Accounting and financial reporting has been guided by regulations for nearly a century. Major crises like The Great Depression and the dot-com bubble have driven or reinforced the need for regulation and harmonization. All leading to stronger frameworks and standards.
Sustainability regulations don’t have the same long history as financial regulations; more like half a page compared to volumes. However, business leaders across Life Sciences and beyond are still required to produce reports and disclosures that can withstand stakeholder scrutiny. Why? Because stakeholders rely on this information to make decisions. As a result, ESG data demands the same level of rigor in governance as financial reporting.
So, how can Life Sciences companies ensure that their processes and governance frameworks deliver reliable and usable data?
Together with our Life Sciences clients, we have embarked on the journey toward robust and reliable ESG reporting, starting with a comprehensive gap assessment. This has allowed us to co-create a prioritized roadmap that includes our three dimensions for success; people, technology and processes.
In this blog, we’ll explore the necessity for processes, technology and adoption, and how our approach is the best way for Life Sciences to ensure they make informed decisions from their ESG data.
For several clients, we thoroughly reviewed and identified all processes where sustainability data is generated at source. Sustainability data is generated across all functions of an organization, and many of these processes are not part of the company’s core business. This makes it quite challenging to isolate.
In particular, for niche processes, we helped to achieve a higher level of established or widely adopted standards. Together with our clients’ process owners, we ensured the execution was more consistent across teams and systems. With often limited automation, we helped our clients put controls in place to mitigate the risk of manual errors; because we recognize that with new processes, you need new controls. Meanwhile, we addressed resistance to change and lingering legacy practices through dedicated change management practices, enabling teams to confidently embrace the new approach.
These process improvements were also mirrored in governance. We worked with our clients towards clear process definitions. If this is missed, assigning ownership becomes difficult, and governance often remains fragmented across departments and regions. Therefore, we paid close attention to addressing these issues. In some cases, sustainability data was not fully integrated into operational systems. This resulted in limited visibility in data quality issues. Even when controls existed, they tended to be reactive rather than proactive; and governance is often perceived as bureaucratic or as a barrier to innovation.
Successfully improving data quality was therefore a multifaceted challenge for our clients, but the efforts in successfully elevating it really paid off. Let’s take a look at the approach we used to get there.
Processes, data standards, governance, and controls all play a central role in ensuring that sustainability data is accurate, consistent, complete, and trustworthy. At the outset of our client engagements, we design an annual sustainability reporting process and handbook that embed these principles in a structured and repeatable way:
We know that consistency, quality, and efficiency don’t happen by accident. They come from well-designed processes. Standardized processes improve consistency and quality, increase efficiency, reduce costs, streamline training, and enable continuous improvement and compliance. Well-structured processes define how data is created, collected, transformed, stored, and used.
As a result, they generate reliable outcomes and help organizations meet customer expectations and regulatory requirements more effectively.
In a world of evolving regulations and a multitude of data sources, defining clear standards is essential. Just as accounting relies on a manual, sustainability reporting benefits from a dedicated reporting handbook. This document sets out timelines, reporting frequency, and organizational responsibilities while clearly defining each KPI, its strategic target, and measurement approach.
At a more granular level, data standards ensure comparability across systems, while defined calculation rules and methodologies provide a solid foundation for implementing tools such as sustainability data hubs, data management platforms, and cataloguing solutions.
Standards turn complexity into clarity, enabling data to drive meaningful decisions.
Good governance is the backbone of trustworthy data. By establishing clear structures, policies, and accountability, governance promotes transparency and responsible decision-making. In sustainability reporting, it ensures that data is timely, consistent, and reliable. These are the definitive hallmarks of compliance and stakeholder confidence.
Process owners, data owners, and stewards collaborate to establish policies and standards for data quality and lifecycle management, guided by principles such as FAIR (Findability, Accessibility, Interoperability, and Reuse). Technology, such as comprehensive data cataloguing tools, can amplify these efforts. Ultimately, this makes governance visible, actionable, and integrated across the organization.
Even the best processes and governance need robust controls to ensure their effectiveness. Controls monitor, enforce, and continuously improve data quality and timeliness. A simple and effective starting point is a reporting calendar. One that specifies what needs to be delivered, by whom, and when.
Beyond that, quality checks such as completeness, anomaly detection, and profiling can be used to generate a comprehensive data quality index. As sustainability reporting increasingly moves toward assurance, audit trails and structured remediation processes become essential. Effective controls transform reporting from a compliance exercise into a reliable tool for insight, decision-making, and strategic growth.
Altogether, governance, standards and controls ensure effective processes. In our holistic capability based approach, we map the dimension process and governance with the people aspect and with technology. That way executive sponsorship is ensured, technology is enabled when needed and people can work effectively, and build new skills as required.
Our clients’ investments in high-quality sustainability data have not only resulted in auditable reports but have also enabled them to use the data for informed decision-making. This has paved the path from mere reporting to performance optimization, growth, and ultimately greater value creation.
*The authors would like to thank Cal Loudon, Adviser at Tenthpin, for his support and insights that were critical in the writing of this article.