Real estate companies are under growing pressure to collect, analyze, and report environmental, social, and governance (ESG) data as part of a larger focus on sustainability. But simply reporting whatever ESG data a firm has on hand is no longer sufficient: Now, the goalpost has shifted to data quality and accuracy. Whether firms are just beginning to establish ESG frameworks or polishing existing platforms and practices, they are all working toward the common goal of improving the integrity and completeness of their data.
ESG reporting has come a long way in the commercial real estate industry. In Europe, institutions are required to include ESG disclosure documents on financial statements. Although similar disclosures are still voluntary in the U.S., investors and other stakeholders are increasingly looking at ESG data as part of their due diligence process.
Companies submitting performance data for the annual GRESB (formerly Global Real Estate Sustainability Benchmark) disclosure now represent over USD $3 trillion in assets globally. That level of participation speaks to the main drivers behind ESG reporting: namely investors, occupiers, and regulators. Here’s why ESG matters to these stakeholders.
Investors – Major players such as BlackRock CEO Larry Fink are helping to push ESG criteria to the forefront for mainstream investors. Fink has been candid about the firm’s new standard for investing, which requires business plans and reporting to include transparency around sustainability and ESG performance. He has stated that BlackRock “will be increasingly disposed” to vote against management companies that haven’t made enough progress on sustainability issues. That’s a clear message from an $80 billion company – and the largest asset manager in the world – and it signals a bigger change ahead for institutional real estate firms.
Occupiers – Numerous corporations have established their own sustainability programs and look to occupy spaces that prioritize similar values and criteria. Many corporations have set lofty goals for the decades ahead. Salesforce, for example, announced that it plans to get to 100 percent renewable energy by 2022. And VMWare announced in 2018 that it achieved its goal of becoming a carbon neutral company two years ahead of schedule.
Regulators – ESG is being further propelled by a changing regulatory landscape. Governments are beginning to mandate that property owners file annual disclosures on carbon emissions. In some cases, properties that exceed set emission levels—or fail to report this data altogether—will be subject to financial fines and penalties. Europe has already set forth strong legislation, such as Clean Energy for All Europeans, which mandates that buildings improve their energy performance, among other directives. Even the United States, which has traditionally fallen behind other developed countries in reducing carbon emissions and adopting renewable energy, is starting to see tougher legislation in these areas. New York City and Washington, D.C. have passed groundbreaking emissions legislation, establishing significant fines for buildings that do not meet reductions goals by deadline.
All of these forces are pushing companies to put ESG frameworks in place to satisfy the demand for more information and greater transparency around ESG. At the same time, stakeholders are asking more discerning questions about the ESG claims made by assets owners to root out inaccuracies or false information that overstates an asset’s environmental sustainability—a tactic known as greenwashing. Real estate companies are now expected to put a greater emphasis on data quality and accuracy in their investor disclosures. The question is no longer “Do you have data?” but “Where did it come from, how has it evolved, and why should we trust it?”
Environmental data sets the foundation
Each of the ESG pillars—environmental, social and governance—is important in its own right. Until now, the “E” and the broader issue of sustainability has dominated the conversation, perhaps because this is the easiest to quantify with hard data. Certainly, sustainability plays a highly dynamic role within the built environment. Commercial buildings generate about 40 percent of total greenhouse gas emissions in developed countries. Efforts to reduce energy consumption, waste output, and greenhouse gas emissions (GHG) are constantly in flux with opportunities to reduce carbon footprints and better manage buildings to reduce costly errors in equipment malfunctions or wasted utility spend.
Firms just getting started with ESG reporting first need to wrap their arms around what environmental data needs to be collected, and determine how to go about collecting it. While materiality of data may differ among companies, investors, and purposes for disclosure, most real estate groups will start measuring utility use and outputs. Assets, portfolios, and funds often collect data such as energy consumption, water consumption, greenhouse gas (GHG) / carbon emissions, and waste.
Gathering this type of data is not always an easy task. Energy is a highly regulated sector, so for some, it is easier to gather data on all of the disparate energy sources an asset is using. However, ease of collection often depends on a building’s lease structure. For example, if a building has a triple net lease, in which tenants are responsible for paying their own utility bills, owners rarely have access to energy consumption data or costs.
Additionally, energy is by no means a single line item: For many companies, calculating energy consumption involves a combination of data points related to the use of electricity, fuel, and renewable energy sources such as wind, solar and hydro power. Each local utility has its own method of sending customers usage information, whether it be via paper and electronic statements or through an online dashboard. Tracking monthly statements across multiple properties, large portfolios, and separately managed real estate funds—all with diverse geographies and myriad utility companies—makes the task exponentially more complex and challenging.
