Chapter 10: Knowledge Conversion
Learning Objectives
After completing this chapter, you will be able to:
- Explain the SECI model and apply it to knowledge conversion initiatives
- Design mentoring and apprenticeship programs that facilitate knowledge transfer
- Conduct effective knowledge interviews that elicit tacit expertise
- Facilitate documentation workshops that convert collective tacit knowledge into explicit assets
- Use storytelling techniques to capture and transfer experiential knowledge
- Identify when tacit knowledge should remain tacit versus be made explicit
- Implement organizational practices that support continuous knowledge conversion
- Apply appropriate technologies to support each mode of knowledge conversion
- Design quality processes for knowledge codification and validation
Introduction
Tacit knowledge - the expertise, judgment, intuition, and skills that reside in people’s minds - represents some of an organization’s most valuable intellectual capital. Unlike explicit knowledge that can be easily documented and shared, tacit knowledge is deeply personal, context-dependent, and difficult to articulate. Yet this is precisely the knowledge that distinguishes expert performance from novice competence.
Converting tacit knowledge to explicit knowledge is one of the most challenging and valuable activities in knowledge management. This conversion makes expertise visible, transferable, and sustainable beyond individual experts. It enables organizations to preserve critical knowledge when experts leave, accelerate learning for newcomers, standardize best practices, and scale expertise across the organization.
However, not all tacit knowledge can or should be made explicit. Some knowledge is inherently tacit and is best transferred through experience, observation, and practice. The art of knowledge conversion lies in identifying which tacit knowledge to target for conversion and applying appropriate techniques to capture and codify it effectively.
This chapter explores the SECI model of knowledge conversion and provides practical techniques for implementing each mode. We will examine socialization practices, externalization methods, combination approaches, and internalization strategies. The chapter also addresses quality standards for knowledge codification and the technologies that support effective conversion processes.
Understanding Tacit Knowledge
Characteristics of Tacit Knowledge
Tacit knowledge has several distinguishing characteristics that make it challenging yet valuable:
| Characteristic | Description | Example |
|---|---|---|
| Personal | Rooted in individual experience and perspective | A senior developer’s intuition about code quality |
| Context-Dependent | Tied to specific situations and environments | Knowing when to escalate vs. investigate further |
| Difficult to Articulate | Hard to express in words or formal language | The ability to diagnose system issues from subtle patterns |
| Action-Oriented | Manifests in skillful performance | Expert troubleshooting or negotiation skills |
| Experience-Based | Accumulated through practice and reflection | Understanding organizational politics and culture |
| Unconscious Competence | Applied automatically without conscious thought | Expert pattern recognition in familiar domains |
Types of Tacit Knowledge
Different types of tacit knowledge require different conversion approaches:
Technical Skills: Physical or cognitive abilities developed through practice (e.g., debugging complex code, diagnosing equipment failures, performing surgical procedures).
Cognitive Skills: Mental models, frameworks, and judgment used in problem-solving (e.g., strategic thinking, design intuition, risk assessment).
Social Knowledge: Understanding of relationships, culture, and interpersonal dynamics (e.g., navigating organizational politics, customer relationship management, team dynamics).
Contextual Knowledge: Understanding of specific situations, history, and environmental factors (e.g., why certain decisions were made, organizational culture nuances, industry-specific context).
Heuristics: Rules of thumb and shortcuts developed through experience (e.g., “When X happens, check Y first,” “This type of customer typically needs Z”).
The SECI Model
Four Modes of Knowledge Conversion
Ikujiro Nonaka’s SECI model describes four modes of knowledge conversion that create a dynamic knowledge spiral. This model is central to understanding how organizations create and amplify knowledge through continuous conversion between tacit and explicit forms.
Socialization (Tacit to Tacit)
Sharing tacit knowledge through shared experience, observation, and practice.
Mechanisms:
- Apprenticeships and mentoring
- Job shadowing and observation
- Collaborative work and communities
- Face-to-face meetings and informal conversations
- On-the-job training
Example: A junior engineer learns troubleshooting techniques by working alongside a senior engineer on actual incidents.
Externalization (Tacit to Explicit)
Articulating tacit knowledge into explicit concepts, models, and documents.
Mechanisms:
- Interviews and dialogues
- Metaphors and analogies
- Documentation workshops
- Storytelling and narratives
- Reflection and after-action reviews
Example: Capturing an expert’s diagnostic process as a documented decision tree or troubleshooting guide.
Combination (Explicit to Explicit)
Combining different bodies of explicit knowledge into new configurations.
Mechanisms:
- Analyzing and synthesizing documents
- Creating summaries and reports
- Database queries and data analysis
- Integrating knowledge from multiple sources
- Organizing and categorizing content
Example: Creating a comprehensive best practices guide by synthesizing lessons learned reports from multiple projects.
Internalization (Explicit to Tacit)
Absorbing explicit knowledge and converting it into tacit knowledge through practice and experience.
Mechanisms:
- Learning by doing
- Simulation and practice exercises
- Reading and studying documentation
- Experimentation and trial
- Reflection on documented experiences
Example: A new team member studies process documentation and, through repeated practice, develops intuitive mastery of the process.
The Knowledge Spiral
These four modes work together in a continuous spiral:
Socialization → Externalization
↑ ↓
Internalization ← Combination
Knowledge is created and amplified as it moves through these modes. An individual’s tacit knowledge becomes explicit through externalization, is combined with other explicit knowledge, is internalized by others who develop their own tacit understanding, which is then shared through socialization, and the cycle continues.
Strategic Implications:
- Organizations should facilitate all four modes, not just externalization
- Knowledge creation is a continuous, dynamic process
- Personal interaction and experience remain essential even in explicit knowledge systems
- Technology should support the entire spiral, not just explicit knowledge storage
- Investment is needed in creating spaces and opportunities for each mode to occur
SECI in Practice
Socialization Techniques
Socialization transfers tacit knowledge through shared experience without explicit articulation. Organizations can systematically enable socialization through:
Communities of Practice
Informal groups that share a passion for a domain and learn together through regular interaction.
Implementation:
- Identify natural communities around shared domains
- Provide meeting space and time for regular gatherings
- Support community coordinators who facilitate discussions
- Enable both face-to-face and virtual interactions
- Recognize community participation as legitimate work
Example: A community of database administrators who meet monthly to discuss challenging problems, emerging technologies, and innovative solutions. Members develop tacit understanding of database optimization through sharing war stories and discussing approaches.
