Data Verification Policy
This policy defines how SICCODE.com verifies industry classifications and business data to support accuracy, neutrality, and repeatability. It complements our verification methodology by specifying source hierarchy, scoring, thresholds, exception handling, and release practices.
This policy does not claim official government authority and does not imply that every record in large datasets is manually reviewed. Instead, it documents governed controls so decisions can be evaluated and defended.
Scope & objectives
- Standards-aligned classification: maintain verified SIC/NAICS assignments aligned with recognized definitions and stable sector boundaries. Benchmark context: Data Accuracy Benchmarks.
- Explainable decisions: store enough evidence and rationale for enterprise documentation, regulated use, and internal QA. Governance context: Data Governance Framework & Stewardship Standards.
- Bias reduction: require independent corroboration for high-impact decisions and apply senior review for exceptions and disputes.
Source hierarchy & scoring
Sources are evaluated by authority, recency, completeness, and consistency. Scoring is used to determine whether evidence meets publication thresholds and whether additional review is required.
| Tier | Typical sources | How it is used |
|---|---|---|
| Primary authoritative | Government datasets, statutory/regulated filings, registrars, regulator data | Preferred for high-stakes decisions; strongest evidence for activity scope and establishment logic |
| Company authoritative | Official websites, annual reports, product/service catalogs, investor materials | Used to confirm offerings and dominant activity; may require corroboration depending on risk level |
| Reputable third-party | Established vendors, industry associations, trade publications with verifiable evidence | Used as corroboration, context, or gap-filling when primary sources are incomplete |
Detailed evidence workflow and validation rules: Data Sources & Verification Process.
Verification thresholds
Publication requirements
- Dual-source rule: publish when evidence is confirmed by two independent sources, or by one primary authoritative source with corroboration appropriate to risk level.
- Primary activity test: assign based on dominant activity (revenue first; otherwise production, employment, hours, or shipments where applicable).
- Scope boundary check: verify included vs excluded activities and avoid “keyword-only” labeling.
Edge cases & documentation
- Confidence notation: ambiguous cases include a concise rationale and evidence summary in lineage notes.
- Alternative codes captured: plausible alternates may be recorded for future review if new evidence appears.
- Escalation triggers: regulated categories, high-visibility records, and conflicts between strong sources route to senior review.
Exception handling & appeals
When evidence is mixed, analysts document hypotheses, alternatives, and the chosen rationale. Appeals or disputes are re-verified by a senior reviewer not involved in the original decision to preserve neutrality and repeatability.
Team and escalation context: About Our Data Team.
Release management
- Scheduled refresh: extended datasets and entities refresh on a defined cycle aligned to governance capacity and evidence availability.
- Standards review: periodic review of hierarchies and crosswalk behavior to preserve comparability over time.
- Change documentation: adds, removals, and reclassifications are tracked with effective dates and governance context to support reproducibility.
Methodology overview: Our Verification Methodology.
Lineage, retention & audit support
- Lineage: records store sources used, review dates, and decision rationale at the level needed for QA and defensibility.
- Retention: lineage artifacts are retained across release cycles to support audits and long-term reproducibility.
- Oversight: reclassifications and drift patterns may be reviewed periodically for consistency and bias mitigation.
Bias mitigation & AI assistance
Automation may flag anomalies and suggest candidates for review, but it does not publish classifications. Human reviewers confirm evidence, document reasoning, and avoid over-reliance on single models, scraped content, or self-reported claims without corroboration.
Compliance & standards alignment
Practices are informed by general principles aligned to quality management and data quality expectations (including ISO-style controls), and are designed to preserve comparability across U.S. economic reporting contexts where SIC/NAICS are used for segmentation, reporting, and longitudinal analysis.
Frequently asked questions
- What qualifies as an authoritative source?
Government datasets, statutory filings, registrar/regulator data, and other primary authoritative records. Company reports and official materials can qualify when corroborated and consistent with stronger sources. - How often are records updated?
Updates follow scheduled refresh cycles plus event-driven review when new evidence appears or when drift is detected. High-impact changes may route to senior review for consistency. - Can a company appeal its classification?
Yes. Organizations can request review and submit supporting evidence. Appeals are re-verified by a senior reviewer not involved in the original decision to preserve impartiality and auditability. - Do you use AI to assign codes?
AI may assist pre-verification (flagging candidates and anomalies). Final published classifications follow governed evidence thresholds and human review where required.
Related resources
Use these pages when you need the underlying methods, governance controls, or benchmarking context.
- Methodology & Data Verification
- Data Sources & Verification Process
- Our Verification Methodology
- Data Accuracy Benchmarks
- Data Governance Framework & Stewardship Standards
- About Our Data Team
If you need the step-by-step workflow, start with the methodology reference. If you need evidence rules and lineage logic, use the sources & verification process page.
Citation & attribution
When referencing this policy in internal documentation, use the citation format below.