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What sort of KM challenges are you facing at work?

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How have you gamified learning and knowledge sharing in your org?

"I keep hearing AI is going to take over everything — even Knowledge Management. Should we be worried?”

The fact of the matter is not at all. AI isn’t here to replace us; it’s here to make us more effective. Think of it as an extra hand that helps us do KM smarter, faster, and with greater impact.”

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Check out the article at the link above.

What do you think? Is (blog author) Ekta Sachania right?

Introduction to Radical Knowledge Management for KM Practitioners

What Is Radical Knowledge Management?

Radical Knowledge Management (Radical KM) represents a fundamental shift from traditional knowledge management approaches. Whilst conventional KM focuses primarily on capturing, storing, and sharing explicit knowledge through databases and documentation systems, Radical KM goes back to the "roots" (the historical meaning of "radical") of how humans actually learn: through play, creativity, and artistic expression.

This approach recognises that in our volatile, uncertain, complex, and ambiguous (VUCA) world, storing knowledge is insufficient. Instead, we need to foster continuous knowledge creation, innovation, and adaptive thinking capabilities within our organisations.

Core Principles

Human-Centred Approach: Radical KM acknowledges that knowledge workers are humans, not machines. It prioritises human needs for reflection, creativity, and meaningful connection in knowledge processes.

Arts-Based Interventions (ABIs): The methodology integrates creative activities—from simple five-minute scribble drawings to multi-day collaborative art projects—into knowledge management practices to stimulate different types of thinking.

Diffuse and Focused Thinking Balance: Drawing on neuroscience research, Radical KM creates space for both analytical problem-solving and the wandering, connective thinking that generates innovation.

Sustainability Mindset: The approach develops behaviours that support long-term thinking, systems awareness, and sustainable decision-making across organisations.

Why Now?

Traditional KM emerged when knowledge was more stable and change occurred more slowly. Today's knowledge workers face:

• Information overload and rapid obsolescence of explicit knowledge
• Increasing automation of routine cognitive tasks
• Growing need for creativity, critical thinking, and emotional intelligence
• Remote and hybrid work environments that challenge traditional knowledge-sharing methods
• Rising employee burnout and disengagement

Radical KM addresses these challenges by reactivating human capabilities that have been "educated out" of many professionals in favour of purely analytical approaches.

Practical Implementation

Tactical Interventions: Quick creative activities (5-10 minutes) that can be integrated into regular meetings as energisers or perspective-shifters.

Studio Interventions: Longer creative sessions designed for strategy development, problem-solving, or team building.

Cultural Integration: Systematic introduction of creative practices to build knowledge-sharing culture, psychological safety, and collaborative problem-solving capabilities.

Evidence Base

The approach draws on:

• Neuroscience research demonstrating how arts engagement affects brain plasticity and cognitive flexibility
• Organisational studies showing improved innovation, engagement, and collaboration through creative interventions
• Learning science indicating that creative activities enhance executive function and knowledge retention

Getting Started

For KM practitioners interested in exploring Radical KM:

1. Start small: Try simple creative icebreakers in team meetings
2. Build support: Work with early adopters and curious team members
3. Document outcomes: Track both quantitative metrics and qualitative feedback
4. Scale gradually: Expand from tactical activities to strategic interventions as comfort and evidence grow

Addressing Concerns

Professional scepticism: Frame activities as business tools for improved thinking and collaboration, not as "art for art's sake"

Time constraints: Emphasise that creative activities often increase rather than decrease efficiency by improving focus and generating better ideas

Cultural resistance: Start with willing participants and let positive outcomes speak for themselves

The Bigger Picture

Radical KM isn't about replacing traditional knowledge management practices but enriching them. It provides tools for the aspects of knowledge work that databases and documentation cannot address: fostering innovation, building relationships, developing resilience, and creating the cultural conditions where knowledge naturally flows and grows.

In an era where artificial intelligence handles increasing amounts of routine information processing, Radical KM helps organisations develop the distinctly human capabilities that remain irreplaceable: creativity, empathy, complex problem-solving, and adaptive learning.

