The chemical industry is facing a dual challenge. On the one hand, regulatory requirements across global value chains are continually increasing. On the other hand, customers, partners, and investors are demanding transparent, reliable, and real-time product and sustainability data. What is still often managed today through emails, PDF documents, and custom interfaces is increasingly becoming a strategic competitive factor. Companies that standardize and automate the exchange of product and sustainability data can measurably enhance their competitiveness, redeploy tied-up resources, and accelerate time to market. Against this backdrop, the publicly funded Chem-X project initiated by the Federal Ministry for Economic Affairs and Energy (BMWE) is gaining importance. The initiative aims to establish standardized and trustworthy data exchange across the chemical industry. The focus is not primarily on technology. What matters is the ability to make data available efficiently, securely, and interoperably across company boundaries.
From regulatory obligation to value driver
For many companies, the discussion begins with regulatory requirements such as Product Carbon Footprints (PCF), Digital Product Passports (DPP), or extended sustainability documentation. However, a recent study by Porsche Consulting shows that the actual potential extends far beyond compliance. In interviews with more than 25 experts from 14 companies in the chemical industry and adjacent sectors, Porsche Consulting identified nine key value dimensions that Chem-X can address. These range from efficiency improvements within individual companies and structural improvements across the industry to new opportunities for cross-industry collaboration. Specifically, the nine dimensions are:
- Efficiency gains
- Risk and compliance
- Growth and additional opportunities
- Structural inefficiencies
- Economies of scale
- Harmonized compliance
- Interoperability
- New sales markets
- Sustainability
Efficiency potential worth millions
The benefits are particularly evident at the company level. Many chemical companies currently invest significant resources in collecting, validating, and sharing product and sustainability data. Media discontinuities, custom interfaces, and manual coordination create a high administrative burden, for example when repeatedly processing safety data sheets or certificates for each supplier. Altogether, this creates substantial economic potential: for a very large chemical company comparable in size to the Chem-X member companies analyzed, efficiency gains of around €90 million per year can be derived across the identified value dimensions. Extrapolated to the entire chemical industry, this corresponds to industry-wide efficiency potential of more than €1 billion annually. The scale illustrates that standardized data exchange goes far beyond optimizing individual processes: with broader adoption of common standards, company-specific efficiency gains can evolve into structural advantages for the entire industry. Through standardized data models and automated data sharing, companies could significantly reduce the effort required for data exchange and reporting. The study identifies potential savings of €15 million to €20 million per year from more efficient data processes alone. A further €10 million to €12 million can be achieved by reducing custom interface solutions. At the same time, process cycle times can be significantly shortened and data quality improved. Alongside the financial benefits, another advantage emerges: experts can focus more on value-creating activities while recurring data exchange processes are automated.
Compliance becomes a scaling factor
Regulatory requirements will continue to increase in the coming years. Many companies still respond to this development with isolated solutions spread across various systems and organizational units. Chem-X takes a different approach: instead of meeting compliance requirements separately for each customer, market, or auditor, data should be provided once in a structured format and then reused multiple times. According to the experts surveyed, this can significantly accelerate audit and compliance processes. Internal audit procedures alone, such as Product Carbon Footprint or mass-balance certification processes, were found to offer potential savings of around €5 million per year. This is not only about efficiency. Transparent and traceable data flows also increase credibility with customers, authorities, and business partners.
Shared standards deliver results
The greatest potential arises when companies act together. Today, many market participants operate their own standards, data models, and interfaces, for example for exchanging safety data sheets, Product Carbon Footprint data, or certificates, often through parallel, incompatible systems such as traditional Electronic Data Interchange (EDI), customer-specific portals, or different data platforms. The result is complex integrations, redundant checks, and high operating costs. The study shows that harmonized standards – shared data formats and data models, for example for Product Carbon Footprints or safety data sheets, industry-wide technical reference architectures, and central exchange platforms – can eliminate significant structural inefficiencies. Reducing fragmented systems and custom interfaces alone is expected to generate industry-wide savings of up to €20 million per year. Additional benefits arise from shared data models, standardized agreements, and reusable technical components. Achieving critical mass is essential. Data ecosystems only deliver their full benefits when a sufficient number of participants adopt the relevant standards. The larger the network, the stronger the economies of scale and network effects.
Data as the foundation for artificial intelligence
In this context, another aspect is becoming increasingly important from a strategic perspective and extends beyond the traditional efficiency discussion: the close relationship between cross-company data availability and the successful deployment of artificial intelligence. AI applications are fundamentally only as powerful as the data foundation on which they are built. Fragmented, inconsistent, or siloed data significantly limits the quality of automated decisions and forecasts, regardless of how advanced the underlying models may be.
For the chemical industry, this means that companies investing today in a standardized and trusted data space such as Chem-X are simultaneously creating the conditions for effectively deploying AI applications across the entire value chain – from plausibility assessments of incoming data and automated compliance checks to AI-supported forecasting in sales and supply chain management. Data availability is therefore becoming more than an operational necessity; it is becoming a strategic prerequisite for future competitiveness. Companies that delay this step risk not only higher operational costs but also losing pace with a new generation of AI-enabled, automated business processes.
Chem-X as a bridge between industries
The findings are particularly interesting regarding collaboration across industry boundaries. Supply chains do not end at the gates of a chemical plant. The automotive industry, healthcare sector, consumer goods industry, and mechanical engineering sector all depend on reliable data. Chem-X can serve as a building block for a cross-industry data infrastructure. Standardized data models such as the digital material passport allow information to be provided once and then reused across different ecosystems. This reduces integration efforts and creates the basis for seamless digital value chains. The study quantifies the potential of interoperable standards alone at around €11.4 million per year.
Particularly close ties exist with Catena-X, the already established data ecosystem of the automotive industry. Both initiatives are actively collaborating to use standards, data models, and technical components jointly wherever possible instead of developing them separately and redundantly. This creates a double benefit for the chemical industry. First, proven concepts from Catena-X – such as secure participant identification, control over data usage and sharing, and documentation of regulatory requirements – can be adopted directly and adapted to industry-specific needs. Second, it establishes the foundation for seamless cross-industry data flows between chemical and automotive companies, which can be implemented much more easily through compatible standards and shared interfaces. This close coordination between Chem-X and Catena-X is therefore a key building block for the long-term success of both ecosystems. At the same time, it creates new opportunities in traceability, the circular economy, and digital product passports. Companies gain stronger foundations for sustainability decisions and can meet regulatory requirements more efficiently.
The decisive success factor: execution
The study makes it clear that the economic benefits of Chem-X will not materialize automatically. Harmonized data models, clear governance structures, and a consistent focus on cross-company use cases are essential prerequisites. According to the experts, the most important fields of action are improving data quality, expanding interoperable standards, strengthening coordination between different X initiatives – especially Catena-X – and establishing clear governance for the further development of the ecosystem. Only on this basis can automation, compliance, AI adoption, and new data-driven value creation be scaled sustainably.
The discussion around data spaces is no longer merely a question of regulatory compliance. Instead, the ability to exchange data securely and in a standardized manner – and therefore the ability to deploy artificial intelligence effectively – is becoming a key competitive factor for the chemical industry. In close coordination with established ecosystems such as Catena-X, Chem-X is creating the foundation for a connected, transparent, and future-ready industry in which data is used as strategically as raw materials or production capacity. The findings demonstrate that data is increasingly becoming a productive resource. Companies that standardize and automate data flows across organizational boundaries not only reduce costs but also create the foundation for faster innovation cycles, new business models, and more resilient supply chains.