In addition to quantitative environmental data, it’s also important for real estate companies to collect qualitative information on sustainability audits, certifications, benchmarks, and projects. And then of course there’s the “S” and the “G” to consider. Though this is often secondary to environmental data for many firms, to achieve real transparency around ESG issues, social and governance data points such as diversity and inclusion, pay equity, employee health and wellness programs, must also be captured and reported to both internal and external stakeholders.
Keeping tabs on all of these types of data is a complicated, time-intensive process that requires subject matter expertise—and the larger the portfolio, the heavier the workload. Old-school practices such as entering information from utility bills into spreadsheets cost time and resources while creating more risks for human error. To that end, innovative software solutions and data automation systems have emerged to help companies do the heavy lifting by automating data collection and verifying data accuracy.
The quest for quality data
It is important to acknowledge that real estate companies are at very different stages in their ESG journeys. Some have fairly sophisticated processes and tools in place for collecting sustainability data, extracting insights, and reporting that information to key stakeholders, while many others are just getting started. However, one of the common challenges for companies across the spectrum is improving sustainability data quality that serves as the foundation for ESG reports and ratings, as well as obtaining actionable information that companies can use to drive business decisions and strategy.
Data quality is critically important for a multitude of reasons. No matter how the data is collected, investors, stakeholders, and companies themselves need to know they have data they can trust. Companies are leveraging environmental data and analysis to improve operating efficiencies that can impact performance at the property, portfolio, company and/or fund level. And from a financial standpoint, accurate ESG data is also important for companies that take advantage of green programs, such as issuing a green bond in the sustainable debt market.
However, that quest to obtain accurate data can lead to a number of pain points. The world of ESG is evolving, and there is still a significant black hole around what data quality means. Some of the questions at the forefront for real estate firms are: How do I trust that data is accurate? And how do I ensure that the level of data is consistent across every asset and asset manager?
Data quality rests on four pillars, which are notably similar to the principles that guide credit ratings agencies:
- Timeliness: The more recent an indicator, the more reflective it is of the current state of the asset or fund. Conversely, the older the data, the more difficult it is for a discerning investor or lender to trust, since they don’t know whether the data is reflective of the current state of the asset/fund under scrutiny.
- Accuracy: Sustainability data can sometimes show sudden spikes in performance. Is that a true shift, or are results skewed by an error or anomaly? Statements that appear too good to be true or are out of step with industry expectations should be detectable, flagged, and explained or corrected. There’s enough comparable information available to know reasonable data coverage rates for a given asset class. Using that contextual understanding, accuracy can be verified through a standard deviation from the mean expectation.
- Completeness: Are an asset’s total floorspace and sub-type(s) defined? Are all meter readings from the time period across all floor area(s) accounted for? Omissions in building definition or meter readings are like words deleted from a sentence – drop too many and it’s not at all clear what type of asset is being evaluated or what meter readings are normal—at which point, benchmarking becomes nearly impossible.
- Auditability: Are the original data points and any subsequent transmissions documented? If you can’t tell where the data came from, or account for how it has evolved over time, why should stakeholders trust the end claim?
Challenges surrounding data quality become increasingly complex as companies scale from the building level to a bigger portfolio or real estate fund. Does the data reported reflect the owner’s total financial stake or operational control in all underlying assets? Does utility data coverage represent the entire building, or only the common spaces? Does capital expenditure on sustainability projects correspond to all affected building areas? These technicalities matter: GRESB performance scores and many other fund-level metrics stem from these and similar questions. This is also the level at which data often becomes muddied.
Leveraging tech solutions
It’s necessary to recognize the problems that exist when identifying best practices for ESG data collection, analysis, and disclosure. New and innovative software applications are emerging to help to address some of the frustrations with achieving data quality and reliability, ensuring greater transparency around ESG to both internal and external stakeholders.
When choosing the right approach for your firm, it’s important to consider how a solution addresses each pillar of data quality.
Automating for accuracy: There are still many companies and consultancies that rely on manual data collection processes, such as entering utility bill data into Excel spreadsheets to track sustainability data and perform calculations. Automating this process removes human error from the equation while saving valuable time and resources. Tools that apply artificial intelligence and machine learning help to identify errors, anomalies or outliers, and “holes” that exist in building data. For example, Measurabl’s platform checks for overlaps or duplicates in data entries that incorrectly show spikes in energy use.
