Use case
Use case3 min readBy The Data Workers Team

Sales forecasting data, run by agents

The forecast is rebuilt in spreadsheets before every call, and surprises happen in the meeting. Here is how Data Workers runs it instead.

Key takeaways

  • •The problem today. The forecast is rebuilt in spreadsheets before every call, and surprises happen in the meeting.
  • •What changes. Agents verify forecast inputs every morning, reconcile bookings to finance and hold changes for the RevOps lead.
  • •What stays with your people. Forecast and bookings models: they drive pay and plans.
  • •The result. The forecast is verified before the call.

The problem today

The forecast is rebuilt in spreadsheets before every call, and surprises happen in the meeting.

What changes with Data Workers

Agents verify forecast inputs every morning, reconcile bookings to finance and hold changes for the RevOps lead.

The workflow: Quality Monitoring agent (run_quality_check) → Schema Evolution agent (detect_schema_change) → Pipeline Building agent (generate_pipeline) → Autonomous Data-Conductor (request_governance_review).
Fig. 1:The workflow: Quality Monitoring agent (run_quality_check) → Schema Evolution agent (detect_schema_change) → Pipeline Building agent (generate_pipeline) → Autonomous Data-Conductor (request_governance_review).

The workflow, step by step

  1. 1.The Quality Monitoring agent calls run_quality_check and ties bookings to finance.
  2. 2.The Schema Evolution agent calls detect_schema_change and maps stage changes.
  3. 3.The Pipeline Building agent calls generate_pipeline and updates the forecast model.
  4. 4.The Autonomous Data-Conductor calls request_governance_review and holds changes for RevOps.

The impact metrics we move

  • •Forecast verified: from about 8 hours to 8-15 min
  • •Bookings tie-out: from about 2 days to 8-15 min
  • •Stage change absorbed: from about 2 days to 15-30 min
Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.
Fig. 2:Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.

What goes on autopilot

  • •Forecast inputs verify every morning, so no surprises in the call.
  • •Bookings tie to finance, so one number for the board.

Where your people stay in charge

Forecast and bookings models always go to a named approver, because they drive pay and plans. Everything starts at L1, observing only, and autonomy rises only on evidence.

The pilot

  • •Scope. Morning forecast verification.
  • •First week. Agents run at L1, observing only, and show the fixes they would have made, with receipts.
  • •By week two. The routine work above runs on its own; anything sensitive stays with a named approver.
  • •At day 30. We review the impact metrics against your baseline:
  • •Forecast verified: from about 8 hours to 8-15 min
  • •Bookings tie-out: from about 2 days to 8-15 min
  • •Stage change absorbed: from about 2 days to 15-30 min
  • •Cost. Start with a pilot ($7,500 one-time, credited in full against the first year). Scale is from $1,000 a month and Enterprise from $3,000 a month, billed annually, with unlimited seats, no usage meter and no markup on model spend. See pricing.

Related: The sales and revenue page · The full team playbook

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