Flow Metrics
Measure engineering throughput using SPACE and flow-based metrics — throughput, efficiency, and delivery rate.
Overview
Flow metrics measure how work moves through your engineering system — not just how fast individuals work, but how efficiently the entire delivery pipeline converts effort into shipped features.
Koalr's Flow Metrics page implements the DORA 2023 team topologies approach to throughput, combining PR throughput, deployment frequency, and flow efficiency into a single dashboard view.
Core flow metrics
Throughput
Total merged PRs per week across the organization. This is the most direct measure of delivery volume.
Throughput = merged PRs / weekThroughput is most useful as a trend metric. A sustained increase in throughput (without a corresponding increase in cycle time) indicates the delivery system is improving.
Flow velocity
Story points or issues completed per sprint, normalized by team capacity. Unlike PR throughput, flow velocity accounts for the complexity and value of work.
Flow velocity = completed story points / sprintFlow distribution
The breakdown of work by type across the team:
| Flow type | Description | Healthy range |
|---|---|---|
| Features | New capabilities | 40–60% |
| Defects | Bug fixes | < 20% |
| Risk / Debt | Tech debt, refactoring | 15–25% |
| Business Enablers | Infrastructure, tooling | 10–20% |
Teams spending > 40% on defects are in reactive mode — customer experience is degrading faster than the team can improve it.
Flow load
The ratio of active work items to team capacity. A flow load > 1.0 means the team has more active work than it can complete — a leading indicator of missed sprint goals and increasing cycle time.
Flow load = active work items / optimal WIP
Optimal WIP = team size × 2 (rough rule of thumb)Flow time (cycle time by work type)
How long each flow type takes to complete. Comparing cycle time for features vs. defects reveals process differences:
- Defects typically cycle faster (smaller scope, urgent priority)
- Features with high cycle time indicate planning or scope issues
Dashboard sections
Flow summary KPIs
- Throughput (PRs/week, current vs. prior period)
- Flow velocity (story points/sprint, current sprint)
- Flow load (active items / optimal WIP)
- Flow distribution donut chart
Throughput trend
12-week line chart of weekly throughput. Annotate with team events (sprints, OKR cycles) to correlate process changes with throughput impact.
Flow distribution over time
Stacked area chart showing how the mix of feature/defect/debt/enabler work has changed over the past 12 sprints. A defect % that is growing is a warning signal.
Flow load over time
Bar chart of flow load per sprint. Sprints where flow load > 1.0 typically result in incomplete sprints and scope carryover.
Work item aging
Table of all in-progress work items ranked by age. Items older than 2 sprints without completion are likely blocked or too large — Koalr flags these as flow blockers.
Configuring flow type classification
Navigate to Settings → Work Config to map your Jira/Linear issue types and labels to Koalr's four flow types:
- Feature:
type = Story OR type = Feature - Defect:
type = Bug - Risk:
label = tech-debt OR type = Refactor - Enabler:
type = Task AND label = infra
Custom classifiers support AND/OR logic and multiple source fields.
Relationship to other metrics
- SPACE Metrics — flow metrics feed the Activity and Efficiency dimensions (SPACE Metrics)
- Cycle Time — flow time per work type is the cycle time broken down by category (Cycle Time)
- WIP Limits — flow load directly reflects WIP accumulation (WIP Limits)
- Technical Debt — the Risk/Debt percentage in flow distribution is a proxy for debt investment (Technical Debt)
- Sprint Burndown — flow velocity per sprint is the burndown's primary input (Sprint Burndown)