Your DORA numbers are only as good as the data behind them.

Deployment frequency, lead time, change failure rate, and recovery time — computed straight from your delivery, accurate and always current. The artifact is a DORA view by team and org, with trends, ready without a data pull.

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1 Regentis ingests pipeline runs, deployments, and incident data continuously.2 The four DORA keys compute on one shared definition, every team.3 A current, comparable DORA view lands for team and org.

Act I · The Tuesday test

The same day, run twice.

Here is the Tuesday before the QBR — once as it goes today, once with DORA wired to your pipeline.

WITHOUT DORA Metrics

WITH DORA Metrics

QBR is Thursday and the DORA slide still shows last quarter. Someone has to re-pull deploys, incidents, and lead times by hand — that someone is you.

COSTS · a day of archaeology

09:00

The four keys are already current — computed from the pipeline overnight, on the same definitions as last quarter.

INSTEAD · current numbers, zero pulls

Two teams turn out to count “a deployment” differently. The chart says one thing, and the room already knows not to trust it.

COSTS · the chart’s credibility

11:30

Every team is measured on one shared definition, so the comparison is the conversation — not the dispute.

INSTEAD · one definition, comparable teams

You ship the deck with a caveat slide explaining the data. Nobody will remember the number; everyone will remember the caveat.

COSTS · the evening, and trust

17:45

The QBR view exports as it stands: four keys, trends, by team — and the same numbers will still be there next week.

INSTEAD · defensible, repeatable, done

Hand-rolled DORA goes stale on arrival — wired-in DORA doesn’t.

Act II · The mechanism

Wired to your pipeline, not assembled for a slide.

The trigger — it reads the source of truth.Regentis ingests pipeline runs, deployments, and incident data from your connected CI/CD and delivery tools — continuously, not at reporting time.
The work — it computes the four keys, one definition everywhere.Deployment frequency, lead time for changes, change failure rate, and time to restore are computed on the same definitions for every team, refreshed as delivery happens. No team-by-team interpretation, no spreadsheet step in the middle.
The artifact — a current DORA view, comparable across teams.The four keys by team and org with trends over time — ready for the QBR, the board pack, or the Tuesday question, without a data-pull scramble.

The mechanism’s artifact: the four DORA keys for the selected scope, each with its definition, its tier, and its trend, current as of the last pipeline run

Act III · What lands on your desk

Numbers you can defend in the QBR.

The DORA dashboard.

All four keys for a team with their trends — current as of the last pipeline run, not the last time someone had a free afternoon.

DORA dashboard: all four keys on one screen — deployment frequency at 3.14 per workday and lead time at 6.40 hours both Elite, change failure rate at 5.8% and recovery time at 2.12 hours both High — each printing the definition it is measured by, each scored against a published threshold, and each carrying its weekly series over a 4-week average

Any team, same definitions.

The four keys for any team in the org, read from the same scope tree on definitions that never flex — switch the team, never the yardstick.

The DORA scope selector open on the organisation’s team tree with Payments Core chosen, and the four keys beneath it unchanged — deployment frequency 3.14 per workday and lead time 6.40 hours both Elite, change failure rate 5.8% and recovery time 2.12 hours both High

Act IV · The hesitations

Fair questions, answered plainly.

We already track DORA in a spreadsheet. Why change? ＋

The spreadsheet works — right up until the numbers need to be current and comparable. Hand-rolled DORA goes stale the day after it’s assembled, and definitions quietly drift between teams until nobody trusts the chart. Wiring the four keys to the pipeline removes the assembly step and the drift at the same time.

Are DORA metrics still enough when AI writes most of the code? ＋

On their own, no — four outcome metrics can’t tell you why delivery changed, only that it did. That’s why DORA is one lens in Engineering Intelligence rather than the whole product: Code Flow Health models the flow behind the outcomes and points at the constraining stage. The four keys stay valuable as the defensible, industry-standard outcome measures — they’re just not the diagnosis.

Will this be used to score individual developers? ＋

No. DORA in Regentis is computed at team and org level, and Regentis’s platform-wide policy is no individual scoring — no leaderboards, no per-person metrics, ever. Delivery metrics attached to people get gamed and breed distrust; attached to systems, they get fixed.

Our incident data is messy — can the failure and recovery keys be trusted? ＋

Honest constraint: change failure rate and time to restore are only as good as the incident signal behind them, which is why Regentis computes them from your connected incident and pipeline data on one consistent method rather than from self-reported postmortems. If your incident tooling isn’t connected yet, start with deployment frequency and lead time — the two keys your pipeline alone can ground — and add the rest when the data is.

Also in Engineering Intelligence

FEATURE · Code Flow HealthYou can feel the delivery slipping, but not where.Find the stage holding delivery back FEATURE · Always-on DevExA DevEx survey only works if people actually answer.Surveys people actually answer

All of Engineering Intelligence

Lights out

Retire the spreadsheet before the next QBR.

Connect your pipeline and incident tools and the four keys start computing immediately — current from the first day of the trial.

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