Measure and demonstrate the impact of GitHub Copilot
Understanding how Copilot is used across your enterprise is the first step to demonstrating its value. Follow this path to establish a usage baseline, see how code is being generated, and connect adoption to measurable outcomes.
Phase 1: Choose metrics to monitor Copilot adoption.
2 ArtikelUnderstand what Copilot usage metrics measure and where the data comes from before you start monitoring adoption. Review the concepts behind usage metrics and the data available through the dashboard and API.
Phase 1: Choose metrics to monitor Copilot adoption.
2 ArtikelUnderstand what Copilot usage metrics measure and where the data comes from before you start monitoring adoption. Review the concepts behind usage metrics and the data available through the dashboard and API.
Phase 2: Monitor usage and adoption
3 ArtikelEstablish a usage baseline, compare active users with assigned licenses, and identify where teams may need more support to adopt Copilot.
Phase 2: Monitor usage and adoption
3 ArtikelEstablish a usage baseline, compare active users with assigned licenses, and identify where teams may need more support to adopt Copilot.
Phase 3: See how code is generated
2 ArtikelReview code generation and Lines of Code metrics to understand how people and agents are using Copilot to produce code.
Phase 3: See how code is generated
2 ArtikelReview code generation and Lines of Code metrics to understand how people and agents are using Copilot to produce code.
Phase 4: Connect adoption insights to engineering outcomes
2 ArtikelDefine the engineering outcomes you want to improve and choose metrics that show progress. Compare adoption insights with metrics from your engineering systems to identify associations and evaluate results.
Phase 4: Connect adoption insights to engineering outcomes
2 ArtikelDefine the engineering outcomes you want to improve and choose metrics that show progress. Compare adoption insights with metrics from your engineering systems to identify associations and evaluate results.
Phase 1: Choose metrics to monitor Copilot adoption.
2 ArtikelUnderstand what Copilot usage metrics measure and where the data comes from before you start monitoring adoption. Review the concepts behind usage metrics and the data available through the dashboard and API.
Phase 1: Choose metrics to monitor Copilot adoption.
2 ArtikelUnderstand what Copilot usage metrics measure and where the data comes from before you start monitoring adoption. Review the concepts behind usage metrics and the data available through the dashboard and API.
Phase 2: Monitor usage and adoption
3 ArtikelEstablish a usage baseline, compare active users with assigned licenses, and identify where teams may need more support to adopt Copilot.
Phase 2: Monitor usage and adoption
3 ArtikelEstablish a usage baseline, compare active users with assigned licenses, and identify where teams may need more support to adopt Copilot.
Phase 3: See how code is generated
2 ArtikelReview code generation and Lines of Code metrics to understand how people and agents are using Copilot to produce code.
Phase 3: See how code is generated
2 ArtikelReview code generation and Lines of Code metrics to understand how people and agents are using Copilot to produce code.
Phase 4: Connect adoption insights to engineering outcomes
2 ArtikelDefine the engineering outcomes you want to improve and choose metrics that show progress. Compare adoption insights with metrics from your engineering systems to identify associations and evaluate results.
Phase 4: Connect adoption insights to engineering outcomes
2 ArtikelDefine the engineering outcomes you want to improve and choose metrics that show progress. Compare adoption insights with metrics from your engineering systems to identify associations and evaluate results.