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We review the decisions, KPIs, reports, source systems, data quality and management rhythms behind visibility, then define what should be standardised, connected, rebuilt or governed, before any dashboard is built.
Select the symptoms you recognise. Conflicting numbers rarely travel alone.
Select the symptoms you recognise to see where an audit would start.
Data visibility is not dashboard design. It is a system connecting five things: the decisions leadership must make, the definitions behind each number, the data and systems those numbers come from, the people who own them, and the actions that follow. When reports conflict or dashboards go unused, the break is almost always somewhere in that chain, not in the charting layer. This audit reviews the whole system, then defines what should be standardised, connected, rebuilt or governed, in that order of preference.
The recurring decisions leadership must make, who makes them, on what cadence, and what each genuinely needs to know: the anchor every other domain is judged against.
Not every visibility problem needs a build. The audit exists to say which fix each finding actually needs, and in what order.
Some findings need metric clarification and a shared dictionary: agreement, not engineering.
Some need Data Engineering: connected sources, clean lineage and reporting-ready datasets before any dashboard makes sense.
Some trace back to how CRM, ERP or ecommerce systems are configured and used: fixed at the source, not in the report.
Some need review cadence, ownership and action loops repaired: a management process change, not another dashboard.
Where a dashboard genuinely is the answer, the audit hands over requirements grounded in decisions, so what gets built gets used.
A prioritised, costed roadmap you own, build with us or without us.
The sequence is deliberate: decisions first, dashboards last.
We start with the decisions, not the data: which recurring management decisions matter most, who makes them, on what cadence, and what each genuinely needs to know.
We interview the people who produce reporting and the people who consume it. The gap between those two experiences is usually where trust broke.
We review the reports, spreadsheets and dashboards in actual use, then trace them back through CRM, ERP, ecommerce and marketing sources to see where each number is born.
Disputed numbers get tested: we follow a metric from its definition through its lineage to its sources, and document exactly where the versions diverge.
Findings are assembled into the decision map, KPI gap analysis, source map and trust register: one connected picture of why visibility fails where it does.
We define what the reporting system should provide (grounded in decisions, not features), including dashboard requirements and the governance model behind them.
We walk leadership through the findings and the roadmap: what to standardise, connect, rebuild or govern, and in what order.
The audit ends with a prioritised roadmap. Some findings need definitions, some need engineering, some need system changes and some need management process. Select a pathway to see how it connects.
Owns: decisions · KPI definitions · sources & lineage · quality · governance · cadence diagnosis.
The KPI framework and decision layer need senior design.
KPI frameworks and one governed decision layer leadership can trust.
Where the audit finds a definitions and decision-layer problem, this consulting pathway designs the fix.
Payment Processing Cost Reduction. An ecommerce retailer was losing a significant percentage of revenue to payment processing and invoice platform fees. Web Lifter redesigned the entire sales and payment workflow, replacing Stripe and Paycove with a direct Westpac PayWay integration and a custom-built invoicing platform. The new architecture reduced transaction costs, streamlined operations, and delivered immediate profit improvements without requiring any increase in sales volume.
Read the case“We can't recommend Web Lifter highly enough … a digital partner who could understand our operations, connect the dots between marketing and backend systems, and deliver real results.”
No. Dashboards are the last thing the audit looks at. Data visibility is a system connecting decisions, definitions, data, ownership and action, and the audit reviews all of it. Many findings turn out to need metric standardisation, governance or a management-process change rather than new tooling.
Organisations with recurring management decisions and multiple data sources, where reports conflict, KPI definitions are contested and leadership no longer trusts the numbers enough to act on them.
That is the most common situation we see. The audit exists precisely for organisations that have already invested in reporting and still cannot get a trusted view, because the break is usually in definitions, lineage, ownership or cadence, not in the tooling.
No. The audit produces dashboard and reporting requirements grounded in the decisions they must serve, plus the governance model behind them. Implementation (dashboards, pipelines or system changes) is scoped separately, and you are free to build with us or with others.
Not by default. The trust and quality register documents where data quality breaks and why, and the roadmap sequences the fixes, but large-scale cleansing or migration is separate engineering work, scoped once the audit shows exactly what is needed.
No. It is a management diagnostic, not an assurance engagement. If you need formal data assurance or compliance certification, this is not the right service, and we will say so.
A short intake covering the decisions you make, reporting frequency, systems, stakeholders and where trust breaks down; then access to the reports, definitions and source systems in scope, and time with the people who produce and use them. No data uploads and no new accounts.
Then that is what the report says. A recurring finding of this audit is that the data is adequate but the review cadence, ownership or action loop is broken, and recommending a process fix instead of a rebuild is exactly the kind of finding a diagnostic should be free to make.
The trust and quality register documents which metrics in scope are reliable, which carry caveats and which should not support decisions until they are fixed, so leadership knows what the current reporting can and cannot carry while the roadmap is implemented.
The roadmap routes each finding to its fix: metric standardisation and decision-layer design through Data & Decision Making, data foundations through Data Engineering, source-system changes through Software Development, ongoing ownership through Technology Managed Services, and where a governed dashboard platform fits, Kepler.
The flagship audit diagnoses constraints across the whole business system: economics, growth, operations, data and technology. This audit goes deep on one domain: why leadership cannot get a trusted view of performance. If reporting and visibility are clearly the problem, start here; if the constraint could be anywhere, start with the flagship.
Scope depends on how many decisions, source systems and stakeholders are in play. That is confirmed on a short scoping call, along with timing and the access we need. The audit is fixed-scope: the deliverables are defined before it starts.