process-audit

name	process-audit
description	Use when an operational process needs its start, end, owner, outcome, representative sample, measured queues or handoffs, bottleneck evidence, or controlled improvement experiment made explicit.
role_groups	["operations"]
jtbd	Process reviews often rely on anecdotes and skip the queue or rework evidence needed to improve them. This defines measurable boundaries, samples representative work, finds bottlenecks from observations, and frames controlled experiments with success measures while keeping human authority explicit.
time_investment	20-30 minutes per process

Process audit

When to use

Use this skill when a repeatable process needs an evidence-backed health audit, measured handoff and rework analysis, bottleneck diagnosis, or a controlled improvement experiment.

Do not use it to change a live process, assign blame, impose a policy, or declare an improvement successful from opinions alone. Not for a process with no explicit start, end, owner, outcome, or observable sample unless those gaps are reported as unknown.

Inputs and source discipline

Define the process boundary with an explicit start event, end event, owner, and desired outcome. Record the review window, timezone, scope, as-of date/time, and source date for the process definition. If ownership or outcome is not evidenced, use TBD or unknown; do not infer it from a job title or the person who supplied notes.

Build a source ledger from representative records, timestamps, queue views, handoff logs, rework records, support or operational data, and participant observations. For each observation record the source, source date, as-of date/time, locator, timestamp and timezone, sampling frame, and freshness. Separate directly observed measures from participant interpretation.

Method

1. State the start, end, owner, outcome, population, and review window. Make the intended outcome testable without assuming that the current process achieves it.
2. Select a representative sample. Document the sampling frame, inclusion and exclusion rules, time window, selection method, sample count, and known coverage gaps. Include normal and exceptional cases when the frame supports them; do not cherry-pick anecdotes. Record observations with citations and confidence.
3. Map the observed path from start to end. Measure active time, waiting time, queue size or age, handoff count and delay, rework count and reason, and outcome status using consistent units and timezone treatment. Keep missing measurements visible.
4. Apply a bottleneck method: compare stage throughput and capacity with queue volume, wait time, handoff delay, and rework. Call a bottleneck only when the measured constraint explains the observed delay or accumulation; otherwise label it a hypothesis and state what would test it.
5. Separate observed friction from inferred causes and list alternatives. Quantify impact only from the sample and source data; do not extrapolate beyond its coverage.
6. Frame a controlled experiment before action: hypothesis, proposed change, baseline or comparison, population, duration, owner or TBD, guardrails, stop condition, follow-up date, and a defined success measure with unit and time window. Human authority must approve the experiment; a recommendation is not a human decision.

Truth and uncertainty rules

Label each boundary, observation, measure, and explanation as observed, inferred, unknown, stale, or contradictory. A queue measure is evidence of queue state, not by itself proof of cause; a participant opinion is not an observation. Preserve contradictory records and explain sampling or instrumentation limits.

Never invent dates, metrics, owners, intent, money, percentages, causes, status, or evidence. Do not invent a sample denominator, use an anecdote as representative, or claim an experiment succeeded before its success measure is observed and reconciled.

Output contract

Return an audit containing:

• explicit start, end, owner, outcome, scope, timezone, review window, and as-of provenance;
• sampling frame and representative-sample method, sample count, coverage limits, and cited observations;
• an observed flow with measured queues, waits, handoffs, rework, units, and source dates;
• bottleneck method, evidence, confidence, alternatives, unknowns, stale inputs, and contradictions;
• a controlled experiment proposal with baseline/comparison, owner or TBD, guardrails, duration, and a measurable success measure; and
• recommendations, clearly labelled as recommendations rather than human decisions, with sources, confidence, unknowns, and contradictions exposed.

Safety and write boundaries

The default is read-only. Do not alter workflow rules, queues, assignments, policies, records, or communications from an audit. For a requested experiment or other action, preview the exact change, scope, owner, audience, and success measure; obtain explicit confirmation from the human authority; then perform only the confirmed action. Do not represent a proposed experiment as approved or active.

Verification and recovery

Read back the audit and reconcile the start/end boundaries, owner, outcome, sample count, denominator, measured queue/handoff/rework totals, source dates, timezone, and success measure with the evidence ledger. After an experiment, read back its measured result and reconcile it with the baseline, comparison, window, and guardrails before claiming success.

If sampling, measurement, read, write, or reconciliation fails, stop and report the failed check and affected stage. Do not retry blindly, discard inconvenient records, or alter the denominator to make a result pass. Re-read the source and destination, mark the result unknown or stale as appropriate, and recover through a human-confirmed correction or a new controlled run with the failure retained.