Measurement & Decision Intelligence Audit

Which numbers can you trust, and what should they help you decide?

An audit of tracking, KPIs, attribution and reporting that checks where the numbers come from, what they mean and whether they support your decisions.

Tell us what is not working

Who this is for: Teams with dashboards and analytics tooling but inconsistent numbers, unclear attribution or low confidence in reporting.
When this helps: Teams or platforms give different answers, and you cannot trace the figures behind an important business decision.
Decision at the end: An agreed priority list and handoff showing which definitions, data gaps and reporting responsibilities to address first.

Value path

Customer and operating signals → informed decisions

The problem: Reports may use different definitions or numbers nobody can trace. Even a reliable measure may lack a clear rule for when to act or a person responsible for doing so.
Evidence we need: The decisions and decision-makers in scope, agreed platforms and periods, metric definitions, tracking plans, source access and current reporting process.

Assess → Transform → Operate → Scale

Understand the problem before deciding what to change.

This engagement covers Assess. Transform, Operate and Scale each need a separate scope and approval. An assessment recommendation does not commit you to later work.

Assess
Understand the problem
Check the evidence and how the work happens. Decide which problem needs attention first.
Transform
Put the change into practice
Agree the scope, responsibilities and success measures, then implement the chosen changes.
Operate
Make the change hold
Support the change in day-to-day use and review whether it is delivering the intended result.
Scale
Repeat what works
Use results from day-to-day work to decide what to improve or extend, retaining the conditions that made it work.

Best for

Teams with dashboards and analytics tooling but inconsistent numbers, unclear attribution or low confidence in reporting.

Boundaries and responsibilities

When this helps: Teams or platforms give different answers, and you cannot trace the figures behind an important business decision.
Why it matters: An improving dashboard metric can still lead to a poor business decision if its definition, source or intended use is wrong.
What you can decide: An agreed priority list and handoff showing which definitions, data gaps and reporting responsibilities to address first.
What is included: Check whether tracking, conversion events, attribution and reporting support the priority decisions.
Reconcile key metrics across the agreed platforms, periods and definitions.
Recommend a measurement framework and prioritised handoff plan.
What we need from you: Read access to the agreed analytics, tag-management, advertising and reporting platforms.
Current KPI definitions, tracking plans, dashboards and relevant data dictionaries.
Working sessions with decision owners, marketing or data leads and implementation owners.
Your responsibilities: Name the decision-makers and agree the decisions, periods, platforms and metrics in scope.
Provide read access to the agreed analytics, tag-management, advertising and reporting systems, with current plans and definitions.
Resolve conflicting definitions, assign implementation responsibilities and agree the order of changes.
Decision criteria: Relevance: does each KPI or report support a named decision?
Traceability: can each measure be followed from its source through calculations to the report?
Quality: are critical events and dimensions complete, consistent and reconcilable?
Priority: which gaps pose the greatest decision risk, given their impact and the work needed?
Before you commit further: Proceed when the metric supports a decision and is traceable and reliable enough for that use.
Validate when targeted evidence or reconciliation can resolve an important gap.
Defer when a wider system, control or responsibility decision must come first.
Stop using a metric when its definition, source or quality cannot be defended.
What is not included: New tracking, dashboard builds, data engineering, media-platform remediation and ongoing reporting operations.
Unagreed platforms, historical data reconstruction and causal attribution beyond the available evidence.
Implementation work is separately scoped after the audit.
How this differs: Focuses on whether measurement and reporting can support decisions, rather than assessing all business opportunities.
Unlike the Digital Growth Diagnostic, it starts with the reliability and use of measurement, not customer acquisition or journeys.

What we examine

01Tracking architecture
02Conversion measurement
03KPI definitions
04Attribution
05Data quality
06Reporting and decision workflows

What you receive

01
A measurement assessment with evidence from the agreed systems
02
A tracking and data gap register naming the metric, source, severity, responsible person and recommended action
03
A KPI framework connecting decisions to metric definitions, dimensions, sources and reporting use
04
Attribution recommendations with confidence limits and unresolved dependencies
05
A reporting design showing decision views, where metrics come from and required controls
06
An implementation plan ranked by decision risk, business impact, effort and dependencies

How it works

01
Agree the priority decisions, decision-makers and sources.
02
Trace KPI and conversion definitions from collection to reporting.
03
Reconcile the agreed metrics and record the evidence and its limits.
04
Design the measurement, KPI, attribution and reporting framework.
05
Rank the gaps and hand over responsibilities and next actions.

What happens next

Decide what to do next.

You receive a prioritised handoff for the agreed team members. Implementation, ongoing performance reporting and decision support are scoped separately once the data requirements are accepted.

Tell us about the problem