5 key challenges for the CSRD implementation initiatives and how to overcome them

The Corporate Sustainability Reporting Directive (CSRD) is more than just a regulatory mandate; it has started a profound corporate movement putting ESG at the core of many ongoing initiatives and on top of corporate executives’ agendas.

As the clock ticks down to compliance deadlines, companies (in Europe but also in Switzerland with exposure to the European market) are grappling with a complex web of challenges. The question is no longer whether to embrace the CSRD, but rather how quickly and effectively adapt to the new reality. Based on our client work, below is a selection of key challenges current CSRD implementation initiatives face and a few ideas on how to overcome them.

1) Regulatory / interpretation challenge

The CSRD represents a significate interpretive challenge for businesses. The directive leaves sometimes room for interpretation and especially for highly diversified businesses the application requires some interpretive work. Both can lead to inconsistencies in reporting and potential regulatory risks.

Overcoming this challenge requires a multi-faceted approach. Collection and elicitation of requirements combined with CSRD trainings are important first steps to establish the baseline. Second, engagement with experts, industry peers and professional associations can provide valuable insights and best practices. Ultimately, selecting the right assurance provider is critical.

2) Organisational challenge

The CSRD mandates a substantial shift in how operations collect, curate and report ESG related information. This requires a comprehensive review of internal structures, processes, roles, responsibilities and culture. Many organisations struggle to integrate the ESG function into their current operating model.

Overcoming this challenge demands the setup of the ESG operating model that should establish clear roles and responsibilities, e.g. ESG data owners, ESG data stewards, business analysts, controllers etc. The new operating model should also address the collaboration with the finance function (e.g. ESG being inside or outside of the finance function) and other data domains (e.g. P&O, operations, procurement). The involvement of operations and business can be addressed by reinforcing the role of data owners and data stewards.

Additionally, fostering a culture of sustainability across the organization is of paramount importance. By empowering the employees to contribute to sustainability goals, organisations can drive innovation and increase value from the ESG. Developing tailored learning & development plans and investing in upskilling and training of the employees is the first step to initiate the cultural change.

3) Data challenge

The CSRD presents a colossal data challenge. Companies must collect, verify, and analyze vast quantities of ESG data, often from disparate sources. This data deluge can be overwhelming, especially for organizations with complex supply chains. In order to successfully manage and report ESG data, you first need to build the right data foundation by effectively collecting, integrating, and delivering trusted data into your environment. Once you have done that, you should leverage AI-powered analytics to take that trusted data and turn it into insights and action – generating visualisations and predictions and providing interactive and fast answers to benefit not just your reporting efforts but for benefit of your overall business.

Overcoming this hurdle to build business value requires a solid data strategy. Investments in data quality process, data control environment and tooling are essential. Also, automation, low-code and robotic process automation can help streamline data collection and data curation. Building strong relationships with suppliers and other control functions within the organisation to improve data sharing is also crucial. 

4) Technology challenge

Technology is fundamental to secure a successful CSRD implementation. Investments are required in robust technological solutions to collect, curate, analyse and report ESG data. Reviewing the technology architecture and determining the ESG data platform (centralized or decentralized) are the first steps. Challenges in this area usually include data integration, quality assurance, complexity with geographical distribution and vendor resp. tool consolidation.

Overcoming these hurdles requires a strong collaboration between the data management and technology functions. Organisations should prioritize implementation and consolidation of data management platforms, specialized ESG reporting software and data analytics tools. Additionally, fostering data-driven culture (e.g. self-services, data democratization) and cybersecurity are of essence.

5) Time challenge

The CSRD is imposing tight deadlines on companies, leaving little room for error. Collecting, analysing, and reporting on a vast array of ESG data within these constraints is a monumental challenge. From data collection to assurance, every process step is time-consuming and involves many resources.

To overcome this, organisations should prioritize and streamline their efforts. Building a solid roadmap with a clear and honest view on the deliverables, their timeline and key risks is a fundamental tool to manage the CSRD implementation initiative. The roadmap should ideally include quick wins (by leveraging automation), risk remediation actions, management of the technical debt as well as organizational and culture-related initiatives. Building a dedicated CSRD team with the necessary expertise can also accelerate the process. Crucially, early planning and preparation are essential to avoid last-minute rushes.

Summary

Finally, driving CSRD implementation initiatives requires integrated approach and delicate planning. We recommend appointing a fully committed ESG team to define the scope of the CSRD implementation initiative and drive its implementation. The roadmap is the key management tool to communicate expectations, show dependencies and ask for help from important stakeholders. Data strategy and clear alignment with the technology architecture are key success factors for a smooth and timely delivery.