Pair Programming and Collaborative Work
Two people working together on the same task, enabling continuous knowledge transfer.
Benefits:
- Real-time transfer of techniques and approaches
- Immediate feedback and correction
- Development of shared mental models
- Natural knowledge flow without formal documentation
Example: Senior and junior developers pair on complex code modules. The junior developer observes expert problem-solving approaches, coding standards, and debugging techniques in action.
Job Rotation Programs
Moving people through different roles or departments to build broad tacit understanding.
Structure:
- 3-6 month rotations across related roles
- Structured handoffs and knowledge transfer
- Reflection periods to consolidate learning
- Debriefs to capture insights from cross-functional experience
Example: IT support staff rotating through application support, infrastructure, and security teams to develop holistic understanding of the IT environment.
Knowledge Cafes and Brown Bag Sessions
Informal knowledge sharing sessions over lunch or coffee where experts share experiences.
Format:
- Voluntary attendance
- Conversational rather than presentational
- Focus on questions and discussion
- Stories and experiences rather than formal content
Example: Weekly lunch sessions where senior engineers share their experiences with specific technologies, lessons from failed projects, or approaches to difficult customer situations.
Externalization Techniques
Externalization articulates tacit knowledge into explicit form, making it visible and shareable.
Critical Incident Technique
Systematically capturing decisions and reasoning from significant events.
Process:
- Identify critical incident requiring expertise
- Interview expert about their reasoning and decisions
- Probe for cues, assessments, and alternatives considered
- Document decision logic and contextual factors
- Review with expert for accuracy
Output: Decision trees, diagnostic guides, or case studies
Example: Capturing how a security expert identified and responded to a sophisticated cyber attack, including the subtle indicators they noticed and the reasoning behind their containment strategy.
Metaphor and Analogy Development
Using comparisons to communicate complex concepts in accessible ways.
Technique:
- Ask experts to explain their domain “like explaining to a child”
- Identify natural metaphors experts use in conversation
- Develop visual metaphors that capture key relationships
- Test metaphors with novices for comprehension
Example: Network security expert describes firewall rules as “border guards who check passports” - making abstract security concepts concrete and understandable.
Video Capture of Expert Performance
Recording experts performing tasks while narrating their thinking.
Method:
- Expert performs task while thinking aloud
- Camera captures both actions and screen (for technical work)
- Expert explains decisions, cues, and reasoning
- Post-production adds annotations and timestamps
- Video becomes training and reference resource
Example: Capturing database performance tuning where expert explains what metrics they examine, what patterns indicate specific problems, and their optimization strategies.
Think-Aloud Protocols
Experts verbalize their thought process while performing tasks.
Application:
- Expert works through real or simulated task
- Continuously narrates observations, thoughts, and decisions
- Facilitator probes for clarification without disrupting flow
- Recording captures complete cognitive process
- Transcript analyzed for decision patterns and expertise
Example: System architect verbalizing their design thinking while creating application architecture, revealing how they balance competing requirements and apply design principles.
Combination Techniques
Combination integrates multiple sources of explicit knowledge into more comprehensive or refined knowledge.
Knowledge Synthesis Projects
Systematically reviewing and integrating knowledge from multiple sources.
Process:
- Define synthesis scope and objectives
- Identify relevant knowledge sources
- Extract key insights, patterns, and contradictions
- Integrate into coherent framework or model
- Validate with subject matter experts
- Publish comprehensive resource
Example: Creating enterprise cloud migration playbook by synthesizing lessons learned from 20 migration projects, vendor best practices, industry frameworks, and research literature.
Cross-Project Learning Reviews
Comparing similar projects to identify patterns and best practices.
Approach:
- Gather lessons learned from multiple projects
- Compare successes and failures
- Identify common success factors and risk patterns
- Extract generalizable practices and guidelines
- Create best practice guide incorporating cross-project insights
Example: Analyzing 15 system integration projects to identify the factors that consistently predict success or failure, resulting in an integration best practices guide.
Knowledge Mapping and Gap Analysis
Identifying what knowledge exists and what is missing.
Steps:
- Map existing knowledge assets by topic and type
- Identify gaps where knowledge is needed but missing
- Prioritize gaps by business impact
- Assign responsibility for filling critical gaps
- Track progress in knowledge coverage
Example: Mapping all documentation for a major application and discovering critical gaps in troubleshooting guides, leading to targeted documentation projects.
Content Curation and Organization
Selecting, organizing, and maintaining collections of explicit knowledge.
Activities:
- Review and select quality content
- Remove outdated or redundant information
- Organize content by user needs and tasks
- Create pathways through complex information
- Maintain and update regularly
Example: Curator reviews 500 knowledge articles about email system, retires 150 outdated articles, consolidates 100 redundant ones, and reorganizes remainder into task-based categories.
Internalization Techniques
Internalization converts explicit knowledge into tacit understanding through practice and experience.
Structured On-the-Job Learning
Combining documentation study with guided practice.
Framework:
- Study explicit knowledge (procedures, cases, examples)
- Observe expert demonstration
- Perform task with expert coaching
- Practice independently with feedback
- Reflect on experience and refine understanding
- Teach others (deepest internalization)
Example: New support analyst studies incident management procedures, shadows experienced analyst, handles incidents with coaching, takes full ownership of incidents, reflects on patterns, and mentors next new analyst.
Simulation and Scenario-Based Training
Creating safe practice environments for skill development.
Types:
- Computer-based simulations of technical environments
- Role-play scenarios for customer interactions
- Tabletop exercises for crisis response
- Case-based learning with discussion
- Virtual labs for hands-on practice
Example: Incident response team practices handling security breaches in simulated environment, developing tacit understanding of coordination, communication, and technical response.
Reflective Practice Protocols
Structured reflection to deepen learning from experience.
Techniques:
- After-action reviews following significant events
- Learning journals documenting experiences and insights
- Peer debriefs discussing approaches and outcomes
- Video review of own performance with expert feedback
- Retrospective analysis of decisions and results
Example: Project managers maintain learning journals throughout projects, noting what worked well, what didn’t, and why. Quarterly reviews with senior PM identify patterns and refine personal project management approach.
