| name | feasibility-analysis |
| description | Project feasibility analysis toolkit. Evaluate technical feasibility, resource requirements, market viability, risk factors, and implementation challenges for informed go/no-go decisions on software projects. |
| allowed-tools | ["Read","Write","Edit","Bash"] |
Project Feasibility Analysis
Overview
Feasibility analysis is a systematic process for evaluating whether a proposed software project is viable and worth pursuing. Assess technical feasibility, resource requirements, market viability, risk factors, and implementation challenges. Apply this skill to make informed go/no-go decisions before committing resources.
When to Use This Skill
This skill should be used when:
- Evaluating new project proposals for viability
- Assessing technical feasibility of proposed features
- Analyzing resource requirements and constraints
- Conducting market viability assessments
- Identifying potential blockers and deal-breakers
- Comparing multiple project options
- Preparing feasibility reports for stakeholders
Visual Enhancement with Project Diagrams
When creating feasibility documents, consider adding diagrams for clarity.
Use the project-diagrams skill to generate:
- Feasibility decision trees
- Risk assessment matrices
- Resource requirement diagrams
- Technical architecture feasibility maps
- Market positioning charts
python .claude/skills/project-diagrams/scripts/generate_schematic.py "diagram description" -o diagrams/output.png
Feasibility Analysis Framework
Conduct feasibility analysis systematically through multiple dimensions.
1. Technical Feasibility
Evaluate whether the project can be built with available technology and expertise.
Technology Readiness Assessment
| Readiness Level | Description | Risk |
|---|
| Mature | Production-proven, widely used | Low |
| Established | Production-ready, growing adoption | Low-Medium |
| Emerging | Early adoption, limited production use | Medium |
| Experimental | Pre-production, research phase | High |
| Theoretical | Conceptual, not yet implemented | Very High |
For each core technology, assess:
- Current maturity level
- Community and vendor support
- Documentation quality
- Talent availability in market
- Long-term viability
Technical Complexity Assessment
Complexity Factors:
| Factor | Low | Medium | High |
|---|
| Integration points | 1-3 | 4-7 | 8+ |
| Data sources | 1-2 | 3-5 | 6+ |
| Custom algorithms | None | Some | Significant |
| Real-time requirements | None | Partial | Critical |
| Scale requirements | <1K users | 1K-100K | >100K |
| Security requirements | Basic | Standard | Stringent |
| Compliance requirements | None | Industry | Regulatory |
Complexity Score: Sum factors and categorize:
- 0-7: Low complexity (straightforward implementation)
- 8-14: Medium complexity (manageable with expertise)
- 15-21: High complexity (significant challenges expected)
- 22+: Very high complexity (consider scope reduction)
Technical Risk Factors
Identify and rate (1-5) these risks:
- Unproven architecture: Novel patterns without precedent
- Integration complexity: Many external system dependencies
- Performance uncertainty: Unclear if requirements are achievable
- Scalability concerns: Uncertainty about growth handling
- Security challenges: Complex threat model or compliance needs
- Data complexity: Large, unstructured, or sensitive data
- Algorithm novelty: Custom ML/AI or complex logic required
Risk Mitigation Questions:
- Have similar systems been built successfully?
- Are there proven patterns we can follow?
- Can we prototype high-risk components early?
- What are fallback options if primary approach fails?
2. Resource Feasibility
Evaluate whether required resources (people, time, money) are available.
Team Capability Assessment
Required Skills Inventory:
| Skill Area | Required Level | Current Level | Gap |
|---|
| Frontend development | | | |
| Backend development | | | |
| DevOps/Infrastructure | | | |
| Database/Data engineering | | | |
| Security | | | |
| Domain expertise | | | |
| Project management | | | |
Levels: None, Basic, Intermediate, Advanced, Expert
Gap Analysis:
- Critical gaps (show-stoppers)
- Important gaps (require hiring/training)
- Minor gaps (manageable with learning)
Timeline Feasibility
Timeline Estimation Factors:
| Factor | Multiplier |
|---|
| Clear requirements | 1.0x |
| Partially defined requirements | 1.3x |
| Evolving requirements | 1.5x |
| Experienced team with stack | 1.0x |
| Team learning new technologies | 1.3x |
| Team new to domain | 1.5x |
| Greenfield project | 1.0x |
| Legacy integration | 1.3x |
| Legacy replacement | 1.5x |
Timeline Reality Check:
- Apply multipliers to initial estimates
- Add 20-30% buffer for unknowns
- Compare to similar past projects
- Identify hard deadlines and assess achievability
Budget Feasibility
Cost Categories to Estimate:
cost_categories:
development:
- Personnel (internal team)
- Contractors/consultants
- Training and upskilling
infrastructure:
- Cloud services (compute, storage, networking)
- Development environments
- CI/CD tooling
third_party:
- SaaS subscriptions
- API costs
- Licensing fees
operational:
- Monitoring and observability
- Support tooling
- Security tools
contingency:
- Risk buffer (15-25%)
- Scope buffer (10-20%)
Budget Viability Assessment:
- Total estimated cost vs. available budget
- Cash flow timing requirements
- Hidden costs identification
- Cost overrun scenarios
3. Market Feasibility
Evaluate whether the project addresses a real market need.
Market Need Assessment
Key Questions:
- Is there demonstrated demand for this solution?
- What problem does it solve, and how painful is that problem?
- Who are the target users, and can we reach them?
- What is the market size (TAM, SAM, SOM)?
- Is the market growing, stable, or declining?
Competitive Landscape Analysis
Competitor Assessment Matrix:
| Competitor | Strengths | Weaknesses | Our Differentiation |
|---|
| | | |
Competitive Position Questions:
- Who are the main competitors?
