Record Completeness
Record completeness measures how many required fields in a profile are populated with usable values.
Allocator relevance: Completeness determines usability—mandate fit and routing fail if key fields (authority, mandate, contacts) are missing.
Expanded Definition
Completeness is best measured against a defined schema of “required” fields, weighted by importance. A record with a name and website is not complete for allocator workflows; decision-maker mapping, mandate signals, ticket size, and verification metadata are often more important. Completeness should also distinguish between “filled” and “verified,” because populated-but-wrong is worse than missing.
Altss-style completeness should be field-weighted: authority and contacts matter more than descriptive text.
How It Works in Practice
Platforms define required fields by entity type, compute completeness scores, and expose filters for users who need only high-completeness targets. Completeness can be tracked over time and improved via enrichment and verification cycles.
Decision Authority and Governance
Governance defines required fields, evidence rules, and how null/unknown values are handled. Without governance, completeness becomes a vanity metric.
Common Misconceptions
- More fields equals better completeness.
- Completeness implies accuracy.
- A single completeness score fits all entity types.
Key Takeaways
- Completeness must be schema-defined and field-weighted.
- Distinguish populated vs verified.
- Completeness is a usability metric, not a truth metric.