Overcoming the ESG data challenge for the common good

This is a guest blogpost by Greg Hanson, VP of EMEA and LATAM, Informatica

Compliance with environmental, social, and governance (ESG) regulations is a necessity in today’s world. ESG policies are designed to ensure businesses are serving the common good as well as their own bottom line. However, while issues around sustainability, ecological impact, and equal opportunity have been high on boards’ agenda for years, that doesn’t mean ESG compliance is easy. Far from it.

ESG: a huge data management problem

Reporting to regulators on ESG means collating and analysing non-financial data – on areas as diverse as water usage, greenhouse gas emissions, or employee experience. For most companies, that data is likely to be much less well-managed, accurate, and thorough than the data they hold on profit and loss, customer service, or warehousing.

To add to that challenge, large, multi-national conglomerates will need to bring together ESG figures from different subsidiaries, legal entities, offices, and suppliers, all of which rely on different tools or data sets. This level of corporate consolidation is a complex process that takes a lot of manual effort for most companies.

Finally, new layers of ESG reporting are being steadily introduced. For example, from January 2024, any organisation that deals in Europe and has more than 400 employees or £40m in turnover will have to comply with the EU’s new Corporate Sustainability Reporting Directive (CSRD).

This regulation affects over 50,000 businesses and means they don’t just have to report on their own operations, but also the carbon emissions of their entire supply chain. For large enterprises, for example Proctor & Gamble or Unilever that have over 50,000 external suppliers, gathering the requisite data is a massive job. And the requirements are only going to get more complex. Organisations don’t want that challenge to be met by a whole series of fragmented technologies and tools. Yet, our recent survey of 600 global executives revealed 50% will use five or more tools to support data management priorities in 2023.

As ESG reporting standards evolve, organisations will increasingly need a single data management platform that offers synergy and simplicity. One that offers the ability to integrate data from multiple points and use powerful Artificial Intelligence (AI) and Machine Learning (ML) principles to simplify reporting and give organisations confidence in the ESG figures they provide.

Steps to successful ESG data management

It’s clear that ESG reporting is a huge data management challenge. The first thing to address is the use of manual processes. Automating processes with technology should be a priority. Especially where suppliers are involved. A self-serve model, where data collection from suppliers is automated and data quality rules are applied from the outset means organisations can be confident in the completeness of the data. It also allows businesses to build intelligence and question or challenge high ESG values, gaining insight into where supply chains or business operations can be decarbonised. Increasingly, this insight will be used to drive the supplier relationship and companies are more likely to select those partners that have a strong sustainability record.

The second is avoiding shortcuts. Taking ownership and full control of data is the only way organisations can prevent inaccurate reporting. Scanning an organisation’s own data assets provides a rich archive of ESG data. Something that is powerful in facilitating compliance and reporting but also identifying gaps or queries that the chief sustainability officer might want to make.

Third, you need to identify where you want to make a difference with ESG practices. That then shapes your action plan and defines the data that needs to be collected and brought under governance. Collecting and integrating this data in a central ESG data lake or lakehouse is the final step. It is vital that organisations create a single, structured view of the relevant data, to ensure a single source of truth for reporting with the ability to facilitate ad hoc queries and requests on demand.

Getting ESG right

ESG compliance has the potential to be a major headache. And it can create considerable problems and cost. But – and it’s an important but – it can also drive significant value for your organisation.

In the world of business-to-consumer sales, ESG is already influencing buyer behaviour in a big way. People want to deal with companies with proven sustainability credentials. They want to know that their online shopping spree hasn’t added an extra ton of CO2 to the atmosphere or contributed to the oppression of vulnerable workers. According to McKinsey, products that can make substantiated ESG claims averaged 28 per cent cumulative growth over the past five years, compared to only 20 percent for products that make no such claims. So, for B2C companies, the benefit of compliance can be seen in the bottom line.

It’s also important to remember that the scope of reporting responsibility goes right up to the top of a company – to the Chief Sustainability Officer (CSO), the Chief Data Officer (CDO) and in some cases the Chief Financial Officer (CFO) and Chief Executive Officer (CEO). This person will be held to account for ESG figures and need proof that data is accurate and justifiable. Just as a CFO or Chief Risk Officer (CRO) would never risk using financial figures they were unsure about; the same level of auditability and traceability will need to be applied to ESG. Getting the data right is non-negotiable.

It’s not a straightforward process, but it’s well worth getting the data work behind ESG reporting right. Not just from the point of view of pleasing the regulator or improving your impact on those around you, but also for the health and growth of your business.

Data Center
Data Management