Estimation

When to Use This Skill

Use this skill when:

• Estimation tasks - Working on estimation techniques including analogous, parametric, three-point, and expert judgment methods. provides effort, cost, duration, and complexity estimates for projects, features, and tasks

• Planning or design - Need guidance on Estimation approaches

• Best practices - Want to follow established patterns and standards

Overview

Systematically estimate effort, cost, duration, and complexity using proven estimation techniques. Supports analogous, parametric, three-point (PERT), and expert judgment methods for projects, features, and tasks.

What is Estimation?

Estimation is the process of forecasting the resources, time, and cost required to complete work. Good estimation balances:

• Accuracy: How close to actual results

• Precision: Consistency of estimates

• Speed: Time to produce estimates

• Communication: Shared understanding of uncertainty

Estimation vs Commitment

Concept Definition Use

Estimate Best guess given current knowledge Planning, forecasting

Commitment Promise to deliver by date/cost Contracts, deadlines

Target Desired outcome to aim for Goals, objectives

Key principle: Estimates are ranges with uncertainty, not single-point guarantees.

Estimation Techniques

Analogous Estimation (Top-Down)

Estimate based on similar past work:

Step Action

1 Identify similar completed project/feature

2 Retrieve actual effort/cost/duration

3 Adjust for differences (complexity, team, technology)

4 Apply adjustment factor

Formula:

New Estimate = Historical Actual × Adjustment Factor

Example: Similar project took 200 hours New project is ~20% more complex Estimate = 200 × 1.20 = 240 hours

When to Use: Early phases, limited detail, experienced teams with historical data

Accuracy: +/- 25-50% (improves with good historical data)

Parametric Estimation

Estimate using statistical relationships:

Element Description

Unit of Work Measurable element (screen, API, table)

Productivity Rate Effort per unit from historical data

Quantity Number of units to produce

Formula:

Estimate = Quantity × Productivity Rate

Example: 10 API endpoints × 16 hours/endpoint = 160 hours

Common Productivity Metrics:

Work Type Metric Typical Range

UI screens Hours/screen 8-40 hours

API endpoints Hours/endpoint 4-24 hours

Database tables Hours/table 4-16 hours

Test cases Hours/test 0.5-4 hours

Documentation pages Hours/page 2-8 hours

When to Use: Repeatable work, good historical data, similar technology

Accuracy: +/- 15-25% (with calibrated rates)

Three-Point Estimation (PERT)

Estimate using optimistic, most likely, and pessimistic values:

Value Symbol Definition

Optimistic O Best case, everything goes right

Most Likely M Most probable outcome

Pessimistic P Worst case, problems occur

PERT Formula (Weighted Average):

Expected = (O + 4M + P) / 6 Standard Deviation = (P - O) / 6

Example: O = 5 days, M = 8 days, P = 17 days Expected = (5 + 4×8 + 17) / 6 = 9 days Std Dev = (17 - 5) / 6 = 2 days

Confidence Intervals:

Confidence Calculation Example (E=9, SD=2)

68% E ± 1 SD 7-11 days

95% E ± 2 SD 5-13 days

99.7% E ± 3 SD 3-15 days

When to Use: Uncertain work, new technology, need to communicate risk

Accuracy: Provides explicit uncertainty range

Expert Judgment

Estimate using collective expert knowledge:

Wideband Delphi Process:

Round Activity

1 Experts estimate independently

2 Collect and share anonymous estimates

3 Discuss high/low outliers, share rationale

4 Re-estimate independently

5 Repeat until convergence (or average)

Planning Poker (Agile):

Step Action

1 Present item to estimate

2 Discuss briefly (2-5 minutes)

3 Each team member selects card privately

4 Reveal simultaneously

5 Discuss outliers

6 Re-vote until consensus

Common Scales:

Scale Type Values

Fibonacci 1, 2, 3, 5, 8, 13, 21, 34, 55, 89

Modified Fibonacci 0, 0.5, 1, 2, 3, 5, 8, 13, 20, 40, 100

T-shirt XS, S, M, L, XL, XXL

Powers of 2 1, 2, 4, 8, 16, 32, 64

When to Use: Complex work, multiple perspectives needed, team alignment

Function Point Analysis

Estimate based on functional size (for larger systems):

Component Description Weight Range

External Inputs Data entering system 3-6

External Outputs Data leaving system 4-7

External Inquiries Read-only queries 3-6

Internal Files Logical data stores 7-15

External Interfaces Shared data 5-10

Process:

• Count each component type

• Classify complexity (low/medium/high)

• Apply weights

• Calculate unadjusted function points

• Apply technical complexity factor

When to Use: Large projects, formal contracts, industry benchmarking

Relative Estimation

Story Points

Relative complexity/effort measure:

Points Relative Size Example

1 Trivial Fix typo, config change

2 Simple Simple bug fix, minor feature

3 Moderate Standard feature, moderate complexity

5 Complex Multi-component feature

8 Very complex Integration work, significant unknowns

13 Epic-sized Consider breaking down

21+ Too large Must decompose

Baseline: Pick a well-understood story as reference (e.g., "this is a 3")

Velocity: Story points completed per iteration (used for forecasting)

T-Shirt Sizing

Quick relative sizing for roadmap planning:

