A footprint is only as good as the data under it
Most food carbon numbers are industry averages wearing a decimal point. We build product footprints from the primary data your own chain already produces, and show exactly how much of each figure is measured rather than assumed.
Reporting season starts from zero, every year
Scope 3 is where nearly all food-sector emissions sit, and it depends entirely on other people's data. So it gets estimated — and an estimate cannot be reduced, only restated.
How it usually goes
- Spend-based factors applied to purchasing data, because that is what is available
- A consultant rebuilds the model each cycle, and leaves with the working file
- Real improvements at a supplier are invisible, because the average did not move
- An assurance provider asks where a number came from, and the trail runs cold
With Carbon Insights
- Primary supplier data where it exists, secondary factors only where it does not — and labelled
- The model lives in your system and carries forward between cycles
- A supplier who genuinely improves shows up in your number, which is the whole point
- Every figure walks back to the record and the party it came from
Primary-data share, stated openly
The most useful thing a footprint carries is an honest account of its own uncertainty. A figure that is 64 % primary data and says so beats a more precise-looking number with no provenance at all.
We track primary-data share per stage and per supplier, so "where would better data change our answer" has a ranked list behind it. That list is also your collection roadmap.
| Stage | kg CO₂e | Primary | Basis |
|---|---|---|---|
| Cultivation | 0.186 | 82% | Grower inputs |
| CA storage | 0.104 | 100% | Metered energy |
| Packing | 0.058 | 71% | Site data |
| Transport | 0.047 | 38% | Part modelled |
| Distribution | 0.025 | 0% | Secondary factor |
| Total | 0.420 | 64% |
Carbon data as a by-product of operational data
Carbon data is usually a by-product of data somebody already collects for an operational reason. A controlled-atmosphere store meters its electricity because energy is a cost — and that same reading is the cleanest input for the storage stage of a footprint.
The same applies to transport legs recorded for cold chain monitoring, yields recorded for quality and inputs recorded for compliance. A well-founded footprint costs far less once the evidence is already flowing for its own sake.
- Product carbon footprints per SKU, per batch and per customer
- Scope 3 category 1 built up from actual purchased volumes, not spend proxies
- Allocation between co-products and grades stated explicitly rather than buried
- Exports shaped for CSRD, VSME and the customer questionnaires you actually receive
| Supplier | kg CO₂e/kg | Primary | Trend |
|---|---|---|---|
| Zuidhoeve | 0.420 | 64% | −8 % y/y |
| Noorderveld | 0.511 | 58% | +3 % y/y |
| Picardie Coop | 0.388 | 41% | First year |
| Category average | 0.560 | — | Secondary |
From supplier inputs to a defensible figure
Collect at source
Growers and sites report the inputs they actually know — fuel, fertiliser, electricity, refrigerant, yield — in the same portal they use for compliance.
Calculate transparently
Recognised factor sets with the version and source recorded against each figure, so a recalculation later can be explained rather than merely noticed.
Grade your own data
Primary share tracked per stage and supplier, with the gaps ranked by how much they could move the answer.
Survive assurance
Every figure links to the record behind it and the party that submitted it, which is the question an assurance provider will actually ask.
Report once, answer many
One dataset feeding statutory reporting, customer questionnaires and your own sourcing decisions, instead of three incompatible exercises.
What it changes
Reporting stops being a project
The model persists between cycles, so each year is an update rather than a rebuild with a new consultant.
Reductions become visible
Primary data means a supplier's genuine improvement reaches your number — which is the only thing that makes engagement worth anybody's time.
Answers that hold up
When an assurance provider or a large customer asks where a figure came from, the trail is there and it is short.
Start with last year's footprint
We will show you how much of it was actually measured, and which three data gaps would change the answer most if you closed them.