Use case
Use case3 min readBy The Data Workers Team

Yield and scrap data, run by agents

Yield and scrap numbers are computed differently by each plant and reconciled to finance at month end. Here is how Data Workers runs it instead.

Key takeaways

  • •The problem today. Yield and scrap numbers are computed differently by each plant and reconciled to finance at month end.
  • •What changes. Agents govern yield and scrap definitions, tie them to finance and trace losses to process steps.
  • •What stays with your people. Inventory write-offs: they hit the P&L.
  • •The result. Plants compare yield on one definition, tied to finance.

The problem today

Yield and scrap numbers are computed differently by each plant and reconciled to finance at month end.

What changes with Data Workers

Agents govern yield and scrap definitions, tie them to finance and trace losses to process steps.

The workflow: Data Context & Catalog agent (define_business_rule) → Quality Monitoring agent (run_quality_check) → Incident Debugging agent (get_root_cause) → Pipeline Building agent (generate_pipeline).
Fig. 1:The workflow: Data Context & Catalog agent (define_business_rule) → Quality Monitoring agent (run_quality_check) → Incident Debugging agent (get_root_cause) → Pipeline Building agent (generate_pipeline).

The workflow, step by step

  1. 1.The Data Context & Catalog agent calls define_business_rule and governs yield and scrap.
  2. 2.The Quality Monitoring agent calls run_quality_check and ties scrap to finance.
  3. 3.The Incident Debugging agent calls get_root_cause and traces losses to steps.
  4. 4.The Pipeline Building agent calls generate_pipeline and maintains yield models.

The impact metrics we move

  • •Yield report: from about a week to ~1 h
  • •Scrap tie-out: from about 2 weeks to under 1 h
  • •Loss traced: from about 3 days to ~1 h
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

  • •Yield and scrap are governed across plants, so comparisons are fair.
  • •Scrap ties to finance, so month end has no surprises.

Where your people stay in charge

Inventory write-offs always go to a named approver, because they hit the P&L. Everything starts at L1, observing only, and autonomy rises only on evidence.

The pilot

  • •Scope. Yield definition across two plants.
  • •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:
  • •Yield report: from about a week to ~1 h
  • •Scrap tie-out: from about 2 weeks to under 1 h
  • •Loss traced: from about 3 days to ~1 h
  • •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 manufacturing hub · The full team playbook

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