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Derived metrics

The dimensions most people actually want to report on aren't Jira fields — how long did this take?, how long has it been stuck?, did it bounce backwards? Insights and charts computes these from each issue's change history and exposes them as first-class dimensions and filters: group by them, bucket them, trend them, and cross-filter on them, with no MDX or scripting.

This is the capability that client-side charting gadgets can't match — they can only group by fields that already exist on the issue.

How they're computed​

  • Change-log rollups. The app replays each issue's changelog into a small set of precomputed, indexed values — cycle-time days and bucket, current-status age, time spent in each status, and a reopen count. This runs as an on-demand computation when you first chart a project and is refreshed on a daily schedule, so charts read precomputed values instead of re-reading every issue's history on each load.
  • Daily snapshots. For state-by-day charts (open issues over time, CFD), the app reconstructs the state of the backlog on each past day from the same change history.
Use a project dataset

The rollups and history are per-project, so derived-metric and flow-history charts need a project (or agile-board) dataset, not an arbitrary cross-project JQL. See Datasets.

The derived dimensions​

Cycle / lead time​

The Cycle time & flow dashboard — median and p85 KPIs, a cycle-time distribution, and a control chart with p50/p85 lines

How long issues took to complete. Available as:

  • a bucketed dimension (cycle-time bucket) for a distribution bar/pie,
  • a measure — median, p75/p85/p90 cycle-time days — for KPIs, and
  • the control chart (a scatter of resolved date × cycle time with percentile lines). See Chart types.

Time in status​

How long issues spend in each status — the flagship "where does work wait?" metric. Chart the average time in status across the workflow.

WIP / status aging​

How long issues have sat in their current status (status-age bucket). Surfaces stale in-progress work that simple counts hide.

SLA state​

Against a target you set (in Options → SLA target), each issue is within or breached. Use it for a "% within SLA" KPI, a breach count, or SLA state grouped by priority.

Reopen count​

How many times an issue moved backwards in the workflow — a quality signal that's invisible to a current-state count.

Flow history (state-by-day)​

From the daily snapshots:

  • Open issues over time — the unresolved backlog day by day.
  • Cumulative Flow Diagram (CFD) — issue count per status per day, as a stacked area.

Velocity & sprint burndown​

From a board dataset and Jira's agile API:

  • Velocity — committed vs. completed points per sprint.
  • Sprint burndown — remaining work vs. the ideal line within a sprint.

Put them to work​

Every derived metric above ships as a one-click recipe in a matching template — Cycle time & flow, Time in status & WIP, SLA & aging, Flow history (CFD), Velocity & burndown. See Templates & recipes.