DEMO CASE STUDY

Cassava Processing Investment Analysis

How the framework identified 8 major blindspots in a $2.5M agro-processing opportunity—potentially saving 18 months and millions in capital.

Investment Scenario (Anonymized Real Pattern)

Sector

Agro-processing (Cassava to flour)

Region

West Africa (Nigeria/Ghana border)

Investment Size

$2.5M equity

Investor Profile

Diaspora consortium

Analysis Timeline

12 hours over 3 days

Framework Modules Used

6 of 17 modules

Initial Pitch Summary

  • ✓ Growing cassava production in region (400,000 tons/year)
  • ✓ High-quality flour demand from regional bakeries
  • ✓ Government support for local value-addition
  • ✓ Strong local partnerships in place
  • ✓ Export potential to neighboring markets

Projected ROI: 35% annually, 3-year payback

Important Disclaimer

This case study is anonymized and represents a common pattern observed across multiple real agro-processing investment proposals. It is illustrative of framework methodology, not a specific client engagement. Details have been modified to protect confidentiality while preserving analytical patterns.

Framework Application: Module-by-Module Analysis

PHASE 1: Market Assessment (Module 1.1)

Evaluating supply availability and market accessibility

Stated Opportunity

  • Local cassava production: 400,000 tons/year
  • Processing capacity gap: 75%
  • Flour import substitution value: $180M

From the pitch deck: "With abundant cassava production in the region and strong government support for value-addition, this processing facility will capture import substitution demand while creating 500+ local jobs. The opportunity is clear: turn agricultural waste into profitable flour production."

Framework Process: Reality Check Questions

  • What % of cassava is already committed (contracts, local consumption)?
  • What's actual surplus available for processing?
  • What's transport cost from farm to facility?
  • What % of production meets quality standards?

BLINDSPOT #1: Aggregation Assumption

Pitch assumes: 400,000 tons available for processing

Reality discovered:

  • 85% already committed to local food supply chains
  • Only 15% (60,000 tons) is genuine surplus
  • Of surplus, only 40% meets processing quality standards
  • Accessible supply: 24,000 tons (6% of stated)

Impact: Business case built on 400k tons. Actual accessible: 24k tons. That's a 94% overestimation.

BLINDSPOT #2: Hidden Transport Economics

Pitch shows: $0.05/kg transport cost (from government study)

Reality discovered:

  • Study based on paved road assumption
  • 70% of production is from unpaved rural roads
  • Real transport cost: $0.18/kg dry season
  • Rainy season transport cost: $0.32/kg
  • Transport cost exceeds processing margin

Impact: Economics only work for farms within 40km of facility. Reduces accessible supply further to ~9,000 tons/year. Minimum viable processing: 15,000 tons/year.

GAP: 60% below minimum viable scale

Decision Implication from Phase 1

Available economically viable supply: ~9,000 tons/year
Minimum viable processing: 15,000 tons/year
Gap: 60% below minimum viable scale

PHASE 2: Political Economy Analysis (Module 2.2)

Mapping power structures and stakeholder incentives

Stated Support

  • Government "strongly supports" local value-addition
  • Tax holidays for processors
  • Import restrictions on flour

Framework Process: Power Mapping

  • Who profits from current flour imports?
  • Who loses if local processing succeeds?
  • Who has political capital to block new entrants?

BLINDSPOT #3: Import Restriction Reality

Stated: Flour imports restricted to support local processing

Reality discovered:

  • 3 import licenses held by politically connected families
  • "Restriction" applies to everyone else, not license holders
  • Existing importers will resist local competition
  • Have blocked 2 previous processing investments via regulatory delays
  • Can delay facility approvals, environmental permits, customs clearance

Impact: Political resistance from entrenched interests with power to block through bureaucratic delays.

BLINDSPOT #4: Government "Support" Reality

Stated: Tax holiday, infrastructure investment, electricity subsidy

Reality discovered:

  • Tax holiday: Real (for first 5 years) ✓
  • Infrastructure investment: Announced 3 years ago, not started ✗
  • Electricity subsidy: Only for facilities >50,000 tons/year capacity ✗
  • Support exists, but only for scale you cannot achieve

Impact: Government support is real but inaccessible at your realistic scale (9,000 tons vs. 50,000 tons required).

