Scope 3 reporting is where most mid-market CSRD projects stall. The requirement is real — ESRS E1-6 mandates disclosure of all material Scope 3 categories — but the data needed to fulfill it is scattered across procurement platforms, travel booking tools, expense systems, and supplier invoices that were never assembled for environmental reporting purposes. The finance team uses the ERP. The sustainability manager uses a spreadsheet. The compliance officer is somewhere in between, trying to figure out what "material" actually means in practice.
This guide is written for the compliance officer who has been handed a list of fifteen GHG Protocol categories and told to produce a Scope 3 inventory for an ESRS E1 disclosure. It covers what CSRD actually mandates, where the data already exists in your systems, where the real gaps are, and how to sequence the work without building a six-month project plan.
What ESRS E1 actually mandates for Scope 3
ESRS E1-6 (paragraph 44) requires disclosure of gross Scope 3 GHG emissions disaggregated by significant GHG Protocol categories. The word "significant" is doing considerable work here — it is not defined as a fixed tonnage threshold but is instead determined by your company-specific double-materiality assessment. This is both the flexibility that makes CSRD proportionate and the source of most compliance team confusion.
For manufacturing and industrial mid-market companies, EFRAG's sector-specific guidance consistently points to Category 1 (purchased goods and services) as the dominant material category — upstream embedded emissions in procured raw materials, components, and services typically represent 60-80% of total value chain emissions for manufacturers. Categories 6 (business travel) and 11 (use of sold products) are frequently material. Category 4 (upstream transportation and distribution) is material for distribution-heavy business models.
Categories that often are not material for a 400-800 person industrial company: Category 10 (processing of sold products), Category 14 (franchises), and Category 15 (investments). You do not need to report these — but you do need to document why they are not material, with reference to your double-materiality assessment outcome.
One practical point worth stating plainly: ESRS E1 does not require you to report all fifteen categories in your first disclosure year. What it requires is a Scope 3 inventory covering material categories and a methodology appendix that explains what was included, what was excluded, and why. A first-year disclosure with well-documented scope and methodology is more defensible to an assurance provider than an undocumented inventory claiming to cover everything.
What your ERP already knows about Scope 3
Category 1 (purchased goods and services) is the most emission-intensive Scope 3 category for most manufacturers and the one your ERP contains the most data about. Your accounts payable module holds a complete record of every supplier payment: vendor identity, NACE or commodity classification, spend amount, and cost center. This is the raw material for a spend-based Category 1 calculation.
The spend-based method multiplies supplier spend (in € or local currency) by an emission intensity factor per procurement category. Intensity factors by NACE sector or spend category are published by EXIOBASE (a global environmentally extended input-output database) and the UK government's environmentally extended input-output model. These factor sets are ESRS-acceptable for companies that do not yet have primary supplier-provided emission data.
Consider a plausible mid-market scenario: a 550-person precision components manufacturer in southern Germany with €80M in annual procurement spend across 340 active suppliers. Their SAP S/4HANA instance contains 11 years of AP data. Running a spend-based Category 1 calculation against that data — applying EXIOBASE 3.8 factors at the NACE 2-digit classification level — takes a matter of hours in an automated system. The result is a Category 1 estimate covering approximately 85% of procurement spend, with the remaining 15% in low-spend or uncategorized vendors flagged for manual review. That is a credible first-year disclosure baseline.
For Category 6 (business travel), SAP Concur and equivalent expense systems record trip type (flight, rail, hotel, car rental), destination, and reimbursement amount. Distance-based emission factors from the BEIS/DEFRA methodology or GHG Protocol-endorsed sources are applied per passenger-kilometer for air travel, and spend-based factors for rail and accommodation. The data quality here is typically high — expense systems are accurate financial records. The main gap is completeness: personal card spending that never hits the expense system requires a coverage estimate.
Where the real data gaps are
Being precise about what is not in your ERP is as important as knowing what is. The following categories typically require data sources outside financial systems:
Category 7 — Employee commuting. Commuting emissions require either a workforce commuting survey (annual, per-site) or a proxy calculation from payroll-derived home location data. Neither is in the ERP. For a company with 500 employees across three sites, a one-time commuting survey requiring 15 minutes per employee is a half-day project — but it needs to happen before the first reporting year closes.
Category 4 — Upstream transportation and distribution. Freight emissions require shipment-level data: weight, distance, and transport mode. This lives in logistics management systems (TMS), 3PL carrier data feeds, or customs/shipping documents. ERP purchase orders contain supplier location and order quantity but rarely contain freight-mode data.
