An automotive OEM or tier 1 supplier can spend a year mapping direct suppliers, sending questionnaires, and reconciling spreadsheets, only to realise that the bulk of its Scope 3 footprint sits one or two layers further back: at the tier 2 stamping shop, the tier 3 resin compounder, the mine feeding a battery cell plant. Tier 1 relationships are contracted and visible. Tier 2 and tier 3 are not, and that is where automotive supply chain carbon reporting breaks down.
This guide explains why tier 2 and tier 3 supplier emissions dominate the manufacturing-phase footprint of an automotive value chain, how to prioritise which suppliers to engage first, which calculation method to use at each tier, and how to run a data collection campaign that does not stall on non-responding suppliers.
For a general definition of what tier 1, tier 2 and tier 3 mean in a supply chain, see our supplier tiers glossary. This article focuses specifically on carbon accounting.
Why tier 2 and tier 3 dominate the automotive footprint
An automotive OEM's own operations, its factories, offices and fleets, sit in Scope 1 and Scope 2, a small fraction of the total footprint for most manufacturers. The overwhelming majority sits in Scope 3, and within Scope 3, the GHG Protocol's Category 1 (purchased goods and services) is consistently the largest single category for manufacturers, one of the upstream Scope 3 categories, according to the GHG Protocol Scope 3 Technical Calculation Guidance.
In automotive specifically, that category is not concentrated at tier 1. A tier 1 supplier assembling a seat module or a wiring harness has already outsourced most of the carbon-intensive steps: steel and aluminium smelting, resin and polymer production, casting, forging, chemical treatment. Those steps sit at tier 2 (component and sub-assembly manufacturers) and tier 3 (raw material processors, foundries, mining and refining operations). No single industry-wide figure reliably splits manufacturing-phase Scope 3 emissions between tier 2 and tier 3, and we would rather say so than quote a number we cannot source. What is well established is the direction: emissions intensity increases as you move upstream toward raw material transformation, since that is where the most energy-intensive processes (smelting, casting, chemical synthesis) happen.
This is why CSRD and CBAM both push companies to look past their direct suppliers. The EU's Corporate Sustainability Reporting Directive requires disclosure under ESRS E1, which includes Scope 3 emissions, and the Carbon Border Adjustment Mechanism targets embedded emissions in imported raw materials such as steel and aluminium, the exact commodities sitting at tier 2 and tier 3 of an automotive chain.
Why the data is hard to get
Three structural problems explain why tier 2 and tier 3 data collection is harder than tier 1.
No direct contract. A tier 1 supplier has a commercial relationship with the OEM. A tier 2 or tier 3 supplier does not: no purchase order, no vendor portal, no existing channel for a data request. The OEM or tier 1 buyer has to go through the tier 1 supplier to even identify the tier 2 supplier, who may treat its own supplier list as competitive information.
Uneven reporting maturity. A large tier 1 supplier with a sustainability team can produce a verified carbon footprint. A tier 3 foundry with 40 employees usually cannot: it may not track energy consumption by product line, may not know what Scope 1, 2 and 3 mean, and has limited resources to respond to a detailed questionnaire, let alone a different one from every OEM touching its output.
Data ownership and multiplication. Every OEM and tier 1 buyer independently asks the same tier 2 and tier 3 suppliers for data, in different formats, on different timelines. A single foundry supplying three tier 1 companies can receive three separate, non-standardised requests for the same underlying production data. This is the problem data exchange standards such as Catena-X were built to solve, by defining a shared automotive-industry data space for Product Carbon Footprint (PCF) exchange so a supplier calculates its footprint once and shares it consistently across customers.
How to prioritise which suppliers to engage
Engaging every tier 2 and tier 3 supplier at once is not realistic, and it is not necessary. Prioritise using three filters, applied in order.
1. Spend concentration. Rank suppliers, or supplier categories where individual tier 2/3 identity is unknown, by the value of purchased goods and services they represent, even indirectly. A small number of commodity categories, steel, aluminium, plastics and electronic components, typically account for a disproportionate share of automotive purchasing spend.
2. Emissions intensity of the commodity. Cross-reference spend against known emissions-intensive processes. Primary steel and aluminium production, battery cell and cathode manufacturing, and chemical/resin synthesis are far more carbon-intensive per euro of spend than plastic injection moulding of low-footprint components. A mid-size spend category in a carbon-intensive commodity can outweigh a larger spend category in a low-intensity one.
