CSRD – Well Prepared Thanks to Data-Driven Intelligence

CSRD – Well Prepared Thanks to Data-Driven Intelligence

Sustainability in Discrete Manufacturing: Capture, Analyse, Report and Optimise. Is sustainability the new compliance?

The intent behind the European Union's Corporate Sustainability Reporting Directive (CSRD) reform is unequivocal: no longer should companies overlook the imperative of sustainability, carelessly navigating the market without a transparent strategy for enhancing both their products and production methods.

No longer should reports be mere procedural exercises; rather, the emphasis lies in presenting substantiated and comparable figures encompassing environmental, social, and corporate governance realms. These figures should offer reliable insights into the genuine status of both the product and the company, exhibiting changes, enabling trend identification, and validating the purposeful nature of corresponding measures.

Certain companies and corporations are committing to climate-neutral production and scrutinizing products for their environmental impact. This aligns with the objectives set by the European Union for the upcoming years: 2035, 2040, or 2050. Regardless of the timeline for achieving these objectives, they represent ambitious goals feasible only when decisions are underpinned by robust data—decisions rooted in data-driven strategies.

Take Ford, for instance: the company has established clear targets across various domains such as climate, waste (e.g., eliminating single-use plastics by 2030), air (zero emissions), energy (100% CO2-free by 2035), water, among others. Ford aspires to attain carbon neutrality by 2050 at the latest.

Though materiality audits to data-driven decision-making: Halfway to CSRD?

Ford has undertaken its 2023 materiality analysis adhering to the standards set by the Global Reporting Initiative (GRI). This process has considered the updated GRI guidelines as well as the anticipated European Corporate Sustainability Reporting Directive (CSRD) regulation.

Sustainability initiatives are comprehensively outlined and cataloged within the company's internal guidelines, subject to continuous progress assessments and developmental reviews. At Ford, these initiatives encompass climate change, waste management, air quality, energy consumption, water usage, material sourcing, safety protocols, human rights, diversity, equality, and inclusion, along with Ford's commitment to enhancing mobility access.

To realize its ambitious objective of achieving carbon neutrality by 2050 at the latest, the company is strategically concentrating on three pivotal areas responsible for 95% of emissions: the production of its own vehicles, associated business operations, and a comprehensive evaluation of the entire supply chain.

The path and the destination are relevant: Example of reused materials.

A vehicle is composed of approximately 75% metals, 17% plastics, 4% liquids, 3% electronic components, and 1% miscellaneous materials. Although 95% of the metals are already subjected to recycling, the realm of plastics presents significant potential for material reusability, thereby contributing to a reduction in the environmental impact of CO2. This is due to the fact that reused materials generally entail fewer greenhouse gas emissions, including CO2, compared to the production of new materials.

The viability of incorporating reusable materials is exemplified by a potential quota of 10 to 20% recycled materials, with an average allocation of around 280kg of plastic per passenger car. This underscores the impact of materiality assessments in facilitating data-driven decision-making processes.

The first step: Collect

Whether reporting or optimization - the first step is to collect relevant and reliable data. This is a step where iPoint classically plays to its potential and reliably maps the necessary processes with its compliance products and prepares data in a comprehensible manner.

Take the collection of all information about the materials and substances used in vehicles, in the plants and after markets. A close link to the International Material Data System (IMDS) and B2B management for suppliers (e.g. documentation of RoHS, REACH, ELV...) not only help to ensure compliance, but also provide valuable information on the respective share of recycled materials, as envisaged in more detail in the vehicle recycling regulation presented by the EU Commission.

Reporting on compliance with various current, but also future regulations and further developments of REACH, SVHC (incl. expiry dates), ELV and Annex II exemptions, EPA, OSHA, GHS, GHG etc. is reliably managed and delivered via a suite of iPoint's software solutions.

The second step: Analysis

In the analysis, one of the tasks is to find out which are the next decisions that are necessary for a positive development to reach the target. For this, it is important to analyse the right data and put it into a context that ultimately makes decision-making possible - based on valid data, facts and figures.

Through IMDS and the support of iPoint software, it is possible to find out where recycled content is in each vehicle and what types are used. Compiled on a dashboard, this data simplifies analysis. As the material specifications include the quantities of recycled content, the team can ensure that all content is reported in the systems (IMDS, iPoint Compliance...).

Basic assessments, aimed at establishing robust, pragmatic, and consequently attainable objectives or delivering continual progress reports on initiatives already underway, can be succinctly encapsulated and communicated through dashboards. This approach serves to guarantee that, within the context of vehicle programs and, by extension, for the overall company, the defined targets are met punctually and in adherence to predefined frameworks (e.g., budgets, use of materials, etc.).

Regional analyses are an important part of this overview due to different recycling environments and local availability of raw materials. Likewise, both post-consumer and post-industrial recyclates can be tracked in this way. The mapping of different product lines can also be implemented in this way. A breakdown by material type and by program management team (e.g. interior, exterior, electrical, etc.) simplifies management and provides transparency, e.g. for the vehicle program manager.

The third step: Report

An exportable parts list with delivery information can help to find the status of recycled content in each part and/or specification. Based on this, work can be done with the supplier to increase or change the percentage of recycled components. Of course, it is only logical to also collect this data to conduct Life Cycle Assessments (LCA), which are becoming more and more important for the calculation of ecological footprints (e.g. carbon footprints). iPoint Product Sustainability allows Product Carbon Footprint (PCF) calculations to be carried out on large quantities with generic models and to identify potential savings by comparing and selecting alternative materials (lists). The connection to IMDS and the high degree of automation through machine learning make the use of iPoint software highly efficient, especially for complex products.

Confluence of compliance and sustainability data

Data-driven decision-making offers clear advantages for different departments and users inside and outside the company. Informed decisions are made based on solid, meaningful, and accurate data for goal setting, budget allocation, material selection, engineering design and manufacturing, which are reflected in the CO2 emissions report figures.

The ongoing and robust audits required for the CSRD are part of this process and can therefore be integrated. In this view, (product) compliance and sustainability data flow together and provide a valid snapshot of the company, its products and the respective environmental impacts. A snapshot that provides information on how and where these influences can be positively changed. Ultimately, transparent data management across the entire supply chain is the key to conclusive analysis with real data.

Bing Xu & Claus Wagner

Bing Xu & Claus Wagner

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