Reliable ESG Data Collection: People Are as Important as Technology

As ESG disclosure requirements become increasingly detailed and complex, the volume of data that companies need to collect and organize is growing exponentially. This trend is driven by multiple regulatory frameworks, including the European Sustainability Reporting Standards (ESRS), the Carbon Border Adjustment Mechanism (CBAM), the Climate Disclosure Project (CDP), the International Sustainability Standards Board (ISSB), and the Science Based Targets initiative (SBTi). Companies of all sizes may need to adjust their data collection methods to meet compliance timelines in the most efficient way.

Technology is only part of the answer

The software industry has developed increasingly sophisticated tools, including artificial intelligence and other powerful modeling capabilities, to assist with ESG data collection. Tools such as generative AI have the potential to revolutionize data collection at a time when reporting requirements are becoming more complex and burdensome. For example, plug-in tools that streamline routine tasks such as utility data collection are already widely available and are being used across the industry.

However, even the most advanced platforms can be hampered by imperfect manual processes. This can manifest as a lack of understanding of data requirements, a lack of clear instructions or guidance on expectations, data quality, and timelines, or simply not having enough time to seriously address these requirements.

Technology is a key part of the solution and may one day reduce the need for human intervention. But systems that are completely free of human intervention are not yet readily available to meet the growing demands of the ESG reporting community.

The inflection point: current capabilities versus growing demands

Despite the promise of new technology platforms, the capabilities and price points of these solutions have not kept pace with the growth in reporting demands. There is no "killer app" on the market, and data requirements are outpacing the capabilities of current technology.

Calculating Scope 1 and Scope 2 emissions is conceptually straightforward. However, calculating Scope 3 emissions is an entirely different matter, requiring the collection of large amounts of data from partners who may not yet be ready to provide it.

Companies also face the challenge of complying with the EU's Corporate Sustainability Reporting Directive (CSRD) and its underlying ESRS rule set. After completing the necessary "double materiality" assessment, companies need to determine which of the hundreds of disclosures must be included in their sustainability statements. For U.S. companies involved in global supply chains, it is crucial to understand the implications of these rules and take initial steps to assess and implement effective data collection systems.

Don't overlook the human factor

Technology platforms require significant investment—ranging from tens of thousands to hundreds of thousands of dollars or more. While large Fortune 500 companies can afford this expense, small and medium-sized manufacturers and organizations find it harder to absorb these costs.

Equally important, at least in terms of time and effort, is ensuring that the people supplying data to the platform fully understand the goals and strategies. Therefore, companies should not neglect the human processes involved in designing, deploying, and maintaining effective ESG data collection and reporting. Simple tools such as Excel spreadsheets have been used effectively—especially when the people using them are familiar with these tools, understand expectations, and are aligned on process and data quality requirements.

Three steps to success

When evaluating and integrating new platforms, here are three guiding recommendations for companies and ESG teams:

1. Assess and leverage existing data sets – Information on material ESG risks and opportunities must be rigorous and supported by verifiable data so that auditors can confidently sift through large amounts of information. Before investing in new platforms, companies must accurately assess and fully leverage existing data sets in other corporate systems, while also evaluating the needs and challenges of interoperability.
2. Choose scalable solutions – Data collection systems must have the ability to scale in order to keep pace with the disclosure needs of growing companies, especially in terms of Scope 3 emissions or global supply chain reporting impacts. Companies should evaluate solutions that are scalable and choose platforms that can meet both current data collection needs and flexibly adapt to future reporting requirements.
3. Invest equally in people – Companies must balance significant investments in new technology with equal investments in the people and processes behind the platform. This ensures that those using the technology can keep up with the latest systems and remain knowledgeable. Now and in the future, companies should invest jointly in training and internal team development just as much as they invest in solutions.

There is no one-size-fits-all technology platform on the market today. Whether companies use sophisticated top-tier systems or rely on more manual processes, it is equally important to invest in the human side of ESG.

Despite the great potential of these platforms now and in the future, ESG literacy must be placed at the forefront of data collection and reporting. As technology rapidly emerges in response to new reporting requirements, employees need to understand not only the importance of the company's ESG strategy, but also how their own roles fit into it, and the specific metrics that need to be tracked.