Traceability Systems

“Traceability is a question. A traceability system is the machinery that can answer it reliably. ”

Traceability describes the ability to follow movement. A traceability system is the infrastructure that makes that ability repeatable. It includes people, identifiers, data capture, business rules, chain-of-custody logic, technology, controls, governance and procedures for the moments when the expected record does not exist.

ISO 22005:2007 sets out principles and basic requirements for the design and implementation of traceability systems in feed and food chains. It begins with objectives. A system designed for product recall may need different speed, precision and data from one designed to assess deforestation risk, preserve identity or support consumer claims.

More data do not automatically make the system better; fitness for purpose does. Every system needs stable identities. Farms, plots, producers, lots, facilities, organisations and transactions must be distinguishable.

If the same farmer receives three identifiers from three projects, records can duplicate production and risk. If one identifier is shared across a cooperative, individual-level claims cannot be supported. Identity resolution is therefore assurance infrastructure, not an IT housekeeping task. Events connect those identities. A product is harvested, aggregated, transformed, split, stored, transported, sold or exported.

GS1's EPCIS standard provides a common language for sharing visibility event data: what was involved, when it occurred, where it occurred and why it occurred in the business process. The model is useful because traceability depends on relationships over time, not a single origin field. Master data provide context.

A farm polygon, certification status, licence, product code or supplier relationship may change less frequently than transactions but remains essential to interpretation. Versioning matters. If a plot boundary is edited after a deforestation check, the system should preserve what boundary was used for the original decision. Chain-of-custody rules determine how attributes survive physical operations.

Identity preserved, segregation, mass balance and book-and-claim systems require different records and permit different claims. A platform cannot resolve a conceptual mismatch between the physical model and public language. The rule must be defined before the database is built. Exceptions reveal the real system.

Bags are re-labelled, phones fail, deliveries arrive without documents, names are spelled differently and lots are mixed unexpectedly.

A traceability design that works only when every actor follows the ideal process will produce gaps or fabricated compliance. Exception handling should define who can correct records, what evidence is required and how changes remain visible. Data quality and incentives are inseparable. Suppliers may be asked to enter detailed information without payment, connectivity or benefit.

Staff may face targets that reward complete records rather than accurate ones. Duplicate or invented data can make coverage look impressive. Controls should test plausibility and provide value to those who generate the data. Security and privacy also matter. Farm coordinates and household details can create risk if shared broadly. Access should follow role and purpose.

Traceability does not require every participant to see every field, and transparency does not justify exposing personal data.

Most importantly, a traceability system can accurately trace a product associated with harmful practice. It provides visibility, not judgement. Due diligence, monitoring and verification use the system to assess what happened at origin and through the chain. A platform that confuses traceability coverage with sustainability performance will turn infrastructure into an unsupported claim.

The discipline is to design backwards from the decision. What question must the system answer, to what precision, within what time and with what confidence? Then define identities, events, custody, evidence, exceptions and governance sufficient for that purpose.

Practical application

Define objectives, users, required precision, chain-of-custody model and claim boundaries. Establish unique identifiers and data standards for actors, locations, products, lots and events. Maintain version history and change control for master data. Test exception scenarios before deployment. Monitor duplication, impossible quantities, missing links and late entries.

Align access with purpose, protect personal data and measure whether the system supports actual decisions rather than only coverage statistics.

Why it matters

Traceability systems connect physical supply chains to evidence. They support recall, due diligence, chain-of-custody control, risk assessment and substantiation. Weak identity and event data can create false confidence at scale.

Common misconception

A traceability system is often treated as a software platform or a map of origins. Technology is only one component. Reliable traceability depends on governed processes, identifiers, custody rules, evidence, exception handling and incentives across organisations.

Connections

Traceability defines the capability; Traceability Systems provide the operating infrastructure. Interoperability allows records to move across organisations. Data Governance assigns authority, while Data Quality determines whether the reconstructed chain is fit for the decision.

A question worth asking

When the physical flow departs from the ideal process, can your system preserve an honest chain of evidence - or does it reward someone for making the record look complete?

Selected references

ISO 22005:2007. Traceability in the Feed and Food Chain - General Principles and Basic Requirements for System Design and Implementation. Codex Alimentarius Commission. 2006. Principles for Traceability/Product Tracing as a Tool within a Food Inspection and Certification System. GS1. 2022. EPCIS and Core Business Vocabulary 2. 0. Golan, E. et al. 2004. Traceability in the U. S.

Food Supply: Economic Theory and Industry Studies. United States Department of Agriculture. ISO 22095:2020. Chain of Custody - General Terminology and Models.