What’s the difference between a roadmap and actual delivery?

A roadmap is the planned sequence of initiatives with timelines and outcomes; actual delivery is what ships, when, and at what quality. Teams track variance (e.g., ±10–20%) between plan and ship dates, scope, and impact. Agile reports (Scrum.org), burn-up charts, and release notes translate plan-to-actual gaps into actionable insights.

How do I measure roadmap vs actual delivery accurately?

Use a baseline snapshot and track schedule variance (%SV), scope change (story points or issues), and throughput (cycle time). Example: If a Q2 epic planned for 8 weeks ships in 10, schedule variance is +25%. Tools: Jira Control Chart, GitHub Deployments API, and DORA metrics (Google’s Accelerate report) for release frequency and lead time.

What KPIs should founders review weekly for plan vs actual?

Review: 1) On-time delivery rate (target ≥80%), 2) Scope churn (<15% added after sprint 1), 3) Lead time (p50/p90), 4) Defect escape rate (<2% critical post-release), 5) Confidence score by epic (1–5). DORA’s Accelerate (Google) supports lead time and deployment frequency as core predictors of performance.

How can we forecast more reliably against the roadmap?

Adopt probabilistic forecasting using historical throughput: produce p50/p80 dates (e.g., p80 = 12 weeks). Apply Monte Carlo with last 90 days of completed items (≥50 samples). Keep WIP limits, slice work to ≤5 days cycle time, and re-baseline monthly. Reference: Troy Magennis’ flow metrics and Monte Carlo methods for agile planning.

What tooling stack best aligns roadmap with actuals?

Combine: Productboard/Aha! for roadmap, Jira/Linear for delivery, GitHub/GitLab for PRs, and Looker/Metabase for metrics. Automate links by epic ID, pull deployment tags, and compute variance dashboards (SV, scope delta, DORA). Many teams hit >85% on-time after adding Monte Carlo forecasts and weekly variance reviews.

Roadmap vs Actual Delivery: Founder-Ready View

Roadmap vs actual delivery is a lightweight activity report that maps planned outcomes to what actually shipped, creating consistent visibility for founders and PMs. It pulls from code changes, not status anecdotes, to show real progress and reduce debate. The goal is faster alignment and fewer status meetings. In our experience working with SaaS teams, executives don't need to hover over engineers; they need a clear release cadence tied to concrete artifacts like pull requests and tags. DeployIt reads your repositories in read-only mode and turns merged work into a plain-language shipping record: a weekly email report every Monday for steering, monthly and quarterly roll-ups for boards and clients, and a real-time dashboard in between. Work is estimated in dev-days (one dev-day is roughly five hours of focused work), and activity from AI coding agents such as GitHub Copilot, Cursor, or Claude Code is detected and attributed by name alongside human developers. The result is a citable snapshot — what shipped, how it maps to the plan, and where slip risk appears early — without micromanagement. Here's how to build an anti-theater report using Git activity and keep everyone honest, gently.

The status gap: plans drift, artifacts don't

In our experience working with SaaS teams, the roadmap says "Q2: revamp billing," while Git shows "five PRs renamed enums and one feature flag — no migration code."

Roadmaps are narrative promises; delivery is a pile of immutable artifacts: commits, tags, release notes, pull-request titles, and deploy timestamps.

Founders need read-only visibility that starts from Git, not slideware. That means asking: what shipped, where, and when, based on code that actually merged.

Narrative vs. artifact reality

A quarterly plan is a story. It compresses scope, risk, and sequencing into a neat theme.

Git history is evidence. It records intent changes, reversals, and scope creep as merge diffs, revert commits, and branching patterns.

The friction comes from trying to answer business questions with anecdotes when the truth is encoded in the repo.

What features shipped to production last week?
Which roadmap items turned into code paths, migrations, or docs?
What was deferred, split, or killed mid-quarter?

DeployIt anchors status to merged artifacts: the weekly report links pull-request titles, tags, and deploys to the roadmap theme they belong to, without asking engineers for status write-ups.

"Plans are persuasion; Git is proof. Start your status from proof."

Narratives drift when discoveries hit. Artifacts don't drift — they accumulate.

A founder view built on Git avoids secondhand summaries and avoids policing. It's pull-only, read-only, and auditable.

Weekly shipping record: a "Shipped" list by repo and theme, estimated in dev-days.
Real-time dashboard: merged PRs, releases, and per-initiative progress between reports.
Named attribution: human developers and AI agents, so you know who — or what — did the work.

This gives you a clear shipping rhythm without creating new work.

ℹ️

Pin status to artifacts. If it didn't merge, it's not shipped. If it merged without a tag or release note, it's not productized yet.

