Diagrams & Visuals - Lesson 1.1: Problem Tree Analysis

Visual Reference Library

This page collects all 8 diagrams from Lesson 1.1 in one place for easy reference. Each diagram uses the Festa Design System colors strategically: Chicken Comb for problems, Apocalyptic Orange for assumptions, Pepper Green for evidence, Pot of Gold for decisions, and Leaf for positive outcomes.

1. Three-Layer Problem Tree Structure

graph TB
    subgraph Effects["🌿 EFFECTS (Branches)<br/>What happens because the problem exists?"]
        E1["Short-term Effects<br/>Immediate consequences<br/>(0-6 months)"]
        E2["Medium-term Effects<br/>Developing impacts<br/>(6 months - 2 years)"]
        E3["Long-term Effects<br/>Lasting consequences<br/>(2+ years)"]
    end

    CP["🌳 CORE PROBLEM (Trunk)<br/>The central issue your project addresses<br/><br/>• Affects specific population<br/>• In defined context<br/>• Observable & measurable<br/>• Urgent"]

    subgraph RootCauses["🌱 ROOT CAUSES (Roots)<br/>Why does the problem exist?"]
        RC1["Level 1: Direct Causes<br/>Immediate factors"]
        RC2["Level 2: Underlying Causes<br/>Why direct causes exist"]
        RC3["Level 3: Structural Causes<br/>Systems & conditions"]
    end

    CP --> E1
    CP --> E2
    CP --> E3

    RC1 --> CP
    RC2 --> RC1
    RC3 --> RC2

    style Effects fill:#72B043,stroke:#007F4E,color:#fff
    style E1 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style E2 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style E3 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style CP fill:#E12729,stroke:#B91C1C,color:#fff,stroke-width:3px
    style RootCauses fill:#F37324,stroke:#EA580C,color:#fff
    style RC1 fill:#FDBA74,stroke:#F37324,color:#2A2A2A
    style RC2 fill:#FDBA74,stroke:#F37324,color:#2A2A2A
    style RC3 fill:#FDBA74,stroke:#F37324,color:#2A2A2A

Core Framework

This diagram shows the fundamental structure of a Problem Tree. The Core Problem (Trunk) in red represents the central issue you're addressing. Root Causes (Roots) in orange show why the problem exists across three levels of depth. Effects (Branches) in green demonstrate the consequences across different time horizons. This tree metaphor helps you map cause-and-effect relationships clearly.

Where else you'll see this: Understanding Problem Tree

2. MCP Research Integration Workflow

graph TB
    Start["🎯 START: Define Your Research Scope<br/><br/>Problem Statement<br/>Geographic/Population Context<br/>Existing Knowledge"]

    Block1["📋 BLOCK 1: System Context<br/><br/>Define AI's Role:<br/>• Evidence-focused research assistant<br/>• Neutral, transparent, concise<br/>• Cite sources (publisher + year)<br/>• Separate facts from assumptions"]

    Block2["🧠 BLOCK 2: Knowledge Context<br/><br/>Share What You Know:<br/>• Draft core problem<br/>• Geographic/population scope<br/>• Existing insights<br/>• Keywords and terms"]

    Block3["🎯 BLOCK 3: Task Context<br/><br/>Define Objectives:<br/>• Preliminary Problem Tree<br/>• Measurable indicators<br/>• 5-10 credible sources<br/>• Uncertainties/assumptions<br/>• Stakeholder questions"]

    Block4["▶️ BLOCK 4: Final Prompt<br/><br/>Clear Instruction:<br/>Generate all outputs using<br/>contexts provided above"]

    AIOutput["🤖 AI OUTPUT<br/><br/>• Problem Tree structure<br/>• Indicator suggestions<br/>• Reading list<br/>• Uncertainties<br/>• Validation questions"]

    Verify["✅ QUALITY VERIFICATION<br/><br/>Check Source Credibility:<br/>• Are sources reputable?<br/>• Are they recent?<br/>• Do links work?<br/><br/>Check Context Fit:<br/>• Matches geography/population?<br/>• Culturally appropriate?<br/>• Any contradictions?"]

