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ESG is not an environmental issue: it's a data sourcing and governance one

"The devil is in the detail – and the key to cracking it lurks in metadata."

The FT has referred to the ESG phenomenon as “one of the most powerful forces in markets at the moment”. ESG funds have attracted over $340 billion in just two short years. The concept of making money while sustainably doing good is not going away any time soon, nor should it. And yet it is causing widespread headaches when it comes to accurately measuring and comparing business’ legitimacy on this basis, writes Lorraine Waters, Chief Data Officer (CDO) at data lineage firm Solidatus.

The root issue is that there’s no universal metric or formula which can be applied to ESG. Organisations are still facing a wide-ranging set of different standards to match up against, not to mention variances in depth of detail required, depending on who is applying their own set of scoring and ratings criteria. There’s also then no clear roadmap on how to improve an ESG score. The devil is in the detail on this issue – and the key to cracking it also lies there, lurking in metadata.

Meeting the requirements of ESG marks a commitment to building a more sustainable organisation and ultimately a climate positive company. This leads to more investment and a competitive edge in a world where heavy penalties will be placed on businesses who do not meet rigorous ecological impact assessments. Step one is to turn this issue on its head. If no single standard applies universally, businesses have to start with what they do have already. They must recognise in the most minute detail what governance, processes and plans are already in place across their organisation which suit ESG principles.

See also: Climate risk data is a hot mess. These open source pioneers want to set things straight.

By mapping their own organisational structure first, it is much easier to then overlap different ESG ratings criteria and pinpoint where the organisation is doing well, or falls outside of a specific set of measures. This is a granular process that goes down to the metadata level within organisations to show how information passes from one hand to another. ESG initiatives cut across a company and require high-level control combined with an understanding of how data requirements intersect.

Looking to this level of detail causes another hurdle. These are large, highly complex and multifaceted organisations with hundreds of thousands of processes, tools and decisions made across a business on a daily basis. The only place to start therefore is the base layer of the organisation – this being the metadata layer which records what happens to information as it passes throughout an organisational structure, by who and in what order, and when. To tackle this requires the application of platforms which can trace and track how this information moves throughout an organisation, through which steps, under whose governance and what happens at each stage.

Data lineage platforms can map disclosures, ‘standards’ and regulations to the people with responsibility for them, as well as to company priorities and the data required to fulfil them. This presents a unified, end-to-end view, both for setting out how a company will deliver on its ESG aims, simultaneously tracking progress on filling data gaps. For example, highlighting how differences in disclosure recommendations for TCFD and WEF impact data required from suppliers and the scope of data for a company’s own disclosures.

See also: Goldman Sachs will add carbon accounting of client portfolios to its investing application.

By starting out at an organisation’s own data layer, it is much simpler to quickly and proactively assess compliance against requirements and standards, in order to demonstrate a company’s adherence to ethical practices. It also means that organisations can maintain a dynamic map of ESG initiatives that prevent a panicked and costly response to new regulatory demands that can disrupt day-to-day business, not to mention keep pace with the rapidly growing sets of standards and criteria in the market.

Taking this view of ESG means experts and owners of parts of the data landscape can contribute collaboratively, with all changes versioned for full change management and comparison. Our solution in particular even allows for experimentation on a linked snapshot of the current view, assessing the impact of making future changes as regulations inevitably evolve and as new data sources and organisations come online.

Moving beyond simple adherence to criteria and into taking proactive action on the true spirit of ESG implementation, this perspective for a business means they can contextualise their ESG initiatives, and design, view and track new ones. This process runs through company principles and priorities, through roles and responsibilities, choice of risk management and ESG assessment methods, to ESG disclosures, ESG ratings and to the supporting metrics and new data source requirements – but ultimately results in a business having ESG principles running through the organisation effectively like a stick of rock.

ESG is not primarily an environmental challenge for businesses. It is instead a data sourcing and governance challenge, requiring transparency and clear links to company objectives to drive it successfully. Dealing with changes in regulations and disclosures is going to be required for a few years to come. Investing in mapping and understanding data flows – and relating them to ESG priorities – will help companies make a positive impact, both with investors, customers and to the wider environment.

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