Final Thought

In a world shaped by AI, automation, and relentless change, the knowledge and capabilities that most need managing are the human ones: curiosity, resilience, empathy, imagination, and the willingness to keep learning. Those are not developed by better taxonomy.

They are developed through practice — and arts-based interventions are one of the most evidence-supported ways to practise them.

Your KM strategy does not need an overhaul. It needs a scribble drawing, and the courage to see what happens next.

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The Answer to the Collaboration Crisis Isn’t Another Platform

(This post was originally shared on my LinkedIn Profile.)

Last week I wrote about the research evidence that our obsession with efficiency and technology has eroded the social capital, trust, and genuine collaboration that make organisations actually work. The response told me the article landed somewhere real.

But a diagnosis without a direction isn’t much use. So this week I want to talk about what I believe a genuine response looks like.

It isn’t another tool. It isn’t a workshop. It isn’t a culture deck with better values on it.

It’s a fundamentally different way of thinking about knowledge — one that starts with people rather than platforms, and with meaning rather than metrics.

What conventional KM gets wrong

Most knowledge management programmes are designed to solve an information problem. Information is scattered, so we build a repository. People can’t find what they need, so we improve search. Expertise walks out the door, so we create a capture process.

These are real problems. But they’re symptoms, not causes.

The actual problem — the one the research keeps pointing back to — is that the conditions for knowledge to flow have broken down. Trust has eroded. Networks have shrunk. Cross-boundary relationships have withered. The informal conversations that carry tacit knowledge, the collegial curiosity that generates new thinking, the relational safety that makes people willing to share what they actually know — all of it has been quietly deprioritised in the name of efficiency.

You cannot fix that with a better taxonomy.

A different starting point

Radical Knowledge Management — the framework I’ve been developing and practising for over a decade — begins from a different premise.

Knowledge is not content. Knowledge is human. It is created through experience, shaped by context, and moved through relationship. It lives in people, between people, and in the culture that connects them. Any KM strategy that doesn’t start there is working on the wrong problem.

Radical KM is built on what I call the MAGIC-SH model: seven conditions that together create an environment where knowledge genuinely flows, where people are willing to share what they know, and where organisations develop the kind of collective intelligence that no platform can replicate.

Those conditions are Meaning, Agency, Generosity, Inquiry, Community, Story, and Humanity.

Let me walk through why each one matters in the context of the collaboration crisis.

Meaning

People share knowledge willingly when they understand why it matters. Not because they’ve been told to fill in the knowledge base, but because they can see the connection between what they know, what others need, and the outcome they all care about.

Efficiency culture strips meaning out of work progressively. It reduces contribution to task completion and measures value in outputs. Radical KM inverts this — it starts by building shared understanding of purpose, so that knowledge-sharing becomes an act of contribution rather than compliance.

Agency

Knowledge hoarding is almost never malicious. It’s usually rational. In environments where expertise equals job security, where being the person who knows something is a form of power, people protect what they know.

Agency addresses this by designing for genuine autonomy and contribution. When people have real influence over how their knowledge is used and recognised, the incentive structure flips. Sharing becomes generative rather than threatening.

Generosity

Generous knowledge cultures don’t happen by accident. They are built through modelling, through recognition, and through the deliberate design of spaces — physical, virtual, and cultural — where people are expected and encouraged to give freely of what they know.

This is directly counter to the transactional logic that dominates most organisations, where knowledge exchange is a negotiation and every interaction has an implied cost-benefit calculation behind it.

Inquiry

The collapse of cross-boundary weak ties that the Microsoft research documented is, at its root, a collapse of curiosity. When people work only within their immediate team, they stop asking questions of the wider organisation. They stop being curious about what’s happening elsewhere, what others have learned, what problems are being solved in parallel.

Radical KM designs explicitly for inquiry — creating the conditions, the habits, and the structures that keep curiosity alive across organisational boundaries.

Community

This is where the research evidence and the framework converge most clearly. Social capital is not built through formal programmes. It is built through communities — genuine ones, where people gather around shared interests, shared challenges, or shared expertise, and where the relationships that form outlast any particular project or process.