When a stakeholder asks "what actually shipped," you answer with artifacts, not opinions. For the broader method, see how to track engineering progress without micromanaging.

Why ticket burndown and DORA alone miss the point

In our experience working with SaaS teams, burndown charts and DORA can look "green" while the feature founders promised never actually shipped to users.

DORA measures deployment speed and stability, and burndown tracks tickets closed, but neither answers "what changed in the product this quarter?"

They abstract away the unit of customer value — the diff.

A sprint can hit 100% burndown from chores, refactors, and tech debt.
High deployment frequency can be hotfixes or copy tweaks, not the API your PMM announced.
Lead time can drop while the flagship integration misses the release window.

Why this matters to founders

Founders need a code-backed view: which PRs merged the actual scope, what changed, and what hit default branches by week.

That's why DeployIt's weekly report rolls up:

The exact pull-request titles and the initiative they map to
A plain-language answer to "what shipped?" grouped by theme
The estimated effort in dev-days, so a week of invisible infrastructure work still shows up honestly

When priorities churn, ticket counts drift from code reality. Merged diffs don't.

The contrarian angle: DORA is healthiest as an internal ops gauge, not as an executive proxy for shipped scope. Treating it as a delivery truth source creates theater — good hygiene, wrong question.

Burndown answers "did we close what we planned?" DORA answers "how fast and stable are deliveries?" Founders ask "what reached users?" That answer lives in merged diffs, not ticket states.

A fictional weekly report entry:

"Billing: 'Introduce usage tiers' — PRs #842, #847 added price calculator and plan limits. Tests added, feature flag on. ~3 dev-days."
"Editor: 'Slash commands' — PR #865 merged parser changes; UI behind beta flag; no rollout yet. ~1.5 dev-days." This is faster and less biased than spelunking boards and chats.

Two practical patterns we recommend:

Anchor roadmap initiatives to repository conventions (PR title prefixes, branch names, release tags); your report will group naturally.
Treat DORA as guardrails; treat the weekly report as the single shipping record for the quarter.

What DeployIt shows: release truth without a scorecard

In our experience working with SaaS teams, the most reliable way to compare roadmap vs actual delivery is to read what merged — and to present it in language a non-technical leader can act on.

DeployIt provides a read-only window into repositories that produces a weekly shipping report and a plain-language answer to "what shipped vs what we planned?"

What "read-only" means in practice

DeployIt connects to your Git provider with read scopes only. It observes and reports; it never blocks a merge, never writes to your repos, and never files tickets on anyone's behalf. When something looks risky — a quiet initiative, an agent PR merged without review — it raises an alert. It does not intervene.

Read-only connection

Point DeployIt at your Git provider with read permissions. No write scopes, no workflow changes for engineers.

Monday weekly report

Every Monday, an email lands with what shipped last week: initiatives, dev-days of estimated effort, and slip signals — readable in five minutes.

Monthly and quarterly roll-ups

Longer-cycle reports built for board packs and client updates: quarter-to-date delivery vs plan, in the same plain language.

AI agent detection

Activity from coding agents (GitHub Copilot, Cursor, Claude Code, and others) is detected and attributed by name, so agent output is measured, not invisible.

ℹ️

DeployIt focuses on artifacts: pull-request titles, release tags, and code paths, translated into initiatives and dev-days. It shows per-developer and per-agent activity because that's what delivery is made of — but it reads and alerts, it never polices.

Why this yields "release truth"

Roadmaps describe intent; repos record reality. Because pull requests are where most teams review and merge change, PR metadata is a dependable ledger for shipped scope.

By grounding visibility in merged work, DeployIt reduces the time leaders spend reconciling tickets to what actually merged. You can see the live view on the activity dashboard.

How the weekly roadmap-vs-delivery report comes together

In our experience working with SaaS teams, the fastest path to "roadmap vs actual delivery" is mapping themes to PRs and tags directly from the repo without adding new fields or rituals.

Connect source repos (read-only)

Install the GitHub app with read access. No write scopes. Select the repos that matter; ignore experiments and archived projects.

Name work after your roadmap

Adopt one lightweight convention so merged work self-organizes:

PR title prefixes like Billing-Q3
Branch naming patterns (feature/billing-q3/*)
Release tags that carry the theme (v1.8.0+billing-q3) No new tools — just naming discipline your team probably half-follows already.

Read the Monday report

Every Monday, the weekly email answers:

Which initiatives moved? Which shipped?
How much effort landed, in dev-days, and from whom — humans and AI agents?
What went quiet, and what merged without mapping to any plan?

