KODA Project - Risk Management Plan
Comprehensive Risk Identification, Assessment & Mitigation Strategy
Table of Contents
Executive Summary
Risk Profile Overview
24
Total Risks Identified
6
Critical Risks
11
High Priority
7
Medium Priority
Risk Distribution by Category
| Risk Category | Critical | High | Medium | Total |
|---|---|---|---|---|
| Technical Risks | 2 | 4 | 1 | 7 |
| Schedule Risks | 1 | 2 | 1 | 4 |
| Resource & Team | 1 | 2 | 1 | 4 |
| External Dependencies | 1 | 1 | 1 | 3 |
| Quality & Security | 1 | 1 | 2 | 4 |
| Business & Operations | 0 | 1 | 1 | 2 |
| TOTAL | 6 | 11 | 7 | 24 |
Top 5 Critical Risks
- Multi-Tenancy Data Isolation Failure (R-T-001) - Complete data segregation breach
- AI Integration Complexity (R-T-002) - Google AI Studio API limitations
- Backend Lead Single Point of Failure (R-R-001) - No backup for critical expertise
- Third-Party API Failures (R-E-001) - WhatsApp Business API instability
- Security Vulnerability in Production (R-Q-001) - Data breach risk
- Aggressive Timeline (R-S-001) - Scope vs. deadline mismatch
Risk Management Methodology
Risk Management Process
- Risk Identification: Continuous throughout project lifecycle
- Risk Analysis: Qualitative assessment (Probability × Impact)
- Risk Response Planning: Mitigation, avoidance, transfer, acceptance
- Risk Monitoring: Weekly review in team meetings
- Risk Reporting: Monthly executive summary
Risk Probability Scale
| Level | Probability | Score | Description |
|---|---|---|---|
| Very Low | 0-10% | 1 | Highly unlikely to occur |
| Low | 11-30% | 2 | Unlikely but possible |
| Medium | 31-50% | 3 | Moderate chance of occurrence |
| High | 51-70% | 4 | Likely to occur |
| Very High | 71-100% | 5 | Almost certain to occur |
Risk Impact Scale
| Level | Schedule Impact | Cost Impact | Quality Impact | Score |
|---|---|---|---|---|
| Very Low | <1 week delay | <2% budget | Negligible | 1 |
| Low | 1-2 weeks delay | 2-5% budget | Minor issues | 2 |
| Medium | 2-4 weeks delay | 5-10% budget | Moderate defects | 3 |
| High | 1-2 months delay | 10-20% budget | Major defects | 4 |
| Very High | >2 months delay | >20% budget | Critical failure | 5 |
Risk Priority Matrix
Risk Score = Probability × Impact
- Critical (20-25): Immediate action required
- High (12-16): Active mitigation needed
- Medium (6-10): Monitor and plan mitigation
- Low (3-5): Monitor only
- Very Low (1-2): Accept risk
Risk Register Summary
All Identified Risks
| ID | Risk Title | Category | Probability | Impact | Score | Priority |
|---|---|---|---|---|---|---|
| R-T-001 | Multi-Tenancy Data Isolation Failure | Technical | Medium (3) | Very High (5) | 15 | Critical |
| R-T-002 | AI Integration Complexity | Technical | High (4) | High (4) | 16 | Critical |
| R-T-003 | Database Performance Issues | Technical | High (4) | Medium (3) | 12 | High |
| R-T-004 | Mobile App Platform Inconsistencies | Technical | High (4) | Medium (3) | 12 | High |
| R-T-005 | Payment Gateway Integration Issues | Technical | Medium (3) | High (4) | 12 | High |
| R-T-006 | Real-time Chat System Scalability | Technical | Medium (3) | High (4) | 12 | High |
| R-T-007 | Complex Booking Logic Bugs | Technical | Medium (3) | Medium (3) | 9 | Medium |
| R-S-001 | Aggressive Timeline | Schedule | Very High (5) | High (4) | 20 | Critical |
| R-S-002 | Phase 1 Mobile App Delay | Schedule | High (4) | High (4) | 16 | High |
| R-S-003 | Backend API Delays | Schedule | High (4) | High (4) | 16 | High |
| R-S-004 | Testing Phase Compression | Schedule | Medium (3) | Medium (3) | 9 | Medium |
| R-R-001 | Backend Lead Single Point of Failure | Resource | Medium (3) | Very High (5) | 15 | Critical |
| R-R-002 | Team Member Turnover | Resource | Medium (3) | High (4) | 12 | High |
| R-R-003 | Flutter Developer Availability | Resource | Medium (3) | High (4) | 12 | High |
| R-R-004 | Part-time DevOps Insufficient | Resource | Low (2) | Medium (3) | 6 | Medium |
