Data-Driven Engineering KPIs

Leverage concrete engineering KPIs to conduct fair, objective, and growth-focused performance evaluations.
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The output-first approach to AI Impact is broken.

Code output is up

Merged pull requests on GitHub have more than quadrupled since 2023, reaching 130M per month in August 2026.
Source: GitHub

Value is flat

Only 6% of companies are “high AI performers” that report “significant” AI impact and ≥5% impact on earnings, unchanged from 2025 to 2026.
Source: McKinsey

A strategy that works: stop slop to accelerate value.

minware’s Lean AI Framework™ unlocks value by eliminating everything that gets in the way: rework, bugs, reviewing low-quality code, context switching, babysitting agents, and more.

Measure best practices that drive AI impact.

Other platforms measure outcomes, but don’t tell you how to get better.
minware offers actionable metrics that help teams improve AI impact.

Team Workflow Efficiency

Ticket Work-in-Progress (WIP)

Planning and Prompting

Ticket Size
Pull Request (PR) Complexity
Pre-Merge Churn Rate
Post-Merge Churn Rate

Session Automation

Human Commit Rate
Agent Session Length
Human Intervention Rate
Cloud Agent Use/Success Rate
Tool Use/Runtime

Culture

AI Rules of Engagement
Read about best practices in the Lean AI Framework

Customize metrics for the way each team creates value.

minware’s hypercube data model and minQL language (patent-pending) interlink and surface every SDLC artifact.
We help you customize editable metric formulas for each team’s value creation workflow – aligning statuses, labels, custom fields, and team conventions.
Any Metric ✕ Any Dimension ＝ Accurate Value-Aligned Insights

Start from comprehensive pre-built reports and industry benchmarks.

How can we fairly analyze individual contributions?

Identify strengths and improvement areas with the Individual Contributor Dashboard dashboard.

Where are the biggest bottlenecks?

Pinpoint where tasks stall and resolve workflow roadblocks faster with clear data in the Ticket Status Workflow Dashboard.

Are best practices being followed?

Ensure each member of your team has the support and skills they need to stick with Sprint Best Practices.
Browse all pre-built reports

minware integrates with every major development tool.

minware also supports custom CSV/JSON and OpenTelemetry data for spreadsheets and internal tools.
See the full list of integrations

Save your tokens and leave the rest to us.

Get trustworthy insights faster with our data infrastructure.
Agents are great at a lot of things – enterprise-grade data quality, performance, and security are not among them.

Automated Caching & Orchestration

The minQL engine dynamically materializes tables and orchestrates updates so your results are always fresh and fast for millions of rows.

Standard Data Modeling & Benchmarks

minware provides pre-built models for common use cases like time allocation, cost attribution, DORA workflow efficiency, Agile and more.

Vendor Data Linking & Normalization

minware normalizes and links AI usage, pull requests, tickets, and more with advanced heuristics for unstructured relationships.

Error Handling & Recovery

minware handles errors caused by vendor API issues, schema updates, data anomalies, and more so your data is available 24/7.

Identity Resolution

minware reconciles names, emails, and user IDs across all vendors and matches them to multi-level team structure from any source.

Role-Based Access Control

Easily control team and individual data access permissions for minware users based on their role and team membership.

On-Premise Ingest Agent

For added security, the on-premise ingest agent runs locally and uploads data to minware. You maintain full control over keys and data.

AICPA SOC 2 Type 2 Certified

minware is SOC 2 Type 2 compliant. Learn more and access the full SOC 2 report from our security documentation.

Frequently Asked Questions

How does minware help define and track KPIs for software development teams?

minware provides delivery-based KPIs derived from Git, ticketing, and CI/CD data. These include planning accuracy, cycle time, review latency, and unplanned work ratio. Unlike subjective scoring or raw ticket counts, these software development KPIs reflect actual engineering activity.

Can minware measure developer performance metrics without time tracking?

Yes. minware calculates developer performance metrics like code contribution frequency, review response time, and rework rate using passive data collection. It does not require developers to log hours or update Jira fields.

Does minware support Git KPIs for engineering leaders?

Yes. minware connects to Git and tracks KPIs like pull request volume, time to merge, unreviewed PR percentage, and contribution consistency. These GitHub KPIs are linked to planning context from Jira.

Can minware help define KPIs for agile and scrum teams?

Yes. minware supports scrum KPIs such as sprint scope accuracy, story point completion, and review cycle time. These agile KPI metrics can be used to measure team health and improve sprint planning.

How does minware support engineering performance reviews?

minware tracks engineering performance metrics over time, including rework trends, code review responsiveness, and delivery predictability. Managers can use these metrics to guide performance reviews with objective data.

Can minware compare KPIs across teams or business units?

Yes. minware enables team benchmarking for KPIs such as velocity, lead time, scope creep, and planning stability. This helps leadership identify strong performers and coaching opportunities.

Does minware identify the most valuable KPIs for engineering outcomes?

minware surfaces actionable KPIs for software development including merge success rate, rework ratio, and carryover percentage. These provide more meaningful insights than raw ticket or point totals.

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