Review Forecast Risk

Sales Leader, Revenue Operations, Executive and Founder.

• Before you commit a number upward.
• The week before the board meeting.
• Any period where last period's forecast missed by more than ten percent.

• Your commit and best-case lists with amounts and close dates
• One line per deal: why it closes
• Last period's forecast accuracy

Best for one task. Copy it, add your information, and run it in your AI assistant.

You are a skeptical forecast reviewer. Here is my commit list for this period: [paste deals with amount, close date, and why each closes]. Stress test it. For each deal, name what must be true for it to close on time and what evidence is missing. Rank the five deals that decide the number. Then give me the commit, the honest range, and what you would tell the board. Do not smooth it over. If a why-it-closes reason is really a hope, call it a hope.

Best for repeatable work. The file includes the process, required inputs, decision rules, quality checks, and output format.

---
name: review-forecast-risk
description: A deal-by-deal stress test of the commit, with the specific deals that decide whether the number lands.
license: MIT
metadata:
  author: The Revenue AI Report
  version: 1.0.0
  last-reviewed: 2026-09-04
  source: https://www.therevenueaireport.com/skills/review-forecast-risk
---

# Review Forecast Risk

A deal-by-deal stress test of the commit, with the specific deals that decide whether the number lands.

## When to use this skill

- Before you commit a number upward.
- The week before the board meeting.
- Any period where last period's forecast missed by more than ten percent.

## Inputs to collect

- Your commit and best-case lists with amounts and close dates
- One line per deal: why it closes
- Last period's forecast accuracy

## Process

1. List the commit deals with the reason each closes.
2. Run the stress test. Read the evidence-missing column first.
3. Send managers to get the missing evidence on the five deciding deals.
4. Set the commit at what survives the stress test, not what the target wants.
5. Record the call so next period's accuracy is measurable.

## Decision rules

- A deal stays in commit only if the buyer has confirmed the process and date in their words.
- If two of the five deciding deals lack evidence, the range, not the commit, goes to the board.
- Missed two periods running? The process changes before the next commit, not just the deals.

## Output requirements

- Per-deal risk note with missing evidence.
- The five deciding deals ranked.
- Commit, honest range, and the board-ready sentence.

## Quality checks

- Every commit deal has buyer-confirmed process and date.
- The range reflects evidence, not optimism.
- The call is recorded for accuracy tracking.

## Limitations

- It reads the notes you give it. It cannot verify that a champion told the truth.
- Point-in-time. A single slip on one deciding deal invalidates the read.

## Example input

Commit $1.4M across 9 deals. Deal A $300k: champion says paper process started. Deal B $220k: waiting on legal since the 12th. Last period: forecast missed by 14%.

## Example output

Commit holds at $1.1M. Range to the board: $0.9M to $1.3M. Deal A lacks proof that procurement has the paper; get the confirmation email or move it to best case. Deal B is a legal queue risk; ask legal for the position in line, in writing.

## Review checklist

- Is each commit deal buyer-confirmed?
- Did the deciding deals get evidence requests?
- Is the range what you would defend in a board meeting?

## Works with

- Playbook: AI assisted pipeline hygiene checklist (L1) (revops, L1) https://www.therevenueaireport.com/playbooks/revops-pipeline-hygiene-checklist-l1
- Playbook: Make conversation data do work (L3) (sales, L3) https://www.therevenueaireport.com/playbooks/conversation-data-to-work-l3
- Playbook: Frontline manager operating system (L6) (enablement, L6) https://www.therevenueaireport.com/playbooks/enablement-manager-operating-system-l6
- Tool: Aviso (Sales & Revenue Intelligence) https://www.therevenueaireport.com/tools/aviso
- Tool: BoostUp (Sales & Revenue Intelligence) https://www.therevenueaireport.com/tools/boostup
- Tool: InsightSquared (Sales & Revenue Intelligence) https://www.therevenueaireport.com/tools/insightsquared
- Tool: Ebsta (Sales & Revenue Intelligence) https://www.therevenueaireport.com/tools/ebsta
- Tool: Forecastio (Sales & Revenue Intelligence) https://www.therevenueaireport.com/tools/forecastio

## Rules of conduct

- Write for a Director, VP, or operator. Short sentences. Explain uncommon terms.
- Separate facts from assumptions. Never hide uncertainty.
- Do not invent numbers, benchmarks, quotes, or customer names.
- Do not send messages, change CRM records, or publish anything unless the user explicitly asks.
- Flag when a decision needs human review.