Size Effort Range Duration Range

XS 1-4 hours < 1 day

S 0.5-2 days 1-2 days

M 2-5 days 3-5 days

L 1-2 weeks 1-2 weeks

XL 2-4 weeks 2-4 weeks

XXL 1-3 months Too big, decompose

Workflow

Phase 1: Prepare

Step 1: Clarify Scope

Estimation Request

Item: [What's being estimated] Requester: [Who needs the estimate] Purpose: [Planning/budgeting/commitment] Deadline: [When estimate is needed] Precision: [ROM/Budget/Definitive]

Scope Definition

• In Scope: [What's included]
• Out of Scope: [What's excluded]
• Assumptions: [Key assumptions]
• Constraints: [Known constraints]

Step 2: Select Estimation Technique

Situation Recommended Technique

Early project phase Analogous + T-shirt sizing

Detailed requirements Parametric + Three-point

Agile backlog Story points + Planning poker

New technology/domain Expert judgment + Three-point

Contract/budget Function points + Parametric

Phase 2: Estimate

Step 1: Decompose Work

Break down into estimable units (half-day to 2-week chunks)

Step 2: Apply Technique

Use selected technique(s) from above

Step 3: Add Contingency

Contingency Calculation

Step 4: Validate

• Sanity check against similar work

• Review with team

• Check for missing items

• Verify assumptions

Phase 3: Communicate

Step 1: Express as Range

Estimate Summary

Effort: 160-200 hours (confidence: 80%) Duration: 4-5 weeks (with 2 developers) Cost: $24,000-$30,000

Key Risks:

• API integration complexity unknown
• Dependency on third-party availability

Step 2: Document Assumptions

Estimation Assumptions

1. Requirements are stable and complete
2. Team has 80% availability (20% overhead)
3. No major technology changes
4. Dependencies delivered on time
5. [Additional assumptions...]

If assumptions change, estimate should be revisited.

Output Formats

Narrative Summary

Estimation Summary

Item: [Feature/Project name] Date: [ISO date] Estimator: estimation-analyst Technique: [Technique used]

Estimate

Basis of Estimate

• Historical Reference: [Similar past work]
• Productivity Rate: [If parametric]
• Expert Input: [Who contributed]

Assumptions

1. [Assumption 1]
2. [Assumption 2]

Risks Affecting Estimate

Recommendations

1. [Next steps for refining estimate]
2. [When to re-estimate]

Structured Data (YAML)

estimation: version: "1.0" date: "2025-01-15" item: "User Dashboard Feature" estimator: "estimation-analyst" technique: "three_point"

scope: description: "Interactive user dashboard with analytics" in_scope: - "Dashboard UI components" - "Data visualization" - "User preferences" out_of_scope: - "Backend analytics engine" - "Real-time updates" assumptions: - "API endpoints available" - "Design mockups complete"

estimates: effort: optimistic: 120 most_likely: 160 pessimistic: 240 expected: 166 unit: "hours" std_deviation: 20 duration: optimistic: 3 most_likely: 4 pessimistic: 6 expected: 4.2 unit: "weeks" cost: expected: 24000 range_low: 18000 range_high: 36000 currency: "USD"

confidence: 0.80 contingency: 0.20

breakdown: - component: "UI Components" effort: 60 technique: "parametric" rate: "15h/component" quantity: 4 - component: "Data Integration" effort: 40 technique: "analogous" reference: "PROJ-123" - component: "Testing" effort: 40 technique: "percentage" percentage: 0.25

risks: - risk: "API complexity higher than expected" probability: 0.3 impact_hours: 30 - risk: "Design changes during development" probability: 0.2 impact_hours: 20

historical_comparison: similar_item: "Admin Dashboard" actual_effort: 180 adjustment_factor: 0.9

Breakdown Table

Effort Breakdown

Estimation Accuracy

Cone of Uncertainty

Estimate accuracy improves as project progresses:

Phase Accuracy Range

Initial concept 0.25x - 4x

Approved project 0.5x - 2x

Requirements complete 0.67x - 1.5x

Detailed design 0.8x - 1.25x

Code complete 0.9x - 1.1x

Implication: Early estimates need wider ranges; refine as knowledge grows.

Estimation Levels

Level Accuracy When Used

ROM (Rough Order of Magnitude) -25% to +75% Initial budgeting

Budget -10% to +25% Project approval

Definitive -5% to +10% Execution baseline

Common Pitfalls

Pitfall Prevention

Single-point estimates Always provide ranges

Optimism bias Use historical data, add contingency

Anchoring Estimate before seeing others' estimates

Planning fallacy Include realistic overhead and risks

Scope creep Document assumptions, re-estimate on changes

Precision theater Match precision to actual knowledge

Integration

Upstream

• Requirements - What to estimate

• risk-analysis - Risks affecting estimates

• stakeholder-analysis - Who needs estimates, precision required

Downstream

• Project planning - Resource allocation, scheduling

• Budgeting - Cost forecasting

• prioritization - Cost input for value/effort analysis

Related Skills

• risk-analysis

• Risks affecting estimates

• prioritization

• Using estimates for prioritization

• decision-analysis

• Trade-off decisions

• value-stream-mapping

• Estimating process improvement effort

Version History

• v1.0.0 (2025-12-26): Initial release