EUDR Un-Redacted – A Detailed and Unredacted view of the EU Deforestation Regulations impact on operators and the supply chain: by Inovasi Digital


EUDR Un-Redacted – A Detailed and Unredacted view of the EU Deforestation Regulations impact on operators and the supply chain: by Inovasi Digital

The EU Deforestation Regulation (EUDR) has been a prominent issue facing many operators across several key commodities who seek to trade them into and out of the European Union (EU). Palm oil is one such commodity, and the EUDR aims to stop deforestation-related commodities from entering supply chains linked to operators in the EU.

What are the basic requirements and demands of the EUDR?

To establish importers of the key commodities requirements, Article-3 of the EUDR gives the essence of that law. In its most basic form, the EUDR demands that imports into (and exports from) into the European Union:

  1. Are deforestation-free;
  2. Can demonstrating legal compliance to national laws; and,
  3. Are able to provide a Due Diligence Statement with geolocations and risk mitigation.

Based on these basic requirements the main challenges facing operators are broad. They can be organized into 5 major categories or requirement / compliance streams.

  1. Mapping supplier information that is pertinent to the EUDR is critical. According to the EUDR, this must include the geolocation of each individual supplier, expressed as a polygon. In palm oil, certification schemes provide some data but much information is kept within national land registrations that are not always accessible.
  2. Forest maps, boundaries, definitions, and risk assessments must be clarified as “deforestation free”. Without a universally adopted map, there will be challenges from conflicting definitions of forest, base-maps and boundaries.
  3. Legal compliance to national laws includes a broad range of legislative and regulatory requirements. There may be overlapping laws, interpretations and outdated legality statuses of suppliers.
  4. The conduct of a risk assessment, especially for moderate to high-risk supply-chains demands operators to provide key information into the specific risks including deforestation and legality risks. Access to reliable data to support risk assessment and mitigation work will be a significant challenge for operators.
  5. The EUDR requires operators to have a risk mitigation approach for suppliers at-risk of breaching the regulations. It requires operators to address risks in their supply chain through having policies, procedures and action plans. Shared risk mitigation becomes necessary or a common approach to pool smaller resources. Smallholders are a significant at-risk group linked to deforestation and illegality.


What are the Processes, Methodologies and Approaches to meet EUDR requirements?

To meet these demands, Inovasi Digital analyzed the regulations in detail and consulted with various bodies and stakeholders to gain a clear picture. The approaches required to meet the challenges include:

  1. Utilizing mill supply-base information, including Traceability to Plantation (TTP) datasets through an integrated traceability system, like Inovasi Agriplot to identify gaps.
  2. Establish deforestation and forest boundary data through incorporating human expertise and on-the-ground knowledge– going beyond satellite imagery to field verification, as well as consulting key stakeholders.
  3. Cross-referencing national land maps and other official sources to align them as well as field boundary delineation.
  4. Risk assessments are relevant jurisdictions to verify risks across various parameters and criteria, including deforestation, legality, social issues, traceability and supply chain complexity.
  5. Risk mitigation includes filling traceability gaps, risk mitigation policies and procedures; and smallholders related activities.

What are the critical baseline categories to meet EUDR needs?

Inovasi Digital has analysed the legislative requirements of the EUDR and organized the demands of the legislation into 3 major data baseline categories.

  1. Supply-base and traceability baselines.
    This includes key types of data in 2 major categories: Supplier information, trade and production data, and, Geolocation data. Supplier information relevant to EUDR requirements are not centralized and access can be restricted, including official data or supplier and operator traceability information. Geolocation data challenges include inconsistent or incomplete land plot data as well as restrictions due to privacy or legal reasons.
  2. Forest-related baselines.
    Forest data baselines cover forest definitions and distortion or ambiguity without a universally referenced forest base map. Different definitions create different baseline maps and interpretations of forest data. Existing global maps are not authoritative or dependable, meaning more verification requirements for forest conditions.

  3. Legal-compliance related baselines.
    Legal compliance baselines include broad sub-categories of data to complete legality verification of suppliers. This can include compliance to laws, regulatory requirements, permits, taxation and other legal instruments, while the source of information is also diverse and dispersed.

What are the information categories and baseline datasets in Inovasi Agriplot’s inventory and Agriplot’s readiness to support EUDR Compliance for partners?

Inovasi Agriplot is built from the experience and knowledge of Earthqualizer Foundation’s leadership in the field of geospatial monitoring for deforestation policy compliance – supporting the most important operators in the palm oil sector implement, monitor and accurately detect deforestation in the supply chain for over a decade.

Inovasi Agriplot is not established on just satellite imagery and datasets of non-spatial information inventories. It incorporates on-the-ground knowledge through our extensive field staff and continued updating of the databases. The way Inovasi Agriplot truly delivers for partners facing EUDR is our accurate, verified and critical disclosure of operators’ key supply-chain situation, its risk profile, and partnering to identify risk mitigation solutions.

