From investment to insurance underwriting to property management and conferences galore, you’ve likely heard ESG (Environmental, Social, Governance) factors are influencing real estate decisions. To the extent you believe ESG is indicative of superior risk-adjusted returns, like BlackRock’s Larry Fink, it’s a positive step for the real estate industry. But without an industry-accepted standard for investment grade ESG ratings, it’s also a recipe for confusion.
To avoid this problem, we need a transparent, timely, and accurate standard for rating real estate assets and portfolios on ESG performance similar to what the finance industry applies to bond issuances. Here’s why and how to go about creating that new world.
“Real decisions are being made. If we don’t trust the data, those decisions can’t be made well.”
A range of green building schemes, standards, and certifications – an estimated 600 globally – already exist to certify or rate individual buildings “green”. There is also one that plays at the portfolio level: GRESB. Other protocols like SASB have introduced real estate-specific reporting frameworks. The problem is that none of these systems provide an investment grade ESG rating akin to those found in traditional financial products, nor do they purport to. As a result, they’re useful proxies in sustainability underwriting but investors and lenders are still left to their own devices to understand the current state and actual ESG performance of an individual asset or portfolio, at much time and expense. The good news is research shows the conversation has shifted from asking whether or not we need ESG data to determining how to gather accurate data to support financial decisions.
“Financial decisions cannot be made on outdated performance, estimates, or inconsistent levels of data quality. The same must be true of an ESG rating system.”
It’s a simple, perhaps obvious assertion. And it is not a knock on the current regimes/approaches. Instead, it’s a reflection of the devilish nature of real estate data.
Take the “E” or environmental aspect of ESG, for example: in commercial real estate, this is substantially driven by utility consumption data and carbon emissions. Utility meters collect this data, which is notoriously noisy – loaded with gaps, overlaps, and abnormalities – and a large portion of meters are not under the landlord’s control. Data inconsistencies are often explained only by contextual information like weather, leasing activity, change in tenants, and renovations; unfortunately, these details are also difficult to track and collate. These blind spots prevent us from understanding the true performance of the whole building. Compounded across many buildings in a portfolio, it becomes difficult to see the forest for the trees.
“The truth of the matter is, it’s complicated… Not all data points are relevant to all people.”
In the absence of the complete picture, building an investment grade understanding of real estate ESG requires industry participants to resort to issuing bespoke data requests and creating custom underwriting models. The tedium, lack of comparability and scalability, and dubiousness of the underlying data quality remain major obstacles to this approach. In their effort to understand the environmental impacts and risks of their assets, PGGM said, “We need data from every asset we have exposure to.”
And yet, the march towards using ESG data to drive decisions in real estate from investment to lending, leasing, and valuation only gathers momentum. The ultimate fix is a complete, real-time “meter-to-market” ESG data chain of custody, which would require collecting ESG data from its sources across a whole building, then aggregating it across a portfolio in a timely manner so that it’s useful for investment, leasing, and lending opportunities. Not to be the bearer of bad news, but we are years away from this ideal in even the most sophisticated portfolios.
So where does that leave us? What action can we take to help get us one step closer to that ideal?
It’s about getting smarter in what data we track, how we analyze and categorize it. Measurabl has been building a SaaS-based data chain of custody for today. As we think about how to scale that, we can’t lose sight of our framework for defining what “Investment Grade” means:
- An investment grade rating should work like traditional bond ratings: the rating tells us about the ability of the underlying asset (building) to return the ESG performance and “yields” claimed.
- To get this investment grade rating, we need to care not only about absolute or peer relative performance (yield), but also the quality of the data on which that claim is based (creditworthiness). In Measurabl’s case, we use two individual scores: a “Performance Score” and a “Trust Score”. The product of these is called the Measurabl Sustainability Rating or MSRTM.
- The ESG Performance Score should be the weighted average at each level in the data chain; currently, that consists of meter –> asset –> fund –> entity.
- The Trust Score is identical in that it is the sum of the score at each level in the data chain, but instead of individual ESG metrics it is a score for (1) completeness – e.g. data coverage and % of readings in a given period analyzed, (2) timeliness – how well does the information reflect the current state and (3) quality – “trustworthiness” as determined by the likelihood of the values provided of data. The components of the Trust Score are peer relative; it’s only fair to compare like-type assets and portfolios as there can be such variation in the real estate industry.
- A sustainability rating like MSR should be relevant to both assets and their aggregate (portfolios).
- This should be customizable between counter-parties depending on what aspects of ESG they care about most (or not at all).
Until we have an industry-accepted ESG ratings system, each organization will need to continue to make do with the practices they’ve found to positively impact their performance investors will continue to ask for ESG data, and may continue to hedge their bets due to the quality of data provided. In the meantime, the industry’s needs only grow.