3. Regulatory exposure. Suppliers of commodities covered by CBAM (notably steel, aluminium and certain precursors), or whose output feeds directly into products reported under CSRD/ESRS E1, should be prioritised regardless of spend rank, since the reporting obligation applies whether or not data collection has started.
The output is a short list, typically the top 20 to 30 supplier categories by combined spend and emissions intensity, engaged first with supplier-specific data requests. Everything below that threshold can be estimated using spend-based methods until capacity allows for deeper engagement.
Calculation methods by tier
Not every tier needs the same precision. The GHG Protocol recognises three calculation approaches, mapping naturally onto the three supplier tiers of an automotive value chain.
For emission factors, spend-based and average-data calculations should be sourced from recognised public databases rather than estimated internally: the ADEME Base Carbone in France, DEFRA conversion factors in the UK, or the US EPA's supply chain factor datasets. For automotive-specific component-level data, Catena-X defines a shared methodology (the PCF Rulebook) so a footprint calculated by one supplier can be reused consistently by every customer that receives it, instead of each buyer applying its own conversion.
The practical approach for most automotive buyers is a hybrid: supplier-specific data for the prioritised short list, average-data for the next tier of significant categories, and spend-based as the default fallback so no category is left uncalculated.
How to run a supplier data collection campaign
A tier 2 and tier 3 campaign works differently from a tier 1 campaign, and it sits inside the broader exercise of measuring value chain emissions, mainly because the OEM or tier 1 buyer usually cannot contact the supplier directly on day one.
Step 1: Map the chain through tier 1. Ask each prioritised tier 1 supplier to disclose its own tier 2 suppliers for the components in scope, as a contractual expectation rather than an optional favour, particularly for suppliers already covered by CSRD themselves.
Step 2: Standardise the request. Use a single data request format across the whole chain, aligned to an existing standard (Catena-X PCF Rulebook, or the GHG Protocol Scope 3 categories) rather than a bespoke questionnaire, so a supplier who has already produced a compliant PCF for another customer can reuse it.
Step 3: Sequence the outreach. Start with the short list from the prioritisation exercise. Contacting every tier 2 and tier 3 supplier simultaneously produces a low response rate and an unsustainable support burden. A phased rollout, quarter by quarter, produces a higher completion rate.
Step 4: Support, do not just request. Many smaller tier 2 and tier 3 suppliers have no in-house carbon accounting expertise. A simple calculation template and a point of contact for questions materially increase response quality and rate.
Step 5: Set a deadline and a review checkpoint. Every request needs an explicit deadline and a scheduled follow-up built in from the start, not an open-ended "please respond when convenient."
Handling non-responding suppliers
Non-response is the norm, not the exception, at tier 2 and tier 3, so the process needs a defined fallback rather than an indefinite wait.
Set a response deadline with automatic escalation. A defined reminder cadence, for example at two weeks and four weeks after the initial request, should trigger automatically rather than relying on manual follow-up. If the supplier sits behind a tier 1 relationship with commercial leverage, escalate through that relationship rather than repeating a direct request already ignored.
Fall back to estimation, not to a data gap. If a supplier has not responded by the review checkpoint, do not leave the category unreported. Apply the average-data or spend-based method as an interim estimate, clearly flagged as estimated, so the footprint calculation remains complete and auditable. Replace it with supplier-specific data as soon as it becomes available, rather than waiting for 100% coverage before updating the footprint.
Track response status as an ongoing metric. A campaign that is not measured (response rate, data quality, time to response) tends to stall silently. Reviewing it on the same cadence as other supplier KPIs keeps it from being deprioritised.
Common pitfalls
Treating tier 1 confirmation as tier 2/3 confirmation. A tier 1 supplier confirming "yes, we've asked our suppliers" is not the same as having received and validated tier 2 data. Track the underlying data, not the intermediate confirmation.
Applying a generic emission factor to a specific material. Using a broad "metal products" spend-based factor for a category that is actually primary aluminium smelting will understate the footprint significantly, since primary aluminium is one of the most carbon-intensive materials in a vehicle. Match the factor granularity to the material.
