Setting the scene – known challenges…
There has been a continuous increase in the amount of data tracking the environmental, social and governance (ESG) performance of firms in recent years – as of December 2019, it was estimated that:
$3trn of institutional assets is now tracked by ESG data globally
(The Economist, 2019)
Externally-sourced data is necessary (though not sufficient) for firms to uncover material risks and opportunities. The challenge remains how best to integrate it into the investment process, and wider operating model, particularly as most firms’ current capabilities are often limited to specific products, rather than enterprise-wide integration.
It is often the case that the product-related tools firms have built use data inconsistently, have limited governance, and are not integrated with the rest of the business. These are not fit for purpose for a firm with an enterprise-wide vision.
While firms may not need to re-adjust their corporate vision, policies, or engagement as they expand their ESG activity, they often need to re-visit their data and technology solutions which are unscalable, with many starting again!
Organisational ESG maturity and ESG data maturity do not necessarily come hand in hand
Beyond the obvious – exploring the challenge further...
A challenge commonly cited with ESG data is poor quality and inconsistency, with the inference that it is naively applied, resulting in suboptimal or unexpected outcomes. While this may be true for screening-only fund strategies, this is less relevant for active managers who use data in a more considered way in their investment process. Solving the quality issue is not insurmountable, though it is challenging to bring together multiple sources to ensure sufficient coverage. Some firms are achieving this through either in-house development or external solutions.
We feel that the greater problem is often evidenced in firms’ operating models, which are under pressure to respond to increasing demand for ESG products. This makes it difficult to move away from a short-term, reactive approach where activity is focused on completing the next product launch, rather than setting up the teams, technology and methodologies required to deliver a firm-wide ESG data strategy.
This is a common journey among asset managers, who find that organisational ESG maturity and ESG data maturity do not necessarily come hand in hand…
Those at the start of this journey commonly struggle with:
- Incomplete datasets, borne out of frustration at the lack of commonality between providers and the number of estimations and proxies used.
- Inconsistent knowledge and application of ESG data between teams. This may be a result of a lack of direction on where ESG data should fit in the investment process, and who should own it.
- Inefficient contracts with disparate sources of data and technology. On top of the obvious financial waste, this contributes to a lack of visibility, traceability and control of data.
- No strategy for wider integration across the operational architecture. When the data has been applied, there is no capture of other information such as why the investment decision was made, or what engagement was undertaken, to enrich future decisions.
These are sizeable hurdles to overcome, but it is important to get these foundational elements right because:
- Clients are demanding it – most asset managers can produce one-off ESG reports at a client’s request, but are not ready to provide this information at scale as demand continues to grow.
- Competitors will move ahead – most asset managers have programmes in place to improve their ESG data capabilities, those who do not make this a strategic priority will fall behind.
How to react – those doing it well…
Like all data, ESG data should be an input to the investment decision process, rather than a decisive factor. This is evidenced by the fact that a company’s ESG score only gives a snapshot in time and is subject to interpretation as to how it was derived. It needs to be supplemented with qualitative assessment and engagement to understand the direction of travel for that company.
We have observed some common features of firms ahead of the curve with ESG data:
1. It is demonstrably embedded into the investment process
Whether qualitative or quantitative, it is considered as part of the fundamental investment case, just as financial metrics are. It is available and applied as part of daily investment activities at both the security and portfolio level.
2. It is central to any technical design decisions
Many clients are looking to enhance their data governance functions and technical architectures. Those doing well place ESG data within the core scope of these changes, and give due consideration to the people, processes and technology through which the data will flow.
3. Client demands are considered upfront
Clients’ requirements are designed into the toolkit, data sets and associated processes. Enhancing the investment process will have limited value without the ability to evidence how data was used and reported back to clients.
Conclusion – an opportunity not to be missed…
There are many challenges to integrating meaningful ESG data and implementing the right frameworks to extract its potential. Some of these are industry-wide, while others are firm-specific.
Clients, asset owners and regulators will soon be demanding that managers can provide insightful ESG data at scale. With these demands comes the opportunity for differentiation, but focused effort, investment and openness to challenge are required. Those who fall further behind risk, at best, continuing an inefficient, reactive approach to ESG, and at worst, a damaged reputation from failing to demonstrate credibility in an area increasingly mandated.