Communities of practice, done well, are the single most powerful KM intervention available. Not because of the knowledge they capture, but because of the trust they generate.

Story

Data informs. Story moves. The knowledge that organisations most need to retain and transmit — the contextual, experiential, relational knowledge that can’t be fully codified — travels in narrative.

Story is also how culture is sustained and changed. The stories an organisation tells about itself, about what it values, about who its heroes are, shape what knowledge gets shared and what gets suppressed.

Humanity

This is the frame that holds everything else. Knowledge management that forgets it is working with human beings — with people who have emotions, relationships, histories, and needs — will always fall short of what’s possible.

Humanity in KM means designing for the whole person, not just the role. It means recognising that psychological safety is not a HR initiative; it’s a knowledge infrastructure issue. It means understanding that the reason knowledge walks out the door is almost always relational, not technical.

Why this matters now

The organisations that will navigate the next decade well are not the ones with the best AI tools or the most sophisticated knowledge repositories. They are the ones that have invested in the human conditions that make knowledge genuinely flow — trust, relationship, meaning, and community.

The collaboration crisis the research describes is real. But it is not inevitable, and it is not irreversible. What it requires is a different kind of intervention — one that takes human beings seriously as the infrastructure of organisational intelligence.

That’s what Radical Knowledge Management is designed to do.

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Your KM Problem Isn’t the Platform and AI isn’t going to fix it

(This post originally appeared on my LinkedIn Profile and received a lot of attention there, feel free to read the comments there.)

I’ve spent my entire career fighting the same battle.

Someone finds out I work in knowledge management, and within minutes the conversation has shifted to SharePoint, or Confluence, or whatever platform is currently being championed as “the solution.” These days, that platform increasingly has “AI-powered” somewhere in the marketing copy.

And I understand why. Technology is visible. It has a price tag, a vendor, a demo. You can point to it in a procurement document. Knowledge — the human, messy, relational kind — is much harder to put in a slide deck.

But here’s what two decades in KM have taught me: the platform is never the problem. And it’s never the solution either. Neither is the AI layer on top of it.

When a knowledge base goes stale three months after launch, that’s not a technology failure. It’s a culture failure. When frontline staff can’t find what they need in the moment of need, it’s usually not because the search function is broken — it’s because the knowledge was never captured in a way that reflects how those people actually think and work.

Now imagine pointing an AI at that same broken foundation. A large language model is extraordinarily good at generating fluent, confident-sounding responses. It is only as trustworthy as the content it draws from. Outdated articles, undocumented workarounds, tribal knowledge that never made it into the system, contradictory guidance left unresolved for years — AI doesn’t fix any of that. It amplifies it. Confidently.

This focus on people and relationships is the heart of Radical Knowledge Management.

Radical KM starts from a simple premise: knowledge lives in people, not systems. Systems can support its flow, but they cannot create it, sustain it, or replace the trust and relationships that make people willing to share what they know. If you haven’t invested in those human conditions first, you can implement the most sophisticated AI-powered platform on the market and still end up with an expensive, high-velocity misinformation engine.

Moving beyond “KM is a technology problem” requires three honest conversations most organisations are reluctant to have:

Who owns knowledge here — and who is excluded from that? Knowledge governance isn’t about permissions and taxonomies. It’s about power. Whose expertise is captured and valued, and whose is invisible? AI will simply encode and accelerate whatever answer your organisation has already given to that question.

What does your culture reward? If people are measured on individual output and knowledge-sharing is an afterthought, no tool will change that — and no AI will surface knowledge that was never shared in the first place.

What does “good” actually look like for the people doing the work? Not for leadership. Not for auditors. For the person answering their fifteenth call of the day, under pressure, needing to find an accurate answer quickly. AI can be a powerful ally for that person — but only if the knowledge behind it has been curated with their reality in mind.

Technology has an important role. I’ve spent considerable time helping organisations choose and implement platforms, assess readiness, and design governance frameworks. The tools matter. AI genuinely matters. But they’re the last conversation, not the first.

The first conversation is about people. What they know, how they share it, whether they feel safe doing so, and whether the organisation has created the conditions for knowledge to actually flow.

