Regulatory Trends in Sustainability Reporting: Aligning Sustainability Data Management, Technology Architecture, and Governance
With the transition from voluntary to mandatory, substantiated, and auditable disclosure of sustainability information, companies need to advance their sustainability reporting processes in the areas of data management, technology architecture, and governance.
by Thea Caminada, Alexandra Neuenschwander and Simone Schimmion
December 2024
Need for Change
Regulatory sustainability reporting requires companies to establish end-to-end data collection, management, and governance processes to align their sustainability reports with regulations. With the transition from voluntary to mandatory, substantiated, and auditable disclosure of sustainability information, data must be high-quality, well-governed, and third-party audited.
The effort associated with delivering sustainability reporting goes beyond the production of the final report. It involves several strategic decisions in data management, system readiness, governance, process design, roles and responsibilities. One of the challenges in sustainability data management and reporting is the evolving regulatory environment and short implementation timelines, while establishing a delivery model that organizes data sourcing, processing, and provisioning in an efficient and auditable manner from multiple and distributed internal and external data sources across the value chain and different teams and systems. In addition, as assurance requirements increase, it is expected that sustainability reporting will increasingly require similar skills and levels of scrutiny as financial reporting.
This article highlights key practices to consider when advancing your sustainability reporting processes, focusing on data management, technology architecture, and governance.
Data Management
To ensure effective and efficient reporting and steering, it is essential to define and agree on guiding principles, such as the data management approach, early in the implementation process. When defining the sustainability data management approach, consider factors like the overall company data strategy that can be leveraged and the sustainability data maturity in different functional and business units.
Depending on the overall company data strategy and sustainability data maturity, the sustainability data strategy can combine elements of both centralized and decentralized data management approaches. Decentralized, where data collection and data quality management are allocated to data owners in the functional and business units with the relevant expertise. Centralized, where a central governance team oversees the process to ensure controls are applied. This is combined with the implementation of an integrated platform consolidating sustainability data across various sources, streamlining data collection and reporting, and facilitating collaboration. Finally, shared sustainability data assets are established centrally ensuring uniformity, accuracy and consistency. This sets the foundation for efficient data management.
Technology Architecture
Leverage existing technology capabilities for sustainability reporting and use criteria-based tool selection and integration to close capability gaps. This approach ensures that the data and technology architecture remains fit-for-purpose, scalable, adaptable, and compliant with evolving standards and regulations.
A comprehensive sustainability reporting approach requires a robust data and technology architecture and solution design that supports efficient data integration and reporting in an auditable manner as well as scalability and adaptability. As sustainability standards and regulations evolve, a modular implementation approach enables companies to adapt their data and technology architecture without overhauling the entire system. This flexibility ensures that companies remain compliant and up to date with minimal disruption.
It is essential to clearly define all business needs for regulatory-driven sustainability reporting; considering for example the sustainability strategy and ambition, regulatory and reporting requirements, material issues, impacted departments, stakeholder expectations, and technology strategy. Designing an effective data and technology architecture requires a comprehensive assessment and understanding of business requirements. This involves considering the company’s existing data and technology capabilities, while also allowing for a criteria-based tool selection and integration to close identified capability gaps.
Beyond robust reporting, disclosure, and analysis functionalities, the ability to efficiently integrate, process, transform, and store both structured and unstructured data is crucial. These capabilities are complemented by strong compliance and auditability features offering limited or reasonable assurance, along with comprehensive data governance and security measures. At the same time, the system must support flexible adaption such as meeting new or changed regulatory requirements and scalability.
Data Governance
Aligned reporting processes and roles build the foundation for establishing ownership across different departments, ensuring audit readiness and enhancing sustainability reporting capabilities. Early involvement and commitment from all impacted stakeholders are critical success factors in the implementation process.
Sustainability data governance is set up to cover aspects such as roles and responsibilities, data quality standards and processes, and audit readiness. It should best leverage existing data governance standards within the company (e.g. financial reporting) and consider market best practices.
The transition from voluntary to mandatory, substantiated, and auditable information necessitates new or changed roles and responsibilities, which may require a fundamental shift in mindset. Once sustainability reporting requirements are collected, harmonizing data needs and defining data ownership is crucial. Early collaboration with key stakeholders is essential to determine and onboard current and future data owners responsible for providing relevant high-quality data.
Ensuring data quality in its key dimensions - completeness, accuracy, consistency, validity, integrity, and timeliness - is critical for reliable and substantiated sustainability information in regulatory reports. Effective data collection and management processes, including data validation, promote accountability, ownership, and commitment across the organization and help scale reporting in case of regulatory changes. A formalized control framework, with stringent risk and control measures tailored to sustainability reporting, ensures consistency and effectiveness. Audit readiness involves preparing for increasing audit requirements from limited to reasonable assurance for the relevant sustainability reports.
Need for Action
The regulatory trends in sustainability reporting require companies to act now. It is a key success factor to involve all relevant departments early on and to apply a holistic view covering data management, technology architecture and governance aspects not separately but as a whole.
Thea Caminada
is a Partner at BearingPoint, Switzerland, leading the service line Finance & Risk. With over 17 years of consulting experience, she specializes in Finance Transformation, finance-tech initiatives, and regulatory reporting. She has delivered end-to-end ESG/CSRD projects, covering regulatory requirements, data discovery, operating models, and reporting solutions. She is an accountant and controller by training and has worked for over 12 years in the functions of Amgen, Sulzer Chemtech, Swisscom and m-real.
Alexandra Neuenschwander
is a Senior Consultant at BearingPoint with expertise in ESG – Regulatory Reporting implementation and delivery, as well as overall project management. She has been assisting clients in the insurance sector with the implementation of agile Target Operating Models, organisational changes and getting ready for regulatory-driven ESG reporting including the publishing of first reports in the EU.
Simone Schimmion
is a Senior Manager at BearingPoint, Switzerland, responsible for regulatory and reporting initiatives with a focus on sustainability. She supported the development and implementation of BearingPoint’s firmwide aligned methodology framework to help clients navigate CSRD/ESRS regulatory reporting requirements. She has delivered multiple projects for international clients in the financial services industry from requirements and target operating model definition to implementation.