RealPage on why investors need an ESG data strategy

Reliable data, leveraging technology and automating wherever possible are key to making the right decisions to manage risk and drive performance, argues RealPage’s Mark Trocolar

This article is sponsored by RealPage

Real estate investors need to design an environmental, social and governance data collection strategy, ensure its quality and embed it into their overall strategy and analysis, not only to address ESG issues but also to maximize returns, says Mark Trocolar, vice-president in the investment management business unit at RealPage, a global provider of software and data analytics to the real estate industry.

How is ESG driving demand for quality real estate data?

Real estate investors, owners and occupiers have all aligned on the importance of ESG for real estate assets. In response to this, ESG has become an integral part of the asset, portfolio and risk management activities at real estate firms of all sizes. As a result, they’re requiring ESG data, in addition to the financial and operational data they already need to drive their strategy and decision-making.

This clearly demonstrates there’s a great need for timely, high-quality data to maximize returns for investors. There have been a variety of studies over the last 24 to 48 months which have shown that companies with strong ESG principles outperform their conventional counterparts over the same period. As a result of that, investors have taken notice. Additionally, regulatory reporting requirements for ESG data are increasing as well. There is a clear alignment of investment management and regulatory reporting requirements driving the demand for ESG data.

How can real estate organizations develop an ESG data collection strategy?

It’s important to note, this is a further development and evolution of an organization’s overall data governance strategy rather than a standalone process. There is also no one-size-fits-all approach, as every organization is different. If an organization is initiating an ESG data collection strategy, it can start off small and simple, and then evolve and grow over time.

The first step to initiate an ESG data collection strategy is to identify the data and ESG principles important to your organization. This should include why they are important and how they will be used to drive investment performance and corporate responsibility. These data requirements should drive action plans for both your assets and your overall portfolio.

The second step is to conduct two separate assessments: materiality and risk. For the materiality assessment, an organization must identify appropriate ESG KPIs – for instance, tracking energy consumption, greenhouse gas emissions, or climate risk data – and guidance frameworks – such as GRESB or CDP – based on your organization’s strategy that will enable you to achieve your goals.

Executing a risk assessment will enable the organization to understand the business impacts of environmental issues on their real estate holdings. This includes identifying physical risks (those associated directly to real estate holdings); social risks (those associated with how your properties add value to the communities where they are located); and transition risks (which are linked to change or shifts in market or non-market factors such as climate policies or technology.)

After identifying organizational priorities and the data required to execute your strategy, the third step is to identify the sources of your data. This means defining how you will obtain property-level environmental and sustainability data, which includes energy usage (electricity, water and gas) and social and governance data regarding demographics and the third-party organizations you work with. Additionally, it is important to consider how often you can obtain the data you require and when it can or should be updated. Typical update frequency for sustainability data is monthly, but social and governance data will likely be less frequent.

Investing in technology for data collection and monitoring is an important component of this overall approach. Organizations should look to automate where possible as manual processes are more likely to break down and generate errors. This approach is no different than that for other financial and operational data for your investments. As a result, ESG data should be aggregated with your organization’s other important data in a single, centralized repository. This will provide the opportunity to combine ESG data with other metrics in order to develop insights and fuel the overall strategy and approach for these properties.

How can you ensure the quality of your ESG data?

Timely, high-quality data is the foundation upon which informed decisions are made. As a result, an organization needs to trust its data and that is best accomplished through a combination of people, process and technology.

The application of technology is the central focus of an efficient and scalable data quality framework. On the sustainability side, energy usage data is ripe for the application of systematic data collection mechanisms. Unfortunately, factors such as building age, infrastructure and even lease terms will impact an organization’s ability to collect this data systematically.

Older buildings, for instance, may require meter or submeter upgrades to facilitate systematic data collection, while triple net leases, where utility bills are paid by the lessee, keep owners and operators out of the loop for utility costs and tracking. This may necessitate a hybrid approach for data collection that includes both systematic and manual methodologies until full-scale automation can be achieved.

Though social and governance data is typically collected with less frequency than environmental data, from an automation perspective, it is no less important. As social and governance disclosures increase in importance for organizations around the world, ESG-related systems, system vendors and data sources (both public and private) are becoming available. ESG data availability is growing and with it comes the ability to automate its capture.

For an organization focusing on quality, once ESG data has been collected, it is crucial it is aggregated in a centralized repository where systematic rules can be executed against it to identify data issues, correlations and generate alerts. As you would for other organizationally important data, ESG data should be systematically scanned, validated and monitored as part of an overarching data governance process so the efforts of knowledgeable resources can be focused on the right data at the right time.

Once you have collected high-quality data, how can real estate managers use it to drive asset-level sustainability improvements?

The primary goals of sustainability programs are minimizing your real assets impact on the environment while simultaneously driving asset outperformance. Once you have a vetted, high-quality data set, you can undertake a variety of comparison, forecasting, and benchmarking analyses to ensure that your assets are on track to hit your performance targets and identify opportunities to exceed them.

When an organization initiates its ESG data collection strategy, it identifies the data required and how that data will be used to drive investment performance and corporate responsibility. These data requirements are an influential component of the asset-level action plan for sustainability improvements.

For instance, KPIs and data requirements for sustainability tracking and monitoring should be transformed into goals for efficiency improvements. Energy consumption for water, gas and electricity can become opportunities for equipment upgrades to reduce consumption. Asset strategy should include determining upgrade costs, comparing them to short and long-term expense reductions to calculate the payback period and the net positive cashflows you’ll receive afterwards.

At an asset level, that will drive additional returns through expense reduction. By tracking efficiency improvements over time, you will see the outperformance achieved by upgrading properties to operate more sustainably. This provides benefits for both owners and occupiers.

Additionally, benchmarking can help drive sustainability-based outperformance. By comparing your asset performance and cost structure against similar properties in similar areas, insights and opportunities for improvement can be identified, such as alternative energy sourcing. There are tools out there to help you do this easily. For instance, Energy Star Portfolio Manager (ESPM) is a terrific free tool that allows you to track property utility usage and benchmark your property – and your entire portfolio – against other properties. According to recent studies, a concerted effort to track and benchmark asset performance using tools like ESPM has led to between 5 and 10 percent improvements in asset efficiency over a three-year period.

How are organizations using social and governance data to drive portfolio strategy?

Organizations tend to focus on sustainability data when they’re trying to drive strategy and returns. But as part of ESG, social and governance data is also of critical importance. Over the last several years, many studies have shown that organizations with strong diversity, inclusion and governance policies perform significantly better in the long term than organizations that don’t have strength in those areas.

Organizations that are looking for social data to drive portfolio strategy should be collecting data on the asset and portfolio level regarding policies, practices and procedures for labor, data privacy and security, diversity and inclusion, health and safety, employee engagement and community relations.

The governance aspect of ESG can be applied to the way in which organizations govern themselves and it talks about how an organization is structured. How are decisions made? How is compensation – executive and non-executive – determined and managed? This also includes policies, procedures and track record in areas such as accounting standards, tax strategies, lobbying and political contributions. Companies lacking clear responsible policies in these areas are at greater risk for reputational, operational, legal and other issues that will negatively impact their ability to drive long-term growth and outperformance.

Capturing social and governance data provides the ability to execute a variety of positive and negative screens. For instance, you can identify organizations whose governance practices align with those of your organization and those that do not. An additional example would be identifying assets with opportunities to drive additional gains in community engagement or safety operations. This all serves to manage risk and maximize the long-term value and performance of your investments.