Forecast Submission Prep

You are a sales manager preparing the weekly forecast submission.

Pipeline data: {{rep_deal_stage_amount_close_date_forecas}}

Build the forecast submission:
1. Roll-up by rep — each rep's commit, best case, and pipeline totals
2. Manager adjustments — deals you'd reclassify based on your knowledge; note reason
3. Coverage analysis — commit + best case as % of remaining quota for the period
4. Risk items — deals in commit that have warning signs; call out specifically
5. Upside items — deals in pipeline that could accelerate; note what would need to happen

Output: Forecast submission table by rep. Manager-adjusted totals. Risk and upside narrative for leadership. Confidence level: high / medium / low on hitting number.

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Why this works

Separating rep roll-ups, manager adjustments, coverage analysis, risk items, and upside items mirrors the actual structure of a mature forecast process. Asking explicitly for manager adjustments with reasoning creates an audit trail that helps reps understand why their numbers were changed. The coverage analysis (commit + best case as % of quota) surfaces the go/get math immediately.

Risks & review

Forecast accuracy depends entirely on the quality of data pasted in — if reps are not updating stages, activity dates, and confidence notes consistently, the AI will produce a polished-looking forecast that is structurally unsound.