| R-E-001 | Third-Party API Failures | External | High (4) | High (4) | 16 | Critical |
| R-E-002 | Google AI Studio Rate Limits | External | High (4) | Medium (3) | 12 | High |
| R-E-003 | Payment Gateway Approval Delays | External | Medium (3) | Medium (3) | 9 | Medium |
| R-Q-001 | Security Vulnerability in Production | Security | Medium (3) | Very High (5) | 15 | Critical |
| R-Q-002 | Insufficient Testing Coverage | Quality | High (4) | High (4) | 16 | High |
| R-Q-003 | GDPR Compliance Issues | Compliance | Low (2) | High (4) | 8 | Medium |
| R-Q-004 | Performance Not Meeting SLAs | Quality | Medium (3) | Medium (3) | 9 | Medium |
| R-B-001 | Scope Creep | Business | High (4) | High (4) | 16 | High |
| R-B-002 | Budget Overrun | Financial | Medium (3) | Medium (3) | 9 | Medium |
Technical Risks (Detailed)
Critical R-T-001: Multi-Tenancy Data Isolation Failure
| Description | Data from one salon/spa leaks to another due to inadequate tenant isolation in database queries |
| Probability | Medium (3) - 40% |
| Impact | Very High (5) - Complete data breach, legal liability, platform shutdown |
| Risk Score | 15 (Critical) |
| Triggers |
• Missing WHERE tenant_id clauses in queries • Shared sessions across tenants • Cache key collisions • API endpoint not filtering by tenant |
| Mitigation Strategy |
PREVENT: • Mandatory database middleware enforcing tenant_id filter • Global query scopes in ORM (Laravel/Eloquent) • Database row-level security (RLS) policies • Separate database schemas per tenant (if feasible) • Code review checklist for all queries DETECT: • Automated tests for cross-tenant data access • Penetration testing focused on multi-tenancy • Database query logging and monitoring • Security audit before each phase launch |
| Contingency Plan |
• Immediate platform shutdown if breach detected • Data forensics to identify affected tenants • Notify affected customers within 72 hours (GDPR) • Implement emergency patch • Full security re-audit before resuming operations |
| Owner | Backend Lead + Project Manager |
| Review Frequency | Weekly |
Critical R-T-002: AI Integration Complexity (Google AI Studio)
| Description | Google AI Studio API may not support required Arabic NLP capabilities or has usage limits |
| Probability | High (4) - 60% |
| Impact | High (4) - Phase 3 features delayed or downgraded |
| Risk Score | 16 (Critical) |
| Triggers |
• Poor Arabic sentiment analysis accuracy • Rate limiting preventing real-time responses • Unexpected API costs • Model training requirements not documented |
| Mitigation Strategy |
Early Prototyping (Month 5): • Build proof-of-concept before Phase 3 starts • Test Arabic text analysis with sample data • Measure API response times and accuracy • Document rate limits and costs Fallback Options: • OpenAI GPT-4 API (more expensive but proven) • Azure OpenAI Service (enterprise support) • Rule-based sentiment analysis (simpler, limited) • Delay Phase 3 AI features to post-launch |
| Contingency Plan |
If Google AI Studio inadequate: • Switch to OpenAI GPT-4 (add ~1,000 JOD/year cost) • Descope AI features to "nice-to-have" • Launch Phase 3 without AI, add later as enhancement |
| Owner | Backend Lead |
| Review Frequency | Weekly in Phase 3, Monthly before |
Additional Technical Risks (Summary)
R-T-003: Database Performance Issues (Score: 12 - High)
- Risk: Complex queries for booking conflicts, calendar availability slow at scale
- Mitigation: Database indexing strategy, query optimization, Redis caching, read replicas
- Owner: Backend Lead
R-T-004: Mobile App Platform Inconsistencies (Score: 12 - High)
- Risk: Flutter widgets behave differently on iOS vs Android, especially camera/calendar
- Mitigation: Early testing on both platforms, platform-specific code where needed, Flutter community forums
- Owner: Flutter Developer
R-T-005: Payment Gateway Integration Issues (Score: 12 - High)
