Enter raw material traceability data
Fill the fields below to evaluate lot identification, document alignment, forward linkage, recall readiness, record quality, and retrieval performance.
Example data table
This example shows how a single traceability dataset can be scored for audits, recall simulations, and incoming material control reviews.
| Scenario | Total Lots | Labeled | Docs Matched | Linked | Recall Tested | Missing | Expired Certs | Scan Events | Avg Retrieval | Overall Score | Rating |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Supplier A - Monthly Review | 150 | 144 | 139 | 136 | 125 | 4 | 3 | 560 | 18.00 min | 90.45% | Excellent |
Formula used
1) Identification Coverage
Identification Coverage % = (Labeled Lots ÷ Total Received Lots) × 100
2) Document Match Rate
Document Match % = (Supplier Documents Matched ÷ Total Received Lots) × 100
3) Forward Link Coverage
Forward Link % = (Production Batches Linked ÷ Total Received Lots) × 100
4) Record Accuracy
Record Accuracy % = ((Total Lots - Missing Records - Expired Certificates) ÷ Total Lots) × 100
5) Retrieval Efficiency
Retrieval Efficiency % = min(100, (Target Retrieval Minutes ÷ Average Retrieval Minutes) × 100)
6) Event Density Score
Event Density % = min(100, ((Scan Events ÷ Total Lots) ÷ 4) × 100)
7) Full Chain Traceability
Fully Traceable Lots = min(Labeled, Documents, Linked) - Missing Records - Expired Certificates
Full Chain % = (Fully Traceable Lots ÷ Total Lots) × 100
8) Overall Traceability Score
Overall Score = 15% Identification + 14% Documents + 15% Forward Link + 10% Recall Drill + 12% Record Accuracy + 10% Retrieval + 10% Event Density + 14% Full Chain
The overall score is bounded between 0% and 100%. Higher results mean stronger evidence continuity, better recall response potential, and cleaner supplier trace records.
How to use this calculator
- Enter the total number of raw material lots received in the review period.
- Add how many lots were labeled correctly and matched with supplier documents.
- Enter how many lots were linked to downstream production or storage records.
- Record recall-tested lots, quarantined lots, missing records, and expired certificates.
- Add scan events to reflect checkpoints such as receipt, release, movement, or consumption.
- Enter the average time required to retrieve a lot history and your target time.
- Press Calculate traceability to show the score above the form.
- Use the CSV and PDF buttons to export the results for quality meetings, supplier reviews, or audit preparation.
Frequently asked questions
1) What does this calculator measure?
It measures how well raw material lots can be identified, documented, linked to production, retrieved quickly, and supported during audits or recall exercises.
2) Why is full chain traceability important?
Full chain traceability shows whether a lot can be followed from receipt through documentation and downstream use. It reduces recall uncertainty and improves containment speed.
3) What are scan events in this model?
Scan events are checkpoints recorded through barcode, RFID, or digital logging. More valid checkpoints usually improve evidence continuity and inventory visibility.
4) Why do expired certificates lower the score?
Expired certificates weaken documentary support for quality status, compliance, and acceptance decisions. They create gaps even when the physical lot is present and labeled.
5) Is a higher quarantine count always bad?
Not always. Quarantine may reflect good containment discipline. However, high quarantine counts can still signal instability, supplier variation, or documentation issues needing review.
6) How should I choose the target retrieval time?
Use the time your quality system expects for finding a complete lot history during an audit, deviation review, or mock recall. Shorter targets raise performance expectations.
7) Can this calculator support supplier scorecards?
Yes. You can run the same logic by supplier, site, month, or material family. That makes traceability performance easier to compare and trend over time.
8) What score range is considered strong?
Scores above 75% are generally strong, while scores above 90% are excellent. Lower scores suggest evidence gaps, slow retrieval, or incomplete lot linkage.