    Tag["🏷️ TAG EVERYTHING<br/><br/>(E) = Evidence-based<br/>Supported by credible sources<br/><br/>(A) = Assumption<br/>Needs stakeholder validation"]

    Output["📊 PRELIMINARY PROBLEM TREE<br/><br/>With evidence and assumptions tagged<br/>Ready for stakeholder validation"]

    Start --> Block1
    Block1 --> Block2
    Block2 --> Block3
    Block3 --> Block4
    Block4 --> AIOutput
    AIOutput --> Verify
    Verify --> Tag
    Tag --> Output

    style Start fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A,stroke-width:2px
    style Block1 fill:#007F4E,stroke:#00b369,color:#fff
    style Block2 fill:#007F4E,stroke:#00b369,color:#fff
    style Block3 fill:#007F4E,stroke:#00b369,color:#fff
    style Block4 fill:#007F4E,stroke:#00b369,color:#fff
    style AIOutput fill:#72B043,stroke:#5b7c37,color:#fff
    style Verify fill:#F37324,stroke:#EA580C,color:#fff
    style Tag fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Output fill:#72B043,stroke:#007F4E,color:#fff,stroke-width:3px

AI-Assisted Research Process

This workflow shows how to use Model Context Protocol (MCP) for AI-assisted desk review. The four-block prompt structure ensures AI provides evidence-based, context-appropriate research. Critical steps include quality verification (checking source credibility) and tagging to separate evidence (E) from assumptions (A) that need community validation.

Where else you'll see this: AI-Assisted Research, Model Context Protocol

3. Problem Tree Analysis Implementation Steps

graph TB
    Phase1["📋 PHASE 1: Research Planning<br/>Duration: 15-20 minutes<br/><br/>Tasks:<br/>• Define problem scope<br/>• Set research objectives<br/>• Prepare documentation system"]

    Phase2["🔍 PHASE 2: AI-Assisted Research<br/>Duration: 30-40 minutes<br/><br/>Tasks:<br/>• Customize MCP prompt<br/>• Execute AI research<br/>• Quality verification"]

    Phase3["🌳 PHASE 3: Problem Tree Construction<br/>Duration: 25-35 minutes<br/><br/>Tasks:<br/>• Extract core problem<br/>• Map root causes (3 levels)<br/>• Identify effects (time horizons)<br/>• Tag (E) or (A)"]

    Phase4["❓ PHASE 4: Stakeholder Preparation<br/>Duration: 15-20 minutes<br/><br/>Tasks:<br/>• Convert assumptions to questions<br/>• Plan validation approach<br/>• Identify stakeholder types"]

    Check["✅ QUALITY CHECK<br/><br/>Is Problem Tree:<br/>• Logical?<br/>• Evidence-based?<br/>• Community-grounded?<br/>• Ready for validation?"]

    Decision{"Ready for<br/>Stakeholders?"}

    Lesson12["➡️ LESSON 1.2<br/>Stakeholder Mapping<br/>& Engagement"]

    Refine["🔄 Refine Analysis<br/><br/>Return to phase<br/>needing improvement"]

    Phase1 --> Phase2
    Phase2 --> Phase3
    Phase3 --> Phase4
    Phase4 --> Check
    Check --> Decision
    Decision -->|Yes| Lesson12
    Decision -->|No| Refine
    Refine --> Phase2

    style Phase1 fill:#007F4E,stroke:#00b369,color:#fff
    style Phase2 fill:#007F4E,stroke:#00b369,color:#fff
    style Phase3 fill:#007F4E,stroke:#00b369,color:#fff
    style Phase4 fill:#007F4E,stroke:#00b369,color:#fff
    style Check fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Decision fill:#F37324,stroke:#EA580C,color:#fff
    style Lesson12 fill:#72B043,stroke:#5b7c37,color:#fff,stroke-width:3px
    style Refine fill:#E12729,stroke:#B91C1C,color:#fff

Step-by-Step Process

Complete Problem Tree Analysis in 4 phases totaling 85-115 minutes. Each phase has specific deliverables and time estimates. The quality check decision point ensures you only advance to stakeholder engagement when your analysis is solid. If not ready, the refinement loop helps you strengthen weak areas before proceeding.