For knowledge management practitioners, this represents both an opportunity and a responsibility to help their organisations not just manage existing knowledge more effectively, but to become more capable of creating the knowledge they'll need for an uncertain future.

I've noticed a trend throughout my career: the KM solutions that were most effective were built quickly, informally, and in response to immediate frustration. Official solutions are built for idealized workflows. Unofficial solutions are built for actual human behavior.

How do you capture the agility of "unofficial" solutions within official KM programs?

1. What unofficial knowledge sharing works better in your organization than your official system?
2. How do you test whether your official KM matches how people really work?
3. When should you formalize unofficial solutions vs. leave them alone?
4. How do you build KM systems that adapt to real behavior instead of ideal behavior?

I'd love to hear your experience.

At Hallmark, our Senior Support had 15 years of brand knowledge in her head. When she announced her retirement, we had 6 weeks to capture what made her 'just know' which concepts would work. Here's what failed, what worked, and the brutal reality about tacit knowledge capture.

Most approaches to capturing tacit knowledge fail because we treat it like explicit information. You can't just interview someone and expect to get the intuitive decisions that come from years of pattern recognition.

What Actually Worked:

• Shadowing during real decision-making (not retrospective interviews) - I recorded her rejecting concepts in real-time, capturing her immediate reactions
• Real-time explanation while working - Having her talk through live problems revealed the "why" behind her instincts
• Creating decision trees from her actual rejections, not just approvals - The "nos" taught us more than the "yeses"

The research backs this up. As one practitioner notes, when experts just observe without explaining, "there is only so much a person can glean when watching someone write or read on their computer." But when they explain everything in real-time, you capture the mental models that make their expertise valuable. Some people don't share specialized knowledge because they see it as job security.

Questions for you:

1. What's the most critical tacit knowledge in your organization that's at risk?
2. Have you tried knowledge capture interviews? What did you miss?
3. How do you identify tacit knowledge before the person leaves?
4. How do you overcome the "knowledge hoarding" mentality?

The attached article shows some exceptional ways to capture knowledge. It dives into advanced strategies with practical techniques like video-to-text transcription, real-time shadowing, and podcast-style knowledge capture.

Execs care about money and results. This article gives some best practices for pitching KM:

• Start with the current state: Show what things were like before. Think onboarding time, call handling time, and rework rates. Track relevant metrics regularly.
• Be clear on goals: Use SMART goals in plain English. Examples: cut support training from 12 to 9 weeks by Q2; reduce double R&D work by 15% in 18 months; boost NPS by 5 points in a year.
• Show results, not activities: Activities are busy work; results get us money. Examples: fewer calls, quicker calls, faster projects, less turnover, faster money.
• Talk to stakeholders: CFOs: Cost savings. Sales: Conversions and quotes. HR: Onboarding speed and retention. Operations: Mistakes and time.

Example: We cut call handling time by a minute across 9,000 calls, saving 150 agent hours, by making articles easier to find.

Now, I'd love to hear your stories:

1. What good KM results have you seen?
2. What baseline metrics did you use and why?
3. What dollar amount can you put on KM's impact?
4. What didn't work with leaders, and what did?

KMI is pleased to announce our newest e-learning course launching mid-September. The self-paced course is based on the popular live/virtual class co-hosted by KMI partner Enterprise Knowledge, LLC.

Includes:

10 hours of content and online materials

KM Foundation online program (for new students)

Interactive e-modules and bonus material

The (original) Taxonomy Design e-learning course - free!

New info is being added soon, but you can visit the Business Taxonomy & Ontology (class) page above for details on the course.

Intro video: https://www.youtube.com/watch?v=XB1PfRtfelg

Email: training@kminstitute.org to be added to our 'interested' list. Early quotes are available too. We're here to help!

Last Fall, we produced a new (short video) series on the AI and KM Connection with KMI Instructor (and a driving force behind the connection) Rooven Pakkiri.

The series was very well received by our global audience, so I thought we'd share it again here.

Click the link for the 3-part Series (plus Intro)...