Decision Implication from Phase 2

Political risk of regulatory blockage: HIGH
Actual government support for your scale: LOW

PHASE 3: Infrastructure Reality (Module 3.1)

Testing infrastructure dependencies against actual conditions

Stated Infrastructure

  • National grid electricity available
  • 95% uptime (per government data)
  • Cold storage available at port for export

From local partner: "The industrial zone has excellent infrastructure. The government report shows 95% grid reliability, and the new cold storage facility at the port makes export logistics straightforward."

Framework Process: Infrastructure Dependency Mapping

  • What breaks if electricity fails?
  • What's backup cost?
  • What's real uptime in practice (not official data)?
  • What's cold chain reality vs. stated availability?

BLINDSPOT #5: Electricity Reality

Government data: 95% uptime (urban average)

Reality discovered:

  • Industrial zone reality: 60-70% uptime
  • Processing requires: 18-20 hours continuous power/day
  • Diesel backup cost: $0.09/kWh
  • Backup power doubles operating cost
  • Makes product uncompetitive vs. imports

Impact: Unit economics dependent on unreliable infrastructure. Cannot compete on cost with imported flour that doesn't carry backup power expense.

Framework Reality Check - Interview with neighboring factory manager: "Government says 95%? Maybe in the capital. Here we run diesel 8-10 hours daily. Some weeks it's 12 hours. Your backup cost will be 40-50% of your power budget, not 5% like you modeled."

BLINDSPOT #6: Cold Chain Assumption

Stated: Cold storage at port, export-ready infrastructure

Reality discovered:

  • Flour requires temperature-controlled storage and transport
  • Cold storage exists but has 8-month waiting list
  • Cold transport exists but costs 3x normal transport
  • Export economics non-viable due to cold chain costs

Impact: Export strategy (30% of business plan revenue) not feasible. Must sell 100% locally where competition is strongest.

Decision Implication from Phase 3

Infrastructure risk makes unit economics uncompetitive
Export strategy not feasible
Must compete 100% in local market (hardest segment)

PHASE 4: Stakeholder Dynamics (Module 4.1)

Mapping stakeholder incentives and alignment

Stated Partnerships

  • "Strong local partners" committed
  • Community support confirmed
  • Government backing secured

Framework Process: Stakeholder Incentive Mapping

  • What does each party actually gain?
  • What are hidden motivations?
  • Where are conflicting interests?
  • What happens to each party if project fails?

BLINDSPOT #7: Partner Motivation

Stated: Local partner committed to operational success

Reality discovered:

  • Local partner: Real estate developer (not agro-processor)
  • True interest: Facility increases land value of adjacent plots he owns
  • Partner brings: Land and political connections (valuable)
  • Partner expects: 30% equity for land + connections
  • Partner has: No agro-processing experience
  • Partner incentive = land appreciation, not operational success

Impact: Partner profits even if operation fails (through land value increase). Incentives misaligned with operational excellence.

BLINDSPOT #8: Community "Support"

Stated: Community welcomes investment, full support

Reality discovered:

  • Community was promised: 500 jobs
  • Facility reality: 45 full-time jobs
  • Seasonal peak: 120 jobs
  • Expectation gap: 10x overpromise
  • Historical pattern: 2 previous factories faced community blockades over job promises
  • Setting up for social license to operate crisis

Impact: Community expectations impossible to meet. Risk of protests, access blockades, political pressure when reality becomes clear.

Decision Implication from Phase 4

Stakeholder expectations misaligned with reality
Partner incentives not aligned with operations
Social license to operate at high risk