Where else you'll see this: Step-by-Step Guide

4. Evidence vs Assumptions Classification System

graph TB
    Finding["📊 RESEARCH FINDING<br/><br/>Identified cause or effect<br/>from analysis"]

    Q1{"Has credible<br/>source citation?"}

    Q2{"Multiple sources<br/>confirm?"}

    Q3{"Matches your<br/>context?"}

    Q4{"Recent &<br/>relevant?"}

    TagE["✅ TAG AS (E)<br/>EVIDENCE-BASED<br/><br/>High confidence<br/>Can use in problem tree<br/>Still invite stakeholder input"]

    TagA["⚠️ TAG AS (A)<br/>ASSUMPTION<br/><br/>Needs validation<br/>Requires stakeholder confirmation<br/>Prepare specific questions"]

    Convert["📝 CONVERT TO<br/>STAKEHOLDER QUESTION<br/><br/>Open-ended<br/>Non-leading<br/>Explores experience"]

    Finding --> Q1

    Q1 -->|No| TagA
    Q1 -->|Yes| Q2
    Q2 -->|No| TagA
    Q2 -->|Yes| Q3
    Q3 -->|No| TagA
    Q3 -->|Yes| Q4
    Q4 -->|No| TagA
    Q4 -->|Yes| TagE

    TagA --> Convert

    style Finding fill:#F6F6F6,stroke:#737373,color:#2A2A2A
    style Q1 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Q2 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Q3 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Q4 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style TagE fill:#007F4E,stroke:#00b369,color:#fff,stroke-width:3px
    style TagA fill:#F37324,stroke:#EA580C,color:#fff
    style Convert fill:#72B043,stroke:#5b7c37,color:#fff

Critical Distinction

This decision tree helps you classify every finding as either (E) Evidence-based (green) or (A) Assumption (orange). Evidence passes all four quality tests: credible citation, multiple sources, context match, and recent relevance. Assumptions fail any test and must be converted to stakeholder validation questions. This prevents you from building your project on unverified claims.

Where else you'll see this: Understanding Problem Tree

5. Problem Tree to Stakeholder Questions Flow

graph TB
    ProblemTree["🌳 PRELIMINARY PROBLEM TREE<br/><br/>With items tagged:<br/>(E) Evidence-based<br/>(A) Assumptions"]

    FilterA["🔍 FILTER<br/><br/>Extract all items<br/>tagged (A)"]

    subgraph Conversion["📝 CONVERSION PROCESS"]
        A1["Assumption:<br/>'Limited access to networks' (A)"]
        Q1["Question:<br/>'What barriers do you face in<br/>accessing professional networks<br/>or mentorship opportunities?'"]

        A2["Assumption:<br/>'Skills mismatch' (A)"]
        Q2["Question:<br/>'What skills do employers need?<br/>How well do training programs<br/>address these needs?'"]

        A3["Assumption:<br/>'Family support crucial' (A)"]
        Q3["Question:<br/>'How do family expectations<br/>affect young women's<br/>economic participation?'"]
    end

    QuestionBank["❓ STAKEHOLDER VALIDATION QUESTIONS<br/><br/>8-10 open-ended questions<br/>Ready for Lesson 1.2"]

    Guidelines["✅ QUESTION QUALITY CHECK<br/><br/>✓ Open-ended (not yes/no)<br/>✓ Non-leading<br/>✓ Explores experience<br/>✓ Culturally appropriate<br/>✓ Encourages storytelling"]

