Runs the forecast twice — once from rep commits, once from deal evidence — and makes the variance the artifact: every gap between what reps say and what signals show gets a written explanation a CRO can interrogate.
The Forecast Reconciliation Agent produces two forecasts, one from rep commits and one from deal evidence, and treats the variance between them as the deliverable: every gap gets a written explanation attached to the number. It is one of fifteen workflows in the Enterprise GTM Agent Stack, an Opsmarshal series on revenue operations.
How the flow runs — live
Both forecasts are preserved. The tension between them is the product.
Forecast calls run on assertion: reps defend numbers, managers apply gut haircuts, and the CRO triangulates vibes. When the quarter misses, nobody can reconstruct which assumption broke.
Two forecasts, one variance report. Each gap names its driver — “3 commit deals show no paper-process evidence” — and snapshots are versioned, so misses become diagnosable: either the model was wrong, or the pipeline was.
| Decision | Choice | Rationale |
|---|---|---|
| Read-mostly by design | The agent never edits rep commits | A system that overwrites rep numbers gets gamed or ignored. Preserving both views keeps the tension visible — and the tension is the product. |
| Explanations over scores | Every variance ships with prose and evidence links | A CRO won't act on “model says 0.62.” A CRO will act on “these 4 commit deals carry zero economic-buyer engagement.” |
Three curated scenarios — one that passes, one that flags for a human, one that the gate blocks. Watch the verdict, the evidence rows, and the audit log.
Governance audit log
Agents don't remove operators — they change what operators watch. Console spec: who owns it, what they check, what pages them, and how they pull the plug.
Leadership treats the signal number as truth; reps stop maintaining CRM because “the model knows.” Mitigation: Both errors are published every quarter. The model earns authority publicly or loses it publicly.
Reps under-commit to beat the model and bank easy wins. Mitigation: Variance is reported in both directions; chronic under-commit patterns surface by rep.
A broken transcript sync silently degrades the signal model for weeks. Mitigation: Input freshness is printed on page one of every report — a forecast with stale inputs says so before it says anything else.
Opsmarshal builds workflows like this one inside client stacks — see revenue operations and GTM stack architecture, or book a call to walk through your own.
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