Data Governance

Data Governance is the set of policies, standards, and processes that define how revenue data is collected, stored, maintained, and used across the organization. It ensures that the data powering decisions, reports, and automations is accurate, consistent, and trustworthy.

Why Data Governance Matters

Every RevOps function depends on data quality. Forecasting requires accurate pipeline data. Lead scoring requires clean contact records. Attribution requires consistent campaign tracking. Territory design requires reliable account data. When data governance is weak, every downstream process suffers.

Core Components

• Data standards: Naming conventions, required fields, picklist values, and formatting rules that ensure consistency across the CRM and MAP
• Data ownership: Clear accountability for who maintains which data sets and who approves changes to schemas and taxonomies
• Data quality monitoring: Automated checks for duplicates, missing fields, stale records, and formatting violations
• Access controls: Role-based permissions that determine who can view, edit, and delete data
• Retention and archival policies: Rules for how long data is kept and when it is archived or deleted

Common Problems Without Governance

• Duplicate accounts and contacts that fragment reporting and confuse routing
• Inconsistent stage definitions that make pipeline reporting unreliable
• Free-text fields where picklists should exist, making segmentation impossible
• Stale data that inflates pipeline and distorts forecasts

RevOps Application

RevOps is the natural owner of data governance because it sits at the intersection of all revenue systems. RevOps defines the rules, implements the tooling, and runs the audits that keep data clean. This is unglamorous work, but it is the foundation that every other RevOps capability depends on.