    ProblemTree --> FilterA
    FilterA --> Conversion
    A1 --> Q1
    A2 --> Q2
    A3 --> Q3
    Conversion --> QuestionBank
    QuestionBank --> Guidelines

    style ProblemTree fill:#72B043,stroke:#007F4E,color:#fff
    style FilterA fill:#F37324,stroke:#EA580C,color:#fff
    style Conversion fill:#F6F6F6,stroke:#737373,color:#2A2A2A
    style A1 fill:#F37324,stroke:#EA580C,color:#fff
    style A2 fill:#F37324,stroke:#EA580C,color:#fff
    style A3 fill:#F37324,stroke:#EA580C,color:#fff
    style Q1 fill:#007F4E,stroke:#00b369,color:#fff
    style Q2 fill:#007F4E,stroke:#00b369,color:#fff
    style Q3 fill:#007F4E,stroke:#00b369,color:#fff
    style QuestionBank fill:#72B043,stroke:#5b7c37,color:#fff,stroke-width:3px
    style Guidelines fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A

From Analysis to Engagement

This diagram shows how to bridge desk research and community engagement. Extract all assumptions (A) from your Problem Tree, then convert each into an open-ended, culturally appropriate question. The examples show proper transformation: assumptions become exploratory questions that invite stakeholders to share their lived experiences. These questions become your interview guide for Lesson 1.2.

Where else you'll see this: Step-by-Step Guide

6. Quality Assurance Testing Flow

graph TB
    Start["📊 COMPLETE PROBLEM TREE<br/><br/>Ready for quality review"]

    Test1["✅ TEST 1: Core Problem Quality<br/><br/>□ Specific population defined?<br/>□ Geographic scope clear?<br/>□ Observable & measurable?<br/>□ Connects to mission?"]

    Decision1{"Pass?"}

    Test2["✅ TEST 2: Root Causes Analysis<br/><br/>□ Causes answer 'why'?<br/>□ 2-3 levels of depth?<br/>□ Mix of (E) and (A)?<br/>□ Multiple categories covered?<br/>□ Potentially addressable?"]

    Decision2{"Pass?"}

    Test3["✅ TEST 3: Effects Mapping<br/><br/>□ Realistic consequences?<br/>□ Multiple time horizons?<br/>□ Individual & system impacts?<br/>□ Clear connection to problem?<br/>□ Demonstrates urgency?"]

    Decision3{"Pass?"}

    Test4["✅ TEST 4: Research Quality<br/><br/>□ Major claims have sources?<br/>□ Evidence separated from assumptions?<br/>□ Knowledge gaps acknowledged?<br/>□ 8-10 validation questions ready?<br/>□ Community-grounded approach?"]

    Decision4{"Pass?"}

    Ready["🎉 READY FOR STAKEHOLDERS<br/><br/>Advance to Lesson 1.2:<br/>Stakeholder Mapping<br/>& Engagement"]

    Refine1["🔄 Refine Core Problem"]
    Refine2["🔄 Deepen Root Cause Analysis"]
    Refine3["🔄 Expand Effects Analysis"]
    Refine4["🔄 Strengthen Evidence Base"]

    Start --> Test1
    Test1 --> Decision1
    Decision1 -->|Yes| Test2
    Decision1 -->|No| Refine1

    Test2 --> Decision2
    Decision2 -->|Yes| Test3
    Decision2 -->|No| Refine2

    Test3 --> Decision3
    Decision3 -->|Yes| Test4
    Decision3 -->|No| Refine3

    Test4 --> Decision4
    Decision4 -->|Yes| Ready
    Decision4 -->|No| Refine4

    Refine1 --> Test1
    Refine2 --> Test2
    Refine3 --> Test3
    Refine4 --> Test4

    style Start fill:#F6F6F6,stroke:#737373,color:#2A2A2A
    style Test1 fill:#007F4E,stroke:#00b369,color:#fff
    style Test2 fill:#007F4E,stroke:#00b369,color:#fff
    style Test3 fill:#007F4E,stroke:#00b369,color:#fff
    style Test4 fill:#007F4E,stroke:#00b369,color:#fff
    style Decision1 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Decision2 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Decision3 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Decision4 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style Ready fill:#72B043,stroke:#007F4E,color:#fff,stroke-width:3px
    style Refine1 fill:#E12729,stroke:#B91C1C,color:#fff
    style Refine2 fill:#E12729,stroke:#B91C1C,color:#fff
    style Refine3 fill:#E12729,stroke:#B91C1C,color:#fff
    style Refine4 fill:#E12729,stroke:#B91C1C,color:#fff

