Feasibility Analysis
Separate viable projects from wishful thinking
Your Progress
Section 3 of 5The $10 Million Question
Can this actually work? Not in theory—in the messy reality of implementation.
The brutal truth: 40% of sustainability projects fail due to feasibility issues that should have been caught during design. Technology that works in a lab fails in the field. Business models that pencil out on spreadsheets collapse under real-world constraints.
🎯 Five Dimensions of Feasibility
A project must pass all five tests. One weak dimension can sink the entire initiative.
Technical
Does the technology work reliably? Can it be maintained locally? Are supply chains robust?
Financial
Can you afford upfront costs? Is the revenue model viable? What's the path to sustainability?
Social
Will people accept and use it? Does it create or reduce inequality? What behavior change is required?
Environmental
How much climate impact? What co-benefits? Any unintended environmental harms?
Institutional
Do policies enable or block this? Can you get permits? Are partners committed?
📋 Interactive: Feasibility Scorecard
Rate your project across 15 weighted criteria. Higher weights indicate deal-breaker factors. Be brutally honest—overconfidence at this stage wastes resources later.
Technical Feasibility
Financial Feasibility
Social Feasibility
Environmental Feasibility
Institutional Feasibility
Rate all 15 criteria to calculate feasibility
⚠️ Seven Feasibility Red Flags
1. "Technology Will Improve"
Betting on future tech breakthroughs. Design for what exists today, not what might exist tomorrow.
2. "Build It and They Will Come"
Assuming demand without validation. Test adoption hypotheses early and often.
3. "We'll Figure It Out Later"
Deferring hard questions (O&M, revenue, governance). These don't get easier—they get more expensive.
4. Single Point of Failure
Project depends on one funder, partner, or approval. Always have backup options.
5. Ignoring Local Context
Copy-pasting solutions from elsewhere. What works in Berlin may fail in Bangalore.
6. Underestimating Time/Cost
Optimistic projections without buffers. Rule of thumb: double the time, add 30% to budget.
7. No Exit Strategy
What if it doesn't work? Define failure criteria and pivot/stop conditions upfront.
📚 Case Study: The $50M Lesson
The Idea
Major foundation funded a $50M program to distribute advanced cookstoves across East Africa. Technology was proven in labs. Financial model showed strong ROI. Impact projections were impressive.
The Reality Check
After 3 years and $15M spent:
- • Only 30% of stoves still in use (technical: local technicians couldn't repair ceramic liners)
- • 40% resold immediately (financial: upfront cost too high despite subsidies)
- • Cultural resistance (social: traditional cooking methods tied to identity)
- • Supply chain collapsed (institutional: import permits constantly delayed)
What Went Wrong
Feasibility analysis checked boxes but didn't dig deep:
- • Lab tests ≠ field durability testing
- • Willingness-to-pay surveys ≠ actual payment behavior
- • Partner MOUs ≠ operational capacity
- • No pilot phase to test assumptions
The Pivot
Program shifted to locally-manufactured stoves (technical feasibility), pay-as-you-go financing (financial feasibility), and co-design with women's groups (social feasibility). New model achieved 85% sustained adoption.
Lesson: Would have saved $35M by doing rigorous feasibility before scale-up.
🛠️ Feasibility Testing Toolkit
Rapid Prototyping
Build cheap, fast versions to test core assumptions. Fail small before spending big.
Pre-Mortem Analysis
Imagine the project failed spectacularly. Work backward: what went wrong?
Red Team Review
Have skeptics tear apart your assumptions. Pressure-test every claim.
Comparable Case Research
Find similar projects. What worked? What failed? Talk to implementers.