Why data management matters in meeting ESG targets - some organizational tips

Although having the relevant data to hand is crucial if organizations are to hit their ESG [Environmental, Social and Governance] goals, it appears that all too few have put the basic foundations in place to make the vision a reality.

ESG-related data is important not just for complying with, and reporting against, the growing number of standards in the area, which include the European Union’s Corporate Sustainability Reporting Directive. It is also vital if companies are to successfully track, measure and manage the impact and progress of their ESG projects. Hilda Davies, Senior Manager of Data Science, Data Engineering and Performance at data-as-a-service provider Snowflake, explains:

ESG is massively complex and continuously evolving. Therefore, using data as a guiding principle is very useful. Without it, it would be near impossible to quantify the impact of an ESG initiative and determine whether it has been effective or not. Data is a critical tool for organizations to understand and improve their ESG performance and has numerous applications beyond just reporting.

Such applications include identifying and creating potential new revenue streams. As Davies says:

Having the right data will inform organizations where they should invest in terms of product development or improvement, with the goal of creating products that are sustainable, socially responsible and aligned with stakeholders’ and investors’ values.

But data also has an important role to play in helping businesses understand the ESG risks they face. John Booth is vice chair of the Green IT specialist group for BCS, the UK’s Chartered Institute for IT. As he points out:

An ESG framework allows stakeholders to assess all risks relating to an organisation and, as such, absolutely needs the data to be credible. In my opinion, it’s impossible to undertake ESG reporting without data. Without data to support organisational statements or initiatives, any statement can be considered 'greenwash', or 'ESG-wash', and leaves you open to reputational risk or worse.

What is ESG data?

As to what ESG data comprises, there are two key elements. The first is common to all businesses and includes greenhouse gas emissions, energy and water usage, waste generation and management, human rights, labour practices and board diversity.

The second component is influenced by the regulatory landscape, which differs based on industry and geography, as well as the individual initiatives and goals organizations have set for themselves. While most of this data will be located internally, some will need to be collected from third parties, such as supply chain partners. But as Davies observes:

When it comes to third parties, it’s crucial organizations take a complete view of their entire supply chain and understand what ESG initiatives they have in place. For example, does their supplier several links down the chain use anti-environmental practices? Not many companies today have this level of visibility but, without it, reporting will always be incomplete and open to questions.

Data gathering brings other challenges too, says David Duffy, Chief Executive and Co-Founder of the Corporate Governance Institute:

You need to be very clear and specific when talking about data collection in different industries. For example, many organizations are trying to become carbon-neutral by 2040. But for that to happen, it’s important to understand what data must be collected to show you’re on the path, who will collect it and how, how it will flow through the organization and what systems support is required. Also how do you ensure your data’s timely? What you don’t want is a mix of data, some of it two years old and some of it a year old as you won’t be comparing like with like.

What to do with your ESG data

Another problem is simply the sheer quantity of (often inconsistent) data most businesses generate, which means having to decide what is relevant or not in an ESG context and how best to fill any remaining gaps. As Davies says:

The effort to tackle ESG data has been ongoing for many years, and a lot of progress has been made. But there’s still a long way to go when it comes to standardisation, transparency and the quality and availability of ESG data, and having consistent reporting frameworks and metrics in place. Because of this, many organizations face difficulties in collecting and analysing their data and measuring how they compare against their counterparts.

To address at least part of this scenario would require more standardization in terms of data definitions, formats and reporting frameworks, she adds – although if businesses were to collaborate with industry peers, stakeholders and supply chain partners to this end, it could make a real difference.

A further challenge many organizations experience, meanwhile, is integrating their ESG data into their business processes and systems. This already difficult requirement is not helped by the fact that all too few accounting and ERP systems currently include adequate levels of ESG support in their software, no matter what their marketing brochures say.

Moreover, unlike the world of financial accounting where businesses have access to auditors to verify their activities and ensure it complies with the law, the same is not true in an ESG context. The problem is this makes it impossible to gauge whether the “ESG information you’re getting is giving a true and fair view”, Duffy says. Put another way:

The foundational stuff isn’t in place. What we’re seeing now is finance functions trying to help out on the ESG side by putting in data definitions and systems and working out how to collect data and report on it. They have a professional background in doing this that ESG functions don’t as they’re often just one or two years old.

The importance of people

But yet another issue here is simply a lack of available ESG-related skills. As Duffy explains:

ESG and sustainability is an evolving and new topic, so there aren’t that many practitioners with the skills around. Hence pricing for these services is high at present, although automated tools and perhaps Digital Product Passports will make the process easier.

Bearing these considerations in mind, Pat McCarthy, Chief Revenue Officer at data integrity tools provider Precisely, is adamant that taking an enterprise-wide approach to ESG data management is the only way forward. This approach requires a board-level executive to take responsibility for oversight of the entire process rather than delegating it to a junior manager armed with an Excel spreadsheet. As he points out:

The idea that ESG is an island isn’t how you should think about it. It should be integrated into your operations to make it sustainable and deliver value. For example, if you can make ESG part of the operational fabric, it’s easier to figure out whether you want to buy skills in or build your own to create a core competency. Also these should be board-level initiatives that are funded properly and broad. Often people just treat them as one-off events that they simply repeat if necessary. It’s a rare few that operationalize things and built them into the fabric of how they run the business.

Operationalizing ESG data

As to how businesses can operationalize ESG, it all comes down to taking a strategic view of the issue, McCarthy says:

It’s important to think about, ‘What problem am I solving?’ and ‘What is my destination?’ as ESG covers all your business processes. You also have to think about your data strategy and what fits into that, so ‘what data, master data and tools do I need to ensure data integrity?’ If you’re a large multinational, doing everything perfectly all at once is impossible, so start small but design for scale. For too long, this has been done in Excel, which isn’t enough to understand data lineages, the update cycle and where and how data is used. Once you do, establish this as a baseline for how data is gathered and curated. It’s important as the C-Suite has to sign off on this, so they’ll want to know where the data comes from etc.

Useful technology to help in this context includes data analytics to monitor, measure and report on ESG performance and trends and AI systems to identify risks, opportunities and develop accurate metrics. As Davies points out:

The importance of ESG data is only set to grow in future, with the ESG data products market expected to grow 45% year-on-year.  With this, there will be a standardization of regulations and reporting frameworks, such as the Global Reporting Initiative  and Task Force on Climate-related Financial Disclosures.  Frameworks such as these will be key in enabling companies to take control of their ESG initiatives and report on their efforts in a consistent and comparable way.

My take

It certainly seems there is a long way to go at every level in getting ESG data management right – despite the pivotal role data plays in enabling organizations to hit their ESG goals. A lack of clear, standardized guidelines and tried and tested expertise appear to be key challenges at a time when regulatory pressure is mounting. While emerging technology in this space will inevitably help somewhat, it is unlikely to be a panacea. All of which means these are likely to be testing times ahead for many businesses as they learn often by trial and error.