Until we’re willing to have that conversation — really have it — we’ll keep buying new platforms, adding AI on top, and wondering why nothing changes.

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Your Organisation Is Losing Its Most Valuable Knowledge — And You’re Looking in the Wrong Place

(This post was originally posted on my LinkedIn Profile.)

Most knowledge management programmes are built on a flawed assumption: that the knowledge worth capturing is the kind you can write down.

Databases. Repositories. Best practice libraries. Lessons learned registers. These are the tools we reach for, and they are not without value. But they systematically leave behind the knowledge that organisations need most — the tacit, relational, embodied, and culturally embedded knowledge that lives in people’s instincts, their ways of seeing, their ability to navigate ambiguity. And when those people leave, retire, or burn out, that knowledge goes with them.

I have spent years pulling at the thread of what it would take to build a genuinely different approach to knowledge management — one that takes seriously the full range of what humans know, not just the fraction that fits into a text field. The review of 70+ research studies that have been sitting on my hard drive has strengthened my conviction that the answer lies somewhere most KM practitioners have not looked: in the arts, in creativity, and in a fundamental rethinking of what knowledge really is.

Creativity Is Not a KM Output. It Is a KM Process.

Most frameworks treat creativity as something that knowledge enables — invest in KM, and innovation follows. The research suggests the inverse is equally true, and arguably more important: creative processes are themselves a primary mechanism for knowledge creation.

This is not a semantic distinction. It has structural implications. If creativity is a core KM process — not a downstream benefit — then knowledge management systems need to be architected around enabling creative application, not just knowledge access and storage.

The practical implication is this: your knowledge management programme will never perform to its potential if it optimises for retrieval while neglecting creation. Knowledge that is shared but not creatively applied circulates without transforming. It becomes organisational wallpaper.

What Neuroscience Is Telling Us About How Knowledge Is Actually Formed

Here is something that does not appear in most KM strategy documents: arts engagement simultaneously activates multiple brain systems — sensory, emotional, memory, and social — that purely linguistic knowledge exchange does not reach.

This is not a soft claim. It is a structural argument, supported by neuroscience research, for why arts-based processes generate different and richer knowledge than text-based alternatives. When we design knowledge processes that engage multiple sensory modalities — visual, auditory, kinaesthetic, tactile — we enhance memory formation, creative connection, and knowledge retention in ways that a well-formatted document simply cannot replicate.

The corollary is equally important: the knowledge that organisations most need to preserve and transfer — what experienced practitioners know through gesture, spatial sense, physical practice, and professional intuition — is precisely the knowledge that conventional KM systems are structurally unable to capture.

The Knowledge Your Organisation Cannot Afford to Keep Losing

Research by Root-Bernstein on Nobel laureates and highly innovative scientists reveals a striking pattern: artistic avocation and scientific or organisational innovation are strongly linked. This is not biographical curiosity. It points to something structural about cognition: the moves developed through artistic practice — observation, pattern recognition, aesthetic discrimination, creative synthesis — transfer directly into knowledge work and produce measurably better outcomes.

Meanwhile, a landmark meta-analysis of 268 publications and 205 documented cases of arts-based interventions in organisations identified 393 distinct positive outcomes. These were not soft or anecdotal: they mapped directly onto what we recognise as KM objectives — improved collaboration, enhanced sense-making, stronger learning cultures, greater capacity to navigate complexity.

The evidence base for arts-informed approaches to knowledge management is substantial. What has been missing is a methodology that makes it organisationally accessible.

The Problem with How We Measure Creativity

One of the most consistent findings in the creativity measurement literature is that organisations damage creative performance by applying innovation metrics to creative processes. The two modes require fundamentally different conditions, incentives, and approaches to evaluation.

The most common way organisations kill creativity is by applying business-case logic too early. Ideation phases — genuinely exploratory, divergent, high tolerance for ambiguity — need to be protected from premature evaluative pressure. This is not a cultural nicety. It is a design requirement.

