Risk Assessment Matrix: E-Commerce Checkout System¶

Project: ShopFlow E-Commerce Platform - Checkout Module Enhancement
Version: 2.0
Prepared By: Sarah Johnson, Test Manager
Date: 2024-03-01
Review Period: Sprint 3 (Week of Feb 26 - Mar 11)
Status: Active Monitoring

Executive Summary¶

This risk assessment matrix identifies, evaluates, and tracks risks associated with the ShopFlow Checkout Module Enhancement project. The matrix is reviewed and updated weekly during sprint planning and whenever new risks are identified.

Current Risk Profile: - Critical Risks: 0 (down from 2 in Sprint 1) - High Risks: 3 (down from 5) - Medium Risks: 6 - Low Risks: 4 - Total Active Risks: 13

Risk Trend: ⬇️ Improving - Several high-priority risks mitigated in Sprints 1-2

Risk Assessment Scale¶

Impact Scale¶

Likelihood Scale¶

Risk Score Calculation¶

Risk Score = Impact × Likelihood

Risk Heat Map¶

                           LIKELIHOOD
         1-Rare   2-Unlikely  3-Possible  4-Likely  5-Almost Certain
       ┌──────────┬──────────┬──────────┬──────────┬──────────┐
5-Crit │  5 (M)   │  10 (M)  │  15 (H)  │  20 (C)  │  25 (C)  │
       ├──────────┼──────────┼──────────┼──────────┼──────────┤
I  4-H │  4 (L)   │  8 (L)   │  12 (M)  │  16 (H)  │  20 (C)  │
M      ├──────────┼──────────┼──────────┼──────────┼──────────┤
P  3-M │  3 (L)   │  6 (L)   │  9 (L)   │  12 (M)  │  15 (H)  │
A      ├──────────┼──────────┼──────────┼──────────┼──────────┤
C  2-L │  2 (L)   │  4 (L)   │  6 (L)   │  8 (L)   │  10 (M)  │
T      ├──────────┼──────────┼──────────┼──────────┼──────────┤
   1-M │  1 (M)   │  2 (L)   │  3 (L)   │  4 (L)   │  5 (M)   │
       └──────────┴──────────┴──────────┴──────────┴──────────┘

Current Risks Plotted:
● RISK-001: Impact 4, Likelihood 2 = Score 8 (Low)
● RISK-002: Impact 4, Likelihood 3 = Score 12 (Medium)
● RISK-003: Impact 5, Likelihood 3 = Score 15 (High)

Active Risks¶

RISK-001: Payment Gateway API Downtime¶

Risk ID: RISK-001
Category: Technical - Third-Party Integration
Date Identified: 2024-01-15
Identified By: Emily Rodriguez, Sr. Test Engineer

Description: PayPal, Apple Pay, or Google Pay APIs may experience downtime or degraded performance during testing or production, preventing users from completing purchases through these payment methods.

Impact Assessment:

Overall Impact: 4 (High)
Likelihood: 2 (Unlikely)
Risk Score: 8 (Low Priority)

Mitigation Strategies:

1. Fallback Mechanisms:
2. Always offer credit card as backup payment option
3. Implement graceful degradation with user-friendly error messages

4. Queue orders for retry when service resumes

5. Monitoring:

6. Real-time monitoring of payment gateway health
7. Automated alerts for API failures

8. Dashboard showing payment success rates

9. Communication:

10. Status page showing available payment methods
11. Email notifications to customers if order pending

12. Clear messaging: "PayPal temporarily unavailable, please use credit card"

13. Testing:

14. Simulate API downtime scenarios in QA
15. Verify fallback logic works correctly
16. Test order queuing and retry mechanisms

Status: 🟢 Controlled - Mitigation implemented and tested
Owner: Emily Rodriguez
Last Review: 2024-02-28
Next Review: 2024-03-14

Status History: - 2024-01-15: Identified, Score 12 (Medium) - 2024-02-10: Mitigation implemented, Score reduced to 8 (Low) - 2024-02-28: Verified in production monitoring

RISK-002: Browser Compatibility Issues with Payment Methods¶

Risk ID: RISK-002
Category: Technical - Frontend
Date Identified: 2024-01-18
Identified By: Lisa Patel, Test Engineer

Description: Apple Pay and Google Pay require specific browser and OS combinations. Older browsers or unsupported platforms may not properly display or function with these payment methods, potentially confusing users or blocking purchases.