Progressive Complexity Pathways
Designing learning paths from simple to complex tasks.
Design Principles:
- Start with simplified, structured tasks
- Gradually increase complexity and ambiguity
- Remove scaffolding as competence develops
- Provide feedback at each stage
- Allow repetition to build automaticity
Example: New developers start with bug fixes in well-structured code, progress to feature enhancements, then to new module development, and eventually to architectural design - each stage building tacit understanding of system design.
SECI Techniques Matrix
The following matrix provides a comprehensive reference for selecting appropriate techniques for each mode of knowledge conversion:
| SECI Mode | Primary Techniques | Supporting Practices | Expected Outcomes |
|---|---|---|---|
| Socialization | Mentoring, apprenticeship, job shadowing, pair programming | Communities of practice, knowledge cafes, rotation programs | Tacit-to-tacit transfer, shared mental models, cultural understanding |
| Externalization | Expert interviews, think-aloud protocols, documentation workshops, storytelling | Critical incident technique, metaphor development, video capture, facilitated dialogue | Documented procedures, decision guides, case libraries, best practices |
| Combination | Knowledge synthesis, content curation, cross-project analysis, data mining | Knowledge mapping, gap analysis, literature reviews, integration projects | Comprehensive guides, integrated frameworks, consolidated best practices |
| Internalization | Practice exercises, simulations, case studies, reflective learning | Structured OJT, progressive complexity, mentored application, learning journals | Skill development, intuitive understanding, expert performance |
Mentoring and Apprenticeship
Structured Mentoring Programs
Mentoring is one of the most effective mechanisms for transferring tacit knowledge:
Program Design Elements:
| Element | Description | Best Practices |
|---|---|---|
| Objectives | Clear goals for knowledge transfer | Define specific skills, knowledge areas, or capabilities to transfer |
| Matching | Pairing mentors and mentees | Consider expertise, learning needs, personality, and availability |
| Structure | Framework for interactions | Regular meetings, defined duration, topics to cover |
| Activities | Types of knowledge transfer activities | Observation, guided practice, reflection, discussions |
| Support | Resources and facilitation | Training for mentors, templates, facilitation, monitoring |
| Evaluation | Assessing effectiveness | Feedback, skill assessment, knowledge retention |
Mentoring Activities for Knowledge Transfer:
- Observation: Mentee observes mentor performing tasks or handling situations
- Guided Practice: Mentee performs tasks with mentor guidance and feedback
- Reflection Discussions: Mentor and mentee discuss experiences, decisions, and reasoning
- Problem-Solving Sessions: Working through challenges together
- Scenario Analysis: Discussing hypothetical situations and approaches
- Knowledge Documentation: Collaboratively documenting key insights and practices
Apprenticeship Models
Structured apprenticeships provide immersive learning experiences:
Cognitive Apprenticeship Approach:
- Modeling: Expert demonstrates the task while making thinking visible through narration
- Coaching: Expert observes learner and provides guidance, feedback, and support
- Scaffolding: Temporary support structures that are gradually removed as competence increases
- Articulation: Learner explains their reasoning and approach
- Reflection: Comparing learner’s performance with expert performance
- Exploration: Learner tackles new problems independently with expert support available
Knowledge Transfer Mechanisms in Apprenticeship:
- Repeated observation of expert performance in diverse situations
- Hands-on practice with immediate feedback
- Progressive complexity as skills develop
- Cultural immersion in professional practices and norms
- Development of professional identity and tacit understanding
Knowledge Interviews and Elicitation
Expert Interview Techniques
Specialized interview techniques elicit tacit knowledge that experts may not consciously recognize:
Critical Decision Method
Focuses on specific incidents where expertise made a difference:
- Incident Selection: Expert identifies a challenging, non-routine incident
- Incident Narrative: Expert describes what happened chronologically
- Timeline Construction: Create a timeline of key events and decisions
- Deepening Probes: Ask about goals, cues, assessments, and decisions at each decision point
Sample Probes:
- “What were you thinking at this point?”
- “What information did you use to make this decision?”
- “What made this option better than the alternatives?”
- “If a novice were in this situation, what might they miss?”
- “What cues told you that X was happening?”
Scenario-Based Interviews
Present hypothetical scenarios to reveal judgment and decision-making:
- Scenario Construction: Develop realistic scenarios with ambiguity and complexity
- Expert Response: Expert explains how they would approach the situation
- Probing: Ask about information sought, hypotheses considered, decisions made
- Variation: Modify scenario parameters to explore boundaries and exceptions
Contrasting Cases
Compare similar cases with different outcomes to identify critical factors:
- Present two similar situations with different outcomes
- Ask expert to explain why outcomes differed
- Identify the critical differences that experts attend to
- Reveal the subtle cues and patterns experts use for assessment
Documentation During Interviews
Techniques for Capturing Interview Content:
| Method | Advantages | Considerations |
|---|---|---|
| Audio Recording + Transcription | Complete capture, allows interviewer to focus | Time-intensive transcription, may inhibit some experts |
| Video Recording | Captures demonstrations and non-verbal cues | More intrusive, larger files to manage |
| Real-Time Note-Taking | Immediate documentation, can be shared quickly | May miss details, divides interviewer attention |
| Mind Mapping | Visual capture of relationships and concepts | Requires skill, may not capture exact wording |
| Screen Recording | Captures technical demonstrations | Only suitable for computer-based tasks |
Post-Interview Processing:
- Review recording/notes immediately while fresh
- Identify key insights, procedures, decision rules, and context
- Organize into structured format (decision tree, procedure, guidelines)
- Create draft documentation
- Review draft with expert for accuracy and completeness
