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ESG Integration Hurdles, and Spreadsheets, Worry Data Experts

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Resourcing constraints and fragmented business practices are holding back companies from integrating ESG processes into their operations. They are also still relying on manual data management to meet their ESG obligations.

These findings, presented in a recent study of corporate ESG preparedness by KPMG, point to potentially dire consequences for financial institutions that use data reported by companies. Sustainability professionals raised concerns that such basic hurdles existed and arguing that overcoming them can be achieved with relative ease. They also stressed that solving them was necessary to enable investors’ to allocate capital to assets that will ease natural and social crises.

“Understandably, financial institutions struggle to effectively manage and scrutiniee data reported through such means as spreadsheets – this can undermine investor confidence and the credibility of ESG claims,” said Amanda Koefoed Simonsen and Christian Boserup, partners at Danish sustainability consultancy ESG Implementation. “Potentially inaccurate and incomplete data provided by reporting entities might unintentionally present a misleading picture of their environmental and social performance.

“For investors and asset managers, poor data management and data quality will affect the percentage of sustainability-backed assets under management and increase their risk of accusations of greenwashing and redwashing,” Simonsen and Boserup told ESG insight.

More Spending

The KPMG survey entitled “Addressing the Strategy Execution Gap in Sustainability Reporting” questioned 550 board members, executives and managers at mostly American and European public and private companies, two-thirds of which have revenues greater than $1 billion.

It found that 90 per cent of all financial institutions and corporates surveyed planned to increase spending on ESG capabilities in the next three years. The figure was a little higher at 91 per cent for the finance sector. Improving ESG data management and reporting capabilities was the single-most important objective, cited by 45 per cent of respondents.

Nevertheless, they also cited significant challenges in achieving their goals. The principle handicaps they cited were insufficient resources or capacity to collaborate effectively and the presence of “internal silos and limited communication between departments”.

It found that the finance sector is prioritising the adoption of advanced data tools “to replace the use of error-prone spreadsheets and enhance decision-making capabilities”. But the report highlights the continued difficulty financial institutions have in sourcing high-quality company-reported ESG data to use in their portfolio and risk-management processes.

That was most apparent in another datapoint that showed that while 83 per cent of companies interviewed thought they were “ahead of their peers regarding ESG reporting”, almost half admitted to still using spreadsheets to manage their data. John Carroll, chief operating officer at Datactics said manual data processes are ill-suited to meeting modern reporting needs.

“We’ve closely observed the implications of firms’ continued reliance on spreadsheets and an array of end user computing to manage ESG data, amid escalating global and European regulatory demands for sophisticated ESG reporting – this approach, while historically prevalent, falls short in addressing the complexity and scope of modern ESG frameworks,” Carroll told ESG Insight. “The nuanced requirements of new standards further evidence the need for a shift towards more advanced, integrated data management solutions that ensure accuracy, compliance, and transparency in ESG reporting.”

Data Management

Many financial institutions are assessing their ESG data management strategies as regulators place more reporting obligations on them and customers demand greater transparency into the ESG performance of their portfolios. The volume, variety and multiple use cases of ESG data makes it a more challenging domain to manage than financial and other conventional data types.

The pre-ingestion processes to which ESG data must be subjected to make it useable could be disrupted if it is handled within manual platforms such as spreadsheets.

“The fact that almost half of companies are still relying on spreadsheets for managing their ESG data underscores a significant challenge in master data management, thereby the reliability of ESG data,” Simonsen and Boserup said.

“This results in difficulties in validating and assuring how data are collected and validated. This limitation also makes it difficult to track historical data modifications – for example those caused by changes in definitions or undocumented corrections from external providers – leading to potential inaccuracies or the risk of unintentional data loss and resulting incompleteness and inaccuracy. When managing large datasets in spreadsheets, vulnerability to human error can further compromise the integrity of ESG reporting, affecting the reliability of the data provided to investors.”

Lost Edge

Reliance on manual technology exposes firms to competitive disadvantages compared with peers that have embraced digitalisation in their data management processes. They will also be outpaced in responsiveness and productivity, said Charles Radclyffe, chief executive of data management start-up EthicsAnswer, which uses artificial intelligence (AI), including GenerativeAI, to help companies report their ESG performances.

Radclyffe said AI was in an advanced stage of development and could be used to replace older systems as part of a comprehensive retooling of data management processes.

“Given that chief sustainability officers are all that stand in the way between us and devastating environmental change (not to mention the inevitable social unrest that comes from not attending to issues of social justice), surely there is some urgency for us to do better than using spreadsheets?,” he told ESG Insight.

Datactics’ Carroll, agreed, saying that transitioning away from legacy systems would enable the extraction of greater value from companies’ data.

“By advocating for and implementing robust data governance models and integrating ESG data into core processes, firms can not only mitigate the risks of greenwashing but also enhance their ESG reporting’s reliability and actionability,” he said. “This evolution is essential for firms aiming to lead in sustainability and transparency, ensuring their ESG practices robustly reflect their commitment to addressing global environmental and social challenges.”

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