Roll up for the quarter

Monthly and quarterly reports assemble the same record at board altitude: delivered vs planned, trend lines, and the initiatives that consumed the quarter. Archive them and quarter-to-date reviews become a ten-minute read.

Reading the report against your plan

The report is opinionated: map intent to delivery with minimal configuration and zero manual tagging.

Planned (Intent)

The initiatives your roadmap slated for this cycle
Owner and target milestone
Planned scope summary and risk notes

Shipped (Delivery)

Merged PRs grouped by initiative, with estimated dev-days
Tags and releases with notes excerpts
Who contributed: developers and named AI agents

Gaps (Delta)

Initiatives with no merged work
Work merged without a mapped initiative
Slipped items with a proposed next step

The Planned column is your roadmap document; the Shipped column is what DeployIt reconstructs from Git. Reading the delta between them takes ten minutes on a Monday — that's the whole ritual.

Interpreting slippage and scope change without blame

In our experience working with SaaS teams, the earliest honest signal of slippage is a week where commit volume stays steady but the ratio of refactors and tests to feature-tagged work flips sharply.

Tie roadmap themes to Git at the source. Prefix pull-request titles and release tags with theme and quarter: "Billing.Q3 — Add proration API." Use branch names like "theme/billing-q3/proration-api." This lets the weekly report group work automatically.

Early warning signals from Git artifacts

Consecutive PRs with titles starting "Fix:" or "Refactor:" under the same theme suggest discovery effort, not feature output.
High churn in the same files without new endpoints or migrations points to unclear requirements. Smaller, clearly-scoped PRs merge faster — keep them small where possible.
Tag drift: release tags without a matching theme prefix signal unplanned work creeping in.

Map intent to delivery using a lightweight tag set:

Releases: v1.8.0+billing-q3
PR titles: Billing.Q3 — "Add invoice preview (behind flag)"
Commits: [billing-q3]feature, [billing-q3]refactor, [billing-q3]spike

Blame-free interpretation comes from comparing theme-labeled intent to the shape of shipped artifacts, not from grading people.

How to read the signals

Compare PR count to net new modules per theme. A spike in new files with few removals suggests additive scope; call a scope review, not a retro hunt.

If two consecutive weekly reports show the same PRs rebased repeatedly, it's a dependency issue. Ask which module or external API is blocking — the answer is in the linked PRs.

A flat week with only "chore/ci" under a theme means discovery or environment setup. Update the roadmap with a "Spike" sub-item and date, and move on.

Example: tagging releases to roadmap themes (illustrative)

Onboarding.Q2 — Release tag v2.3.0+onboarding-q2 with PRs:
- "Onboarding.Q2 — Email magic-link endpoint"
- "Onboarding.Q2 — Refactor user-token service"
- "Onboarding.Q2 — Add rate limits (guardrail)"
Weekly view: 5 PRs — 2 feature, 2 refactor, 1 guardrail. Trend fine; if next week shows 0 feature and 4 refactor, schedule a scope checkpoint.

This approach pairs intent labels with actual artifacts so founders can answer "what shipped?" confidently. For the demo-day version of the same idea, see running a sprint review straight from Git history.

FAQ: governance, security, and rollout next steps

In our experience working with SaaS teams, the fastest way to de-risk a "roadmap vs actual delivery" rollout is a two-week pilot on one or two repos before any org-wide enablement.

Data access and least privilege

DeployIt runs on least-privilege Git scopes and does not write to your repos or tickets.

Access: read-only Git integration; no write scopes.
Data types: commit metadata, pull-request titles and state, branch names, tags and releases, and the diffs needed to estimate effort in dev-days.
Your code is never used to train models. Full stop.

DeployIt shows per-developer and per-agent activity, because delivery is made of individual contributions — including AI agents' PRs. What it doesn't do is score personality, track time at the keyboard, or block anyone's work. It reads Git, estimates effort, and alerts when something drifts. Interpretation stays human.

DeployIt is free during early access. Paid plans are planned for January 2027 at $19 per active human developer per month. There is nothing to buy today — early-access users simply use the product.

Yes. Commits and PRs co-authored or authored by coding agents (Copilot, Cursor, Claude Code, and others) are detected and attributed by name. Detection is heuristic — clearly labeled, not claimed as infallible — and it makes agent output visible in the same reports as human work.

Pilot first, then scale

Start with one squad and one repo.

Week 1: connect repos (read-only), pick your naming convention, receive the first Monday report.
Week 2: review report accuracy with your PM or tech lead, adjust filters, add a second repo. Then compare last quarter's intent to shipped PRs.

Ready to see what your team shipped?

Connect a repo read-only and get your first Monday report. Free during early access.