The research recommends measuring creative process quality alongside outputs: psychological safety levels, diversity of perspectives in dialogue, quality of questioning, willingness to challenge assumptions. And it argues for tracking disposition indicators as leading measures — curiosity, comfort with ambiguity, eagerness to explore — because these predict creative output better than measuring outputs directly.

This is a genuinely different logic from most organisational measurement frameworks, and it matters because the wrong measurement approach actively undermines the thing you are trying to build.

The Rise of AI Makes This More Urgent, Not Less

Two threads in the research address the AI question directly, and both arrive at the same place: the risk is not competition between human and artificial intelligence. The risk is substitution — outsourcing creative processes to AI in ways that reduce human engagement in precisely the activities that generate authentic knowledge and genuine human connection.

The knowledge created through creative, arts-informed processes carries something that AI-assisted processes cannot replicate: the self-disclosure and authentic engagement of human beings working through complexity together. This is not sentimentality. It is a functional argument for why relational knowledge — the kind created in the interspace between people — remains irreducibly human, and why protecting it matters more as AI becomes more capable, not less.

AI belongs in knowledge management as infrastructure: search, synthesis, organisation. Human creative engagement belongs at the centre, not as a nice-to-have, but as the core activity that makes the rest of it worth doing.

What This Means for How Organisations Should Approach KM

The research points to several structural changes that would make a genuine difference.

Organisations need to create what researchers call interspaces — protected environments, physical and psychological, where conventional organisational norms are temporarily suspended so that genuinely different knowledge can emerge. The arts are particularly effective at creating these spaces because they carry cultural permission for experimentation and ambiguity that normal business contexts do not. But the research is clear that an interspace only delivers KM value if insights flow back into mainstream practice. The re-integration pathway matters as much as the creative space itself.

Demographic diversity is necessary but not sufficient. What the research points to is cognitive diversity — different thinking modes, expertise domains, and problem-solving approaches — as the primary driver of creative knowledge work. The research from Unilever’s innovation practice establishes this as the primary predictor of creative problem-solving performance. And it requires facilitation processes designed to harness the productive friction of different perspectives, rather than suppressing it in the name of social comfort.

Knowledge management needs to be framed as a wellbeing and human development practice, not merely an efficiency tool. The neuroscience literature establishes that arts engagement generates measurable benefits to stress resilience, emotional regulation, and cognitive flexibility — all of which directly affect the quality of knowledge work over time. Organisations that attend to the human experience of knowledge work generate more and better knowledge. This is not a values claim. It is a performance claim.

A Different Kind of Knowledge Management is not just Possible. It Is Necessary.

We are asking our organisations to navigate a world of genuine complexity — technological disruption, demographic change, shifting social expectations, and wicked problems that do not yield to standard playbooks. The knowledge management frameworks we inherited from the 1990s were designed for a different world. They optimised for efficiency, standardisation, and explicit knowledge. They have served their purpose.

What we need now is a methodology that takes seriously the full spectrum of what human beings know — including the knowledge that lives in the body, in relationships, in aesthetic sensibility, in the capacity to sit with ambiguity long enough to generate something genuinely new.

That is what Radical Knowledge Management is designed to do.

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Radical KM Institute Announcement

There are now three courses/programs available on the RadicalKM.Institute website.

The White Belt course has been available since earlier this year (February 2024), and is an introduction to Radical KM, it is free. You can find out about it here.

The Green Belt course has just been released (November 2024). It takes Radical KM a step further, with more complex ideas about implementing/using Radical KM. The course includes videos and other supplemental information. You can find out about it here.

Finally, an comprehensive program including 1:1 coaching. This program is designed to complete the Radical KM picture and help knowledge managers implement Radical KM in their organisation by providing in depth Radical KM knowledge and 1:1 coaching. You can check it out here.

As always, if you have any questions, feel free to get in touch, I’m always happy to talk. You can book a time with me here.

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Creating a knowledge sharing culture

Are you wondering how to create a culture more conducive to knowledge sharing, collaboration, innovation, trust, and respect?

Radical Knowledge Management will do that for you.

Implementing Radical KM addresses a whole host of challenges being face in organisations and really is the silver bullet it appears to be.

