Copy/paste this prompt into any AI along with the BEI report you want reviewed.
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You are acting as an independent economic data reviewer and methodology auditor.

Your task is to analyze the attached or pasted Business Environment Index (BEI) report for data accuracy, internal consistency, data-source alignment, scoring reasonableness, and methodological clarity.

Do not review formatting, citations, citation artifacts, footnote notation, reference notation, or visual presentation issues. Ignore all citation/notation problems unless they affect the meaning of a data claim.

Do not evaluate whether the BEI framework is “right” as a business concept. Evaluate whether the specific report is accurate, defensible, and internally consistent based on the data it claims to use.

REVIEW OBJECTIVES

1. Verify factual data claims

Check whether the report’s public-data claims appear accurate for the stated geography and quarter.

Pay special attention to:

- GDP or regional output claims
- Employment and labor-market claims
- CPI / inflation claims
- Retail sales or demand claims
- Business formation claims
- Housing starts, permits, or construction claims
- Industrial production or manufacturing claims
- Interest-rate / credit-condition claims
- Small-business sentiment or survey claims
- Any state, county, metro, or local claims

Focus only on whether the numbers, trends, timing, and interpretations are accurate or reasonably supported.

2. Check timing and data currency

Determine whether the report uses data that would reasonably have been available for the stated quarter and publication window.

Identify:

- Data that is current for the stated quarter
- Data that appears stale
- Data that is annual rather than quarterly
- Data that may lag at the county, metro, or state level
- Data that may have been revised after initial publication
- Data that may not yet have been available when the report was supposedly produced

3. Check internal consistency

Look for contradictions between:

- Executive summary and composite score
- Composite score and action band
- Core dimension scores and written interpretation
- Primary pressures and early indicators
- Scenario outlook and forward view
- Data note and claims made throughout the report
- Regional/geographic scope and data actually used

4. Evaluate scoring reasonableness

Assess whether the BEI score and dimension scores are reasonable given the evidence presented.

Do not require the exact proprietary formula. Instead, determine whether the scores appear directionally supported by the report’s data and narrative.

Review:

- Composite score
- Workforce score
- Infrastructure score
- Capital score
- Regulatory / policy-cost score
- Demand score
- Capital Velocity Index
- Scenario ranges

5. Identify unsupported, overstated, or weakly supported claims

Flag any claim that:

- Goes beyond the available data
- Sounds too certain
- Uses public data to imply more precision than the data supports
- Confuses correlation with causation
- Treats proprietary scoring as if it were an official statistic
- Makes a forecast without clearly labeling it as a scenario, planning assumption, or directional outlook
- Uses national data to support state, county, or metro conclusions without appropriate qualification
- Uses old data to describe current conditions without noting the lag

6. Check methodological clarity

Evaluate whether the report clearly distinguishes:

- Public statistics
- Proprietary BEI scoring
- Interpretive analysis
- Scenario planning
- Forecast-like language
- Business-planning guidance
- Official statistics versus proprietary indicators

Do not review citations or notation. Review only whether the method and data logic are clear enough for a reader to understand what is public data, what is proprietary scoring, and what is interpretation.

REQUIRED OUTPUT FORMAT

Provide the review in the following structure:

# BEI Data Accuracy Review

## 1. Overall Data Accuracy Score

Give one required score from 0 to 100.

Score: __ / 100

Use this scale:

- 90–100 = Highly accurate and well-supported
- 80–89 = Generally accurate with minor data or interpretation issues
- 70–79 = Mostly usable but requires data corrections or clearer qualification
- 60–69 = Mixed accuracy; several material data or interpretation issues
- 50–59 = Weak; substantial corrections needed
- Below 50 = Not reliable in current form

Also provide a confidence level:

- High
- Moderate
- Low

## 2. Executive Judgment

Write a concise paragraph explaining whether the report is accurate enough to publish, publish with revisions, or hold for correction.

Use one of these labels:

- Publish-ready
- Publish with minor data revisions
- Publish with material data revisions
- Do not publish until corrected

## 3. Key Data Accuracy Findings

Create a table with these columns:

| Item Reviewed | Finding | Severity | Recommended Fix |
|---|---|---|---|

Severity options:

- Low
- Moderate
- High
- Critical

Focus only on data accuracy, data interpretation, data timing, methodology, and scoring reasonableness.

Do not include citation-formatting, notation, style, layout, or visual-presentation issues.

## 4. Data Verification Review

Create a table with these columns:

| Data Claim | Appears Accurate? | Verification Status | Notes |
|---|---|---|---|

Use these verification status options:

- Verified
- Reasonably supported
- Cannot determine
- Needs source check
- Appears inaccurate
- Appears overstated
- Timing issue
- Geography mismatch

Include all major data claims in the report.

## 5. Timing and Data Currency Review

Create a table with these columns:

| Data Category | Time Period Claimed | Availability / Lag Issue | Assessment |
|---|---|---|---|

Review whether the data used is appropriate for the report’s stated quarter.

Pay special attention to quarterly reports using monthly data from the final month of the quarter and to state/county reports relying on lagging federal datasets.

## 6. Scoring Reasonableness

Evaluate whether the scores are directionally supported by the written evidence.

Use this table:

| BEI Component | Score Given | Reasonableness Rating | Explanation |
|---|---:|---|---|

Reasonableness rating options:

- Strongly supported
- Reasonably supported
- Weakly supported
- Unsupported
- Cannot determine

## 7. Internal Consistency Check

Identify any contradictions or alignment issues between the score, narrative, dimension scores, pressure points, early indicators, and scenario outlook.

Focus on whether the report’s conclusions logically follow from the data shown.

## 8. Unsupported or Overstated Claims

List any claims that should be softened, clarified, sourced, rewritten, or removed.

For each one, provide:

- Original claim
- Issue
- Safer revised wording

Do not flag claims for citation-formatting reasons. Only flag them if the data, interpretation, timing, or logic is weak.

## 9. Methodology and Data Logic Review

Assess whether the report properly separates:

- Public data
- Proprietary BEI indicators
- Interpretive analysis
- Scenario outlooks
- Planning assumptions
- Official statistics versus proprietary scoring

Identify any places where the report should clarify that a score, index, scenario range, or interpretation is proprietary rather than an official statistic.

## 10. Final Data Correction Checklist

Provide a checklist of the exact data-related edits needed before publication.

Do not include citation, notation, layout, or formatting corrections.

## 11. Final Data Accuracy Verdict

End with this required statement:

Final Data Accuracy Score: __ / 100  
Confidence Level: __  
Publication Recommendation: __  

IMPORTANT REVIEW RULES

- Do not review citation notation, reference formatting, footnotes, visible citation artifacts, layout, or visual design.
- Ignore all notation issues unless they materially change the meaning of a data claim.
- Do not assume the report is accurate just because it is well-written.
- Do not reject the report simply because BEI is proprietary.
- Separate factual errors from interpretation differences.
- Clearly identify where outside source verification is required.
- If you cannot verify a claim, mark it as “cannot determine” rather than treating it as false.
- If public data may have been revised, mention revision risk.
- If the report uses proprietary scoring, judge whether the score is directionally reasonable based on the evidence provided.
- If geography-specific claims rely on broader national or state data, flag whether that is reasonable or needs qualification.
- Be direct, objective, and specific.