🎯 Learning Objectives
By the end of this lesson, you will be able to:
Break down complex social challenges
Systematically analyze any social issue by identifying root causes, defining the core problem clearly, and mapping consequences across different time horizons and impact levels.
Use AI strategically for research
Leverage AI tools through the Model Context Protocol (MCP) to accelerate desk review while maintaining research rigor, source credibility, and analytical integrity.
Build a preliminary Problem Tree
Create a structured Problem Tree that clearly separates evidence-based findings from assumptions requiring validation, providing transparency for stakeholders and funders.
Prepare targeted validation questions
Convert assumptions into open-ended, non-leading questions that guide meaningful stakeholder conversations and community engagement in Lesson 1.2.
Create a foundation for project design
Establish a solid analytical foundation that will inform every subsequent step: stakeholder mapping, Theory of Change, logframe development, activity design, and proposal writing.
💡 Skills You Will Gain
Analytical Skills
- → Systems thinking: Understanding how causes, problems, and effects interconnect
- → Root cause analysis: Going 2-3 levels deep with "Why?" questioning
- → Evidence evaluation: Assessing source credibility and relevance
- → Pattern recognition: Identifying themes across multiple causes and effects
Research Skills
- → AI prompt engineering: Structuring effective prompts using the MCP framework
- → Desk review methodology: Conducting efficient secondary research
- → Source verification: Checking credibility, recency, and context fit
- → Knowledge gap identification: Recognizing what you don't know and need to validate
Communication Skills
- → Problem framing: Articulating problems without embedded causes or solutions
- → Stakeholder question design: Crafting open-ended, non-leading questions
- → Visual documentation: Creating clear tree diagrams for presentations and proposals
- → Assumption transparency: Clearly flagging what's evidence vs. what needs validation
📚 Prerequisites
Prerequisites
- Basic understanding of social impact work: Familiarity with nonprofit, NGO, or social enterprise contexts
- Access to AI tools: ChatGPT (free or paid), Claude, or similar for MCP research (optional but recommended)
- Problem area identified: A general sense of the social issue you want to address
Helpful (But Not Required)
- Research experience: Prior desk review or literature review work is helpful but not necessary
- Project management basics: Understanding of project planning concepts makes connections clearer
- Stakeholder relationships: Existing connections to community members or partners will help in Lesson 1.2
⏱️ Time Commitment
📦 What This Lesson Includes
5-Minute Video Overview
Visual demonstration with timing markers and real examples
Problem Tree Framework
Complete guide to causes, core problem, and effects analysis
AI-Assisted Research Guide
Model Context Protocol integration for desk review
Downloadable Templates
Problem Tree worksheet and validation question generator
Real-World Examples
Nigeria Youth Livelihood Problem Tree case study
Quality Checklist
Standards for evidence-based analysis
How This Connects to Other Lessons
Problem Tree Analysis is the foundation that everything else builds on:
graph TD
%% Foundation - Lesson 1.1
L11["📚 LESSON 1.1
Problem Tree Analysis
• Define core problem
• Map root causes
• Identify effects
• Tag evidence (E) vs assumptions (A)"]
%% Module 1 - Building Foundation
L12["🗺️ LESSON 1.2
Stakeholder Mapping
• Validate assumptions
from Problem Tree"]
L13["📊 LESSON 1.3
Synthesize Data
• Refine Problem Tree
with stakeholder insights"]
L14["🎯 LESSON 1.4
Theory of Change
• Flip Problem Tree
into positive pathway"]
%% Module 2 - Operationalize
MOD2["🚀 MODULE 2: Operationalize
Your cause-effect logic becomes
the backbone for all operations"]
L21["📋 Lesson 2.1
Logical Framework
(Causes → Outputs)"]
L22["⚙️ Lesson 2.2
Activity Design
(Target root causes)"]
L23["✍️ Lesson 2.3
Proposal Writing
(Problem section ready)"]
L24["💰 Lesson 2.4
Budget Estimation
(Costs linked to causes)"]
%% Relationships - Flow from foundation
L11 --> L12
L11 --> L13
L11 --> L14
L12 --> MOD2
L13 --> MOD2
L14 --> MOD2
MOD2 --> L21
MOD2 --> L22
MOD2 --> L23
MOD2 --> L24
%% Festa Design System Colors
%% Foundation - Pot of Gold (critical starting point)
style L11 fill:#F59E0B,stroke:#D97706,stroke-width:4px,color:#1F2937,font-weight:bold
%% Module 1 Lessons - Pepper Green (building blocks)
style L12 fill:#10B981,stroke:#059669,stroke-width:2px,color:#fff
style L13 fill:#10B981,stroke:#059669,stroke-width:2px,color:#fff
style L14 fill:#10B981,stroke:#059669,stroke-width:2px,color:#fff
%% Module 2 Container - Leaf (practical application)
style MOD2 fill:#72B043,stroke:#5A8F36,stroke-width:3px,color:#fff,font-weight:bold
%% Module 2 Lessons - Leaf lighter shade
style L21 fill:#84C556,stroke:#72B043,stroke-width:1px,color:#fff
style L22 fill:#84C556,stroke:#72B043,stroke-width:1px,color:#fff
style L23 fill:#84C556,stroke:#72B043,stroke-width:1px,color:#fff
style L24 fill:#84C556,stroke:#72B043,stroke-width:1px,color:#fff
💡 The Learning Journey
Lesson 1.1 (shown in gold) is the foundational lesson that everything else builds upon. Your Problem Tree directly feeds into stakeholder validation, data synthesis, and Theory of Change. These three lessons converge to inform all Module 2 operational activities—logframes, activities, proposals, and budgets.
⚠️ Common Pitfall
Many projects skip or rush problem analysis, jumping straight to solutions. This leads to unfocused interventions, weak proposals, and missed opportunities. Invest time here—it pays dividends throughout your project design process.
🚀 Ready to Start?
Ready to Start?
Now that you understand what you'll learn, move to Why This Matters to see real-world impact of strong vs. weak problem analysis, then dive into the core methodologies.