L-R: Mansoor, Marks, Goudarzi, Kosulko, and Thomas.

What are the concerns with data?

Several senior industry figures have said that ESG data siloes are almost unavoidable unless organisations have a dedicated strategy in place.

The complexity of effectively managing data was a big topic at last week’s ESG Investment Leader | Europe 2023 event, with speakers taking part in a panel called “Actioning ESG data through the operational and regulatory pipeline: How can strategies be improved?”. One conclusion was that the disconnect between data points and useable data points was improving – however, issues such as perpetually-changing regulatory benchmarks hindered this improvement. 

The discussion was moderated by David Thomas, Director of Infrastructure at GRESB, and included Salim Mansoor, Global Head of Investment Compliance, Alternatives, at Allianz Global Investors, Michael Marks, Head of Investment Stewardship & Responsible Investing Integration at Legal & General Investment Management (LGIM), Julia Kosulko, Operations and Sustainability Manager at Stockholm-based Infranode, and Aria Goudarzi, Head of ESG Data at Neuberger Berman. 

"The challenge is that there’s difficulty in [identifying pain points] at all. This is because

different parts of companies mean different data sets.”

The panellists were quick to list their pain points when asked where they struggled with providing ESG data. “On the private markets side, we had a complete lack of data up until a couple of years ago, but now it’s caught up,” said Mansoor.

He added that his work was almost completely in private markets. “Now the issue has become one of finding the exact granular data that we need. For instance, what metric exists that can show if a certain asset will have a positive contribution?” 

Marks, who oversaw portfolios that were more split between public and private, noted that he was seeing the same problem in public markets. “There, the challenge is that there’s some difficulty in [identifying pain points] at all. This is because different parts of companies – for example, those that are private versus public – mean different data sets.”

To combat this issue, he said that “narrowing down data points” was critical. 

Kosulko added that her company had an active ownership model, which involved sitting on boards as both majority and minority owners. Doing so, however, meant they had a governance issue related to the ESG data pain point angles. “What is the cycle of data generation? What are the key performance indicators (KPIs) for this company?” she asked. “That’s the sort of information I need.” 

As an investor, Kosulko said, she found that those questions were often the most difficult to answer, due to the fact that governance issues were so opaque and thorny to resolve. 

Managing consistency 

When the panellists were asked how issues around data duplication, inconsistency, and silos could be mitigated, they each had personal experiences to share – which highlighted just how widespread and far-reaching frustrations are.

“My biggest fear [at past employers] was if the office in Singapore and the office in London

reported two different sets of data that a client could see.”

“You need to centralise,” was Goudarzi's succinct answer. He said he was an advocate for the process after working at several multinational, multi-office organisations where duplication concerns had been prevalent – and caused further difficulties. “My biggest fear [at past employers] was if the office in Singapore and the office in London reported two different sets of data that a client could see, which would them make them concerned about us.”

Marks, also at a massive firm, said that managing size could be difficult and often prohibited quick fixes to silo and inconsistency issues. “We're big, so complexity and silos are hard to avoid. Different managers needed different things,” he said. “We're dealing with imperfections, and we have to embrace it. Some things are precise – for example, our board's gender diversity – and we can easily measure them, and some things aren't, like climate effects, and the models are often wrong.” 
 
Marks’s point also fed into a question from Thomas on what “data utopia” looked like. Many of the panellists were convinced it was a long way away – if possible, at all.

“The key questions are ‘what am I trying to achieve with the data and data flow?’ and ‘how do we act on it?’,” said Kosulko. “It comes back to the basics of what we're trying to trace,” she added. 

Mansoor said that the idea of ‘finding utopia’ via better data use was a misnomer. “It is investors who need to build procedures,” he said, adding that a root-cause approach would be more productive and result in more consistency and fewer silos. This practice needed to be ingrained in an organisation from the beginning and built upon as it grew in size and complexity – rather than the other way around.

Looking forward 

Ultimately, the panellists were all confident that more, higher quality ESG data was being produced. Historical sets were increasingly available, as were forward-looking models and projections.

"TNFD will be a nightmare for reporting companies, and I don't know how

investee companies will drive these issues forward."

The bigger issue was around shifting regulatory frameworks and differing reporting needs. Regulators wanted and asked for different things. “There are still issues,” said Marks. “Certain areas have no data, and standardisation is a problem.” 

He was expecting more difficulties down the road. “The Taskforce on Nature-related Financial Disclosures (TNFD) will be a nightmare for reporting companies, and I don't know how investee companies will drive these issues forward,” he added. 

Nevertheless, the panel was still convinced that, at the end of the day, more data was a good thing – and that, if mobilised correctly, it would eliminate some issues around reporting. 

 

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