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Tformance
Analytics Deep Dive

Find delivery bottlenecks before they become status updates

Cycle time, review load, PR flow, and trend changes from GitHub. Use AI-related signals as a secondary lens.

Overview

Team health at a glance

Key metrics cards show PRs merged, cycle time, review time. Health indicators flag what needs attention.

  • PRs merged, cycle time, review time at a glance
  • Health indicators for quick status checks
  • Week-over-week comparisons built in
analytics/overview
Analytics overview tab
analytics/ai-adoption
AI adoption analytics
AI Signals

Use AI as one lens, not the whole story

Compare delivery outcomes for work with and without AI-related signals. See whether review time and flow improve as the signal mix changes.

  • Cycle time and review-time comparison against the baseline
  • Signal share trends by repo and over time
  • AI-related signals used as supporting context, not ground truth
Delivery

Where work gets stuck

Cycle time trends reveal bottlenecks. PR size distribution shows if PRs are staying small.

  • Time in coding, review, and merge phases
  • PR size distribution (lines changed)
  • Week-over-week velocity trends
analytics/delivery
Delivery analytics
analytics/quality
Quality analytics
Quality

Catch quality drift before it becomes rework

Track review rounds, revert patterns, and large-PR risk. See where quality problems start instead of learning from the incident report.

  • Revert rate tracking
  • Review rounds per PR
  • Large PR and rework patterns
Team

Balance the load

See reviewer workload distribution and contributor flow without turning the dashboard into a leaderboard.

  • Contributor throughput patterns
  • Review load distribution
  • Team-level flow trends without surveillance framing
analytics/team
Team analytics

Want to dig into specific PRs?

Use PR Explorer to filter, annotate, and export the data behind these metrics.

Open PR Explorer →

See what is slowing delivery before it becomes a status meeting

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