Sample audit report

Product process audit
— excerpt

This is what you actually get: an anonymized excerpt from a real audit of a B2B SaaS company (4 product squads, ~35 people in product & engineering). The full report covers 12 metric areas; here are 6 of them.

All numbers are real but the company is anonymized with their approval. Your audit will look at the same areas — with your data, your context, and recommendations specific to your teams.

1. Delivery metrics

How fast and how predictably work moves from "committed" to "in customers' hands".

Cycle time (commit → production)Needs attention
34 daysmedian, observed
7–14 dayshealthy range for this context

Finding: the flow, not the coding, is slow. Items spent 61% of cycle time waiting — in review queues, in "ready for QA", and blocked on a single shared designer. Actual hands-on time was ~9 days.

Recommendation: introduce WIP limits per squad, split the design bottleneck by embedding design earlier, make wait states visible on the board. Expected effect: cycle time under 15 days within a quarter.

Sprint predictability (committed vs delivered)Needs attention
52%avg. of committed scope delivered
80%+healthy range

Finding: mid-sprint scope injection from stakeholders was the top cause — on average 28% of sprint work was added after planning, mostly via direct Slack requests to engineers.

Recommendation: a single intake path for urgent requests through the PM, an explicit "interrupt budget" per sprint, and making injected work visible in the sprint review.

Release frequencyImproving
every 3 wkscurrent
weekly+target for this product

Finding: releases were batched around a manual regression suite (2 days of QA per release), which pushed teams to bundle changes — increasing risk per release.

Recommendation: automate the top-20 regression scenarios first (est. 3 weeks of effort), then decouple squad releases. Smaller releases = less risk, faster feedback.

2. Discovery metrics

Whether the team is building the right things — not just building things right.

Customer contact per PMNeeds attention
0.7customer conversations / PM / month
4+healthy baseline

Finding: PMs spent 71% of their calendar time in delivery ceremonies and internal syncs. Discovery existed as a phase in the roadmap, not as a continuous habit. Two of four squads shipped major features in the last 6 months with zero user validation.

Recommendation: a standing weekly research slot per squad, a shared interview pipeline owned by the PM group, and cutting 3 of 7 recurring internal syncs (details in the full report).

Idea-to-validation ratioImproving
9%of shipped features had a stated hypothesis + success metric
60%+healthy baseline

Finding: the backlog was output-framed ("build X") rather than outcome-framed ("move metric Y"). Post-release, nobody checked whether features worked — success was "shipped on time".

Recommendation: a lightweight hypothesis template on every epic (2 fields: expected outcome, how we'll measure), plus a monthly "did it work?" review. Low effort, changes the conversation.

3. Team & process health

Whether the ceremonies and structures actually produce decisions and improvement.

Retro action completionFixable fast
12%of retro action items completed
70%+healthy baseline

Finding: retros generated 5–8 actions each, none with an owner or a deadline; the same three problems appeared in retro notes for five consecutive months. The team had stopped believing retros change anything.

Recommendation: max 2 actions per retro, each with an owner and a check-in at the next retro. One structural problem per month escalated to leadership with a decision deadline.

Executive summary — top 3 moves (from the full report)

  1. Kill the wait states: WIP limits + design embedded earlier → biggest single lever on cycle time.
  2. Protect the sprint: single intake path + interrupt budget → predictability from 52% toward 80%.
  3. Make discovery a habit, not a phase: weekly research slot + hypothesis template on every epic.

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