Revenue operating model rebuilt for agents (L6)
Process, data model, and roles are redesigned on the assumption that agents perform the routine work. Stages, fields, and approvals are rebuilt around machine readable state rather than around what humans could be bothered to update.
The steps
- 01
Delete fields nobody uses
Tool: Salesforce
Audit field usage and remove anything not populated or not consumed by a report, workflow, or agent. Every dead field degrades both human and agent accuracy. Owner: RevOps lead. DoD: at least a quarter of unused fields removed.
- 02
Make stage exit criteria machine checkable
Tool: Salesforce
Each stage exit is a verifiable condition, for example a named economic buyer contact role exists and a mutual plan document is attached. Opinion based stages cannot be governed by agents. Pitfall: keeping subjective stage definitions and blaming the agent for forecast noise. DoD: every stage has at least one machine checkable exit condition.
- 03
Rebuild roles around exceptions
Tool: Manual
Define who owns exception handling, data stewardship, and agent supervision as real roles with time allocated. These are the jobs the model creates. Owner: RevOps leader. DoD: role descriptions approved with time allocation.
- 04
Contract the data layer
Tool: Snowflake
Publish data contracts for the tables agents read: schema, freshness, ownership, and breakage process. Agents fail silently on stale data far more often than they fail loudly. Owner: data team. DoD: contracts published for the core revenue tables.
Tools in this playbook
- Salesforce
- Manual
- Snowflake
Next playbooks
Unfamiliar terms are defined in the AI and Revenue Dictionary. Related frameworks live in the framework library.