Category 11 — Use of sold products. If you manufacture products that consume energy or fuel during operation — pumps, compressors, HVAC equipment, vehicles — the emission intensity during use requires engineering input: energy consumption per product unit per operating hour, multiplied by expected lifetime hours. This data lives in product engineering documentation, not the ERP. It is the most technically demanding category and is frequently documented as a data gap in first-year disclosures.
Supplier-specific emission factors. Moving from spend-based to activity-based Category 1 calculation requires primary data from your Tier 1 suppliers — their own Scope 1 and Scope 2 emissions attributed to goods supplied to you. This supplier engagement program takes multiple reporting cycles to build. It is not a year-one requirement, but your gap analysis should document the roadmap toward primary data collection.
The methodology documentation CSRD expects
ESRS E1-6 (paragraph 51) requires disclosure of the methodologies, significant assumptions, and data sources used for each Scope 3 category reported. This methodology appendix is not a formality — it is the document your assurance provider will work through line by line. Getting it right matters more than the precision of the tonnage figures.
For each significant category included in your inventory, the methodology appendix should document:
- Data source: Which system, which module, which data extract — e.g., "SAP S/4HANA FI-AP module, vendor invoices, FY2024 full-year extract"
- Calculation method: Spend-based, activity-based, or supplier-specific — with the rationale for which method was used given available data quality
- Emission factor source and version: e.g., "EXIOBASE 3.8 NACE sector intensity factors (kg CO2e per €1,000 spend), accessed May 2025" — the version pin is essential for year-on-year comparability
- Coverage and boundary: What percentage of spend or activity was covered; which vendors or categories were excluded and why; which sites or subsidiaries were included in the boundary
- Data quality rating: ESRS references a qualitative data quality hierarchy — primary data, secondary data from industry averages, and estimated data. Documenting where each category falls supports assurance review
This level of documentation sounds onerous, but it maps directly to what an ERP-sourced automated calculation naturally produces. Every calculation based on a GL transaction has a source document reference. Every emission factor application has a version-pinned factor identifier. An automated pipeline generates this provenance trail by construction. A spreadsheet-based process requires someone to manually maintain it — and frequently does not.
The sequencing that actually works for mid-market teams
Given the resource reality of a compliance team that is also handling other regulatory obligations, the following sequencing avoids the failure mode of trying to do everything in year one:
- Confirm material categories through your double-materiality assessment. This is the gating step — do not start data collection before you know which categories are in scope. The assessment takes 4-8 weeks with a facilitator and should output a signed-off materiality matrix.
- Build the Category 1 spend-based baseline from ERP AP data. This is the highest-impact, most automatable step. Connect your ERP, run the NACE-based spend classification, generate the first estimate. Flag the coverage gaps (uncategorized vendors, intercompany transactions to exclude) for manual review.
- Run Category 6 from your expense system. Connect Concur or equivalent. Apply BEIS distance-based factors for flights. This category is well-defined, well-factored, and produces high-confidence output with minimal manual effort.
- Run Category 2 (capital goods) from your fixed asset register if CapEx is material. This is a standard ERP module — fixed asset register by asset class, spend-based or depreciation-adjusted.
- Document data gaps for Categories 4, 7, and 11 with a structured gap statement: what data would be needed, how you plan to collect it, and by which reporting year you intend to include it. This converts a gap into a disclosure commitment, which is acceptable under ESRS.
We are not suggesting that this sequencing is the only valid approach. For companies with particularly material Category 11 exposure — manufacturers of energy-intensive equipment sold to heavy industry, for example — front-loading the engineering data collection may be warranted. The point is that the sequencing should follow materiality, not category number order.
A note on assurance expectations in year one
For companies subject to CSRD Article 19a for the first time, limited assurance (as opposed to reasonable assurance) is the initial standard for sustainability disclosure. Limited assurance under ISAE 3000 or equivalent national standards does not require the assurance provider to independently verify every data point — it requires evidence of a documented, defensible methodology and an absence of material misstatement indicators.
This means a well-documented first-year Scope 3 inventory with clear coverage statements and a structured gap analysis is more likely to pass limited assurance review than a less documented inventory with higher apparent precision. Your assurance provider needs to be able to trace the methodology. Whether the Category 1 estimate is 45,000 tCO2e or 47,000 tCO2e matters less than whether they can reproduce the calculation from the underlying source data and factor documentation.
Greenopsiq's output package for ESRS E1 includes the data lineage report that assurance providers request: source document references, factor version identifiers, coverage percentage per category, and a machine-readable methodology appendix. The gap analysis dashboard additionally documents which categories are estimated versus measured and the planned data quality improvement roadmap. Request a walkthrough to see what this output looks like for your industry and reporting boundary.