Impact Assessment:

Overall Impact: 4 (High)
Likelihood: 3 (Possible)
Risk Score: 12 (Medium Priority)

Mitigation Strategies:

1. Feature Detection:
2. Detect browser capabilities before showing payment options
3. Hide Apple Pay on non-Safari browsers
4. Hide Google Pay on non-supported browsers

5. Progressive enhancement approach

6. User Communication:

7. Clear messaging: "Apple Pay available in Safari" if detected unavailable
8. Browser upgrade recommendations for unsupported users

9. Prominent display of always-available credit card option

10. Comprehensive Testing:

11. Test on all major browsers (Chrome, Firefox, Safari, Edge)
12. Test on multiple browser versions (current and previous 2 versions)
13. Mobile browser testing (iOS Safari, Chrome Android)

14. Automated cross-browser testing in CI pipeline

15. Graceful Degradation:

16. Ensure credit card option always works
17. No broken UI elements on unsupported browsers
18. Fallback styling for older browsers

Status: 🟡 In Progress - Mitigation partially implemented
Owner: Rachel Kim, Frontend Developer
Last Review: 2024-02-28
Next Review: 2024-03-07

Actions Remaining: - ✅ Feature detection implemented - ✅ Cross-browser test suite created - 🔄 Testing in progress on older browser versions - ⏳ Final verification needed on iOS Safari 14

Status History: - 2024-01-18: Identified, Score 12 (Medium) - 2024-02-15: Mitigation started - 2024-02-28: Testing phase

RISK-003: Performance Degradation Under Load¶

Risk ID: RISK-003
Category: Technical - Performance
Date Identified: 2024-01-20
Identified By: Anna Kowalski, Performance Tester

Description: Checkout process may experience performance degradation during peak traffic periods (e.g., holiday sales, promotional events). Real-time shipping calculations and payment processing add latency that could result in slow page loads or timeouts.

Impact Assessment:

Overall Impact: 5 (Critical)
Likelihood: 3 (Possible)
Risk Score: 15 (High Priority)

Mitigation Strategies:

1. Performance Optimization:
2. Implement caching for shipping rates (5-minute TTL)
3. Lazy load non-critical UI elements
4. Database query optimization for checkout flow
5. CDN for static assets

6. Redis caching for session data

7. Load Testing:

8. Test with 1,000+ concurrent users
9. Identify bottlenecks in checkout flow
10. Stress test payment gateway integrations
11. Test database connection pooling

12. Weekly performance baseline monitoring

13. Scaling Strategy:

14. Auto-scaling configured for application servers
15. Database read replicas for load distribution
16. Queue-based processing for non-critical operations

17. Circuit breakers for third-party API calls

18. Monitoring & Alerts:

19. Real-time performance monitoring (New Relic/Datadog)
20. Alert when response time >3 seconds
21. Alert when error rate >1%

22. Dashboard showing checkout funnel performance

23. Capacity Planning:

24. Project peak load: 5,000 concurrent users
25. Current capacity: 2,000 concurrent users
26. Plan infrastructure upgrade before holiday season
27. Budget approved for additional servers

Status: 🟡 In Progress - High priority mitigation underway
Owner: Anna Kowalski, Performance Tester & DevOps Team
Last Review: 2024-03-01
Next Review: 2024-03-08

