Empowering the automotive sector for human rights and environmental
due diligence and to drive collaborative action
Empowering the automotive sector for human rights and environmental
due diligence and to drive collaborative action


The methodology used to development the RMO can be grouped in five categories:

Data collection methods

The value chain information, the market intelligence data and the ESG risk identification were done by reviewing secondary data. Primary data collection through stakeholder engagement was also done to address research gaps or triangulate information where relevant. In addition, part of the market intelligence data was provided by Argus Media*. Secondary data reviewed included:

  • Publicly available information (reports, media articles, academic papers, industry briefings, etc.)
  • Reported incidents and materialised risks linked to each commodity and at different stages of the value chain.
  • Standards and initiatives applicable or relevant for the minerals in scope.

Stakeholder interviews have included industry associations and independent experts.

*Disclaimer: The data provided by Argus in the form of tailored report for the Raw Material Outlook has not been fully triangulated or verified. Data and information contained in the tailored report for the Raw Material Outlook come from a variety of sources, some of which are third parties outside Argus’ control and some of which may not have been verified. All analysis and opinions, data, projections and forecasts provided may be based on assumptions that are not correct or which change, being dependent upon fundamentals and other factors and events subject to change and uncertainty; future results or values could be materially different from any forecast or estimates described.

Reference framework of risk identification and analysis

The United Nations Guiding Principles (UNGPs) on Business and Human Rights have been used as the main reference framework for risk identification, analysis and prioritisation (as explained later). The UNGPs outline (principle 18 specifically) that business enterprises should identify and asses any actual or potential adverse human rights impacts with which they may be involved either through their own activities or because of business relationships. The analysis done for the development of the RMO has expanded this concept to broader environmental, social and governance risks. Given the extended scope the outcomes should be considered as indicative at this stage and in the context of the automotive sector, rather than from the perspective of doing due diligence for a specific company’s value chain and direct business relationships. Moreover, the risk identification has been based on:

  • Reported materialised risks, which have been used as evidence to support the identification of impacts at each stage of the value chain.
  • Materials specific processing methods and technology, which guided the identification of potential risks even when evidence would not be found. This method has been particularly useful to identify risks to the environment and health and safety, both for workers and communities
Risk classification

Identified risks have been categorised following the Consolidated Framework of Sustainability Issues for Mining which resulted from the comparison and synthesis of sustainability issues and requirements in the mining sector done by the Bundesanstalt für Geowissenschaften und Rohstoffe (BGR). The classification has slightly been adapted to include sub-issues which were not included in the framework.

Risk prioritisation

The data collected through the RMO will be used to guide a preliminary risk prioritisation across the value chain stages for each material. Following the UNGPs methodology, this initial prioritisation, should be then complemented by engaging affected parties and other relevant stakeholders. The preliminary assessment prioritises risks based on saliency, which is defined by the risks’ severity and likelihood.

  • Severity: calculated as a compound score of scale (i.e., gravity of impact), scope (number of individuals affected) and irremediability (the ease with which those impacted could be restored). The assessment of these three parameters is done against each risk summary and according to the data collected. It is then combined into an overall severity score.
  • Likelihood: evaluated on a geographical basis, using human rights databases and available benchmarks to determine how likely a particular risk is to occur in a particular country or region. These benchmarks are the same for all countries / regions to ensure comparability and consistency. The market intelligence data is used to determine the likelihood based on production countries. For value chain stages where market intelligence data is not available currently, the locations of materialised risks is used instead.

The value chain approach has led to the identification of potential leverages for the automotive industry to consider. Recommendations include sector-wide collaborative actions, considerations for individual companies for their own responsible sourcing practices, and multi-stakeholder collaboration opportunities. The leverages are defined based on the methodology outlined by the Shift in the guidance: Using Leverage in Business Relationships to Reduce Human Rights Risks.

Research notes and limitations

This section includes some important notes and limitations which should be noted while reviewing the information presented in the RMO. These are separated between general limitations and the ones which apply to specific materials.

General limitations

  • By looking at all value chain for each material, the research team was exposed to large volumes of data and areas to explore and investigate. As such, the data included in the RMO does not intend to be exhaustive, however it rather focused and prioritised providing a reasonable overview of critical information to map the value chain and identify most salient risks.
  • Information conveyed in public reporting on ESG impacts is often contested and not uniformly reported. This creates challenges in verifying accuracy and as such any reports are best treated as indicative. Certain risks therefore might require further enquiry and investigation with relevant stakeholders.
  • Within the timeframe available to develop the RMO, stakeholders’ interviews have focused on addressing research gaps at indicative level and not on specific materialised impacts or reported incidents.
  • The manufacturing and intermediary products stages of most materials require further analysis, considering the many companies involved at these stages and the diverse use of the materials.
  • The assessment has been partially subject to English language bias. Beyond English, Portuguese and Chinese have also been used to search for information where relevant. This may create a data bias against certain geographical regions such as Latin America and Asia.
  • Whether or not a situation, environmental or human rights abuse had been resolved remained unclear in many cases as following initial reporting there is often little follow up. As such, it was very difficult to obtain latest position on a given incident or situation.
  • It was difficult to accurately identify contemporary relevant stakeholders, particularly companies involved. This was due to changes in the parties in many cases, as well as sometimes confusion in public reporting.
  • In some instances, placing company operations within a precise value chain stage has been challenging given that publicly available information was not always clear whether a given set of circumstances or impacts related to mining or processing operations, and, if the latter, which processing operations.
  • The ESG risk identification and analysis does not intent to assign responsibilities to specific parties. It rather focuses on identifying which impacts are already or potentially taking place, so to direct further analysis and due diligence.
  • Risk identification has been more extensive on the upstream stages of the value chains, specifically mining and processing stage. Once the material is further transformed in intermediary or manufacturing products, a broader analysis would be required and tracing down impacts across manufactures has been considered out of scope. Further risk identification would require combining the existing data with specific automotive manufactures supply chain mapping.

