The Origin:
Every plot documented before the authority asks
From 30 December 2026 the EU Deforestation Regulation applies to large and medium-sized companies, from 30 June 2027 to small ones. The first placer submits the due diligence statement; the buyer still carries the risk that the goods are not marketable. A verification model reviews polygons and risks automatically.
This module is part of a nine-part model calculation on a fictitious mid-sized chocolate manufacturer (€95 million net revenue, 140 items, 4 lines). All euro amounts are derived from the documented assumptions of the sample company. They are not results of real customers and not a performance promise. Which values are achievable on your data is shown only by a pilot.
01 The problem - the statement is there, the check is not
Simplification shifts the burden, it does not remove it
The amended regulation relieves downstream buyers of administrative duties: only the first placer submits the due diligence statement. Commercially the risk stays with the buyer: a marketing ban hits the goods, not the offender. Without knowledge of one's own first placers and without checking their polygons, the buyer buys blind.
The sample company sources cocoa products from 11 first placers. Each delivers plot polygons and a risk assessment. Reviewed manually means: by sample, without repetition, without documentation of thresholds. A verification model turns that into a complete, repeatable review with a prioritised list for the human.
The cut-off date for deforestation remains 31 December 2020; fines whose maximum is at least four percent of EU annual turnover.
02 The model - formal check, then risk per plot on public data
Geometry, area, duplicates, overlaps; then share of pixels with forest loss after the cut-off date, with threshold sensitivity disclosed
The method is documented in two in-house papers: Six Months before the New EUDR Deadline places the amended regulation and names what a mid-sized company must do by the deadline; the paper on the reliability of individual pixels shows why the threshold of the cocoa probability layer must be disclosed. A verification result that does not state its sensitivity to this threshold cannot be judged.
Plots total 1,800, to be reviewed manually 280 Formally faulty 74, overlap 38, risk above threshold 0.5: 168
Public forest-loss layers are regionally aggregated; they do not replace an on-site check of the individual supply polygon. The model says which plots a human must look at, not that the others are harmless. A third postponement of the regulation is not ruled out. The due diligence obligation remains unaffected.
03 Business impact - review effort, not supply risk
The lever: automated review replaces half of the manual check; supply risks are deliberately not quantified
Every assumption comes from the sample company and is stored centrally. With your figures the input changes, not the method.
| Position | Value |
|---|---|
| First placers with due diligence statement | 11 |
| Full-time equivalents manual review × full cost per position | 1,5 × €70,000 |
| Base: Review costs / year | €105,000 |
| Lever: Share replaced by automated review (assumption) | 50 % |
| Result: savings / year | €52,500 |
Staffing assumptions of a sample company. Supply interruption, reputation and insurance conditions are not quantified.
The amount is the smallest of the series, the question the most urgent: by the deadline the list of first placers must exist, and every buyer needs a repeatable check. What a marketing ban for one season would cost is deliberately not calculated by this module - it would be a number without an anchor.
04 Next steps in your factory
From the supplier list to a repeatable check
The list of suppliers submitting the due diligence statement must exist before anything else; it is organisational, not technical work.
The delivered polygons run through the formal check and risk assessment with three thresholds. You see how many plots per threshold are due for review.
Every new due diligence statement produces a prioritised list for quality assurance, with documented thresholds as evidence.