We’ll probably never know if it was the global pandemic, the natural disasters that plagued the country or the widespread movement for racial justice—but commercial real estate stakeholders emerged from 2020 with a newfound commitment to environmental, social and governance factors, also known as ESG. In the last two years, CRE developers, owners and investors have announced aggressive targets to achieve carbon neutrality, invest in renewable energy and increase hiring diversity. 

When it comes to meeting these lofty goals, owners are quickly met with a harsh reality: measuring and tracking ESG metrics can be really, really difficult. Thankfully, technology is helping CRE stakeholders keep their word. Artificial intelligence and machine learning can collect and interpret essential carbon emissions data, track ESG performance and enhance industry transparency. 

ESG Exuberance 

Commercial real estate was the natural candidate to lead the discussion about ESG. Globally, buildings are responsible for 39% of energy-related carbon emissions, generated from a combination of building operations, which accounts for 28% of carbon emissions, and materials and construction, which contributes 11%.

So, it stands to reason that commercial real estate developers, owners and stakeholders are in a position to make a significant environmental impact through their real estate holdings—and most are fervently getting on board. According to a survey from KPMG, 85% of companies are aligning their strategy to focus on ESG metrics in making investment decisions, and 82% of commercial real estate investors made the same claim in a recent ULI survey. It’s clear that the events of the last two years have encouraged increased adoption of ESG policy with 54% of companies saying that COVID-19 forced sustainability considerations to the top of the agenda. 

The industry is also moving the needle on the social pillar of ESG by focusing on diversity and inclusion programs and community-oriented investing. In PwC’s Emerging Trends in Real Estate 2022 survey, nearly 70% of respondents said that the real estate industry could alleviate systemic racism, and in a CBRE report on ESG investment, 54% of institutional investors ranked social change as one of the primary factors of sustainable investment. 

The enthusiasm around ESG is only going to grow. This year, 67% of leaders in PwC’s 2021 Global CEO survey said that they were planning to increase investment in ESG initiatives—and there is a financial incentive. Numerous studies have shown that companies with ESG-aligned strategies have better financial performance and higher occupancy. That’s because most tenants (83%) are also demanding sustainable buildings and 30% of Fortune 500 companies have publicly announced climate goals, up from only 6% just four years ago. From a regulatory perspective, ignoring ESG isn’t an option. EU laws are targeting a reduction in carbon emissions by at least 55% by 2030, and the US aims to reduce emissions by at least 50% by 2030. 

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AI Creates Standardized ESG Ratings

Achieving ESG targets will require a focused, data-oriented strategy. In addition to making changes and upgrades to the physical building, ESG compliance requires copious amounts of data collection and analysis to track and report consumption. According to CBRE, measurement is “a critical starting point to any ESG program.” Currently, ESG organizations IFRS Foundation, CDP and the World Economic Forum are working to create standardized assessment criteria, and data will undoubtedly play a crucial role in the evolution of measurement and reporting standards.

The current system is in dire need of an upgrade. Today, companies receive an ESG rating from a third-party organization that uses limited and unreliable data and fractured criteria to produce a score that most industry experts agree is not a good indicator of ESG performance. A lack of standardization is one of the biggest challenges. As Terence Tse writes in a paper for the ESCP Business School, the five largest rating companies had a correlation of only .61% on the scores of more than 800 companies. That is staggering. 

AI technology can collect and process qualitative data to standardize reporting and measurement and produce more consistency and transparency for investors and the industry. Algorithms can be trained to source non-traditional data sets as well to produce a thorough picture of energy usage, which could include how building materials are sourced and delivered, commuting activity to and from a building, air quality, management diversity and other asset-level insights beyond simply tracking water, energy and carbon emissions. At the occupier level, AI can scan social media, customer review sites like Yelp and corporate information sites like Glassdoor to produce an ESG rating.

Standardization of ESG ratings will help organizations better identify areas of improvement and create more effective sustainability strategies, and it will help companies achieve outlined targets and share those successes with the industry. 

AI-Driven Reporting Creates a Competitive Advantage

For CRE stakeholders, standardized and data-backed ESG metrics will serve as proof that the organization is meeting ESG targets and genuinely investing in sustainability. This is going to be increasingly important in capital raising efforts because, as noted above, most investors have ESG mandates for capital placement.

Last year, mutual funds and exchange-traded funds invested nearly $300 billion in sustainable assets worldwide. As Greg Smithies, a partner at Fifth Wall and leader of its climate technology investment team, said in a recent New York Times article, “If I have better ESG data, I can attract more capital, at a better cost of capital.” Ultimately, owners with data-backed reporting will have a competitive advantage in the capital markets. 

Accurate ESG reporting can also boost NOI, creating long-term value and a better exit cap rate. Reduction in carbon emissions and other energy-related waste reduces energy costs and drives operational efficiency, in turn increasing NOI. Data-backed metrics allow investors to see the economic impact that an ESG strategy has on a current investment or prospective investment, providing high-value insight to create an ESG strategy. 

Some investors already require this level of due diligence when considering an investment, according to Oliver Light, commercial director for asset manager Carbon Intelligence, who has said that the company’s “largest clients will no longer buy an asset until our team of engineers has done a due diligence report on that acquisition.”

Commercial real estate players are already seeing the advantages of a data-backed ESG strategy pay off. At Northspyre, we are deeply invested in the power of AI and data and analytics to drive value in real estate projects. The same tools are amplifying the adoption of ESG initiatives to push the needle on sustainability in our industry and for a better world. The added value and higher returns are just icing on the cake. 

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