The pursuit of the perfect data set seems to be the new obsession of the ESG industry. I have the unenviable task of helping our investment and product teams navigate new sustainability regulations. The standards are tough, as they should be. They require evidence, again, no issues here. And they require data. Sounds good, right?
Therein lies the challenge. Generally speaking, investors like measurability, comparability and clean audited data which looks the same, acts the same and can be neatly benchmarked and tracked over time. Sustainability data has none of these features (except maybe carbon). Sustainability is complex, nuanced and ever-changing. Case in point: the EU has been debating the definitions and measurement of ‘green’ and ‘sustainable’ for years now and after that exercise, no one is the wiser.
The International Sustainability Standards Board (ISSB) is aiming to bring more consistency to sustainability data globally, but its main focus is on measuring sustainability risk (i.e. the impact that a sustainability issue may have on company financial performance), not on measuring sustainability outcomes (the impact the company has on the real world).
Objectively measuring a sustainability outcome and doing it in a robust, evidencable and credible way is difficult. It is even more difficult doing it at a portfolio level where investments sit across multiple companies, sectors and countries. The sustainability data that is relevant to an investment decision quite rightly differs by asset class, company, industry and geography. In many cases the data doesn’t exist (the age-old and somewhat tired complaint of sustainable investors!).
Measuring sustainability outcomes is also difficult because a single data point only gives you part of the picture of whether a company is sustainable or not. For example, a company could be great on carbon or be creating market-leading drugs that save lives but perform below average on gender diversity. Are they a sustainable company? If you rely solely on data to answer this question, you will inevitably get it wrong.
See also: FSC stocktake shows biodiversity data and modelling challenges
For fixed income investors, getting your hands on good quality data and drawing conclusions from it is even more challenging and the nuance is even more pronounced. Take Bazalgette Finance for example: a bond that funds the construction of the ‘super sewer’ under the Thames River. If you relied on the carbon data alone to make your decision, you would never put it in your sustainable fund – building sewers involves a lot of embedded carbon after all. But consider the fact it will clean up the Thames by diverting around 16 million cubic metres of sewage discharges in a typical year while also improving the network’s resilience to the growing London population and the physical impacts of climate change, then you will likely come to a different conclusion.
Does that mean measuring sustainability performance is futile? Absolutely not. Sustainability regulations require it for good reason – we need to be transparent, credible and evidence-based if we are to gain the trust of our clients. There is a place for data, as it can help you draw conclusions, challenge assumptions and provide insights. But sustainability data needs to be used with caution and applied with skill to avoid unintended outcomes or spurious conclusions.
It’s not all bad news. With complexity comes great opportunity. We find that a lack of data, misunderstanding of data or inadequate public disclosure can often generate great investment ideas and allow us to invest in companies that investors with a more ‘tick-box’ approach typically avoid. We think this is what our clients expect us to do – to find the great ideas that other people overlook or don’t have the depth of skill or experience to find. My conclusion therefore is that there is no such thing as perfect sustainability data and there likely never will be. We need to move the conversation on to talk more holistically about the tools, skill and judgement required to make sustainable investment decisions and stop waiting for data to provide us the answers.