ProblemSymptomArts-based Solutions
Uncertainty and exaggerated sense of urgency▸ People are stressed, worried, overwhelmed▸ Support mental health and well-being
▸ Creating space for reflection
No sense of purpose/meaning▸ Disengagement
▸ Connections have been broken
▸ No sense of belonging
▸ No empathy and compassion		▸ Build teams, connections, engagement
▸ Build a sense of belonging
▸ Build/develop empathy and compassion for self and others
Lack of Agency▸ Don’t know what they want, what they can do, what is possible
▸ People starting to think like AI/ computers		▸ Build sense of purpose and meaning, big picture
▸ Create/develop agency
Lack of critical thinking▸ Don’t know who/what to believe
▸ Lack of curiosity and creative problem solving		▸ Critical thinking to discern what is real and what is fake
▸ Support trial and error, and iteration

You can check out my recent ReWorked column for more information or watch this webinar I did with KMI.

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Radical KM Workshop Feedback

I was recently asked to help a university class that was working on a module entitled, “creating, managing and using knowledge in organisations”. The instructor is someone in my network who wanted her students to learn about Radical KM. Due to technical reasons it wasn’t possible for me to lead the session live.

The students watched a recording of a webinar I did about Radical KM and then the instructor lead them through the workshop that I had prepared and sent her. What follows is the email I received back with the classes comments and reflection on the session. I have removed any identifying information for privacy, otherwise what follows is a straight cut and paste.

Hi Stephanie,

I hope this message finds you well. 

On behalf of the class, I just wanted to express our gratitude for preparing today’s workshop. It was a refreshing change for us, and everyone had a lot of fun. I just thought I would summarise our thoughts below:

As in your video seminar, beginning with the flower meditation served as a way to concentrate our focus on the workshop, and allowed us to clear our minds of any other conflicting thoughts. For me, doing this meditation with the class as opposed to on my own, forced me to concentrate more on my flower. However, the collective energy in the room definitely improved since we had all engaged in the same activity to start our day. Some individuals in the class visualised imagery in relation to flowers in their garden or that they had bought as part of a bouquet, linking the meditation to everyday life.

We chose to build a business case for arts-based practices within a law firm, specifically pitching to senior management. In our initial discussion, we decided that this case should be presented by a dedicated KM team, ensuring robust evidence to back up the importance of arts-based practices. We also discussed issues surrounding the use of language like ‘radical’ and ‘creative’, and concluded that the best interests of the law firm should be the primary goal (i.e. billable hours).

The first scribble drawing exercise left us feeling chaotic, energised, surprised and stressed at points. Our stream of consciousness writing exercise following provided an opportunity for us to document our feelings in the moment. For myself, I found that each new scribble drawing that landed in front of me was not what I was expecting. It was very interesting to see how each member of the class interpreted the scribble drawings differently.

Reflecting on this, our following discussion on our business case centred on the benefits of arts-based practices for relaxation, fresh perspectives and taking a break for logical thinking. We added to our business case suggesting that implementing these practices in a law firm would allow for more contribution, an improvement in culture and employees feeling more present. We decided that these practices should be started in a trial so that Senior Management have the opportunity to see how they would fit with practicing law.

The major theme that emerged was nostalgia. It seems that the freedom of a blank piece of paper and an abundance of colouring materials sparked memories of an incredibly tangible time in our lives. I found myself wanting to be very logical with my second scribble. I wanted to make sure that I could definitely fill the page in 5 minutes by choosing the most appropriate pattern – making sure I didn’t run out of time. I am a very logical person when it comes to problem solving so this exercise has prompted me to try and take more creative and abstract approaches in the future.

Our last discussion on our business case led us to decide that Senior Management would just have to try a meditation or scribble method to reveal the true benefits. In our case we would argue that these methods are appropriate as they do not require preparation, promote child-like energy, provide a step away from work and offer personalisation. This way, management could trust that each individual in the organisation is empowered to take arts-based practices and customise it to their needs.

Overall, the class found this a great exercise to implement some of the other ideas we have discussed throughout the semester and truly see them in practice. This was a very insightful an enriching workshop, thanks again!

Kind regards,