- Refine based on feedback
Documentation Workshops
Facilitated Group Documentation
Workshops bring together multiple experts to collaboratively document shared practices:
Workshop Design:
Pre-Workshop Preparation:
- Define scope and objectives
- Identify and invite participants (mix of experts and practitioners)
- Gather existing documentation and common questions
- Prepare templates and materials
- Communicate objectives and expectations
Workshop Structure (typical 2-4 hours):
- Introduction (15 min): Objectives, agenda, ground rules
- Current State Review (30 min): Review existing documentation and identify gaps
- Knowledge Capture (90-120 min): Collaborative documentation creation
- Review and Refinement (30 min): Group review of created content
- Next Steps (15 min): Assign follow-up actions and ownership
Facilitation Techniques:
| Technique | Purpose | Application |
|---|---|---|
| Round Robin | Ensure all voices are heard | Each participant contributes in sequence |
| Silent Generation | Generate ideas without groupthink | Participants write ideas individually before sharing |
| Affinity Grouping | Organize related concepts | Group similar ideas and identify themes |
| Dot Voting | Prioritize topics or issues | Participants vote on importance or priority |
| Think-Pair-Share | Develop ideas collaboratively | Individual reflection, pair discussion, group sharing |
| Parking Lot | Manage scope and side discussions | Capture off-topic items for later consideration |
Process Documentation Workshops
Specific format for documenting complex processes:
Process Mapping Activity:
- Identify Process Boundaries: Define start and end points, inputs and outputs
- Map Happy Path: Document the standard, successful process flow
- Identify Decision Points: Where decisions or variations occur
- Document Variations: Alternative paths and exception handling
- Capture Decision Logic: Criteria and factors for decisions
- Note Roles and Handoffs: Who does what, where work is transferred
- Identify Risks and Issues: Common problems and how to address them
Outputs from Process Workshop:
- Visual process map or flowchart
- Detailed procedure document
- Decision criteria or rules
- Exception handling guidelines
- Roles and responsibilities matrix
- Quality checkpoints and success criteria
Tacit to Explicit Conversion Techniques
Documentation Methods
Converting tacit knowledge into documented explicit knowledge requires systematic approaches:
Procedure Documentation
Step-by-step instructions for performing tasks:
Structure:
- Purpose and scope
- Prerequisites and required resources
- Detailed steps with decision points
- Expected results and verification
- Exception handling and troubleshooting
- Related procedures and references
Best Practices:
- Use active voice and imperative mood (“Click the button” not “The button should be clicked”)
- Include screenshots or diagrams for visual guidance
- Test procedure with target users
- Include “why” information for context, not just “how”
Decision Trees and Diagnostic Guides
Visual representations of expert decision-making:
Development Process:
- Identify decision starting point
- Map first decision or assessment
- Document criteria for each branch
- Continue branching for subsequent decisions
- Terminate branches at resolution or action
- Validate with expert and test with users
Example Application: IT support diagnostic tree that guides troubleshooting based on symptoms, system responses, and test results.
Checklist Development
Memory aids and quality assurance tools:
Types:
- Read-Do: Read each item and perform action
- Do-Confirm: Perform work from memory, then verify with checklist
- Challenge-Response: Two-person verification for critical items
Design Principles:
- Focus on critical items, not comprehensive lists
- Keep items specific and actionable
- Test under realistic conditions
- Revise based on user feedback and failures
Video Capture Techniques
Video is particularly effective for capturing tacit knowledge with visual or physical components:
Screen Recording with Expert Narration
Application: Technical tasks performed on computers
Process:
- Expert prepares example scenario
- Screen recording software captures actions
- Expert narrates decisions and reasoning while working
- Post-production adds chapters, annotations, captions
- Video indexed by topic for easy reference
Tools: Camtasia, OBS Studio, Loom, Microsoft Stream
Demonstration Videos
Application: Physical procedures, equipment operation, interpersonal skills
Elements:
- Introduction explaining context and objectives
- Step-by-step demonstration with clear camera angles
- Explanation of common mistakes and how to avoid them
- Tips and tricks from experienced practitioners
- Summary of key points
Storytelling Techniques
Stories capture contextual richness that procedures cannot convey:
Experience Story Format
Structure for documenting learning experiences:
# [Descriptive Title]
## Context
- Time period and setting
- Key players and their roles
- Relevant background and constraints
## Challenge
What problem, issue, or opportunity arose?
What made it difficult or significant?
## Actions and Decisions
What was done and why? Include:
- Key decisions and rationale
- Alternative approaches considered
- Critical turning points
- Expert judgment applied
## Outcomes
What resulted from these actions?
- Immediate results
- Longer-term consequences
- Unexpected outcomes
## Lessons and Insights
What can others learn from this experience?
- Key takeaways
- Principles or guidelines
- Applicability to other situations
- What would be done differently
## Discussion Questions
- Questions to stimulate reflection
- How would you have handled this?
- What factors would change your approach?
Story Collection Strategies
Elicitation Approaches:
- “Tell me about a time when…” interviews
- Story circles where teams share experiences
- Incident debriefs captured as stories
- Video interviews with retiring experts
- Written story submissions with templates
Organization:
- Tag by domain, topic, and lessons
- Link to related procedures and guidelines
- Create story collections around themes
- Make searchable by scenario or challenge type
Metaphor and Analogy Development
Making complex concepts accessible through comparison:
Metaphor Creation Process:
- Identify Core Concept: What needs to be explained?
- Find Familiar Analogy: What everyday experience is similar?
- Map Relationships: How do elements correspond?
- Test Understanding: Does it aid comprehension?
- Note Limitations: Where does the metaphor break down?
