Webinar “Building a production area dataset for management and EUDR compliance: A bottom-up approach” organized by the Agri-Forestry Policy Research Network on June 23, 2026, raised a central issue: traceability is not just a technical market requirement, but is becoming a driving force for restructuring the entire management approach of agricultural and forestry product sectors in Vietnam. In this context, the production area database plays a foundational role.
1. Traceability: From Market Requirement to Data System Reform Pressure
According to Mr. To Xuan Phuc – Forest Trends organization, traceability is becoming a mandatory requirement, especially for high-risk commodities and major export markets like the EU. The EUDR regulation requires traceability to each production plot, leading to a demand for accurate spatial and temporal data. In Vietnam, a clear legal framework and regulations such as Decree 37/2026 and related policies, requiring businesses to implement traceability, share data with management agencies, and for the State to build data infrastructure for traceability.
However, reality shows that the current data system does not meet this requirement. As shared at the webinar, data is scattered among businesses, cooperatives, farmers, and management agencies, lacking connectivity and standardization. This situation creates a paradox: “lack of data in a sea of figures,” making full and reliable traceability difficult.
2. The Gap Between “Production Unit Codes” and Substantive Traceability
One of the important topics discussed was the role and limitations of production unit codes (PUC). Currently, PUC is primarily seen as a technical tool for short-term traceability, helping to meet export market requirements. However, according to Dr. Pham Tuan Anh – former Director of the Department of Agriculture and Rural Development of Dak Nong province (formerly), PUC only reflects about 1/3 of the production picture, with most areas not fully monitored. The reality in Dak Nong shows that out of 129 codes issued, only 103 are still active, and about 20% have been revoked or discontinued, reflecting issues with data updating and maintenance.
The gap between “codes issued” and “actual production” indicates that:
- PUC is not sufficient to ensure deep traceability to individual plots
- Data is not regularly updated
- Lack of operational mechanisms to maintain the system
Therefore, traceability cannot solely rely on PUC but requires a complete and “living” cultivation area database system.
3. Production Area Data: The Substantive Foundation of Traceability
Speakers agreed that: Traceability can only operate effectively when based on an accurate, updated, and interconnected cultivation area database. A cultivation area database is understood as a collection of information about:
- Area, yield, output
- Ownership
- Spatial (maps, coordinates) and temporal data
From a management perspective, this data serves to:
- Develop realistic policies
- Identify risk areas
- Monitor compliance in the supply chain
From a business perspective, this is a condition for:
- Implementing traceability according to market requirements
- Transparent supply chains
- Reducing legal and commercial risks
More importantly, Dr. Pham Tuan Anh emphasized: “A production area database is not the destination of traceability, but rather the foundation for shifting from administrative management to data-driven commodity sector governance.”
4. The Bottom-up Approach: A Condition for “Living” Data
A highlight of the webinar was the proposal for a bottom-up approach in building production area data. Accordingly, data can only be sustained when all participating stakeholders benefit:
- Farmers: receive market information, weather warnings, disease alerts
- Businesses: manage raw material areas, transparent supply chains
- State: has a basis for accurate decision-making
This mechanism creates a “symbiotic data ecosystem,” rather than a top-down, imposed system. Experience from Dien Bien and Son La shows that:
- It can be implemented using local internal resources, without requiring excessive external resources
- The role of commune and village levels is crucial in data collection and updating
- Training needs to be organized following the ToT – ToF model, implemented from the provincial to the grassroots level
Mr. Ha Cong Tuan, former Permanent Deputy Minister of the Ministry of Agriculture and Rural Development (now the Ministry of Agriculture and Environment), emphasized that for data to be “living,” it needs to be:
- Digitized and integrated with maps
- Cover 100% of the area
- Regularly updated by the closest level to the people (commune level)
5. Major Challenge: Data Interoperability and Multi-stakeholder Cooperation
A recurring issue discussed was the lack of data sharing among stakeholders, especially between businesses and management agencies. The current situation shows that businesses hold data but do not share it, the state has statistical data but lacks detail, and the data is insufficient for traceability to individual plots. This leads to information overlap, wasted resources, and difficulty in implementing traceability according to EUDR requirements. Therefore, all speakers affirmed the need to promote public-private cooperation in data building and sharing, standardize tools and systems, and ensure strong coordination from the Central Government. In particular, as Mr. Pham Dinh Lai (Sub-Department of Cultivation and Plant Protection of Dien Bien) shared, the production area data challenge “must go hand in hand” among the State – businesses – and the people, and can only succeed when a community is formed to collectively build and operate the data.
6. From Traceability to Commodity Sector Governance
The overarching message of the webinar was: Traceability is not the ultimate goal; instead, it is merely a “gateway” to establish a comprehensive data system, increase transparency in the supply chain and data governance, and gradually transition to data-driven commodity sector governance. When the data is good enough, the system can answer practical management questions such as:
- Where are the compliant supply sources located?
- Which areas need resource prioritization?
- What are the output and harvest times?
This is precisely the shift from passive, report-based management to proactive, real-time data-driven operation.
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