- Risk: Local Jordanian payment gateways may have poor documentation or unstable APIs
- Mitigation: Select well-documented gateway, build payment abstraction layer, implement retry logic
- Owner: Backend Developer
R-T-006: Real-time Chat System Scalability (Score: 12 - High)
- Risk: Socket.io connections don't scale to 1000+ concurrent users
- Mitigation: Use Redis adapter for Socket.io, horizontal scaling with load balancer
- Owner: Backend Lead
R-T-007: Complex Booking Logic Bugs (Score: 9 - Medium)
- Risk: Edge cases in booking rules (e.g., double-booking, cancellation windows)
- Mitigation: Unit tests for all booking scenarios, manual QA testing, staged rollout
- Owner: Backend Developer + QA
Schedule Risks (Detailed)
Critical R-S-001: Aggressive Timeline
| Description | 8.4 months to build 3 full applications + backend + AI is extremely ambitious |
| Probability | Very High (5) - 80% |
| Impact | High (4) - Delayed launch, rushed code, quality issues |
| Risk Score | 20 (Critical) |
| Root Causes |
• Scope includes 3 separate apps (Mobile, Team, CORE) • Multi-tenancy adds significant complexity • AI integration requires experimentation • No buffer for unexpected issues • Fixed deadline vs. feature-rich scope |
| Mitigation Strategy |
Prioritization (Must/Should/Could): • MUST: Phase 1 core booking + Mobile App • SHOULD: Phase 2 loyalty + Team App • COULD: Phase 3 AI + advanced CRM Phased Launch: • Launch Phase 1 first (MVP) on schedule • Phase 2 & 3 can slip without breaking commitment Scope Reduction Options: • Defer Team App to post-launch • Simplify KODA CORE to essential features only • Remove AI features from initial launch • Cut social media integrations |
| Contingency Plan |
If 4+ weeks behind schedule: • Emergency scope review with Executive Sponsor • Formally descope Phase 3 AI features • Add 1 month to timeline (cost: ~9,400 JOD) • OR Accept delayed Phase 2/3 launch |
| Owner | Project Manager |
| Review Frequency | Weekly |
Additional Schedule Risks (Summary)
R-S-002: Phase 1 Mobile App Delay (Score: 16 - High)
- Risk: Flutter developer encounters platform-specific issues
- Mitigation: Start Mobile App early in parallel with backend, add buffer week, identify backup Flutter developer
R-S-003: Backend API Delays (Score: 16 - High)
- Risk: Backend Lead overloaded with complex multi-tenancy + integrations
- Mitigation: Backend Developer takes more tickets, Frontend starts with mock APIs
R-S-004: Testing Phase Compression (Score: 9 - Medium)
- Risk: If development runs late, QA testing gets squeezed
- Mitigation: Shift-left testing (QA involved early), automated testing, accept minor bugs for Phase 1
Resource & Team Risks (Detailed)
Critical R-R-001: Backend Lead Single Point of Failure
| Description | Backend Lead is sole expert on multi-tenancy architecture and AI integration |
| Probability | Medium (3) - 40% |
| Impact | Very High (5) - Project could halt if Backend Lead leaves or falls ill |
| Risk Score | 15 (Critical) |
| Triggers |
• Backend Lead resignation or long-term illness • Family emergency requiring extended leave • Burnout from overwork • Better job offer from competitor |
| Mitigation Strategy |
Knowledge Transfer: • Backend Lead documents architecture decisions weekly • Backend Developer shadows complex implementations • Code reviews mandatory for all Backend Lead work • Monthly architecture review sessions Backup Resources: • Identify external senior backend consultant (on standby) • Backend Developer trained as backup • Maintain good relationship with Backend Lead (retention) Retention: • Ensure competitive compensation • Recognize contributions publicly • Avoid excessive overtime • Career development discussions |
| Contingency Plan |
If Backend Lead leaves: • Immediately engage external consultant (cost: ~3,000 JOD/month) • Promote Backend Developer to lead (with pay increase) • Extend timeline by 4-6 weeks • Descope Phase 3 AI features if necessary |
