Data governance
Two people pull a revenue number for the same quarter and get different results. The meeting becomes an argument about whose spreadsheet is right instead of a conversation about what to do. Data governance prevents this — it establishes one definition of revenue, one source of truth, and clear rules about who sees what. It also defines what 'productivity' means, what counts as a 'no-show,' and how missing data gets handled. Without it, every dashboard is a opinion. With it, your team spends meetings making decisions instead of debating numbers.
Go deeper
Your HVAC company's GM in Phoenix says last quarter's revenue was $2.1M. Your CFO says it was $1.8M. They are both right — the GM is counting booked revenue including pending change orders, the CFO is counting collected revenue. Your board meeting just became an argument about spreadsheets instead of a conversation about strategy. This is a governance problem, not a data problem.
The trap most companies fall into is thinking governance means locking things down — more restrictions, more approvals, more bureaucracy. It does not. Governance means clarity. It means writing down that 'revenue' on the ops dashboard means booked revenue and 'revenue' on the finance dashboard means collected revenue — and labeling both. It means deciding that regional managers can see individual technician performance but branch managers cannot see other branches. These are business decisions, not IT decisions, and they take an afternoon to make but save months of confusion.
Questions to ask
- Can you show me the written definition of our top five KPIs — and when was it last updated?
- If a new hire asks 'what does revenue mean here,' where do they find the answer?
- Who has the authority to change a metric definition, and what is the change process?