project-estimation

---
name: project-estimation
description: >
license: MIT
---

# Project Estimation

## Table of Contents

- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)

## Overview

Accurate project estimation determines realistic timelines, budgets, and resource allocation. Effective estimation combines historical data, expert judgment, and structured techniques to minimize surprises.

## When to Use

- Defining project scope and deliverables
- Creating project budgets and timelines
- Allocating team resources
- Managing stakeholder expectations
- Assessing project feasibility
- Planning for contingencies
- Updating estimates during project execution

## Quick Start

Minimal working example:

```python
# Three-point estimation technique for uncertainty

class ThreePointEstimation:
    @staticmethod
    def calculate_pert_estimate(optimistic, most_likely, pessimistic):
        """
        PERT formula: (O + 4M + P) / 6
        Weighted toward most likely estimate
        """
        pert = (optimistic + 4 * most_likely + pessimistic) / 6
        return round(pert, 2)

    @staticmethod
    def calculate_standard_deviation(optimistic, pessimistic):
        """Standard deviation for risk analysis"""
        sigma = (pessimistic - optimistic) / 6
        return round(sigma, 2)

    @staticmethod
    def calculate_confidence_interval(pert_estimate, std_dev, confidence=0.95):
        """
        Calculate confidence interval for estimate
        95% confidence ≈ ±2 sigma
        """
        z_score = 1.96 if confidence == 0.95 else 2.576
// ... (see reference guides for full implementation)
```

## Reference Guides

Detailed implementations in the `references/` directory:

| Guide | Contents |
|---|---|
| [Three-Point Estimation (PERT)](references/three-point-estimation-pert.md) | Three-Point Estimation (PERT) |
| [Bottom-Up Estimation](references/bottom-up-estimation.md) | Bottom-Up Estimation |
| [Analogous Estimation](references/analogous-estimation.md) | Analogous Estimation |
| [Resource Estimation](references/resource-estimation.md) | Resource Estimation |
| [Estimation Templates](references/estimation-templates.md) | Estimation Templates |

## Best Practices

### ✅ DO

- Use multiple estimation techniques and compare results
- Include contingency buffers (15-25% for new projects)
- Base estimates on historical data from similar projects
- Break down large efforts into smaller components
- Get input from team members doing the actual work
- Document assumptions and exclusions clearly
- Review and adjust estimates regularly
- Track actual vs. estimated metrics for improvement
- Include non-development tasks (planning, testing, deployment)
- Account for learning curve on unfamiliar technologies

### ❌ DON'T

- Estimate without clear scope definition
- Use unrealistic best-case scenarios
- Ignore historical project data
- Estimate under pressure to hit arbitrary targets
- Forget to include non-coding activities
- Use estimates as performance metrics for individuals
- Change estimates mid-project without clear reason
- Estimate without team input
- Ignore risks and contingencies
- Use one technique exclusively