Sustainability management in the polycrisis: Why waiting for regulation for ESG, EUDR, and CSRD is not an option

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Companies in Europe are facing a polycrisis of geopolitical tensions, skills shortages, supply chain risks, and increasing pressure to achieve climate neutrality. At the same time, the regulatory framework is becoming increasingly volatile. The renewed postponement of the EU Deforestation Regulation (EUDR), the discussion about staggered application dates, and the ongoing adjustments to the Corporate Sustainability Reporting Directive (CSRD), the European Sustainability Reporting Standards (ESRS), the Corporate Sustainability Due Diligence Directive (CSDDD), and the Carbon Border Adjustment Mechanism (CBAM) show that the rules of the game can change at short notice. Those who continue to align their sustainability management, ESG strategy, and data architecture exclusively with the precise fulfillment of individual regulations risk not only high adjustment costs but also misguided investments with an uncertain ROI.

Data fragmentation in global supply chains

In many companies, the data required for professional ESG management is not yet available in their own ERP system, but is distributed among suppliers, logistics partners, and service providers along global value chains. Network supply chains created by nearshoring, multi-sourcing, and resilience-driven redesigns significantly increase the complexity of data collection, validation, and aggregation along the supply chain. In our experience, without a clean data model, clear responsibilities, and governance, the result is a patchwork of tables, formats, isolated solutions, and manual workarounds—with a correspondingly high risk of errors, liability, and reputational damage.

At the same time, regulations such as the Corporate Sustainability Reporting Directive (CSRD), the European Sustainability Reporting Standards (ESRS), the Corporate Sustainability Due Diligence Directive (CSDDD), and national climate reporting requirements are tightening the requirements for transparency, auditability, and comparability of sustainability metrics. ESG performance is thus becoming a decisive competitive and financing criterion: Investors, banks, and customers are demanding reliable data from companies on emissions, supply chain risks, and governance structures. This data is increasingly influencing ratings and financing conditions. Companies that invest now in structures, processes, and systems for strategic ESG management reduce their risk of sanctions, gain access to capital, and improve their position in tenders—and not only in the public sector.

Data architecture as the foundation of modern ESG management

The good news for you: sustainability and digitalization are not opposites, but mutual enablers. Without digital platforms, data pipelines, integration architectures, and analytics, supply chains, emissions, and social risks cannot be reliably managed. Conversely, sustainability, with its environmental, stakeholder, and impact perspectives, provides a clear regulatory framework for aligning your digitalization programs with resilience, efficiency, risk reduction, and new business models. If you understand ESG management as a data and platform issue, you create the basis for anchoring reporting, control, and innovation in a common data architecture.

A holistic ESG management approach is not based on the currently “loudest” regulation. Instead, you should build a consistent data and process basis across the relevant standards and requirements. Companies that have clearly defined and updated their key figures, data sources, and responsibilities can address new regulatory requirements primarily through configuration and mapping rather than through a constant stream of new ad hoc projects.

Three principles are central to your work:

• First, a “One ESG Data Backbone,” i.e., a central data model with clear governance that integrates financial and sustainability data and enables multiple uses.
• Second, the “beyond reporting” approach, in which valuable ESG data is used not only for disclosure requirements, but also for control processes, pricing, product development, and risk management.
• Third, thinking in terms of platforms rather than tools, i.e., building open, scalable IT architectures that can be used to flexibly connect primary data from new sources such as supplier data, IoT, satellite data, or AI-based estimation methods.

The real value of ESG data comes from the interaction of internal and external, structured and unstructured information. In addition to ERP and MES data, this includes certificates, audit reports, geodata, text information from supplier communications, third-party ratings, and industry-specific benchmarks. With the help of uniform data models, automated quality checks, and intelligent links, you can derive robust situation reports from this data. These form a stable basis for management decisions in crises, transformation, and investment planning.

Procurement, supply chain, and new business models as key ESG levers

The biggest data gaps in ESG management and supply chain compliance are often found at the beginning of the value chain, for example in raw materials, intermediate products, and technical equipment. Procurement thus becomes a key discipline in sustainability management: ESG requirements must be anchored in tenders, contracts, and supplier relationship management, including clear obligations for the provision, quality assurance, and updating of data. Data cooperation along the supply chain, for example in the form of joint platforms with suppliers, machine manufacturers, or logistics service providers, helps to meet EUDR, CSRD, and CSDDD requirements more efficiently. At the same time, this can establish data-based transparency for upcoming, far more comprehensive requirements, such as circular economy models.

Only on this basis can new business models such as product-as-a-service, take-back programs, or second-life concepts be implemented in a scalable and controllable manner.

If your company's core competence is not in the area of sustainability, you should not start with the goal of achieving a perfect ESG score. A clear, pragmatic roadmap for ESG and data management is more important and more effective.

Conclusion: Strategic ESG and data management instead of waiting for regulatory certainty

In our project practice, five steps have proven successful: First, we clarify materiality and the legal situation, i.e., we record the relevant ESG risks, opportunities, and regulatory obligations in a structured manner – especially with a view to 2026, when many new data-driven requirements will come into force. Second, we create a data map to identify existing systems, data sources, and gaps along the value chain. Third, we define an ESG data architecture that describes target visions for platforms, integrations, and governance and is designed to be technology-neutral and cloud-enabled. Fourth, we prioritize quick wins that reduce compliance risks, increase efficiency, and open up revenue potential. Fifth, drive scaling and automation, gradually roll out processes, responsibilities, and technical solutions, and enrich them with AI and analytics capabilities.

Our key message is this: in a rapidly changing ESG landscape, waiting for perfect regulatory texts or final deadlines is no longer a viable strategy. By establishing strategic ESG and data management with a stable ESG data backbone, integrated platforms, and cooperative supply chain approaches now, your company will regain its ability to act.

At the same time, adesso can help you develop an innovation agenda from the tedious reporting obligation with digital solutions for end-to-end data architectures, modern cloud, integration, and AI services. This allows you to systematically combine sustainability goals and economic success. Good luck!

Feel free to contact me if you have any questions on this topic.