Inovasi Agriplot draws upon detailed and specific verifiable information across various sources, and in-house data-sets including spatial data, legal documentation, trade data and field verified information. This provides Inovasi Agriplot with an existing database of verified and reliable information covering over 28 million Ha, over 8,000 facilities, over 2,300 mills in 35 countries and 10,000 + FFB dealers. Our TTP data covers over 1,700 mills.

Forest and deforestation information is a core expertise of Inovasi Digital, respected and acknowledged through the stable of partners EQ and ID advises on deforestation monitoring. EQ is the leader in deforestation monitoring. Inovasi Agriplot will deploy various databases:

  • EQ’s inhouse high-resolution forest cover base-map
  • EQ’s bi-weekly deforestation monitoring database, since 2016
  • Field verifications information
  • Stakeholder advise 
  • Credible NGO/community grievances

This extensive experience allows Inovasi Digital to provide unsurpassed accurate forest and deforestation alerts or risk profiling. Our system is backed by the following database coverage:

  • Forest cover (including peat forest) area inside oil palm licensed area: 2,3 million ha 
  • Historical deforestation cases from 31 Dec 2020: 214 cases (50K+ha) in 8 countries

An equally comprehensive and in-depth coverage of legal issues has been assembled through past deforestation monitoring work, demonstrating an appreciation of the legal component in effective deforestation monitoring. The scope of legality datasets includes:

  • Alignment of National Land Registration (e.g., ATR-BPN, Jupem, e-lasis) with Planted Area Patterns
  • National Land Use Plans and Allocations (e.g., KLKH, Jupem)
  • Registration of Indigenous Peoples’ (IP) Land
  • Official Court Records
  • Credible NGO and Media Reports
  • Certification Schemes assessment disclosure information
  • Company Disclosures through stock market, voluntary or public access modes

This extensive, detailed and referenced information provides a legality database for Inovasi Digital that already encompasses the following datasets:

Supplier legal plot boundary

  • Corporate:  396,059 plot
  • Outgrower:  6,689 plot
  • Scheme smallholder:  941 plot
  • Independent Smallholder:  2,604,313 plot
  • Social grievance cases from 2020: 698 cases (26 countries)

In addition, with many of the EUDR commodities being supplied by smallholders and informal chains-of-custody or opaque status of production, Inovasi Digital’s partners will benefit from the database, and extensive understanding of the socio-legal context smallholders operate to profile the risk associated with smallholders. Inovasi Agriplot will allow for greater risk assessment and mitigation measures because of the datasets on the following:

  • Administrative boundary up to village levels
  • Corporate profiles information: Notarial act, company disclosures, 

Inovasi Agriplot provides industry leading datasets and clarity on smallholders’ status with experience in interpreting the existing legal status of smallholders for appraising their risk profile.

  • Adminitrative boundary up to village levels
  • Corporate profiles information:  1,386 group company, 


Inovasi Agriplot’s Mill Assessment and Risk Approach.

Inovasi Agriplot categorizes mills and supply-chains according to their risk-probability segments. To meet EUDR Due Diligence Statement and risk assessment needs, the system will categorize the supply-base and mill that is supplying the EU according to 4 distinct risk profiled segments.


Figure 1: Inovasi Agriplot process flowchart


Based on the availability and reliability of TTP information from a participating mill, the TTP data is either processed through a risk layer assessment and compliance attribution test, or, where the availability of TTP data is low or unavailable, a precautionary approach is applied – using a conservative estimate of 50km radius from the mill to the potential supply-base and processing these potential suppliers against the risk layer assessment and compliance attribution test.

After the assessment and test, the mill will be assigned to one of the 4 risk-profile types as shown in the flowchart. Mills identified without non-compliance are ready to provide data for Due Diligence Statements (DDS). However, where risks are identified further risk assessments are needed to verify the exact risk types and profiles of suppliers for further action. The risk status is further refined using a linkage within supply-base or association criteria into risk sub-categories of; mills to links with non-compliance within 50km radius; mills linked to 3rd party suppliers with non-compliance; and, mills linked to managed plantations with non-compliance. Each sub-category will suggest the potential mitigation approaches to address the identified or potential risks.

In addition to understanding the types of risks – deforestation, legality or other risks – attention will be needed to address the situation of smallholders in the supply-chain, as they are present in all the commodities affected by the EUDR. Additionally, they are often associated with deforestation, illegality and other potential EUDR non-compliance.

Moving forward with an accurate, verifiable and dependable system – Inovasi Agriplot 

Through the Inovasi Agriplot approach, the risks and requirements of the EUDR have been revealed so operators can make informed decisions on the best approaches to comply with the EUDR. The Inovasi Agriplot approach, system and experience shows a deep appreciation of the challenge, built upon the expertise and knowledge as the leader in deforestation monitoring and spatial analysis in Southeast Asia. Positioned with a unique combination of spatial data, big-data processing, and on-the-ground knowledge, Inovasi Agriplot is the most accurate platform for tackling any operator’s EUDR needs, from understanding their supply-base to completing DDS requirements to risk assessments and effective mitigation approaches.

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