Driven by various regulatory frameworks, companies of all sizes may need to retool their approaches to data collection to meet compliance timelines in the most effective ways possible.
By Matthew Gardner
The onset of ever more detailed, increasingly complex ESG disclosure expectations has created an explosion in the sheer volume of data that must be collected and compiled by companies.
Driven by regulatory frameworks like the European Sustainability Reporting Standards (ESRS), Carbon Border Adjustment Mechanism (CBAM), Climate Disclosure Project (CDP), International Sustainability Standards Board (ISSB) and Science-Based Targets (SBTi), companies of all sizes may need to retool their approaches to data collection to meet compliance timelines in the most effective ways possible.
Technology is part of the answer
The software industry has developed increasingly sophisticated tools, including AI and other powerful modeling capabilities, to assist in ESG data collection efforts. Tools such as generative AI hold great promise to transform data collection as reporting requirements become more complex and cumbersome. Plug-in tools that simplify mundane tasks such as collecting utility data, for example, are already widely available and being utilized across the industry.
However, even the most sophisticated platforms can be stymied by imperfect human-powered processes. That can manifest in a lack of understanding of the data needs, the absence of clear instructions or guidance regarding expectations, data quality and timelines, or simply not having adequate time to address the requirements in a diligent manner.
Technology is a key part of the solution and could, one day, make human intervention less needed. But systems that operate completely independent of human intervention are not readily available to meet growing needs and demands from the ESG reporting community.
An inflection point: current capabilities vs. increasing demands
Despite the promise that novel technology platforms hold, the capabilities and price points for these solutions are not keeping up with the demand for increased reporting. There is no killer app on the market, and the demand for data is outstripping the capabilities of the current technology.
Calculating scope 1 and 2 emissions is conceptually straightforward. However, calculating scope 3 emissions is another question altogether and requires large amounts of data to be collected from partners who might not be prepared to provide it.
Companies also face challenges to navigate compliance with the EU’s Corporate Sustainability Reporting Directive (CSRD) and the underlying ESRS ruleset.
After completing the required “double materiality” assessment, companies then need to determine which of the hundreds of disclosures they must provide in their sustainability statements. For U.S.-based companies that participate in global supply chains, it is essential that they understand the implications of these rules and take the first steps to assess and implement effective data collection systems.
Do not neglect the human equation
Technology platforms require significant investment — tens of thousands to hundreds of thousands of dollars or more. While large Fortune 500 companies can justify this expense, it is more difficult for small- and medium-sized manufacturers and organizations to absorb this cost.
Equal investment, at least in time and effort, is required to ensure that the people feeding data to the platforms are well versed in the objectives and strategies.
Therefore, it is important that companies do not neglect the human-powered processes to design, deploy, and maintain an effective ESG data collection and reporting. Simple tools such as Excel spreadsheets have been used to great effect — especially when the people using them are familiar with them, understand the expectations, and are aligned on the process and data quality requirements.
Three steps for success
As companies and ESG teams attempt to balance growing disclosure demands with emerging new data collection tools, here are three points of guidance as it relates to evaluating and integrating new platforms:
- Assess & leverage existing data sets – It is essential that information on material ESG risks and opportunities is rigorous and supported by verifiable data, so auditors can confidently sort through the glut of information. Before making significant investments in new platforms, companies must accurately assess and fully leverage existing data sets from other enterprise systems while evaluating interoperability needs and challenges.
- Select scalable solutions – Data collection systems must have the ability to scale, if they are going to keep pace with a growing company’s disclosure needs, especially as it relates to scope 3 emissions or reporting impacts of their global supply chain. Companies should evaluate solutions with scalability in mind and select a platform that supports their data collection needs today with the flexibility to meet future reporting demands.
- Invest equally in people – Companies must balance significant investments in new technology with equal investment in the people and processes behind the platforms. This ensures the people using the technology are up to speed and knowledgeable on the latest systems. Today and in the future, companies should co-invest in training and internal team development as much as invest in solutions.
There is no one-size-fits-all technology platform on the market today. Whether a company is using a sophisticated, top-shelf system or relying on more manual processes, it is of equal importance that they invest in the human aspect of ESG.
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