Manu's Vault

Knowledge Silos Pattern

6 min readStatus:Seedling

Core Idea

Knowledge silos occur when information and expertise become trapped within organizational boundaries (teams, individuals, systems) and don’t flow to where they’re needed. This anti-pattern leads to duplicated work, missed opportunities, and organizational fragility. Silos are the enemy of knowledge flow.

What Are Knowledge Silos?

Definition:

  • Pockets of knowledge isolated from the rest of the organization
  • Information exists but doesn’t reach people who need it
  • Expertise concentrated in one place, inaccessible to others
  • Boundaries that block knowledge flow

Common Forms:

  • Team silos: Frontend team doesn’t share with backend team
  • Individual silos: Only one person knows critical system
  • System silos: Documentation scattered across disconnected systems
  • Domain silos: Business knowledge separated from technical knowledge

How Silos Form

Organizational Structure:

  • Teams organized by technology (DB team, Frontend team, etc.)
  • Physical separation (different offices/time zones)
  • Reporting hierarchy creates boundaries
  • See Conway’s-Law - communication structure shapes system

Cultural Factors:

  • Competition between teams for resources
  • Knowledge hoarding for job security
  • “Not my problem” mentality
  • Fixed mindset (see Growth Mindset)

Technical Factors:

  • Different documentation systems
  • Access controls too restrictive
  • No shared communication channels
  • Incompatible tools

Time Pressure:

  • “No time to share, must ship”
  • Knowledge sharing seen as overhead
  • Short-term optimization over long-term value

Symptoms of Knowledge Silos

Duplication:

  • Multiple teams solving the same problem
  • Reinventing wheels unknowingly
  • “I wish I’d known you already built that”

Single Points of Failure:

  • “Only Alice knows how the payment system works”
  • Bus factor of 1 (org fails if person leaves)
  • Bottlenecks: everything waits for the expert

Slow Onboarding:

  • New team members take months to be productive
  • “Tribal knowledge” not documented
  • “You should have asked Bob” (but how would they know?)

Inconsistent Solutions:

  • Each team invents their own approach
  • No shared patterns or practices
  • Difficult to move between teams

Missed Opportunities:

  • Solutions from Domain A could help Domain B, but no one knows
  • Innovation blocked by lack of cross-pollination
  • Can’t see the bigger picture

Impact on Knowledge Flow

Silos are the antithesis of knowledge flow:

High Silos = Low Flow

Team A ─────X───── Team B
   │                  │
Knowledge           Knowledge
  stuck              stuck

When silos exist:

  • Knowledge can’t reach where it’s needed
  • Learning happens in isolation
  • Same mistakes repeated across boundaries
  • Organization can’t leverage its collective intelligence

Breaking Down Silos

1. Structural Changes:

  • Cross-functional teams (not technology silos)
  • Rotation programs (people move between teams)
  • Matrix structures (dual reporting)
  • Communities of practice across teams

2. Cultural Changes:

  • Reward sharing, not hoarding
  • Make heroes of teachers, not secret-keepers
  • Celebrate questions and curiosity
  • Foster growth mindset

3. Technical Solutions:

  • Centralized documentation (single source of truth)
  • Shared communication channels (Slack channels, wikis)
  • ADRs accessible to all
  • Internal tech talks and demos

4. Process Changes:

  • Design reviews with cross-team participation
  • Code review across team boundaries
  • Retrospectives that include other teams
  • Regular knowledge-sharing sessions

Role of T-Shaped People

T-shaped people are silo breakers:

Person A (DB Deep) ──X──── Person B (Frontend Deep)
                   silo

Person C (T-Shaped: DB + Frontend breadth) bridges:

Person A ←── Person C ──→ Person B
         Knowledge flow restored

How T-shaped people break silos:

  • Understand both sides of the boundary
  • Can translate between specialists
  • Recognize when knowledge from one domain applies to another
  • Build relationships across teams
  • Facilitate communication

