Sustainability Meets Data Management
Sustainability without transparent data is akin to a compass without a needle. A company cannot hope to know where it stands and what levers it can usefully pull without any precise or reliable information at its fingertips. The clearer a view it can get of what is going on along its value chains, the more targeted it can be in making sustainability-related decisions, steering improvements, and demonstrating progress convincingly.
Sustainability stands or falls with the availability of sound data. Anyone looking to make solid decisions and be in control of impactful measures will need underlying data that, from procurement and logistics through to development and production, consists chiefly of primary data, which comes straight from its contractual partners. Secondary data – i.e., general market data and averages – that is used initially is transformed into verifiable parameters, while isolated queries are turned into end-to-end chains of data. The biggest challenges here are twofold: first, how to calculate product carbon footprints (PCFs) accurately along complex supply chains; and, second, how to ensure the consistent application of principles pertaining to the circular economy. These are aimed at keeping resources within the economic cycle for as long as possible, for example through durable product designs, recyclable materials, the reuse of components, and transparent flow of materials and substances along the value chain. Both of these require integrated systems, valid primary data, and common standards – throughout the entire value chain.
Sources, granularity, quality, and the pace of change: the four obstacles encountered day to day
A sustainability compass with a clear focus hinges on data from many different sources being brought together to paint a coherent overall picture. Complexity begins with the sheer diversity of sources: ERP and procurement systems, energy monitoring, production and quality data, transportation and logistics data, information from suppliers, and external databases. These sources rarely speak the same language, and they follow different systematic frameworks. Second, an end-to-end calculation of the PCF calls for a high degree of granularity, i.e., material compositions, parts lists, energy consumption levels in each process step, reject rates, modes of transportation, and distances traveled. Instead of “just” a number, what companies are dealing with here is a mosaic made up of many strands of information that are assembled with precision. Third, the quality and availability of data. Businesses rely on data from their supply chain, because they cannot see directly into upstream production processes and there are no precise supply chain structures. Many suppliers still lack standardized systems for capturing their data and furnish incomplete or highly unsound information. These gaps are often filled using secondary data, but this tends to be less accurate as it is aggregated and based on averages. Plus there is the need for training right along the supply chain: What exactly is required? In what depth? In line with what standard? Fourth: the pace of change – because emission factors change (e.g., the energy mix, recycling rates), processes become more efficient, and materials are swapped for other ones. Instead of being a static number, therefore, a PCF is an indicator that has to be updated at periodic intervals.
Several production steps are involved in manufacturing this elastomer gasket for a battery storage system, with each individual stage generating specific data points that are used to calculate the product carbon footprint.
From process to profile: how details shape the footprint
At ElringKlinger, a PCF is calculated “from cradle to gate,” i.e., from when the raw materials are extracted to when the product leaves the factory premises. The use phase and end-of-life recycling are not included for now due to the lack of available data, so that procurement, development, production, and, ultimately, customers can obtain reliable CO2 data about the making of their products that stands up to comparison. While a life cycle assessment (LCA) considers several environmental impact factors across a product’s entire life cycle, the PCF – as a subset of the LCA – just looks at carbon emissions.
To ensure that these metrics are determined consistently and efficiently within the company, ElringKlinger uses a dedicated PCF system that maps the PCF calculation in a methodologically sound way and brings together data flows from procurement, production, and logistics. For the upstream value chain, a methodological manual was written to ensure a clear delineation of system boundaries, data depth, allocation, and cut-off criteria, and standardized templates for capturing data were created. The next step involves providing targeted training for staff in the business and corporate units. ElringKlinger is also pressing ahead with digital orchestration so that automated workflows will be able to link up procurement, energy, and manufacturing data in the future.