Ignoring double counting across tiers. If a tier 1 supplier reports its own Scope 3 (which includes its tier 2 suppliers' emissions) and the OEM separately collects tier 2 data directly, the same emissions can be counted twice unless the methodology explicitly reconciles the two.
Waiting for perfect data before reporting anything. CSRD and CBAM timelines do not wait for 100% supplier response rates. A transparent estimate, clearly labelled by calculation method, is defensible. An unreported category is not.
How Kabaun supports automotive Scope 3 tracking
Kabaun's carbon calculation engine covers Scope 1, 2 and 3 across all 15 GHG Protocol Scope 3 categories, applying emission factors from 8 public databases (270,000 factors in total), supporting the spend-based and average-data methods described above for tier 2 and tier 3 suppliers without primary data.
For prioritised suppliers, Kabaun's automated supplier relaunch feature sends and tracks data collection requests, reducing the manual follow-up load. Data can be imported via CSV/Excel with AI-assisted mapping, or through the API and ETL connectors for organisations integrating supplier data from an existing procurement system. Uncertainty analysis on calculated results matters when a footprint mixes supplier-specific, average-data and spend-based figures across tiers, letting the confidence level of each figure be tracked rather than presented as uniform precision. Multi-entity and multi-site management supports organisations tracking emissions across several plants feeding into a consolidated footprint.
Conclusion
Tier 2 and tier 3 suppliers sit outside the direct contractual relationship that makes tier 1 collection comparatively straightforward, but they are where the most carbon-intensive processes in an automotive value chain happen. A strategy that only reaches tier 1 will systematically underrepresent the footprint. Prioritise by spend and emissions intensity, match the calculation method to what data is realistically available at each tier, standardise the request format, and build a defined fallback for non-response instead of letting the process stall.
Kabaun automates supplier relaunches, applies GHG Protocol-aligned calculation methods across all Scope 3 categories, and tracks data uncertainty as the footprint moves from estimated to supplier-specific. Get in touch to see how it applies to your supply chain.
FAQ: Frequently Asked Questions
What is the difference between tier 1, tier 2 and tier 3 suppliers in an automotive supply chain?
Tier 1 suppliers sell directly to the OEM (for example, a seat module or wiring harness manufacturer). Tier 2 suppliers sell components or materials to tier 1 suppliers (for example, a stamped metal parts manufacturer). Tier 3 suppliers sit further upstream, typically raw material processors such as steel mills, foundries or chemical producers. For a fuller definition, see our supplier tiers glossary.
Why are tier 2 and tier 3 suppliers important for Scope 3 emissions reporting?
The most energy-intensive processes in vehicle manufacturing, such as steel and aluminium smelting, casting, and chemical synthesis, generally happen at tier 2 and tier 3, not at tier 1 assembly. A footprint that only accounts for tier 1 data systematically misses a large share of purchased goods and services emissions (GHG Protocol Category 1).
Which calculation method should be used for tier 2 and tier 3 supplier emissions?
It depends on data availability. Spend-based calculation (purchase value × economic emission factor) works when no supplier data exists. Average-data calculation (physical quantity × material factor) improves accuracy when the material is known. Supplier-specific data, based on a measured Product Carbon Footprint, is most accurate but requires the supplier to provide it. Most automotive buyers mix all three depending on priority ranking.
What should be done when a tier 2 or tier 3 supplier does not respond to a data request?
Set a defined deadline with automatic reminders, escalate through the tier 1 supplier relationship where possible, and fall back to a spend-based or average-data estimate rather than leaving the category unreported. Clearly flag estimated figures as such, and replace them with supplier-specific data as it becomes available.
Is there an industry standard for exchanging automotive supply chain emissions data?
Catena-X is a shared automotive-industry data space that includes a Product Carbon Footprint (PCF) Rulebook, designed so a supplier can calculate its footprint once and share it consistently with multiple automotive customers instead of responding to a different format for every buyer.
Do CSRD and CBAM apply to tier 2 and tier 3 automotive supplier emissions?
CSRD requires large EU companies to report Scope 3 emissions under ESRS E1, which includes upstream purchased goods and services regardless of supplier tier. CBAM specifically targets embedded emissions in imported goods such as steel and aluminium, commodities typically sourced from tier 2 and tier 3 suppliers in an automotive chain.