Commodity specific limitations

Bauxite / Aluminium

  • Reporting on the mining stage was more extensive than for other value chain stages, with evident limitations for casting, intermediary products, semi-fabrication and manufacturing stage which deserve further analysis.
  • In some instances, lack of consistency of reports in terms of clearly differentiating between alumina refining and aluminium smelting made attribution of impacts to a certain value chain stage more difficult.
  • The recycling stage deserves further analysis as drawing impacts specific to aluminium within the current scope presented limitations.

Graphite (Natural)

  • Reporting on graphite was considerably low compared to other minerals, presenting graphite as somewhat of a blind spot. As result, a notable segment of public reporting expressing concern over graphite cited situational indicators for concern, rather than specific instances of ESG breaches.
  • The opacity of the global graphite supply chains and distortions in trade data that, for example, present traders as major graphite exporters, rendered it more challenging to clarify the issue of scope of risk, despite the fact that there were clear indictors of risk sources that could potentially contaminate the supply chain (e.g., North Korea and Pakistan).
  • Distinguishing between natural and synthetic graphite production was often difficult and, in some cases, appears to have likewise caused confusion among certain market intelligence analysis. Reporting on impacts on communities generally referenced graphite production “factories” without specifying whether factory processes related to the processing of natural graphite or synthetic graphite.
  • Distinguishing between different graphite processing, and sometimes even between the impacts of mining and processing, was rendered difficult by generic or vague reporting. Reporting often discussed impacts without reference to specific triggers or causes, leaving this down to deduction, where possible. In one case, minerals experts reported confusion as to why certain triggers such as high dust particle emissions should be generated by a processing facility of the nature described in reporting.

Iron ore – Steel

  • Limited reporting was available for the beneficiation, fabrication and recycling stages which all deserve further analysis in terms of materialised impacts and risks.
  • As the value chain looked at iron as raw material and then steel production as main application, the analysis has been limited to iron, and for steel production impacts identified focused on the actual processing and operations, and it did not look into other components in detail.


  • Limited public information is available on magnesium impacts. When data was available, in some instances, it has proven difficult to link reported impacts to specific value chain stages or to clearly define the severity and cause of impact because of the limited information available.
  • Accessing market information beyond the mining stages has been challenged by the limited publicly available information.
  • The OECD data on trade provides values in US dollar instead of volume of traded material, which instead would provide a more accurate analysis.


  • Limited public information is available on manganese impacts. When data was available, in some instances, it has proven difficult to link reported impacts to specific value chain stages or to clearly define the severity and cause of impact because of the limited information available.
  • Accessing market information beyond the mining stages has been challenged by the limited publicly available information.
  • The OECD data on trade provides values in US dollar instead of volume of traded material, which instead would provide a more accurate analysis.


  • As molybdenum is often extracted as a by-product of other principal minerals (copper, etc.), there was minimal information available on molybdenum mining, refining, etc. alone, on its own with its own separated impacts. Much of the information was extracted from information gleaned from copper mining, or tungsten mining, etc.
  • Minimal public information available on trading, warehousing, transportation.
  • Minimal public information available on some of the later stages of the value chain, including component manufacturing, product manufacturing, and recycling and disposal. This could be because molybdenum is often extracted as a by-product of other minerals, and therefore is found in minimal amounts toward the later value chain stages.


  • The sheer volume of reporting in respect of nickel mining and processing operations created a heavy bias on the upstream processes involved in nickel production. It also meant that several cases could not be included simply due to scope limitations, and the impacts reported.
  • Some situations appear to be protracted and evolving, whereas others are simply seldom reported on. Nearly all materialised risk were considered temporally relevant either because events had taken place during the reference period (as well as before it) or because reporting on events had taken place during the reference period in a manner that suggested that the issues remained unresolved.
  • Reporting tended to focus on nickel production “projects”, which could involve both mining and processing. This made it difficult to distinguish which part of the value chain a given impact related to. For example, many metallurgical facilities are set up as projects to reduce transportation costs locating smelters and refiners close to mines. Moreover, legal arrangements between entities operating each facility can vary and be complex. As such, nickel has been proven more difficult to disaggregate actions between mining and refining in numerous cases, either because impacts coalesce or because of the way in which cases are reported. It can be likewise difficult to distinguish between smelters and refiners where reference to impacts is particularly focused on human health or environmental outcomes rather than modes or triggers of harm.
  • There were certain instances of companies implicated in serious ESG risks in one location but having operations elsewhere that are best in class for lower impact. In some cases, these companies would continue to operate extremely damaging operations elsewhere, claiming that impacts were being addressed without resolving the situation, or else ceasing damaging activities but failing to address historical impacts.


  • In some instances, it has proven difficult to link reported impacts to specific value chain stages or to clearly define the severity and cause of impact because of the limited information available.


  • Considering that tantalum is often extracted as by-product, risk identification specific to tantalum has been more difficult, as many reports do not differentiate or make explicit the implications of tantalum specific production.
  • Data available on 3Ts’ mines in eastern DRC is often aggregated across 3Ts minerals (especially when two or more occur in the same area), and not in all cases it was possible to single out tantalum specific impacts.


  • The value chain stages refining, smelting and roasting were combined, as much of the literature seemed to combine these stages or use the terms interchangeably, and it has proven more difficult to associate impacts to specific value chain stages.
  • Minimal public information available on trading, warehousing, transportation.