| Owner | Project Manager + HR |
| Review Frequency | Monthly |
Additional Resource Risks (Summary)
R-R-002: Team Member Turnover (Score: 12 - High)
- Risk: Any developer leaving mid-project causes knowledge loss and delays
- Mitigation: Competitive pay, good work environment, knowledge sharing culture, backup developers identified
R-R-003: Flutter Developer Availability (Score: 12 - High)
- Risk: Flutter developer only needed 5.7 months, may take other work and become unavailable
- Mitigation: Contract with clear availability requirements, retain through Phase 1 with reduced hours, identify backup Flutter developer
R-R-004: Part-time DevOps Insufficient (Score: 6 - Medium)
- Risk: Infrastructure issues arise outside DevOps engineer's 6 hours/week
- Mitigation: DevOps engineer on-call for emergencies, Backend Lead has basic DevOps skills, automate common tasks
External Dependencies & Third-Party Risks (Detailed)
Critical R-E-001: Third-Party API Failures
| Description | WhatsApp Business API, payment gateway, or SMS service experiences downtime or instability |
| Probability | High (4) - 60% |
| Impact | High (4) - Core features unavailable, customer dissatisfaction |
| Risk Score | 16 (Critical) |
| Key Dependencies |
• WhatsApp Business API (notifications) • Payment Gateway (bookings) • SMS Gateway (OTP, reminders) • Email Service (Mailgun/SendGrid) • Google AI Studio (Phase 3) |
| Mitigation Strategy |
Resilient Design: • Retry logic with exponential backoff • Circuit breaker pattern (fail fast) • Queue failed requests for retry • Graceful degradation (fallback to email if WhatsApp down) Redundancy: • Primary + backup SMS gateway • Email as fallback for all notifications • Cache payment gateway health status Monitoring: • Health checks for all external APIs • Alert on >5% API error rate • Dashboard showing API uptime |
| Contingency Plan |
• Maintain list of alternative providers • Abstract API integrations (easy to swap) • Communication plan for customers during outages |
| Owner | Backend Lead + DevOps |
| Review Frequency | Weekly |
Additional External Risks (Summary)
R-E-002: Google AI Studio Rate Limits (Score: 12 - High)
- Risk: AI requests exceed free tier limits, causing unexpected costs or throttling
- Mitigation: Aggressive caching of AI responses, rate limiting user requests, budget monitoring
R-E-003: Payment Gateway Approval Delays (Score: 9 - Medium)
- Risk: Payment gateway merchant account approval takes 2-4 weeks
- Mitigation: Apply for merchant account in Month 1, use test/sandbox mode for development
Quality & Security Risks (Detailed)
Critical R-Q-001: Security Vulnerability in Production
| Description | Critical security flaw discovered after launch (SQL injection, XSS, authentication bypass) |
| Probability | Medium (3) - 40% |
| Impact | Very High (5) - Data breach, legal liability, reputation damage |
| Risk Score | 15 (Critical) |
| Common Vulnerabilities |
• SQL injection (database queries) • Cross-Site Scripting (XSS) • Insecure authentication • Sensitive data exposure • Broken access control • CSRF attacks |
| Mitigation Strategy |
Secure Development Practices: • Use ORM (Eloquent) to prevent SQL injection • Input validation on all user inputs • Output encoding to prevent XSS • JWT tokens with short expiration • HTTPS everywhere, HSTS headers • Rate limiting on authentication endpoints Security Testing: • OWASP Top 10 checklist • Penetration testing before each phase launch • Automated security scanning (Snyk, OWASP ZAP) • Code review focused on security Compliance: • GDPR data protection requirements • Secure password hashing (bcrypt) • Audit logs for sensitive actions |
| Contingency Plan |
If vulnerability discovered: • Emergency patch within 24 hours • Notify affected users • Forensic analysis to determine scope • Full security audit post-incident |
| Owner | Backend Lead + QA Engineer |