Minding the gaps: One of the biggest concerns for companies is assessing completeness of their data sets. If you are looking at trends, does it make sense to compare two different years? Different building types have different lease structures, which prevents some property owners from being able to capture all of the data that they might need. It’s important to evaluate environmental data in the context of what data is being captured, and how data completeness changes over time as it relates to year-over-year comparisons and trends analysis. Companies need to have visibility into what information they have and what they are missing.
Keeping data up to date: Data becomes less reliable the longer it sits on a shelf. That’s why Measurabl advocates a dynamic approach to data with information that refreshes frequently— typically monthly, as new utility bills are posted. The best way for companies to gain real insight into consumption patterns and identify areas for reduction is to update the data on a regular basis. In many ways, this provides better insights and a more manageable process than a huge, once-a-year push to collect data for annual reports.
Clear chain of custody: When pulling data from disparate sources, it can be a challenge to ensure accuracy. Creating a direct data link to the original source is the safest way to ensure data integrity and avoid introducing human error. For example, Measurabl’s data automation technology allows users to pull usage information directly from utility providers, so there is no chance that someone can type the wrong numbers into a spreadsheet. The platform also tracks unusual spikes in usage and intensity or dramatic year-over-year changes.
Next Up: Physical climate risk assessment
The commercial real estate industry is continuing to improve its standards and practices for collecting reliable sustainability data. Now, the conversation is shifting toward resilience. Moving beyond a building’s impact on the environment, resilience considers the environment’s impact on buildings. As such, companies are increasingly examining physical climate risk as it pertains to flooding, hurricanes, tornadoes, wildfires, heat stress, drought conditions, and other factors exacerbated by climate change. Ultimately, every asset will be affected in some way by climate change—the key is determining to what degree and to which types of risks it is exposed.
Not surprisingly, real estate investors, lenders, and insurance companies are also taking physical climate risk into consideration when determining where to place capital. On the bright side, climate risk data is highly actionable: Companies can target improvements to ensure that a building remains operational in the face of climate-related shocks (such as severe storm systems) and stressors (such as rising sea levels).
Physical climate risk information is used in due diligence for acquiring or disposing of assets. It can also be applied to developing risk mitigation strategies, such as erecting sea walls or moving critical equipment to higher floors to avoid potential flood damage. This information can also help firms assess residual impacts to an asset’s value over time due to various climate conditions. That’s why Measurabl includes functionality that enables customers to examine asset-level physical climate risk across their portfolios.
Physical climate risk is an increasingly important aspect of ESG disclosure. One group aiming to improve physical climate risk reporting for real estate and capital markets is the Task Force on Carbon Financial Disclosure. An industry-led initiative, TCFD developed a voluntary framework for climate disclosures. Its mission is to develop consistent, voluntary climate-related financial risk disclosures that companies can use to share relevant information with investors, lenders, insurers and other stakeholders. The task force is also working to help companies better understand what kinds of information financial markets want them to disclose in order to measure and respond to physical climate risks.
There is a growing list of examples that show climate resiliency is gaining traction in public and private sector companies, as well as financial markets. For example, Moody’s announced last year that it would acquire a majority stake in Four Twenty Seven Inc., a leading provider of data and analysis related to physical climate risks. This integration enhances Moody’s growing portfolio of risk assessment capabilities. It also underscores the growing attention within capital markets to address sustainability issues and incorporate climate risk into economic modeling, credit ratings, and industry indexes.
More work ahead
There are initiatives on all sides aimed at improving disclosure and quality of ESG data. On the regulatory side, there are organizations such as Mission Data, which is working to liberate data from utility companies and make it easier to share, in the spirit of establishing open access for better decision making. GRESB also is working on a new performance data standard that seeks to answer a number of pressing questions: What is the definition for data quality? What is everyone actively doing today to determine if their data is high quality? How do we ensure that the data that we are collecting and using to make decisions is complete and accurate?
Rather than creating myriad notions of what defines “good data,” Measurabl supports the establishment of a single industry standard for data quality. In fact, it was one of the first data partners to meet with GRESB and provide insight on practices and standards related to ESG data quality. Data integrity has been a focus area for Measurabl for some time, and it is something that we continue to strive for, not only to better assist our customers but also to help move the broader ESG movement forward.
As ESG has become more prevalent and widely embraced across the commercial real estate industry, the attention continues to shift from quantity to quality. Organizations don’t want 1,000 indicators on ESG. They want a specific set of data they know they can trust.