Mid-market teams with revenue between $30M and $500M rarely suffer from a lack of data. They suffer from too many versions of it. Finance reports one revenue figure, sales reports another, and the leadership meeting starts with an argument about whose number is right. Good data governance fixes that by making ownership, access and report quality explicit.
Start with named ownership
Every important dataset needs one accountable owner, usually the head of the function that uses it most. Finance owns the general ledger and budget tables, sales owns pipeline and bookings, and operations owns inventory and throughput data. The owner approves definitions, answers questions about the data and signs off on changes. A shared register listing each dataset, its owner and its refresh schedule is enough to begin.
Write down the metric definitions
Disagreements usually come from definitions, not arithmetic. Does revenue mean invoiced, recognised or collected? Does a customer count include trial accounts? Record each definition in plain language, store it next to the report and change it only through the owner. Teams in SaaS, manufacturing, healthcare, education and financial services benefit from this step because their metrics often carry contractual or regulatory meaning.
Set access rules by role
Not everyone needs every column. Row-level security and workspace permissions in Power BI let regional managers see only their region while leadership sees the full picture. Sensitive fields such as salary, patient identifiers or student records should sit in restricted workspaces with a small, named list of approved viewers. Review that list every quarter and remove people who have changed roles.
Certify the reports people rely on
Report sprawl is a governance problem. When dozens of dashboards claim to show the same thing, nobody trusts any of them. Pick the reports used in board packs, forecasts and customer commitments, then mark them as certified once the owner has checked the data source, the refresh and the logic. Uncertified reports can still exist for exploration, but they carry a visible label so nobody mistakes them for the source of truth.
Handle change requests properly
New data sources, new metrics and new report requests should arrive through one route. A simple request form, a short review by the data owner and a change log that records what was altered and why will prevent the quiet edits that cause numbers to drift. When a definition changes, note the date so that historical comparisons stay honest.
Keep the process light
Governance fails when it becomes paperwork. A short monthly review with the data owners, a clear change log and a visible list of certified reports are usually enough. The goal is fewer surprises in the leadership meeting, not more meetings.
If your team wants help setting this up, GrowthBI provides data strategy and advisory support covering ownership models, metric definitions and certification workflows, alongside data analytics delivery in Power BI.
Engagement details
GrowthBI works with mid-market organisations with $30M to $500M in revenue. Power BI dashboard projects range from $5,000 to $30,000 AUD, and ongoing services start from $2,000/month.
Timeline: 1 to 6 weeks, depending on the data preparation required.