The upstream emissions in the value chain (Scope 3) present a particular challenge. Since many suppliers do not yet have any mature systems in place for capturing data, ElringKlinger is increasing its share of primary data in stages with the aid of standardized data specifications, onboarding guides, and a gradual transition phase from secondary to primary data. Where there is still a lack of primary data, quality-assessed secondary data is used – though this will gradually be replaced going forward. The Group uses the data maturity level, which is recorded for each PCF in the ERP system, to assess the maturity of the data in accordance with the system defined specifically for this purpose.
A look at the production lines shows what level of detail is needed: Even an apparently simple metal component like an elastomer gasket for a battery storage system involves numerous production steps, from stamping/punching and pre-treatment processes through to injection-molding and post-treatment processes, including the testing processes integrated into each step. Every single one of these phases comes with its own energy requirements, reject rates, and material loss. The amount of methodological effort expended remains the same along the entire supply chain. Bought-in raw materials also require valid, sound data based on corresponding process and production information from their suppliers, meaning that every supplier faces the same workload for capturing and validating data. In order to obtain realistic figures, therefore, ElringKlinger links its PCF models closely with real-life production data, both in its own business and along the upstream value chain.
Through standardization and qualification, ElringKlinger creates a substrate of underlying data that not only enables transparency but also makes an active contribution to lasting improvements in products and processes. This turns the “cradle-to-gate PCF” into a strategic lever for unlocking more environmentally conscious decisions, measurable progress on decarbonization, and supply chains that are fit for the future.
For ElringKlinger, the next big step will be to develop products in a way that is geared consistently toward the LCA right from the start.
Design for circularity: Impact starts on the drawing board
Thinking in terms of the circular economy broadens your perspective. Rather than thinking merely of CO2, in other words, you need a holistic view of material flows, usage models, and durability to determine how sustainable a product ultimately is. For ElringKlinger, therefore, the next big step will be to develop products in a way that is geared consistently toward the LCA right from the start. The sooner environmental effects become visible, the more targeted your efforts can be at optimizing materials, structures, and processes – specifically where the most impact can be had: in design.
Such a holistic assessment requires precise, readily accessible data management spanning all the phases of a product’s life. The key is to understand what materials go into what components, in what amounts, and along with what critical substances, and how their properties change over repeated cycles of use. At the same time, recyclates must be clearly identifiable – including their origin, quality grades, and carbon footprint – enabling engineering and procurement teams to make sound decisions.
One current challenge lies in the fact that there are as yet no consistent or, more importantly, standardized indicators available for circularity – there is still no uniform industry definition for metrics like material circularity, recyclate rates, repairability, and dismantling assessments. This is precisely what ElringKlinger is taking as its starting point in a bid gradually to establish a consistent system of metrics for KPIs relevant to the circular economy and, further down the line, to integrate it directly into its development milestones. This will allow LCA-based design to become a core element of the product creation process.
Many legal developments in Europe are pointing toward digital product passports (DPPs) becoming a key tool for mapping LCA data completely electronically in the future. DPPs pool material, process, and sustainability information in one place throughout a product’s life cycle, thus establishing a consistent and uniform data substrate for the first time, from raw materials right through to recycling. For ElringKlinger, this means that development teams can identify and manage environmental impacts early on, while manufacturing and quality departments benefit from absolute transparency in terms of materials, and recycling can be made much more efficient as a result. Although the DPP will be hard work to introduce, from interfaces and data models through to permissions, it will unlock a crucial benefit by transforming the LCA from a merely analytical tool into an integrated basis for decision-making along the entire value chain.
As ElringKlinger gradually makes design for circularity an integral part of its operations, its current data management set-up will grow into an effective instrument for steering and control, enabling targeted assessments of and improvements to products to reduce their environmental impact, increase their material efficiency, and bring about a future in which the circular economy is actively embraced.
Data as a compass: transparency, trust, speed
Data management is the backbone of credible sustainability and a compass that will provide guidance if it contains comprehensive, high-quality data. It lays the foundation for operational excellence, from precise PCFs through to a circular economy that is managed effectively. Companies that invest in systems and standards today will enjoy greater transparency, trust, and speed in their transformation, because reliable data will keep them competitive over the long term.