| Review Frequency | Weekly security checks, penetration test before each phase |
Additional Quality & Compliance Risks (Summary)
R-Q-002: Insufficient Testing Coverage (Score: 16 - High)
- Risk: Aggressive timeline forces reduced QA testing, bugs slip to production
- Mitigation: Automated unit/integration tests, QA involved early, accept minor bugs for MVP
R-Q-003: GDPR Compliance Issues (Score: 8 - Medium)
- Risk: Missing data protection requirements (right to deletion, data portability)
- Mitigation: GDPR checklist review, privacy policy drafted, data retention policies defined
R-Q-004: Performance Not Meeting SLAs (Score: 9 - Medium)
- Risk: API response times >500ms, app sluggish under load
- Mitigation: Load testing in Month 6, database optimization, CDN for static assets
Business & Operational Risks (Detailed)
High R-B-001: Scope Creep
| Description | Stakeholders request new features mid-project, expanding scope beyond 27 screens |
| Probability | High (4) - 60% |
| Impact | High (4) - Budget overrun, schedule delays, team burnout |
| Risk Score | 16 (High) |
| Common Triggers |
• "Just one more small feature" • Competitor analysis showing new features • Sales team promises to customers • User feedback during beta testing • Executive requests |
| Mitigation Strategy |
Formal Change Control: • All scope changes go through Change Request process • Change Request must include cost/schedule impact • Approval required from Executive Sponsor • Change log maintained Backlog Management: • New requests added to "Post-Launch" backlog • Clear definition of "in scope" vs "future enhancement" • Product Owner protects team from ad-hoc requests Stakeholder Communication: • Monthly demos showing progress • Set expectations early: MVP first, enhancements later • Highlight trade-offs (new feature = delayed launch) |
| Contingency Plan |
If scope creep occurs: • Formally document impact on budget/schedule • Require Executive Sponsor to approve delay or budget increase • Push back on non-critical features |
| Owner | Project Manager + Product Owner |
| Review Frequency | Weekly |
R-B-002: Budget Overrun (Score: 9 - Medium)
- Risk: Project exceeds 81,555 JOD budget due to delays or scope changes
- Mitigation: Weekly cost tracking, 10% contingency reserve, monthly budget reviews, scope reduction if needed
- Owner: Project Manager + Finance
Risk Monitoring & Control
Risk Review Schedule
| Frequency | Activity | Participants | Deliverable |
|---|---|---|---|
| Daily | Monitor critical risks (R-T-001, R-S-001, R-R-001) | Project Manager | Risk dashboard updated |
| Weekly | Team risk review in sprint retrospective | Full Team | Risk register updated |
| Monthly | Executive risk report | PM + Executive Sponsor | Risk report document |
| Phase End | Risk review & lessons learned | Full Team + Stakeholders | Updated risk register |
Risk Reporting
Weekly Risk Status
- Update risk scores based on current status
- Flag new risks identified
- Report mitigation progress
- Escalate critical risks to Executive Sponsor
Monthly Executive Summary
- Top 5 risks and mitigation status
- Risks closed since last month
- New risks identified
- Risk trend analysis (improving/worsening)
- Budget impact of realized risks
Risk Escalation Criteria
Escalate to Executive Sponsor if:
- Any risk score reaches 20+ (Critical)
- Multiple High risks (12+) occur simultaneously
- Mitigation requires >5,000 JOD budget increase
- Schedule delay >4 weeks likely
- Security breach or data loss occurs
Risk Response Strategies
| Strategy | When to Use | Example |
|---|---|---|
| Avoid | Eliminate the risk entirely | Remove AI features to avoid Google AI Studio risk |
| Mitigate | Reduce probability or impact | Code reviews to reduce data isolation failures |
| Transfer | Shift risk to third party | Use managed cloud services (AWS handles infrastructure) |
| Accept | Acknowledge risk, no action | Accept minor UI inconsistencies for MVP |