Examples:
- “Firewall as border checkpoint” for network security
- “Database indexes like book index” for query optimization
- “API as restaurant menu” for system integration
- “Git branches like parallel universes” for version control
Explicit to Tacit Techniques
Training Design for Internalization
Converting explicit knowledge to tacit understanding requires experience and practice:
Learning Path Design
Structured progression from explicit learning to tacit mastery:
Stage 1: Cognitive Understanding
- Read documentation and procedures
- Watch demonstration videos
- Attend presentations or lectures
- Study examples and case studies Outcome: Intellectual understanding
Stage 2: Observed Application
- Watch experts perform in real situations
- Observe decision-making in action
- See variation and exception handling
- Understand context and judgment Outcome: Contextual understanding
Stage 3: Guided Practice
- Perform tasks with expert coaching
- Receive immediate feedback
- Make mistakes in safe environment
- Develop procedural fluency Outcome: Supervised competence
Stage 4: Independent Application
- Perform tasks independently
- Handle increasingly complex cases
- Develop personal approaches
- Build experience base Outcome: Autonomous performance
Stage 5: Mastery and Innovation
- Handle novel situations intuitively
- Teach and mentor others
- Adapt and improve practices
- Contribute to explicit knowledge Outcome: Expertise and innovation
Simulation and Practice Exercises
Creating safe learning environments:
Types of Simulations:
Technical Simulations
- Virtual labs for system administration
- Sandboxes for software development
- Simulated networks for security training
- Test environments for configuration practice
Interpersonal Simulations
- Role-play for customer service
- Negotiation scenarios
- Difficult conversation practice
- Leadership and management simulations
Crisis Simulations
- Incident response tabletop exercises
- Business continuity drills
- Security breach scenarios
- System failure response practice
Design Principles:
- Realistic complexity and ambiguity
- Opportunity for failure without real consequences
- Immediate feedback on decisions
- Multiple practice cycles
- Progression from simple to complex
Mentored Practice Programs
Combining explicit knowledge with tacit development:
Structured Practice Framework:
- Preparation: Study relevant explicit knowledge
- Planning: Discuss approach with mentor
- Performance: Execute task independently
- Observation: Mentor observes without intervening
- Debrief: Discuss what happened and why
- Reflection: Learner identifies insights and areas for improvement
- Iteration: Repeat with increasing complexity
Coaching Techniques:
- Ask guiding questions rather than providing answers
- Help learner recognize patterns and principles
- Provide feedback on both outcomes and reasoning
- Share expert perspectives and alternatives
- Encourage experimentation and learning from mistakes
Knowledge Codification
Codification Standards
Ensuring documented knowledge is usable and maintainable:
Quality Criteria for Codified Knowledge:
| Criterion | Description | Assessment Questions |
|---|---|---|
| Accuracy | Information is correct and verified | Has subject matter expert reviewed and approved? |
| Completeness | All essential information is included | Can user complete task with only this documentation? |
| Clarity | Information is understandable to target audience | Have target users tested and validated comprehension? |
| Currency | Information is up-to-date | When was content last reviewed and updated? |
| Consistency | Aligns with standards and other content | Does it use standard terminology and formats? |
| Conciseness | Includes essential information without unnecessary detail | Is every sentence necessary? |
| Accessibility | Easy to find and access when needed | Can users locate this within expected timeframe? |
Documentation Standards
Structural Standards:
- Title: Clear, descriptive, follows naming convention
- Metadata: Author, date, version, category, tags
- Purpose Statement: Brief explanation of what and why
- Audience: Who should use this information
- Content Structure: Logical organization with clear sections
- Visual Elements: Screenshots, diagrams where helpful
- Related Content: Links to related knowledge
- Maintenance Information: Review frequency, owner
Style Standards:
- Language: Clear, professional, appropriate for audience
- Voice: Active voice, second person (“you”)
- Tense: Present tense for current procedures
- Terminology: Standard terms defined in glossary
- Formatting: Consistent use of headings, lists, emphasis
- Accessibility: Alt text for images, clear language
Review and Validation Processes
Multi-Level Review Process:
Level 1: Technical Review
- Subject matter expert verifies accuracy
- Checks completeness of content
- Validates technical details and procedures
- Confirms current applicability
Level 2: User Testing
- Representative users attempt to use documentation
- Test under realistic conditions
- Identify unclear or missing information
- Provide feedback on usability
Level 3: Editorial Review
- Review for clarity and readability
- Check adherence to style standards
- Verify proper formatting and structure
- Ensure consistency with other content
Level 4: Final Approval
- Content owner approves for publication
- Verify metadata and classification
- Establish review schedule
- Authorize publication
Quality Assurance Checklist:
Knowledge Article Quality Checklist
Technical Quality:
☐ Technically accurate and verified by SME
☐ Complete information for intended task
☐ Current and reflects current environment
☐ Tested by actual use or walkthrough
Usability:
☐ Clear and understandable to target audience
☐ Logical structure and organization
☐ Appropriate level of detail
☐ Includes helpful visuals where appropriate
Standards Compliance:
☐ Follows documentation templates
☐ Uses standard terminology
☐ Proper categorization and tagging
☐ Complete and accurate metadata
Accessibility:
☐ Proper heading hierarchy
☐ Alt text for images
☐ Clear link text
☐ Readable font and contrast
Maintenance:
☐ Owner assigned
☐ Review schedule established
☐ Version controlled
☐ Update process defined
Technology for Knowledge Conversion
Tools for Each SECI Mode
Socialization Technologies:
| Tool Type | Purpose | Examples | Best For |
|---|---|---|---|
| Collaboration Platforms | Enable real-time and asynchronous interaction | Microsoft Teams, Slack, Discord | Communities of practice, informal knowledge sharing |
| Video Conferencing | Face-to-face remote interaction | Zoom, Teams, Google Meet | Mentoring sessions, knowledge cafes, virtual co-working |
| Virtual Whiteboarding | Collaborative visual thinking | Miro, Mural, Microsoft Whiteboard | Brainstorming, problem-solving sessions |
| Social Networking | Connecting people with expertise | Yammer, Workplace, LinkedIn | Finding expertise, informal connections |
Externalization Technologies:
| Tool Type | Purpose | Examples | Best For |
|---|---|---|---|
| Video Capture | Recording expert demonstrations | Camtasia, Loom, OBS Studio | Technical procedures, think-aloud protocols |
| Screen Recording | Capturing computer-based work | Camtasia, Snagit, Loom | Software tutorials, technical demonstrations |
| AI Transcription | Converting speech to text | Otter.ai, Microsoft Teams transcription, Google Recorder | Interview transcription, meeting notes |
| Mind Mapping | Visual capture of concepts | MindMeister, XMind, Miro | Interview capture, concept mapping |
| Documentation Tools | Creating structured content | Confluence, SharePoint, Notion | Procedures, guides, reference documentation |
| Diagramming Tools | Creating visual representations | Visio, Lucidchart, Draw.io | Process flows, decision trees, system diagrams |
Combination Technologies:
| Tool Type | Purpose | Examples | Best For |
|---|---|---|---|
| Knowledge Management Systems | Organizing and connecting content | Confluence, SharePoint, ServiceNow | Centralized knowledge repository |
| Content Management Systems | Publishing and maintaining content | Drupal, WordPress, SharePoint | Public-facing knowledge bases |
| Search Engines | Finding relevant information | Elasticsearch, Google Search Appliance | Accessing distributed knowledge |
| AI/ML Tools | Automated analysis and synthesis | IBM Watson, Azure Cognitive Services | Pattern recognition, content recommendations |
Internalization Technologies:
| Tool Type | Purpose | Examples | Best For |
|---|---|---|---|
| Learning Management Systems | Structured learning paths | Moodle, Cornerstone, SAP SuccessFactors | Training programs, certification tracks |
| Virtual Labs | Safe practice environments | Cloud sandbox environments, Docker containers | Technical skill development |
| Simulation Platforms | Realistic practice scenarios | Custom simulations, game-based learning | Complex procedures, crisis response |
| Performance Support | Just-in-time guidance | WalkMe, Whatfix, embedded help | On-the-job application |
AI and Automation in Knowledge Conversion
AI-Powered Transcription
- Automatic speech-to-text conversion of interviews and meetings
- Speaker identification and separation
- Time-stamping for easy reference
- Translation capabilities for multilingual content
Applications:
- Converting expert interviews to searchable text
- Creating meeting transcripts for knowledge capture
- Generating captions for video content
Natural Language Processing
- Automatic extraction of key concepts and entities
- Summarization of lengthy documents
- Sentiment and tone analysis
- Question generation from content
Applications:
- Generating summaries of lessons learned reports
- Extracting action items from project retrospectives
- Identifying common themes across multiple documents
Chatbots and Virtual Assistants
- Interactive access to documented knowledge
- Natural language queries
- Conversational guidance through procedures
- Escalation to human experts when needed
Applications:
- First-line support for common questions
- Interactive troubleshooting guides
- Training reinforcement and practice
Tool Selection Criteria
Evaluation Factors:
- Alignment with SECI Mode: Does tool support intended conversion type?
- User Adoption: Will target users adopt and use effectively?
- Integration: Does it integrate with existing systems?
- Scalability: Can it grow with organizational needs?
- Cost: Does value justify investment?
- Security: Does it meet security and compliance requirements?
- Maintenance: What are ongoing support requirements?
- Accessibility: Is it accessible to all users?
Storytelling and Narrative Techniques
Power of Stories in Knowledge Transfer
Stories are a natural way humans share and remember complex, contextual knowledge:
Why Stories Work:
- Engage emotion and attention
- Provide context and meaning
- Are memorable and easily recalled
- Convey complexity and ambiguity
- Transfer values and culture along with facts
- Show rather than tell
- Build empathy and connection
Types of Knowledge Stories
Experience Stories: Personal accounts of significant events, successes, failures, or learning experiences.
Structure:
- Context: Setting and situation
- Challenge: Problem or issue faced
- Actions: What was done and why
- Outcome: Results and consequences
- Lessons: Insights and takeaways
Case Studies: Detailed examination of specific situations or decisions.
Elements:
- Background information
- Problem or opportunity
- Analysis and decision-making process
- Implementation and results
- Discussion of key factors and alternatives
War Stories: Dramatic accounts of challenging or crisis situations.
Value:
- Show expertise in action under pressure
- Reveal hidden complexity and judgment
- Provide vicarious experience
- Build community and shared identity
Capturing and Structuring Stories
Story Elicitation:
Opening Questions:
- “Tell me about a time when…”
- “What’s the most challenging situation you’ve faced with X?”
- “Can you describe a case where things went wrong?”
- “What’s a success you’re particularly proud of?”
Deepening Questions:
- “What were you thinking at that moment?”
- “What made this situation different or challenging?”
- “What would someone less experienced have missed?”
- “Looking back, what would you do differently?”
Story Repository and Access
Organizing Stories:
- Tag by theme, domain, and lessons learned
- Link to related procedures or guidelines
- Include metadata (context, actors, timeframe)
- Create story collections around common themes
Using Stories:
- Training and onboarding programs
- Team discussions and knowledge sharing sessions
- Decision support (similar situations and how they were handled)
- Cultural transmission (organizational values and norms)
Knowledge Conversion Workflow
The following diagram illustrates the complete knowledge conversion process:
Figure 10.1: Knowledge Conversion Workflow
┌────────────────────────────────────────────────────────────────┐
│ KNOWLEDGE CONVERSION PROCESS │
└────────────────────────────────────────────────────────────────┘
Phase 1: IDENTIFICATION
┌──────────────────────────────────────┐
│ • Identify critical tacit knowledge │
│ • Assess conversion feasibility │
│ • Select target knowledge domain │
│ • Identify knowledge holders │
└────────────┬─────────────────────────┘
│
↓
Phase 2: ELICITATION (Externalization)
┌──────────────────────────────────────┐
│ • Conduct expert interviews │
│ • Facilitate workshops │
│ • Capture stories and experiences │
│ • Record demonstrations │
│ • Extract decision logic │
└────────────┬─────────────────────────┘
│
↓
Phase 3: CODIFICATION
┌──────────────────────────────────────┐
│ • Structure captured knowledge │
│ • Create documentation │
│ • Develop visual aids │
│ • Apply quality standards │
│ • Technical review │
└────────────┬─────────────────────────┘
│
↓
Phase 4: VALIDATION
┌──────────────────────────────────────┐
│ • Expert review for accuracy │
│ • User testing for usability │
│ • Editorial review for clarity │
│ • Standards compliance check │
└────────────┬─────────────────────────┘
│
↓
Phase 5: PUBLICATION (Combination)
┌──────────────────────────────────────┐
│ • Publish to knowledge repository │
│ • Categorize and tag │
│ • Link to related content │
│ • Announce availability │
└────────────┬─────────────────────────┘
│
↓
Phase 6: INTERNALIZATION
┌──────────────────────────────────────┐
│ • Training and education │
│ • Practice exercises │
│ • Mentored application │
│ • Simulation and scenario practice │
└────────────┬─────────────────────────┘
│
↓
Phase 7: SOCIALIZATION
┌──────────────────────────────────────┐
│ • Knowledge sharing sessions │
│ • Communities of practice │
│ • Peer learning │
│ • Continuous improvement │
└──────────────────────────────────────┘
↓ (Continuous feedback loop)
┌──────────────────────────────────────┐
│ Phase 8: MAINTENANCE & EVOLUTION │
│ • Monitor usage and feedback │
│ • Update based on experience │
│ • Identify new tacit insights │
│ • Return to Phase 1 (Knowledge Spiral) │
└──────────────────────────────────────┘
Caption: This workflow illustrates the complete knowledge conversion cycle, showing how knowledge moves through the SECI spiral while being formally captured, validated, and disseminated.
Position: Place after the Knowledge Conversion Workflow section heading to provide visual reference for the process.
When to Keep Knowledge Tacit
Strategic Choices About Externalization
Not all tacit knowledge should be made explicit. Consider the trade-offs:
Arguments for Keeping Knowledge Tacit:
| Reason | Explanation | Examples |
|---|---|---|
| Impossible to Articulate | Some knowledge cannot be fully expressed in words | Recognizing quality in design, expert pattern recognition |
| Context-Critical | Knowledge is too dependent on specific context to generalize | Nuanced customer relationship management |
| Continuously Evolving | Knowledge changes faster than documentation can be updated | Rapidly changing technology landscapes |
| Competitive Advantage | Explicit knowledge could be copied by competitors | Proprietary techniques, unique expertise |
| Lost in Translation | Codification loses essential nuance and richness | Cultural understanding, political savvy |
| Better Transferred Through Experience | Practice and observation are more effective than documentation | Physical skills, interpersonal abilities |
Arguments for Making Knowledge Explicit:
| Reason | Explanation | Examples |
|---|---|---|
| Knowledge Risk | Critical expertise held by few individuals | Retirement, turnover, single points of failure |
| Scalability | Many people need access to the knowledge | Standard procedures, common troubleshooting |
| Consistency | Need standardized approaches | Compliance requirements, quality standards |
| Training Efficiency | Accelerates learning for new team members | Onboarding, skill development |
| Continuous Improvement | Explicit knowledge can be analyzed and refined | Process optimization, best practice evolution |
| Legal/Regulatory | Documentation required for compliance | Audit trails, regulatory compliance |
Hybrid Approaches
Often the best approach combines explicit documentation with tacit transfer:
Documented Frameworks with Tacit Application: Provide explicit frameworks, guidelines, or checklists, but develop judgment through mentoring and practice.
Minimum Viable Documentation: Document critical minimum (key principles, decision frameworks, common patterns) while recognizing that expertise requires experience.
Communities of Practice: Create spaces where explicit resources supplement ongoing tacit knowledge sharing through discussion and collaboration.
Case Libraries: Document specific cases and examples rather than attempting to create comprehensive procedural documentation.
Organizational Practices for Knowledge Conversion
Creating Conditions for Conversion
Organizations can implement practices that facilitate ongoing knowledge conversion:
Ba (Enabling Context)
Create spaces and contexts that support knowledge conversion:
| Type of Ba | Focus | Examples |
|---|---|---|
| Originating Ba | Socialization - face-to-face interaction | Team rooms, coffee conversations, informal gatherings |
| Dialoguing Ba | Externalization - collective reflection | Brainstorming sessions, workshops, communities of practice |
| Systemizing Ba | Combination - organizing explicit knowledge | Documentation systems, databases, intranets |
| Exercising Ba | Internalization - active application | Projects, simulations, hands-on training |
Time and Permission
Explicitly allocate time and grant permission for knowledge activities:
- Schedule regular knowledge sharing sessions
- Include knowledge documentation in work plans
- Recognize documentation as legitimate work
- Provide writing and facilitation support
- Celebrate knowledge contributions
Reflection Practices
Build reflection into work processes:
- After-action reviews following projects or incidents
- Regular retrospectives for teams
- Personal reflection time
- Peer review and feedback sessions
- Journaling or learning logs
Knowledge Conversion Roles
Knowledge Brokers: Individuals who facilitate knowledge flow between groups, translating and connecting knowledge across boundaries.
Knowledge Engineers: Specialists in eliciting and structuring expert knowledge, often using formal knowledge engineering methodologies.
Documentation Specialists: Writers and editors who help subject matter experts articulate and document their expertise clearly.
Community Facilitators: Individuals who cultivate communities of practice where tacit knowledge is shared through dialogue and collaboration.
Mentoring Coordinators: Professionals who design, implement, and support mentoring programs that transfer tacit knowledge.
Conversion Quality Checklist
Use this checklist to ensure quality in knowledge conversion projects:
Planning Phase: ☐ Critical knowledge domain clearly identified ☐ Knowledge holders identified and available ☐ Conversion objectives defined and documented ☐ Appropriate conversion methods selected ☐ Resources allocated (time, budget, support) ☐ Timeline established with milestones ☐ Success criteria defined
Elicitation Phase: ☐ Sessions scheduled with appropriate experts ☐ Interview guides or workshop plans prepared ☐ Recording equipment tested and working ☐ Multiple sessions conducted for comprehensive coverage ☐ Diverse perspectives captured (multiple experts) ☐ Context and rationale captured, not just procedures ☐ Edge cases and exceptions explored
Codification Phase: ☐ Appropriate documentation format selected ☐ Content structured logically and clearly ☐ Visual aids created where helpful ☐ Standard templates and styles applied ☐ Technical terminology used correctly ☐ Cross-references to related content included ☐ Metadata complete and accurate
Validation Phase: ☐ Subject matter expert reviewed and approved ☐ Target users tested documentation ☐ Feedback incorporated into revisions ☐ Editorial review completed ☐ Standards compliance verified ☐ Accessibility requirements met ☐ Final approval obtained
Publication Phase: ☐ Published to correct repository location ☐ Properly categorized and tagged ☐ Related content linked bidirectionally ☐ Ownership and maintenance assigned ☐ Availability communicated to target audience ☐ Training or guidance provided if needed ☐ Usage analytics tracking enabled
Post-Publication: ☐ Usage monitored and tracked ☐ User feedback collected ☐ Regular reviews scheduled ☐ Update process established ☐ Continuous improvement mechanisms in place
Practical Implementation Guide
Knowledge Conversion Project Approach
Phase 1: Planning
- Identify Target Knowledge
- What tacit knowledge is critical?
- Who holds this knowledge?
- What is the knowledge risk?
- What is the business impact?
- Assess Conversion Feasibility
- Can this knowledge be articulated?
- What level of externalization is realistic?
- What combination of tacit and explicit transfer is optimal?
- Select Conversion Methods
- Interview, workshop, mentoring, or combination?
- What tools and support are needed?
- Who will facilitate the process?