Framework Output: Decision Memo

DECISION MEMO: CASSAVA PROCESSING INVESTMENT ASSESSMENT EXECUTIVE SUMMARY: HIGH-RISK / LIKELY NON-VIABLE CORE FINDING: Initial pitch contains 8 major blindspots that fundamentally alter investment economics and risk profile. CRITICAL BLINDSPOTS IDENTIFIED: 1. Supply Availability: 6% of stated (not 100%) - Stated: 400,000 tons available - Reality: 24,000 tons accessible - Economically viable: 9,000 tons 2. Transport Economics: 3.6x higher than stated - Stated: $0.05/kg - Reality: $0.18-0.32/kg - Impact: Only 40km radius economically viable 3. Political Resistance: Import license holders will block - 3 families control flour import licenses - History of blocking previous processing investments - Bureaucratic delay capacity confirmed 4. Government Support: Exists but not for your scale - Subsidies require 50,000+ tons/year capacity - You can access 9,000 tons/year maximum - Tax holiday is real, other support inaccessible 5. Infrastructure Dependency: 60% uptime vs. 95% claimed - Government data: 95% (urban average) - Industrial reality: 60-70% - Backup power doubles operating cost 6. Export Viability: Cold chain costs prohibitive - 8-month waitlist for cold storage - Cold transport 3x normal cost - Export plan (30% revenue) not viable 7. Partner Alignment: Land play, not operational commitment - Partner is real estate developer - Profits from land appreciation regardless of ops success - No agro-processing experience 8. Community Expectations: 10x gap creates social risk - Promised: 500 jobs - Reality: 45 full-time jobs - Historical pattern: Blockades over job promises REVISED ECONOMICS: Metric | Pitch | Framework Analysis ------------------------|-----------------|------------------- Available supply | 400,000 tons | 24,000 tons Processing capacity | 50,000 tons/yr | 9,000 tons viable Transport cost | $0.05/kg | $0.18-0.32/kg Electricity uptime | 95% | 60-70% Backup power cost | Not modeled | Doubles op-cost Export revenue | 30% of total | 0% (non-viable) Unit economics | Profitable | Marginally negative Political risk | Low | High Exit options | Export/sale | Very limited Social license risk | Low | High DECISION RECOMMENDATION: DO NOT PROCEED with current structure. ALTERNATIVE PATHWAYS (if must pursue): Option A: Radical Scale-Down • Target: 12-15k tons/year (not 50k) • Model: Contract farming within 30km radius only • Market: Local only (abandon export plan) • Partner: Operating partner with agro experience, not land partner • Capital: $800k (not $2.5M) • Risk: Still faces political resistance + infrastructure issues Option B: Different Crop/Location • Framework reveals: Cassava + This Region = structural issues • Consider: Same processing model + different crop/region • Requires: New market assessment with framework Option C: Pass (Recommended) • Most prudent given blindspot density • Framework revealed: Opportunity not as pitched • Capital preserved for better opportunities TIME & CAPITAL SAVED: • Framework analysis: 12 hours over 3 days • Alternative: 18 months to discover via execution • Capital preserved: $2.5M • Learning: Systematic blindspot identification works KEY LEARNING FOR DIASPORA INVESTORS: This case demonstrates 4 common diaspora blindspots: 1. Aggregation blindspot: Assume all production available 2. Infrastructure optimism: Believe government data 3. Partnership trust: Assume aligned incentives 4. Scale miscalculation: Bigger = better assumption All four patterns present in this case.

What This Case Study Demonstrates

1. Systematic Blindspot Identification

Not random questions. Structured across all modules. Reveals hidden dependencies systematically.

2. Political Economy Integration

Goes beyond market analysis. Identifies who profits/loses. Reveals true barriers.

3. Reality-Based Analysis

Challenges stated assumptions. Applies regional knowledge. Adjusts for real conditions.

4. Decision Architecture

Clear GO/NO-GO framework. Alternative pathways. Risk-adjusted recommendations.

5. Time Compression

12 hours vs. 18 months. Structured vs. trial-and-error. Learning without losing capital.

6. Reusable Process

Same framework applies to next opportunity. Build capability, don't just analyze once.

Important Case Study Disclaimers

This Case Study Is:

  • ✓ Anonymized real pattern (not specific client)
  • ✓ Illustrative of framework application methodology
  • ✓ Based on common blindspot patterns observed
  • ✓ Representative of systematic approach

This Case Study Is NOT:

  • ✗ Specific investment advice for cassava processing
  • ✗ Guarantee of framework results in all cases
  • ✗ Exhaustive analysis (full analysis uses all 17 modules)
  • ✗ Substitute for professional due diligence

Your Analysis Will:

• Be specific to your investment opportunity
• Require your inputs and supplementary research
• Need additional investigation where framework identifies gaps
• Benefit from combining framework with local expertise

Framework's Role:

The framework structures your analysis, identifies blindspots systematically, and provides decision architecture. It does NOT analyze for you—you remain the researcher, decision-maker, and risk-taker.

Ready to Apply This to Your Investments?

This case study showed just 6 of 17 modules. See how the complete framework works, review sample content, or understand the methodology.

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