VeloWiseengineering delivery intelligence

See how VeloWise works

Turn software delivery data into clear insights about progress, risk, bottlenecks, scope changes, and release readiness.

Try the sample project
  • Sprint
  • Epics
  • Stories
  • Tasks
  • Status
  • Scope changes
  • Release information
VeloWiseDelivery data → VeloWise

1/5Bring your delivery data together.

The demo, step by step

A fictional team, one sprint, analysed the way VeloWise analyses yours. Every number below is example data.

  1. Bring your delivery data together.

    Sprints, epics, stories and tasks, their status history, scope changes and release information come together in one model of delivery. VeloWise maps each workflow status to a delivery stage — development, code review, QA, done, released — so every team is read the same way — see how software delivery workflows differ between teams, or the supported data sources.

  2. See how delivery changes as the sprint progresses.

    The team committed to 60 issues. By day 8, 15 more had been added, taking the sprint to 75. 48 issues are complete, 41 of them in production; 12 are in QA and testing.

  3. Understand what changed — not just the final numbers.

    • Scope increased +25% — 60 committed → 75 in scope.
    • QA / test bottleneck — 12 waiting in QA — usually 5 at this point.
    • 9 items likely to carry over — 3 not started · 3 blocked · 3 aging in development.
    • 7 completed items not yet released — 48 completed · 41 in production.

  4. VeloWise explains what happened — and shows its evidence.

    Scope increased during the sprint while work accumulated in QA. Engineering completion remained ahead of production releases, contributing to carryover.

    Each part of the explanation cites its evidence: Scope +25% (60 → 75); QA / test: 12, usually 5; 48 completed, 41 released; 9 likely to carry over.

  5. Finish with a delivery story leadership can act on.

    • Sprint health: 64% complete — 48 of 75 issues
    • Scope change: +25% — +15 since the start
    • Primary constraint: QA / test — 12 waiting, usually 5
    • Likely carryover: 9 — not started, blocked or aging
    • Released: 41 — 7 more done, awaiting release

From delivery data to delivery intelligence

How VeloWise worksExample delivery data
  1. Delivery datasprint, epics, stories, tasks, status
  2. Analyzestages, scope, flow, history
  3. Explainwhat changed, and why
  4. Communicatea leadership-ready view

Four steps, run the same way every time — so the answer is consistent and the evidence is always one click away.

Analyze compares the sprint with its own plan (original commitment vs current scope) and with the team’s history (is this queue larger than usual?). Explain turns the signals that matter into plain sentences, each backed by the numbers behind it. Communicate gives leaders a short view they can trust, without anyone assembling it by hand. Every rule is documented in the methodology.

It works with your workflow, whatever it looks like

No two teams name their workflow the same way. One team moves work from Coding to Peer Review to Testing; another from Development to PR to SIT to UAT. VeloWise does not assume that a status called “Done”, “QA” or “Complete” means the same thing everywhere. It maps each of your statuses to a delivery stage, and you can adjust the mapping.

Your statuses, read as delivery stagesExample delivery data
  1. DevelopmentCoding, In Progress, Active
  2. Waiting for reviewReady for Review, PR Open
  3. Code reviewPeer Review, PR
  4. QA / validationTesting, SIT, Verification
  5. Ready for releaseDone, Awaiting Deploy
  6. ReleasedProduction, Deployed

Waiting states stay waiting states, so VeloWise can tell work being tested from work waiting to be tested.

Because every stage is read the same way, the same questions work for every team: where work accumulates, how long it waits, where carryover starts, and whether engineering-complete work reaches production. The guide to software delivery workflows explains the common workflow models, why the difference between active and waiting work matters, and includes a workflow designer you can try. To see how queues become bottlenecks, read how to find bottlenecks in software delivery.

What VeloWise helps you understand

See every capability on the VeloWise features page, or start with engineering delivery intelligence for better planning and fewer surprises.

Stop reporting numbers. Start explaining delivery.

Engineering teams already have more delivery data than anyone reads: every status change, every sprint, every release. Dashboards turn it into charts. What leaders still lack is the explanation — and so managers rebuild it by hand, every sprint, in slides and status meetings.

The same sprint, reported two waysExample delivery data

Reporting numbers

64% complete

  • 48 of 75 issues done
  • 41 released
  • 12 in QA
  • Leadership asks: is that good or bad?

Explaining delivery

Scope grew; QA is the constraint

  • Scope +25% after the start
  • QA holds 12 (usually 5)
  • 7 complete but not yet released
  • 9 likely to carry over — act now

Numbers say what. An explanation says why — and what to do next.

VeloWise is built to answer the questions leaders actually ask:

  • What changed? Scope added and removed since the start, and when.
  • Why did it change? The signals behind the numbers, with the evidence for each.
  • Where is work stuck? Stages holding more than usual, and work that has been there too long.
  • What has actually shipped? Released work, separate from work that is merely done.
  • What does leadership need to know? A short, consistent view — how to communicate sprint progress to leadership.

Know what is happening. Understand why. Keep everyone aligned.

See what your delivery data is telling you.

Import your delivery data, or explore the synthetic sample project first. Analysis runs in your browser.

Analyze your delivery dataTry the sample project