Where the number starts
Which systems, events, fields, and behaviours record the underlying business reality.
Metric Trust Audit
Stop arguing over the number your business depends on.
A fixed-scope diagnostic for one contested metric
If one important number appears in dashboards, spreadsheets, and meetings but different teams do not fully agree which version is right, the problem is not solved by another chart. The audit traces where trust breaks from capture through to value, including semantic-layer assumptions and AI-readiness risk, then shows what to fix first.
Best for revenue, churn, active customers, CAC, pipeline, margin, forecast, or another metric that is slowing decisions down.
The problem
The meeting stalls before the decision
The visible symptom is a disagreement about a number. The deeper cost is decision drag: people spend time checking, defending, reconciling, and re-explaining the metric before anyone can act.
- Finance has one version: the board pack, P&L, invoice, or month-end view.
- The business has another: the CRM, dashboard, spreadsheet, or operating report.
- The data team gets pulled in: not just to fix logic, but to explain reality.
The diagnostic
Trace one metric from capture to value
The audit uses the Reporting Trust value chain as the operating map. The point is not to audit the whole data estate. The point is to inspect one decision-critical number deeply enough to find whether trust breaks in capture, transformation, interpretation, action, or value realisation. With the semantic layer made explicit, the chain is Capture -> Transform [Semantic Layer Gate] -> Interpret -> Act -> Realise. The gate is checked at the exit of Transform, before humans or AI interpret the metric.
How it becomes a metric
The definitions, joins, exclusions, calculations, semantic assumptions, reports, dashboards, and spreadsheet logic involved.
Why teams disagree
The context, caveats, evidence, and stakeholder assumptions needed to explain what the number means.
Which decision it affects
The meeting, workflow, owner, threshold, or operating rhythm where the number is supposed to change behaviour.
What value is at stake
The business impact of making the number trusted enough to support decisions without repeated reconciliation.
Good fit
Use this when one number has become a trust problem
This is for a specific contested metric, not a vague data strategy conversation. The narrower the metric, the cleaner the diagnosis.
- The dashboard says one thing and the spreadsheet says another.
- Finance, sales, marketing, product, or operations disagree on the same number.
- A board pack, forecast, KPI review, or trading meeting keeps returning to reconciliation.
- People trust the people explaining the number more than the reporting system itself.
- AI summaries or automation are being considered, but the metric logic is not trusted.
Common entry points
Start with the number people already argue about
What you get
A practical evidence pack, not another vague recommendation deck
Metric definition map
Data value chain map
Source-to-report lineage
Transformation logic review
Semantic-layer assumption check
AI-readiness risk summary
Stakeholder disagreement summary
Context and evidence gap assessment
Decision-use map
Trust risk score
Prioritised fix roadmap
Executive summary
Boundaries
Fixed scope keeps the work useful
The audit is designed to find the first high-leverage fixes. It does not pretend that one short diagnostic can rebuild an entire data operating model.
- A full data warehouse rebuild
- A general dashboard production project
- A broad transformation programme
- A promise to fix every reporting issue
- Unbounded stakeholder workshops
Start here
Describe the contested metric
Share the metric, where disagreement shows up, and which decision it affects. If there is a fit, the next step is a short scoping call to confirm whether a fixed diagnostic makes sense, including whether the metric is safe for AI summaries, automation, or workflow triggers.
You do not need a full data strategy project to start. Start with the one number already slowing the business down, then trace where the value chain breaks.