Common Silo Scenarios

Scenario 1: Expert Hoarding

  • Problem: Senior developer hoards knowledge for job security
  • Impact: Team dependent, can’t function without them
  • Solution: Pair programming, documentation, deliberately spread knowledge

Scenario 2: Team Boundaries

  • Problem: Frontend and backend teams don’t communicate
  • Impact: Poor API design, mismatched expectations
  • Solution: Cross-functional teams, API design reviews together

Scenario 3: Documentation Scattered

  • Problem: Docs in Confluence, GitHub, Google Docs, Notion, wikis
  • Impact: Can’t find information, knowledge effectively siloed
  • Solution: Single source of truth, clear information architecture

Scenario 4: Business-Tech Divide

  • Problem: Business knowledge stays with product, tech with engineering
  • Impact: Engineers build wrong thing, product can’t evaluate feasibility
  • Solution: Embedded product in engineering, engineers in business discussions

Silos vs Boundaries

Not all boundaries are bad:

Healthy Boundaries:

  • Clear ownership and responsibility
  • Defined interfaces between teams
  • Autonomy within domains
  • Knowledge shared across boundaries when needed

Unhealthy Silos:

  • Knowledge trapped, not shared
  • No communication across boundaries
  • Rigid, impermeable walls
  • Competition instead of collaboration

The difference: Boundaries with bridges vs. walls without doors

Measuring Silo Impact

Quantitative Indicators:

  • Time to onboard new team members
  • Number of people who can answer questions about a system
  • Frequency of duplicated solutions
  • Cross-team communication metrics

Qualitative Indicators:

  • “I didn’t know you were working on that”
  • “Wish someone had told me sooner”
  • “I would have done it differently if I’d known”
  • “Who can I ask about X?” (if answer is only one person, silo exists)

Connection to Architecture

Architects play a key role in preventing silos:

System Architecture Creates Silos:

  • Monolithic systems = teams organized around layers (silo-prone)
  • Microservices = teams organized around domains (less silo-prone)
  • See Conway’s Law

Architect as Facilitator:

  • Design for knowledge flow, not just system flow
  • Create contexts for cross-team learning
  • Break down walls through communication structures

Documentation Architecture:

  • ADRs prevent temporal silos
  • Centralized, accessible documentation prevents system silos
  • Clear information architecture prevents finding silos

Sources

Team Topologies and Organizational Design:

  • Skelton, Matthew and Manuel Pais (2019). Team Topologies: Organizing Business and Technology Teams for Fast Flow. IT Revolution Press.
    • Four fundamental team types and interaction modes
    • Conway’s Law and organizational design
    • Breaking down silos through team topology
    • Chapter 3: “Team-First Thinking”
    • ISBN: 978-1942788812
    • Available: https://teamtopologies.com/book

Conway’s Law:

Knowledge Management:

  • Davenport, Thomas H. and Laurence Prusak (1998). Working Knowledge: How Organizations Manage What They Know. Harvard Business School Press.

    • Knowledge silos as organizational dysfunction
    • Communities of practice as bridges
    • ISBN: 978-1578513017

  • Nonaka, Ikujiro and Hirotaka Takeuchi (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press.

    • Knowledge creation in organizations
    • SECI model (Socialization, Externalization, Combination, Internalization)
    • Breaking barriers to knowledge flow
    • ISBN: 978-0195092691

Organizational Silos:

  • Lencioni, Patrick (2006). Silos, Politics and Turf Wars: A Leadership Fable About Destroying the Barriers That Turn Colleagues Into Competitors. Jossey-Bass.
    • Leadership perspective on organizational silos
    • Practical approaches to breaking silos
    • ISBN: 978-0787976385

Note

This content was drafted with assistance from AI tools for research, organization, and initial content generation. All final content has been reviewed, fact-checked, and edited by the author to ensure accuracy and alignment with the author’s intentions and perspective.

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