How to Evaluate an Explainable Business Match Score
A buyer guide for reading a score as an explanation of fit rather than a promise or opaque ranking.
Evaluate a business match score by reading its factors, hard failures, confidence and missing information—not the headline number alone. Ask which need and offer were compared, how quantity and units were normalised, which constraints can block the candidate, what evidence is current and which policy version produced the result. Use the score to focus human review, never to guarantee suitability.
The SCORE reading method
Separate signal, constraints, observable evidence, remaining uncertainty and evaluation policy so the number stays traceable.
| Dimension | What to examine | Decision rule |
|---|---|---|
| Signal | Inspect the shared concepts and the exact need-offer relationship. | Reject scores built only on broad category similarity. |
| Constraints | Read every hard failure before considering weighted factors. | A blocker overrides the total. |
| Observable evidence | Check evidence source, verification state and validity period. | Reduce confidence when claims are unsupported or expired. |
| Remaining uncertainty | Identify missing quantity, geography, timing or profile fields. | Turn decision-relevant unknowns into focused questions. |
Example: 78 points with one hard failure
A candidate scores well on product, quantity and timing but lacks evidence for a mandatory certification.
The correct outcome is blocked, not high confidence. The score explains attractive fit; the hard failure explains why the candidate cannot progress.
Illustrative scenario, not a customer claim or guaranteed outcome.Questions to ask about FoundBefore scores
FoundBefore records factor explanations, confidence, hard failures and the scoring-policy version for deterministic industrial-resource candidates.
The score is an evaluation aid. Participants decide whether to clarify, reject or proceed to a consent-gated introduction.
Limits and responsibilities
- Weights reflect policy choices, not universal truth.
- Missing data can make precise numbers misleading.
- A score cannot assess every legal or commercial risk.
FoundBefore does not guarantee a match, buyer, supplier, partnership or completed deal. Identity disclosure requires mutual consent, and the controlled pilot does not replace procurement, contracting or human review.
Trust the explanation only when the factors, blockers, evidence and policy version are visible and reviewable.