Four-Stage Quality Assurance

Before engaging stakeholders, test your Problem Tree against four quality standards. Each test has specific checkboxes to verify completeness. If any test fails, the diagram guides you to targeted refinement actions (red boxes) that address the specific weakness. Only when all four tests pass should you proceed to Lesson 1.2. This prevents wasting stakeholders' time with poorly prepared analysis.

Where else you'll see this: Quality Checklist

7. Nigeria Youth Livelihood Example

graph TB
    subgraph Effects["🌿 EFFECTS"]
        E1["High youth income insecurity (E)"]
        E2["Rural-urban migration (E)"]
        E3["Lost economic potential (A)"]
    end

    CP["🌳 CORE PROBLEM<br/><br/>Young adults aged 18-25 in rural<br/>communities have limited access to<br/>decent employment opportunities"]

    subgraph Level1["🌱 LEVEL 1: Direct Causes"]
        DC1["Skills-market mismatch (E)"]
        DC2["Geographic access barriers (A)"]
        DC3["Weak entrepreneurship<br/>ecosystem (A)"]
    end

    subgraph Level2["🌱 LEVEL 2: Underlying Causes"]
        UC1["Outdated curricula (E)"]
        UC2["Limited vocational training (E)"]
        UC3["Poor transportation (E)"]
        UC4["Limited internet (A)"]
        UC5["Low startup capital access (A)"]
        UC6["Few business mentors (A)"]
    end

    CP --> E1
    CP --> E2
    CP --> E3

    DC1 --> CP
    DC2 --> CP
    DC3 --> CP

    UC1 --> DC1
    UC2 --> DC1
    UC3 --> DC2
    UC4 --> DC2
    UC5 --> DC3
    UC6 --> DC3

    style Effects fill:#72B043,stroke:#007F4E,color:#fff
    style E1 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style E2 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style E3 fill:#FDBA74,stroke:#F37324,color:#2A2A2A
    style CP fill:#E12729,stroke:#B91C1C,color:#fff,stroke-width:3px
    style Level1 fill:#F37324,stroke:#EA580C,color:#fff
    style DC1 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style DC2 fill:#FDBA74,stroke:#F37324,color:#2A2A2A
    style DC3 fill:#FDBA74,stroke:#F37324,color:#2A2A2A
    style Level2 fill:#F37324,stroke:#EA580C,color:#fff
    style UC1 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style UC2 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style UC3 fill:#A3D977,stroke:#72B043,color:#2A2A2A
    style UC4 fill:#FDBA74,stroke:#F37324,color:#2A2A2A
    style UC5 fill:#FDBA74,stroke:#F37324,color:#2A2A2A
    style UC6 fill:#FDBA74,stroke:#F37324,color:#2A2A2A

Real-World Application

This complete Problem Tree example focuses on youth employment in rural Nigeria. Notice how causes and effects are tagged: (E) for evidence-based items supported by research (shown in lighter green), and (A) for assumptions needing community validation (shown in light orange). This mixed approach is realistic. You'll rarely have 100% evidence for everything. The key is transparency about what you know vs. what you need to verify with stakeholders.