Current Metrics (as of 2024-03-01): - Average checkout time: 3.8 seconds (Target: <3 seconds) - 95^th percentile: 6.2 seconds (Target: <5 seconds) - Error rate: 0.3% (Target: <0.5%) ✅ - Concurrent user capacity: 2,000 (Target: 5,000)

Actions Remaining: - ✅ Caching implemented for shipping rates - ✅ Database queries optimized - ✅ CDN configured - 🔄 Load testing in progress (target 5,000 users) - ⏳ Auto-scaling configuration pending - ⏳ Infrastructure upgrade approval needed

Status History: - 2024-01-20: Identified, Score 20 (Critical) - 2024-02-05: Optimization sprint started - 2024-02-20: Initial optimizations completed, Score reduced to 15 (High) - 2024-03-01: Load testing phase

RISK-004: Test Data Quality and Coverage¶

Risk ID: RISK-004
Category: Process - Test Data
Date Identified: 2024-01-22
Identified By: Maria Garcia, DBA

Description: Test data may not adequately represent production edge cases, international addresses, special characters, and diverse customer scenarios. Insufficient test data coverage could result in defects slipping to production.

Impact Assessment:

Overall Impact: 3 (Medium)
Likelihood: 3 (Possible)
Risk Score: 9 (Low Priority)

Mitigation Strategies:

1. Comprehensive Test Data:
2. 500 user accounts with diverse profiles
3. 100+ products across price ranges
4. 150 addresses covering all US states and 20 countries
5. Special characters in names and addresses

6. Edge cases: very long names, unusual addresses

7. Data Validation:

8. Review test data coverage against requirements
9. Peer review of test data sets
10. Gap analysis comparing to production data patterns

11. Quarterly test data refresh

12. Production-Like Scenarios:

13. Anonymized production data samples (GDPR-compliant)
14. Simulate high-value orders, bulk purchases
15. Test with expired cards, insufficient funds scenarios

16. International address formats

17. Automated Data Generation:

18. Faker.js for generating realistic test data
19. Automated scripts for data refresh
20. Data seeding included in CI/CD pipeline

Status: 🟢 Controlled - Comprehensive test data prepared
Owner: Maria Garcia, DBA
Last Review: 2024-02-28
Next Review: 2024-03-28

Status History: - 2024-01-22: Identified, Score 12 (Medium) - 2024-02-01: Test data preparation completed - 2024-02-28: Validation complete, Score reduced to 9 (Low)

RISK-005: Insufficient Mobile Testing Coverage¶

Risk ID: RISK-005
Category: Technical - Mobile
Date Identified: 2024-01-25
Identified By: Lisa Patel, Test Engineer

Description: Mobile devices represent 45% of traffic but testing coverage on physical devices is limited. Testing primarily on simulators/emulators may miss device-specific issues with touch interactions, payment methods, and responsive design.

Impact Assessment:

Overall Impact: 4 (High)
Likelihood: 3 (Possible)
Risk Score: 12 (Medium Priority)

Mitigation Strategies:

1. Physical Device Testing:
2. Acquired device pool: 2 iPhones, 2 Android phones, 1 iPad
3. Priority devices: iPhone 13/14, Samsung Galaxy S21/S22
4. Test on real devices for critical flows

5. BrowserStack for additional device coverage

6. Mobile-First Test Approach:

7. Mobile test cases prioritized in test plan
8. Dedicated mobile testing time each sprint
9. Touch interaction testing (tap, swipe, pinch-zoom)

10. Mobile payment methods (Apple Pay, Google Pay)

11. Responsive Design Validation:

12. Test at multiple viewport sizes
13. Portrait and landscape orientations
14. Different screen densities (1x, 2x, 3x)

15. Accessibility on mobile (screen readers)

16. Cloud Testing Platforms:

17. BrowserStack for extended device matrix
18. Test on older iOS versions (15, 16, 17)
19. Test on older Android versions (11, 12, 13)

