How far has your company come in moving towards a more sustainable future and equality? While you are busy finding the reply to this question, we bet that as an executive, you feel deeply concerned about the ESG (environmental, social, and governmental) risks, namely ESG data management.
Since adhering to sustainability standards became a business imperative, global corporations and privately owned companies started to prioritize ESG compliance and reporting, challenging executives with approaches to ESG data governance and transparency.
As of 2022, 60% of CEOs reported feeling pressure to be more transparent about their organization’s sustainability performance. If this pressure is falling down on you as well, we would like you to rest assured: you are not alone.
In this blog, we’ve prepared an informative roadmap that sheds light on ESG data management and contains practitioners’ tips based on collaboration with industry leaders.
Understanding ESG data management
While diversity, equality, and inclusion (DEI) have always been important for world-renowned companies, the past few years have cemented the significance of sustainability and ethical practices in business operations across organizations of different scales and maturity.
Being deeply concerned about climate change, social responsibility, and corporate governance, global authorities are introducing increasingly stringent ESG reporting requirements and standards. Along with the growing pressure falling down on business executives, these requirements have faced organizations with the need to adapt their IT systems to systematically collect, aggregate, and report on a broad range of ESG data.
Collecting ESG data: motives and sources
During one of their round table sessions on the challenges and opportunities of ESG data management, Deloitte practitioners highlighted three motives that drive the current need for data management:
- Laws and regulations
- ESG strategy
- Financial requirements
If we take a deeper dive into each of the motives, it becomes clear that the ESG data definition encompasses the whole variety of sustainability-related data collected from both inside and outside an organization. These include the standards per se, data collected from the company’s teams and departments, stakeholder requirements, external reports provided by rating agencies and specialist bureaus.
Although aligning the requirements with the information coming from distributed sources often becomes the most complex of all ESG data issues, there are more roadblocks companies face on their way to sustainability.
Challenges of ESG data management
The ESG concept is still relatively fresh. While the first equality and environmental concerns date back to 1970-1990s, the requirements continue to evolve as the understanding of sustainability and responsible business practices deepens. New frameworks, standards, and reporting guidelines emerge as stakeholders demand greater transparency and accountability.
This volatility is a real challenge for modern organizations, as they need to constantly adapt their strategies and find new approaches to ESG data management.
- The inconsistency of ESG data standards. ESG guidelines and reporting frameworks vary between regions, industries, and organizations. This diversity makes it challenging for companies to determine which specific metrics and disclosures are relevant to their operations and stakeholders. As a result, organizations may find themselves grappling with the dilemma of choosing among multiple frameworks, leading to inconsistent data collection and reporting practices.
- Difficulties in ESG data sharing. Often concerned about privacy, stakeholders hesitate to share their ESG data, as others might be using it to gain a competitive edge. As a result, the ecosystem does not fully harness the potential of the wealth of information at hand. Moreover, the presence of privacy laws, such as GDPR, adds an additional layer of complexity to data sharing.
- Complicated in-house coordination. Modern data ecosystems still lack standardization—collected data is often stored in different formats and is not synchronized. This not only prevents investors from getting a realistic picture of ESG initiatives within an organization but complicates progress tracking and reporting, bringing companies a leap behind efficient ESG data management.
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What makes a successful ESG data management strategy
Data management is the core task in achieving ESG regulatory compliance. If we decompose the latter into milestones, we’ll see that data is playing the first cast.
As you see, ESG data management is a systematic process of collection, validation, reporting, analysis, and engagement to meet stakeholder expectations and contribute to sustainability goals. Here is what this process usually entails according to the data analytics best practices.
- Data collection. Gathering relevant data from internal and external sources, including financial records, operational metrics, and third-party providers.
- Standardization. Ensuring data is structured and formatted consistently to enable meaningful comparisons and analysis.
- Validation. Verifying the accuracy and completeness of data to minimize errors and inaccuracies.
- Integration. Combining data from different sources and departments to create a comprehensive ESG dataset.
- Reporting. Preparing regular ESG reports and disclosures, often following standardized frameworks like GRI or TCFD.
- Analysis. Using data analytics tools to derive insights, identify trends, and measure performance against ESG goals.
- Stakeholder engagement. Engaging with investors, regulators, customers, and other stakeholders to understand their ESG concerns and priorities.
- Compliance. Ensuring compliance with relevant ESG regulations and standards, adapting to changes as they arise.
- Risk management. Identifying and mitigating ESG-related risks to protect the company's reputation and financial stability.
- Strategic planning. Incorporating ESG insights into long-term business strategies to drive sustainability and value creation
- Continuous improvement. Continually assessing and refining ESG data management processes to enhance transparency and accountability.
While analytics plays a pivotal role in ensuring consistent ESG data management, in reality, the process dramatically depends on people who are responsible for ESG initiatives within a company. That’s why closing the data management loop requires implementing a user-centered approach to sustainability compliance and reporting.
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ESG data management tips and best practices
So, the key to successful ESG data management lies in both the realm of data analytics and experience design. In this paradigm, data science runs under the hood of a data management ecosystem, while ESG BI and visibility practices reshape the process by ensuring transparent access and intuitive use of ESG data.
Here are some consistent principles that build up a solid ESG data management foundation and encompass both the analytical and visibility parts of the process.
- Ensure easy access to ESG data. Once building a strong data governance strategy and getting a steady flow of relevant data, make sure dedicated users can get instant access to it through intuitive user flows and easy navigation patterns.
- Build data integrity. In line with data collection, validation, and systematization, think of creating a common look and feel for your ESG data management platform. This way you can enhance the experience users are getting from interactions with ESG data and streamline operations.
- Establish transparency and trust. Make sure your teams are getting relevant up-to-date information they can further use for ESG compliance and reporting. Develop comprehensive data views while ensuring real-time updates and concise data representation throughout the system.
- Embed scalability by design. Build a reliable infrastructure and make sure your data processes and design system are scalable enough to support you in the future when the requirements and data volumes transform and grow and new user roles appear.
- Enable intuitive data sharing and reporting. While setting up integrations with dedicated BI and analytics systems, develop a consistent digital experience that would allow for easy data export and sharing. This will streamline data management activities for your team and give you a strong competitive advantage.
At Trinetix, we’ve always considered sustainability as paramount in both our corporate practices and the digital partnerships we’ve been through. When it comes to efficient ESG data management, we’ve got a real success story to share.
When integrating sustainability management and reporting became an aim of our Fortune 500 client, we brought in our best technical talent to develop an innovative user-facing impact measurement framework that would help the client pivot ESG initiatives from scratch.
- Created a digital concept that encompasses the whole variety of global ESG regulations and allows for mapping specific sustainability goals to relevant standards
- Developed comprehensive checklists with core milestones to enable 360-degree visibility into sustainability compliance
- Introduced comprehensive progress dashboards with status tracking and export capabilities to simplify the ESG regulatory reporting process
As a result, our client not only managed to prioritize ESG compliance and data management but also unlocked a new revenue stream and became recognized for bringing innovation into ESG data management.
Want to learn the full story of our Fortune 500 client?
Inefficient data management can become a major roadblock for both growing organizations and mature enterprises that make use of ESG initiatives. Just like any other business endeavor, achieving sustainability requires a deep understanding of a company’s operations and business objectives.
For more than 12 years in business, we at Trinetix have helped world-renowned companies leverage a strategic approach to innovation and achieve sustainable growth. If you also aim to build an actionable ESG strategy that keeps your business priorities first – let’s chat!