Where else you'll see this: Examples

8. Module Integration Flow - Lessons 1.1 to 1.4

graph TB
    L11["📊 LESSON 1.1<br/>Problem Tree Analysis<br/><br/>OUTPUTS:<br/>• Preliminary Problem Tree<br/>• Evidence-based findings (E)<br/>• Assumptions to validate (A)<br/>• Stakeholder questions"]

    L12["🤝 LESSON 1.2<br/>Stakeholder Mapping<br/><br/>USE LESSON 1.1 FOR:<br/>• Validation questions<br/>• Identifying stakeholders<br/>• Testing assumptions<br/>• Gathering community insights"]

    L13["🧩 LESSON 1.3<br/>Synthesize Data<br/><br/>USE LESSONS 1.1 & 1.2 FOR:<br/>• Organizing stakeholder insights<br/>• Converting (A) to (E)<br/>• Refining Problem Tree<br/>• Identifying patterns"]

    L14["🎯 LESSON 1.4<br/>Theory of Change<br/><br/>USE REFINED PROBLEM TREE FOR:<br/>• Effects → Impact & Outcomes<br/>• Core Problem → Purpose<br/>• Root Causes → Activities<br/>• Logic pathway design"]

    Module2["➡️ MODULE 2<br/>Operationalize<br/><br/>Theory of Change becomes:<br/>• Logical Framework<br/>• Activity Design<br/>• Proposal Writing<br/>• Budget Estimation"]

    L11 --> L12
    L12 --> L13
    L13 --> L14
    L14 --> Module2

    L11 -.->|Validation Questions| L12
    L11 -.->|Original Problem Tree| L13
    L12 -.->|Community Insights| L13
    L13 -.->|Refined Problem Tree| L14

    style L11 fill:#E12729,stroke:#B91C1C,color:#fff,stroke-width:3px
    style L12 fill:#F37324,stroke:#EA580C,color:#fff
    style L13 fill:#F8CC1B,stroke:#CA8A04,color:#2A2A2A
    style L14 fill:#007F4E,stroke:#00b369,color:#fff
    style Module2 fill:#72B043,stroke:#5b7c37,color:#fff,stroke-width:3px

Building Foundation Journey

This diagram shows how Lesson 1.1 connects to the rest of Module 1. Your Problem Tree outputs directly feed into Lesson 1.2 (stakeholder questions), then both feed into Lesson 1.3 (synthesis), which refines your Problem Tree for Lesson 1.4 (Theory of Change). The dotted lines show information flow between lessons. By Lesson 1.4, your initial assumptions have been validated, and you have a community-grounded foundation for Module 2's operational planning.

Where else you'll see this: This is the culminating diagram shown on the lesson index page

How to Use These Diagrams

📚 For Learning

• Start with Diagram 1 (Three-Layer Structure) to understand the core framework
• Study Diagram 2 (MCP Workflow) before doing AI-assisted research
• Reference Diagram 3 (Implementation Steps) while working through the lesson
• Use Diagram 7 (Nigeria Example) as a concrete reference point

🛠️ For Implementation

• Print Diagram 4 (Evidence vs Assumptions) as a desk reference while tagging findings
• Use Diagram 5 (Stakeholder Questions) when converting assumptions to interview questions
• Follow Diagram 6 (Quality Assurance) as a final checklist before stakeholder engagement
• Share Diagram 8 (Module Integration) with team members to show how the lessons connect

Color System Guide

Festa Design System Colors Have Strategic Meaning:
🔴 Chicken Comb (Red) = Problems, failures, critical issues requiring attention
🟠 Apocalyptic Orange = Assumptions, warnings, items needing validation
🟢 Pepper Green (Dark) = Evidence-based findings, solutions, validated information
🟡 Pot of Gold (Yellow) = Decision points, opportunities, key questions
🌿 Leaf (Light Green) = Positive outcomes, effects, growth, success indicators

Where These Diagrams Appear in Context

While this page collects all diagrams in one place, they're also embedded contextually throughout the lesson's child pages:

Conceptual Pages:

• Understanding Problem Tree - Diagrams 1, 4
• AI-Assisted Research - Diagram 2
• Model Context Protocol - Diagram 2

Practical Pages:

• Step-by-Step Guide - Diagrams 3, 5
• Quality Checklist - Diagram 6
• Examples - Diagram 7
• Lesson Index - Diagram 8