- What is our unique value proposition?
- Can we compete on features, price, or experience?
- Are there barriers to entry?
- Is there room for another player?
Market Timing Assessment
| Timing | Description | Implication |
|---|
| Too early | Market not ready, user education needed | High risk, long runway required |
| Early | Market emerging, first-mover advantage possible | Medium risk, faster execution helps |
| Right time | Market established, clear demand | Lower risk, differentiation critical |
| Late | Market saturated, incumbents entrenched | High risk, disruption required |
4. Operational Feasibility
Evaluate whether the project can be successfully deployed and operated.
Organizational Readiness
Assess the organization's ability to:
- Adopt new technology and processes
- Support the solution post-launch
- Handle change management requirements
- Maintain the solution long-term
Operational Requirements
Key Operational Factors:
| Factor | Requirement | Current Capability | Gap |
|---|
| 24/7 operations | | | |
| Incident response | | | |
| User support | | | |
| Data backup/recovery | | | |
| Security monitoring | | | |
| Performance monitoring | | | |
| Compliance reporting | | | |
Integration Feasibility
For each required integration:
| System | Integration Type | Complexity | Risk |
|---|
| API / File / DB / Event | Low/Med/High | |
Integration Risk Factors:
- API stability and documentation quality
- Authentication/authorization complexity
- Data format compatibility
- Rate limits and quotas
- Vendor reliability and support
5. Legal and Compliance Feasibility
Evaluate regulatory, legal, and compliance requirements.
Regulatory Requirements
Common Compliance Frameworks:
| Framework | Applicability | Effort |
|---|
| GDPR | EU personal data | High |
| HIPAA | US healthcare data | Very High |
| SOC 2 | B2B SaaS | Medium-High |
| PCI-DSS | Payment card data | High |
| CCPA | California consumer data | Medium |
Compliance Assessment:
- Which regulations apply?
- What controls are required?
- What certifications are needed?
- What is the timeline and cost for compliance?
Intellectual Property Considerations
- Are there patent concerns?
- Are there licensing restrictions on dependencies?
- Do we have rights to required data?
- Are there trademark considerations?
Feasibility Scoring
Overall Feasibility Score
Rate each dimension (1-5):
| Dimension | Score | Weight | Weighted Score |
|---|
| Technical Feasibility | | 25% | |
| Resource Feasibility | | 25% | |
| Market Feasibility | | 20% | |
| Operational Feasibility | | 15% | |
| Legal/Compliance Feasibility | | 15% | |
| Total | | 100% | |
Score Interpretation:
| Total Score | Recommendation |
|---|
| 4.0-5.0 | Strong Go - Proceed with confidence |
| 3.0-3.9 | Conditional Go - Proceed with mitigations |
| 2.0-2.9 | Caution - Address significant concerns first |
| 1.0-1.9 | No Go - Major barriers, reconsider or pivot |
Go/No-Go Decision Criteria
Automatic No-Go Triggers:
- Critical technology not available or unproven
- Required skills unavailable and unhirable
- Budget shortfall >50%
- Timeline impossible for hard deadline
- Regulatory showstopper
- Market doesn't exist
Conditional Go Requirements:
- All critical risks have mitigation plans
- Resource gaps have remediation paths
- Timeline achievable with buffer
- Budget within 20% of estimate
- Clear path to market
Feasibility Report Structure
Executive Summary
- Project overview (2-3 sentences)
- Overall feasibility score and recommendation
- Key strengths (2-3 bullets)
- Critical concerns (2-3 bullets)
- Go/No-Go recommendation with conditions
Detailed Analysis
For each feasibility dimension:
- Score and rationale
- Key findings
- Risks identified
- Recommendations
Risk Register
| Risk | Category | Likelihood | Impact | Score | Mitigation |
|---|
| | | | | |
Recommendations
If Go:
- Required actions before starting
- Risk mitigations to implement
- Key success factors
- Monitoring metrics
If No-Go:
- Primary blockers
- What would need to change
- Alternative approaches to consider
- Potential pivot options
Appendices
- Detailed cost estimates
- Technology assessment details
- Competitive analysis data
- Compliance requirements checklist
Decision Framework Templates
Technical Feasibility Decision Tree
Is core technology production-ready?
├── No → Can we use proven alternatives?
│ ├── No → HIGH RISK / Consider No-Go
│ └── Yes → Evaluate alternatives
└── Yes → Do we have required expertise?
├── No → Can we hire/train in time?
│ ├── No → MEDIUM-HIGH RISK
│ └── Yes → Add to resource plan
└── Yes → Are there integration risks?
├── Yes → Prototype integrations early
└── No → LOW TECHNICAL RISK
Resource Feasibility Decision Tree
Is budget sufficient for scope?
├── No → Can scope be reduced?
│ ├── No → No-Go or find additional funding
│ └── Yes → Reprioritize features
└── Yes → Is team available?
├── No → Can we hire in time?
│ ├── No → Extend timeline or reduce scope
│ └── Yes → Add hiring to plan
└── Yes → Is timeline realistic?
├── No → Negotiate deadline or reduce scope
└── Yes → RESOURCE FEASIBLE
Best Practices
Do's
- Use real data and research, not assumptions
- Involve stakeholders in assessment
- Document all assumptions
- Consider multiple scenarios (optimistic, realistic, pessimistic)
- Update feasibility as new information emerges
- Be honest about uncertainties
Don'ts
- Don't let confirmation bias drive conclusions
- Don't ignore red flags or inconvenient findings
- Don't rely on single points of failure
- Don't assume best-case scenarios
- Don't skip dimensions because they seem "obvious"
- Don't conflate feasibility with desirability
Final Checklist
Before completing feasibility analysis:
