Most reporting problems are plumbing problems. Before anyone can trust a dashboard, the ingestion has to be reliable, the data model has to be agreed, the quality has to be tested on every run, and the lineage has to be traceable. That is the bulk of what this practice does: build the platform, move the data onto it correctly, and put the governance around it that keeps it correct as the business changes. Analytics and reporting sit on top once the foundation actually holds.
The common signature is a warehouse nobody fully trusts and a monthly close that starts with a week of reconciliation.
One practice covering the platform, the pipelines that fill it, and the governance that keeps it honest.
We do not reinvent the delivery method per client. What changes is the content of each phase, and what you sign off before the next one starts.
Data landscape assessment: sources, flows, owners, and the specific reports nobody trusts — with the reasons why, traced to the pipeline that causes them.
Target platform architecture, data model, quality standards, and a governance framework that settles who owns which definition before anything is built.
Pipelines and models built with tests on the data itself, so a breaking upstream change fails loudly rather than quietly producing a wrong number.
Cutover with parallel running against the existing reports until the figures reconcile, then decommission of whatever the new platform replaces.
Ongoing pipeline operations, quality monitoring, and a defined path for changing a definition without breaking every downstream report.
We measure this practice on whether the reports people actually use are trusted enough to decide from, and on how much time your teams stop spending reconciling. Both are visible within a quarter.