Using the "Group by" dimension to understand your metrics

Last updated: December 12, 2025

Overview

The Group by Dimension feature allows you to break down and analyze your engineering metrics across different organizational and work attributes. Instead of viewing aggregate metrics for your entire organization or team, you can segment data by dimensions like team, person, repository, job level, and more.

Accessing the Feature

You can access the Group by Dimension feature on most metrics pages in Span:

  1. Navigate to any metrics report (e.g., DORA metrics, PR cycle time, deployment frequency)

  2. Look for the "Group by" dropdown in the metrics page header

  3. Click to open the dimension selector and choose your preferred dimension

Your selection is automatically saved and persisted in the URL, making it easy to share specific views with teammates.

Available Dimensions

You can group metrics by the following dimensions:

People-Related

  • Person - Individual team members

  • Job Level - IC level (e.g., Senior Engineer, Staff Engineer)

  • Job Title - Role (e.g., Product Manager, Software Engineer)

  • Job Family - Department (e.g., Engineering, Product, Design)

  • Location - Geographic location or office

  • Tenure - Length of employment (e.g., 0-1 year, 1-3 years)

Organizational

  • Team - Teams/groups in your organization

  • Team Path - Full hierarchical path of a team

Infrastructure

  • Repository - Code repositories

  • Service - Microservices or logical service divisions

Note: Not all dimensions are available for all metrics. The dropdown automatically shows only compatible dimensions based on your selected metrics.

Common Use Cases

Compare Team Performance

Break down PR cycle time by team to identify which teams have longer review cycles and may need process improvements.

Analyze Individual Contributions

View deployment frequency by person to understand individual productivity patterns and identify top performers or those who may need support.

Organizational Insights

Compare metrics across job levels, families, or locations to understand how different segments of your organization perform.

Infrastructure Analysis

Group metrics by repository or service to identify which parts of your codebase have the highest deployment frequency, longest lead times, or other characteristics.

How to Use

Basic Workflow

  1. Open a metrics report with the data you want to analyze

  2. Click the "Group by" dropdown in the page header

  3. Select a dimension (e.g., Team, Person, Repository)

  4. View the breakdown:

    • Charts update to show separate lines/bars for each dimension value

    • Data tables show one row per dimension value with aggregated metrics

  5. Optional: Filter specific values - After grouping, use filters to focus on specific teams, people, or repositories

Advanced Options

Hierarchical Team Grouping: When grouping by Team, you can specify the hierarchy level (e.g., group by Department vs Squad level).

Multiple Visualizations: Results appear in both chart and table formats, allowing you to visualize trends and export detailed data.

Time Granularity: Combine dimension grouping with time-based breakdowns (daily, weekly, monthly) for deeper analysis.

Example: Finding PR Cycle Time Bottlenecks

Goal: Identify which team has the longest PR cycle time

Steps:

  1. Navigate to Metrics → Pull Request → Cycle Time

  2. Set your desired date range (e.g., last 90 days)

  3. Click "Group by" and select "Team"

  4. Review the chart showing each team's cycle time trend

  5. Check the data table for specific numbers (average, median, P95)

  6. Optionally filter to compare specific teams side-by-side

Result: You can quickly see which teams have consistently high cycle times and need process improvements.

Tips

  • Start broad, then narrow: Begin by grouping at a high level (e.g., Team), then filter to specific values for deeper analysis

  • Combine with filters: Use dimension grouping alongside date range and other filters for precise analysis

  • Share insights: Copy the URL to share your specific view with teammates—all settings are preserved

  • Watch for sample sizes: Smaller teams or individuals may show more volatile metrics due to lower data volumes

Limitations

  • Some dimensions may not be available for certain metrics based on data compatibility

  • Access to certain dimensions (especially HR-related like job level or tenure) may be restricted based on your permissions

  • Individual-level breakdowns should be used carefully and in accordance with your organization's privacy practices

Need help? Contact your Span administrator or reach out to support@span.app.