Data-Driven Engineering KPIs

Leverage concrete engineering KPIs to conduct fair, objective, and growth-focused performance evaluations.
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Time Spent Pre/Post-Review
Story Points Completed
AI Chat
Never Merged Code

Improve your development lifecycle end-to-end

Quality

Track bug rates, time-to-fix, and more to address quality issues at their source.

Efficiency

Look at cycle times, task sizes, and more to uncover hidden bottlenecks.

Predictability

Compare ticket, sprint, and project progress to plans and pinpoint delivery risks.

Value

See where engineering time went to track effort vs. value delivery.

Answer real questions with minware’s report library

Story Points Completed

How can we fairly analyze individual contributions?

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

Where are the biggest bottlenecks?

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

Are best practices being followed?

Ensure each member of your team has the support and skills they need to stick with Sprint Best Practices.
See Your Data

Debug bottlenecks with ease

Debug bottlenecks with ease

Zoom in with minware’s full work timeline to see exactly what happened and why.
minware builds the timeline from Git, ticket, and meeting data using our patent-pending time model – no time tracking required.
Read about minware’s time model >

Break down metrics by any historical field

Break down metrics by any historical field

All reports are fully editable with minware’s report builder.
Break down metrics like PRs merged or active work time by any current or historical field (e.g., PR approval or ticket label).
minware natively stores the complete history of every field (including custom fields and labels) for seamless end-to-end visibility.
See report builder live >

Customize any metric with minQL

Customize any metric with minQL

Skip the Jira cleanup – all metrics are fully editable with minQL formulas.
Access any field from any source (including custom CSV/JSON uploads) with a full suite of database functions for total control and flexibility.
minQL also supports advanced SQL features like time-series joins and window functions.
Read the minQL docs >

Integrate with any source and front end

Integrate with any source and front end

minware integrates with popular Git, ticket, and calendar systems, as well as any custom CSV/JSON format.
View reports in minware’s dashboards, download CSV, or connect to any tool with our minQL-based ODBC driver.
See all integrations >
GitHub
Azure
Jira
Google
CSV/JSON
More
Data Ingest
Identity Linking
Time Modeling
Performance Caching
Time-Native minQL Engine
minware Dashboards
CSV Export
BI Tools
Headless ODBC

Enterprise flexibility, security, and performance

We designed minware from the ground up for Fortune 500 customers to handle homegrown systems, fragmented tools, large orgs, and secure environments.

Dynamic Table Caching

The patent-pending minQL engine dynamically caches tables for on-the-fly custom metrics with instant results for millions of rows.

Custom Data Integration

Integrate seamlessly with any structured or semi-structured data source including flat file uploads and custom APIs. Read more >

Identity/Team Management

minware automatically normalizes aliases across all your systems and supports multi-level team structure imports in any format. Read more >

Role-Based Access Control

Easily control team and invidual data access permissions for minware users based on their role and team membership. Read more >

On-Premise Ingest Agent

The on-premise ingest agent uploads files to a shared storage bucket. You maintain full control over keys and data. Read more >

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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