Claude Code ROI Measurement Guide

A comprehensive guide to measuring the return on investment for Claude Code implementation in your development organization.

Overview

This repository contains a complete walkthrough for setting up telemetry, measuring costs, tracking productivity, and calculating ROI for Claude Code usage. Whether you're an individual developer or managing a large engineering team, this guide provides the tools and metrics needed to make data-driven decisions about AI coding assistance.

What's Included

• Telemetry Setup: Complete Prometheus and OpenTelemetry configuration
• Cost Analysis: Real usage patterns and pricing breakdowns across different plans
• Productivity Metrics: Key indicators for measuring developer efficiency
• ROI Calculations: Framework for calculating return on investment
• Automated Reporting: Integration with Linear for comprehensive productivity reports

Key Metrics Tracked

• Cost Metrics: Total spend, cost per session, cost by model
• Token Usage: Input/output tokens, cache efficiency
• Productivity: PR count, commit frequency, session duration
• Team Analytics: Usage by developer, adoption rates

Contents

• claude_code_roi_full.md - Complete implementation guide
• docker-compose.yml, prometheus.yml, otel-collector-config.yaml - Docker Compose and metrics collection setup
• sample-report-output.md - Example automated reports
• report-generation-prompt.md - Prompt template for generating productivity reports

Getting Started

Read the complete guide in claude_code_roi_full.md for detailed setup instructions, real-world examples, and actionable insights for your organization.

Contributing

This guide is based on real-world implementation experience. If you have additional insights or improvements, please feel free to create an issue / PR.

This guide was written by Kashyap Coimbatore Murali