## Evidence

This skill is grounded in The Revenue AI Report research:
- https://www.therevenueaireport.com/research/proof-gap
- Related analysis: https://www.therevenueaireport.com/blog/pipeline-truth-test-for-ai




Source and updates: https://www.therevenueaireport.com/skills/review-forecast-risk

1. 1.List the commit deals with the reason each closes.
2. 2.Run the stress test. Read the evidence-missing column first.
3. 3.Send managers to get the missing evidence on the five deciding deals.
4. 4.Set the commit at what survives the stress test, not what the target wants.
5. 5.Record the call so next period's accuracy is measurable.

• A deal stays in commit only if the buyer has confirmed the process and date in their words.
• If two of the five deciding deals lack evidence, the range, not the commit, goes to the board.
• Missed two periods running? The process changes before the next commit, not just the deals.

• Per-deal risk note with missing evidence.
• The five deciding deals ranked.
• Commit, honest range, and the board-ready sentence.

Commit $1.4M across 9 deals. Deal A $300k: champion says paper process started. Deal B $220k: waiting on legal since the 12th. Last period: forecast missed by 14%.

Commit holds at $1.1M. Range to the board: $0.9M to $1.3M. Deal A lacks proof that procurement has the paper; get the confirmation email or move it to best case. Deal B is a legal queue risk; ask legal for the position in line, in writing.

• Is each commit deal buyer-confirmed?
• Did the deciding deals get evidence requests?
• Is the range what you would defend in a board meeting?

What does the Review Forecast Risk skill do?

A deal-by-deal stress test of the commit, with the specific deals that decide whether the number lands.

Who is the Review Forecast Risk skill for?

Sales Leader, Revenue Operations, Executive and Founder. It sits at the intermediate level and takes about 30 minutes.

What do I need before I start?

Collect these first: Your commit and best-case lists with amounts and close dates; One line per deal: why it closes; Last period's forecast accuracy.

What is the difference between the quick prompt and the SKILL.md file?

The quick prompt is for one task. Copy it, add your information, run it. The SKILL.md file is for repeatable work: it carries the process, required inputs, decision rules, quality checks, and output format so an AI assistant runs the same way every time.

What should I check before trusting the output?

Is each commit deal buyer-confirmed? Did the deciding deals get evidence requests? Is the range what you would defend in a board meeting?

Is it free to use?

Yes. Every skill on The Revenue AI Report is free and published under the MIT license. Attribution is welcome, not required.

• It reads the notes you give it. It cannot verify that a champion told the truth.
• Point-in-time. A single slip on one deciding deal invalidates the read.

Run the skill, then roll it out with a playbook. Vendor links are supporting context, not a recommendation.

• Playbook: AI assisted pipeline hygiene checklist (L1) (revops, L1 L1 Starter)
• Playbook: Make conversation data do work (L3) (sales, L3 L3 Integrated)
• Playbook: Frontline manager operating system (L6) (enablement, L6 L6 Rebuilt)
• Tool: Aviso (Sales & Revenue Intelligence)
• Tool: BoostUp (Sales & Revenue Intelligence)
• Tool: InsightSquared (Sales & Revenue Intelligence)
• Tool: Ebsta (Sales & Revenue Intelligence)
• Tool: Forecastio (Sales & Revenue Intelligence)

• Research: proof gap
• Related analysis