Status: 🟢 Controlled - Mobile testing expanded
Owner: Lisa Patel, Test Engineer
Last Review: 2024-02-28
Next Review: 2024-03-14

Status History: - 2024-01-25: Identified, Score 16 (High) - 2024-02-10: Device pool acquired - 2024-02-28: Mobile testing coverage increased, Score reduced to 12 (Medium)

RISK-006: Scope Creep from Feature Requests¶

Risk ID: RISK-006
Category: Project Management
Date Identified: 2024-02-01
Identified By: Robert Martinez, Project Director

Description: Stakeholders continue to request additional features (e.g., cryptocurrency payment, buy-now-pay-later integrations) that were not in original scope. Accepting these requests could delay release and increase risk of defects.

Impact Assessment:

Overall Impact: 4 (High)
Likelihood: 4 (Likely)
Risk Score: 16 (High Priority)

Mitigation Strategies:

1. Change Control Process:
2. All new features require formal change request
3. Impact analysis (timeline, resources, risk)
4. Steering committee approval required

5. Document trade-offs and implications

6. Stakeholder Management:

7. Weekly status updates to stakeholders
8. Clear communication of current scope
9. Product backlog for future enhancements

10. "Parking lot" for ideas deferred to v3.6

11. Release Planning:

12. Fixed release date: April 3, 2024
13. Feature freeze date: March 11, 2024
14. Only critical defect fixes after freeze

15. New features planned for v3.6 (Q3 2024)

16. Prioritization Framework:

17. Must-have vs. nice-to-have classification
18. ROI analysis for new feature requests
19. Technical feasibility assessment
20. User research to validate necessity

Status: 🟢 Controlled - Change control process enforced
Owner: Robert Martinez, Project Director
Last Review: 2024-03-01
Next Review: 2024-03-08

Recent Change Requests: - Cryptocurrency payment (Bitcoin, Ethereum) - Deferred to v3.6 - Buy-now-pay-later (Klarna, Affirm) - Deferred to v3.6 - Gift card payment - Deferred to v3.6 - Multi-currency support - Under evaluation for v3.6

Status History: - 2024-02-01: Identified, Score 16 (High) - 2024-02-15: Change control process implemented - 2024-03-01: Enforced successfully, remains High priority for monitoring

RISK-007: Payment Gateway Certification Delays¶

Risk ID: RISK-007
Category: Compliance - Security
Date Identified: 2024-02-05
Identified By: Tom Anderson, Security Tester

Description: PCI-DSS compliance certification and payment gateway security audits may take longer than expected, potentially delaying production release. Required for processing credit card payments.

Impact Assessment:

Overall Impact: 4 (High)
Likelihood: 2 (Unlikely)
Risk Score: 8 (Low Priority)

Mitigation Strategies:

1. Early Engagement:
2. Security audit scheduled for Week of March 13
3. Pre-audit security review completed
4. Documentation prepared in advance

5. Auditor availability confirmed

6. Compliance Readiness:

7. Security requirements checklist completed
8. Penetration testing scheduled for March 15
9. Vulnerability assessment completed

10. Encryption verified for payment data

11. Contingency Planning:

12. Buffer time in schedule for audit findings
13. Expedited audit option available (additional cost)
14. Phased rollout if partial certification possible

15. Emergency escalation path to auditor

16. Parallel Processing:

17. Non-payment features can be deployed
18. Gradual rollout approach possible
19. Guest checkout without payment can go live
20. PayPal/Apple Pay/Google Pay have separate certifications

Status: 🟢 On Track - Audit scheduled, preparation complete
Owner: Tom Anderson, Security Tester
Last Review: 2024-03-01
Next Review: 2024-03-15 (Post-Audit)

Audit Schedule: - Pre-audit review: March 10 ✅ - Security audit: March 13-15 - Remediation: March 16-18 (if needed) - Certification: March 20 - Buffer: March 21-25

Status History: - 2024-02-05: Identified, Score 12 (Medium) - 2024-02-20: Early preparation reduced likelihood, Score 8 (Low) - 2024-03-01: On track for scheduled audit

RISK-008: Inadequate UAT Participation¶

Risk ID: RISK-008
Category: Process - User Acceptance Testing
Date Identified: 2024-02-10
Identified By: Jennifer Lee, Product Owner

Description: Business stakeholders may have limited availability for UAT (March 18 - April 1), potentially missing critical business requirements or usability issues that only stakeholders can validate.

