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Estimates Are Consistently Wrong
Persistently inaccurate estimates erode stakeholder trust and make planning nearly impossible. GitScrum's historical data and velocity tracking help teams identify estimation patterns, calibrate their predictions using actual completion data, and gradually improve predictability over time.
Why Estimates Fail
| Cause | What Happens | Solution |
|---|---|---|
| Optimism bias | "Should take 2 days" takes 5 | Use historical data |
| Hidden complexity | Simple feature is complex | Spike before estimate |
| Missing work | Forgot testing, review, deploy | Definition of Done checklist |
| Scope creep | Requirements grow | Lock scope, track changes |
| Dependencies | Waiting on others | Map dependencies upfront |
| Context switching | Multiple projects fragment time | Account for overhead |
Estimation Improvement Framework
ESTIMATION ACCURACY JOURNEY
Level 1: Chaos
┌─────────────────────────────────────────────────┐
│ Estimates: "It'll take about a week" │
│ Reality: 1 day to 3 weeks │
│ Variance: ±200% │
└─────────────────────────────────────────────────┘
Level 2: Awareness
┌─────────────────────────────────────────────────┐
│ Track estimated vs actual │
│ Identify patterns ("we're always 2x") │
│ Apply multipliers to raw estimates │
└─────────────────────────────────────────────────┘
Level 3: Process
┌─────────────────────────────────────────────────┐
│ Break down into small tasks │
│ Estimate as team (planning poker) │
│ Use relative estimation (story points) │
│ Variance: ±50% │
└─────────────────────────────────────────────────┘
Level 4: Data-Driven
┌─────────────────────────────────────────────────┐
│ Use historical velocity │
│ Provide ranges, not points │
│ Track by work type (feature vs bug) │
│ Variance: ±25% │
└─────────────────────────────────────────────────┘
Level 5: Probabilistic
┌─────────────────────────────────────────────────┐
│ Monte Carlo simulations │
│ "80% confident by March 15" │
│ Continuous recalculation │
│ Variance: Quantified with confidence │
└─────────────────────────────────────────────────┘
Track and Learn Pattern
ESTIMATION TRACKING
Sprint 12 Estimation Analysis:
┌─────────────────────────────────────────────────┐
│ │
│ Task Estimated Actual Ratio │
│ ───────────────────────────────────────────── │
│ API endpoint 3 pts 5 pts 1.67x │
│ UI component 2 pts 2 pts 1.00x │
│ Database work 5 pts 8 pts 1.60x │
│ Bug fix 1 pt 1 pt 1.00x │
│ Integration 3 pts 7 pts 2.33x ⚠️ │
│ │
│ Sprint Average: 1.52x (we underestimate 52%) │
│ │
│ Patterns Identified: │
│ • Integration work consistently 2x+ │
│ • Bug fixes are accurate │
│ • API work underestimated │
└─────────────────────────────────────────────────┘
APPLY LEARNINGS:
┌─────────────────────────────────────────────────┐
│ Work Type Multiplier │
│ ────────────────────────────── │
│ Bug fixes 1.0x │
│ UI components 1.0x │
│ API work 1.5x │
│ Database work 1.5x │
│ Integration 2.5x │
│ New technology 3.0x │
└─────────────────────────────────────────────────┘
Range Estimation
INSTEAD OF POINT ESTIMATES, USE RANGES
❌ "This will take 5 days"
✅ "This will take:"
┌─────────────────────────────────────────────────┐
│ Best case: 3 days (everything goes right) │
│ Most likely: 5 days (normal complexity) │
│ Worst case: 10 days (if we hit problems) │
│ │
│ Confidence: Medium (new area of code) │
│ Key risks: API documentation unclear │
└─────────────────────────────────────────────────┘
COMMIT TO: "We'll deliver between 5-10 days,
update at midpoint"
Best Practices
- Track actual vs estimated for every task
- Estimate as a team not individually
- Break work down to 1-2 day chunks
- Use ranges not single points
- Apply learned multipliers by work type
- Include all work (testing, review, meetings)
- Re-estimate when scope changes
- Celebrate improving accuracy not just delivery
Anti-Patterns
✗ Punishing wrong estimates (kills honest estimation)
✗ Converting story points to hours
✗ Estimating work you don't understand
✗ Not tracking estimation accuracy
✗ Single person estimates for team work
✗ Never adjusting estimates when scope changes