Phase 2: Elicitation
- Prepare
- Schedule sessions with experts
- Prepare questions and scenarios
- Set up recording and documentation tools
- Conduct Sessions
- Apply selected elicitation techniques
- Capture knowledge through notes, recording, or real-time documentation
- Probe for context, rationale, and judgment
- Process Results
- Review and analyze captured information
- Identify patterns, principles, and key insights
- Begin structuring knowledge into usable formats
Phase 3: Documentation
- Structure Knowledge
- Select appropriate format (procedure, decision tree, guidelines, cases)
- Organize content logically
- Create initial draft
- Review and Refine
- Expert review for accuracy
- User testing for clarity and usability
- Iterative refinement
- Finalize
- Editorial polish
- Final expert approval
- Prepare for publication
Phase 4: Integration
- Publish and Announce
- Add to knowledge repository
- Communicate availability
- Integrate into relevant workflows
- Support Internalization
- Training or learning resources
- Opportunities for practice
- Mentoring or coaching to support application
- Monitor and Maintain
- Track usage and feedback
- Update as knowledge evolves
- Retire when no longer relevant
Review Questions
- SECI Model Application
- How would you apply Socialization mode to enable junior DBAs to learn from expert database administrators?
- What Externalization techniques would you use to capture the troubleshooting expertise into documentation?
- How would you use Combination to integrate this captured knowledge with existing documentation?
- What Internalization approaches would help junior team members develop tacit understanding from the explicit documentation?
- Conversion Method Selection
- Which knowledge conversion techniques would be most appropriate for capturing a retiring project manager’s knowledge of organizational relationships and political dynamics?
- Why might these techniques be more effective than others for this type of knowledge?
- What are the limitations of explicit documentation for stakeholder management knowledge?
- How would you balance tacit and explicit transfer for this knowledge domain?
- Quality Assurance
- What validation steps would you take to ensure a documented incident diagnosis decision tree is accurate and complete?
- Who should be involved in the review process (experts, users, others)?
- How would you test the decision tree’s usability with the target audience?
- What criteria would you use to assess the quality of the documented knowledge?
- Technology Selection
- What are the pros and cons of using written procedures with screenshots for capturing system configuration procedures?
- What are the advantages and disadvantages of video screen recordings with narration?
- How do interactive simulations compare to the other approaches?
- What factors would influence your choice among these three options?
- Strategic Decision
- What factors would you consider in deciding whether to externalize unique threat detection expertise?
- How would you assess the knowledge risk of not documenting this expertise?
- How would you evaluate the competitive advantage concerns of documenting it?
- What hybrid approach might balance knowledge preservation with competitive protection?
Key Takeaways
- The SECI model describes four modes of knowledge conversion that work together in a continuous knowledge spiral: Socialization (tacit-to-tacit), Externalization (tacit-to-explicit), Combination (explicit-to-explicit), and Internalization (explicit-to-tacit)
- Organizations should facilitate all four modes of conversion, not focus exclusively on externalization and documentation
- Tacit knowledge - expertise that exists in people’s minds - is among an organization’s most valuable and vulnerable assets
- Mentoring and apprenticeship are powerful mechanisms for transferring tacit knowledge through observation, guided practice, and immersive experience
- Specialized interview techniques (critical decision method, scenario-based interviews, contrasting cases) can elicit tacit knowledge that experts may not consciously recognize
- Documentation workshops bring together multiple experts to collaboratively externalize shared practices and processes
- Video capture is particularly effective for procedures with visual or physical components, enabling experts to demonstrate while narrating their thinking
- Storytelling and narratives are effective for capturing and transferring complex, contextual knowledge that is difficult to express in procedural documentation
- Not all tacit knowledge should or can be made explicit - strategic choices should consider feasibility, value, knowledge risk, and the most effective transfer mechanisms
- Quality codification requires clear standards, multi-level review, and validation with both experts and target users
- Technology should support the entire SECI spiral, not just explicit knowledge storage - including collaboration tools for socialization, capture tools for externalization, and practice environments for internalization
- Organizational practices (reflection routines, communities of practice, enabling contexts) create conditions that support continuous knowledge conversion
- Successful knowledge conversion requires both appropriate techniques and organizational conditions that provide time, permission, and support
- The goal is not to eliminate tacit knowledge but to create a dynamic balance where tacit and explicit knowledge complement each other
Summary
Converting knowledge between tacit and explicit forms is central to organizational learning and knowledge management. This chapter has explored the SECI model - Socialization, Externalization, Combination, and Internalization - as a comprehensive framework for understanding knowledge conversion. Each mode plays a critical role, and together they form a continuous spiral that amplifies knowledge throughout the organization.
Effective knowledge conversion requires multiple approaches tailored to different types of knowledge and organizational contexts. Socialization techniques like mentoring, communities of practice, and collaborative work enable tacit-to-tacit transfer through shared experience. Externalization methods including specialized interviews, documentation workshops, video capture, and storytelling help articulate tacit knowledge into explicit forms. Combination techniques synthesize and organize explicit knowledge into more comprehensive and usable resources. Internalization approaches including training, simulation, and mentored practice convert explicit knowledge into tacit understanding and capability.
Quality in knowledge conversion demands attention to codification standards, validation processes, and appropriate technology selection. Documentation must meet clear quality criteria including accuracy, completeness, clarity, and currency. Multi-level review involving experts, users, and editors ensures converted knowledge is both technically correct and practically usable. Technology should support the entire SECI spiral, providing tools for collaboration, capture, organization, and practice.
Strategic decisions about which knowledge to convert and how require careful consideration. Not all tacit knowledge should be made explicit - some is impossible to fully articulate, some is better transferred through experience, and some provides competitive advantage that could be lost through documentation. Organizations must balance knowledge risk, scalability needs, and transfer effectiveness when deciding conversion approaches.
Ultimately, successful knowledge conversion depends on creating organizational conditions that support continuous conversion: enabling contexts (Ba) for each mode, allocated time and permission for knowledge activities, reflection practices built into work processes, and specialized roles to facilitate conversion. The goal is not to eliminate tacit knowledge but to create a dynamic ecosystem where tacit and explicit knowledge continuously interact, amplify each other, and drive organizational learning and innovation.
The next chapter examines knowledge organization and classification - the systems and structures that make captured and converted knowledge discoverable and usable across the organization.
Chapter Navigation
| Previous Chapter | Table of Contents | Next Chapter |
|---|---|---|
| Chapter 9: Knowledge Capture and Creation | Handbook Home | Chapter 11: Knowledge Organization and Classification |