Impact Assessment:

Overall Impact: 4 (High)
Likelihood: 3 (Possible)
Risk Score: 12 (Medium Priority)

Mitigation Strategies:

1. Early UAT Planning:
2. UAT schedule shared 6 weeks in advance
3. Calendar holds for key stakeholders
4. Backup UAT testers identified

5. Clear roles and responsibilities defined

6. Flexible UAT Approach:

7. Remote UAT testing option
8. Evening/weekend availability if needed
9. Recorded demo sessions for async review

10. Prioritized test scenarios (critical first)

11. Communication Strategy:

12. Weekly UAT reminders starting March 1
13. Clear expectations document sent to stakeholders
14. UAT test scripts provided in advance

15. Training session scheduled for March 15

16. Risk-Based UAT:

17. Focus on high-risk, high-impact scenarios
18. Pre-UAT demo to key stakeholders
19. Incremental feedback sessions
20. Early identification of blockers

Status: 🟡 Monitoring - UAT planning in progress
Owner: Jennifer Lee, Product Owner
Last Review: 2024-03-01
Next Review: 2024-03-08

UAT Participation Confirmed: - ✅ Product Owner: Jennifer Lee (full availability) - ✅ Business Analyst: Tom Chen (75% availability) - ✅ Marketing Manager: Susan Park (50% availability) - ⏳ Finance Manager: Pending confirmation - ⏳ Customer Service Lead: Pending confirmation

Status History: - 2024-02-10: Identified, Score 12 (Medium) - 2024-02-25: UAT invitations sent, commitments being collected - 2024-03-01: Partial confirmation received

RISK-009: Knowledge Transfer for Production Support¶

Risk ID: RISK-009
Category: Operational
Date Identified: 2024-02-15
Identified By: Michael Chen, QA Lead

Description: Production support team may not have adequate knowledge of new checkout features, troubleshooting procedures, and common issues, leading to longer incident response times and poor customer support.

Impact Assessment:

Overall Impact: 3 (Medium)
Likelihood: 3 (Possible)
Risk Score: 9 (Low Priority)

Mitigation Strategies:

1. Knowledge Transfer Sessions:
2. Training scheduled for March 20-22
3. Hands-on workshop with support team
4. Demo of all new features
5. Common issues and troubleshooting guide

6. Q&A session

7. Documentation:

8. Support runbook created
9. FAQ document for common issues
10. Troubleshooting flowcharts
11. Video tutorials for support processes

12. API documentation for technical team

13. Shadowing Period:

14. Support team shadows QA testing (March 18-22)
15. Exposure to real issues and resolutions
16. Access to test environment for practice

17. Participation in defect triage meetings

18. Rollout Support:

19. QA team on-call first 2 weeks post-launch
20. Daily stand-ups with support team first week
21. Dedicated Slack channel for questions
22. Known issues list updated daily

Status: 🟡 In Progress - Knowledge transfer planning
Owner: Michael Chen, QA Lead
Last Review: 2024-03-01
Next Review: 2024-03-15

Documentation Status: - ✅ Support runbook: 80% complete - ✅ FAQ document: Complete - 🔄 Video tutorials: In production - ⏳ Troubleshooting guide: Started

Status History: - 2024-02-15: Identified, Score 9 (Low) - 2024-03-01: Knowledge transfer materials in development

RISK-010: Regression in Existing Checkout Features¶

Risk ID: RISK-010
Category: Technical - Quality
Date Identified: 2024-02-20
Identified By: David Kim, Test Engineer

Description: While adding new checkout features, existing checkout functionality for registered users may be inadvertently broken or degraded. Regression defects could impact current customers who are familiar with existing checkout flow.

