At Clearyst, we’ve worked with companies across a number of industries from Retail & CPG to Manufacturing and Industrials. They’re each taking a vastly different approach to sustainability data depending on the sophistication of existing operations, the intricacies of their particular industry, as well as the accessibility and size of their budgets. Sometimes executives, including CEOs/CIOs/CSOs, are unaware of what useful data they have and how to access it. While companies attempt to improve efforts, they’re not able to manage what they can’t measure, or even collect in the first place.

In the first of this two-blog series, we’ll outline the importance of sustainability data, the challenges companies are facing, as well as some existing gaps we’ve observed in working with our prospects and customers.  

The Importance of Sustainability Data for Business Decision Making

Leaders, consumers, investors, and employees are demanding businesses increase focus on sustainability - expecting not just reports but genuine, measurable impact. Sustainability data isn’t merely a tool for compliance or reporting; it’s a strategic asset.

By leveraging this data in more ways than one, businesses can uncover opportunities for innovation, streamline operations, and strengthen trust with stakeholders. We call this approach “upcycling” sustainability data - taking data and transforming it into something with greater value. For example, instead of using data for one particular compliance report and then throwing it away, companies can leverage this data to generate additional insights, impact and value in other parts of the business.

Ultimately, it’s about turning responsibility into a competitive advantage.

So why isn’t everyone identifying and collecting sustainability? The simple answer - it’s hard.

Existing Challenges

Traditional data systems were designed to meet the operational needs of businesses, focusing on efficiency and performance rather than addressing the unique, multi-faceted challenges presented by sustainability efforts. As such, these legacy systems pose several innate challenges including:

• Availability - Many organizations lack the infrastructure or systems to capture and store sustainability-related data, especially when it comes to tracking information across complex supply chains or remote locations. Current methodologies rely on multiple versioned excel sheets, scanned PDFs, and sometimes even emails.
• Ever-Changing Data Quality - Much of the data relies on self-reporting, which can result in inaccuracies, inconsistencies, or even misrepresentation, making it difficult to ensure reliability.
• Standardization - With no universal standard for sustainability metrics, comparing, integrating, or aggregating data across industries, regions, or organizations becomes a major obstacle.
• Complexity - Sustainability spans a wide range of factors, from emissions and water usage to biodiversity impacts, demanding approaches that can handle these interconnected and intricate metrics.
• Changing Dynamics & Evolving Regulations - Sustainability is a moving target, as goals and metrics evolve alongside shifting regulations in various countries and regions, necessitating constant updates to data collection processes.

These systemic challenges underline the need for flexible, modern solutions capable of meeting the growing demands for transparency, accountability, and actionable insights in sustainability.

Identifying the Gaps

To prevent decision organizations from making decisions based on incomplete or unreliable information, it’s also essential to address the gaps in sustainability data. Here are actionable steps to uncover where the gaps lie in your data collection and reporting processes:

• Audit Your Data - Review what data you collect, where it’s from, and identify missing or duplicated information, especially in complex areas like supply chains.
• Engage Stakeholders - Collaborate with teams, suppliers, and customers to understand data-sharing practices and resolve barriers like privacy concerns. It’s a people and process problem as much as a technology problem.
• Use Technology - Using AI-based data cataloguing systems that enable integrations to manage the inherent challenges of real world sustainability data.
• Benchmark Metrics - Compare your data to industry standards such as GRI or CDP to spot inconsistencies or incomplete areas. Leverage dynamic benchmarks as data is generated to assess quality with feedback loops.
• Address Resource Needs - Identify gaps in tools, expertise, or funding. If resources are limited, consider external solutions or partnerships to bridge them.

By understanding where your sustainability data falls short, you can take actionable steps to address these issues. Comprehensive, reliable data is the backbone of informed decision-making, allowing your organization to track progress, build trust with stakeholders, and drive measurable impact toward sustainability goals.

Conclusion

Sustainability data has become a vital asset for businesses striving to meet growing demands from stakeholders and regulators while driving meaningful change. Despite the challenges of availability, quality, standardization, and complexity, addressing these issues is essential to unlocking the true value of sustainability efforts. By identifying and resolving data gaps, organizations can transform challenges into opportunities, leveraging accurate, comprehensive data to make informed decisions and create lasting impact. While creating and implementing a roadmap with the right tools, collaboration, and commitment may be complex, businesses can turn sustainability into a powerful strategic advantage — not just for compliance, but for innovation, trust, and long-term success.

Stay tuned for our second blog of this two-part series, where we will introduce solutions to these challenges and best practices for implementing a successful data strategy.