Impact Assessment:

Overall Impact: 4 (High)
Likelihood: 2 (Unlikely)
Risk Score: 8 (Low Priority)

Mitigation Strategies:

1. Comprehensive Regression Testing:
2. 250 regression test cases identified
3. Automated regression suite: 180 tests (72%)
4. Manual regression suite: 70 tests (28%)
5. Run full regression weekly

6. Regression before each release candidate

7. Test Automation:

8. Selenium tests for critical paths
9. Cypress E2E tests for full checkout flow
10. API tests for backend integrations
11. Visual regression testing (Percy.io)

12. Performance regression tests

13. Version Control & Rollback:

14. Feature flags for new functionality
15. Easy rollback capability
16. Blue-green deployment strategy

17. Canary release (5% → 25% → 100%)

18. Monitoring:

19. Real-time error tracking (Sentry)
20. Checkout conversion funnel monitoring
21. A/B testing framework
22. User session recording (Hotjar)

Status: 🟢 Controlled - Comprehensive regression coverage
Owner: James Wilson, Automation Engineer
Last Review: 2024-03-01
Next Review: 2024-03-15

Regression Test Results (Latest): - Total tests: 250 - Passed: 247 (98.8%) - Failed: 2 (0.8%) - Minor cosmetic issues - Blocked: 1 (0.4%) - Environment issue

Status History: - 2024-02-20: Identified, Score 12 (Medium) - 2024-02-28: Automation coverage increased, Score reduced to 8 (Low) - 2024-03-01: Weekly regression showing consistent pass rate

Risk Summary Dashboard¶

Current Risk Distribution¶

Risk Priority Distribution:

Critical (20-25): ███ 0 risks (0%)
High (15-19):     ████████████ 3 risks (23%)
Medium (10-14):   ██████████████████ 6 risks (46%)
Low (5-9):        ████████████ 4 risks (31%)

Top 5 Risks by Score¶

Risk Trend Analysis¶

Week over Week Change:

Closed Risks This Period: - RISK-011: Third-party library vulnerabilities (Closed 2024-02-28) - RISK-012: Test environment instability (Closed 2024-02-26)

Risk Management Process¶

Weekly Risk Review¶

Frequency: Every Monday, 10:00 AM
Attendees: - Sarah Johnson, Test Manager (Chair) - Robert Martinez, Project Director - Michael Chen, QA Lead - James Wilson, Development Lead - Key stakeholders as needed

Agenda: 1. Review risk heat map and trends (10 min) 2. Status update on high-priority risks (15 min) 3. New risks identified (10 min) 4. Mitigation progress review (15 min) 5. Action items and owners (10 min)

Risk Escalation¶

Escalation Criteria: - Risk score increases to Critical (20-25) - High risk not mitigated within 2 weeks - New critical risk identified - Multiple high risks in same category

Escalation Path: 1. Level 1: Test Manager (immediate) 2. Level 2: Project Director (within 24 hours) 3. Level 3: VP Engineering / VP Product (within 48 hours)

Action Items¶

Appendix: Closed Risks¶

RISK-011: Third-party Library Vulnerabilities (CLOSED)¶

Status: Closed 2024-02-28
Resolution: All vulnerable dependencies updated to patched versions. Security scan showing zero critical vulnerabilities.

RISK-012: Test Environment Instability (CLOSED)¶

Status: Closed 2024-02-26
Resolution: Infrastructure upgraded, stability monitoring implemented. Environment uptime >99.5% for past 2 weeks.

Document End

Last Updated: March 1, 2024
Next Review: March 8, 2024
Document Owner: Sarah Johnson, Test Manager