Global investor interest in ESG data has reached unparalleled levels in 2024. According to a recent EY Survey of institutional investors, 88% of respondents reported an increase in the use of ESG data over the past year. Worldwide sustainability bond issuance reached the $1 trillion mark in 2024 further underscoring the need for ESG data.
ESG reporting has often been viewed as a way to build a brand’s reputation by demonstrating good governance and transparency. Companies report ESG data on ways they are lowering and assessing risks, improving sustainability performance and ensuring long-term resilience.
The external benefits of reporting include not only attracting investors, but also customers and talent. In addition to these external reporting purposes, there are numerous internal business-focused reasons to use ESG data. Indeed, companies that solely report their ESG performance for external validation may lose important strategic opportunities for using the data.
Annual ESG reporting vs operational ESG reporting purposes
It helps to distinguish two ways that ESG data is used in annual reporting for the public and external stakeholders and ongoing operational reporting for internal management. These two purposes for ESG data differ significantly.
ESG reporting standards tend to focus on long-term risk reduction through target setting and measuring progress against these targets. Companies all have different perspectives on the level of publicity they want related to their sustainability initiatives.
While the information can be used to attract investors, customers, employees and other stakeholders, it can also draw negative attention if companies receive accusations of greenwashing: misleading the public by overstating environmental or other non-financial performance. Companies may also choose to avoid scrutiny for their endeavors if they are viewed as irrelevant to the core business strategy.
Companies need to strike a balance in their reporting, and present information in a way that reflects strong business alignment and societal benefits without overstating positive actions. While annual ESG reporting tends to focus more on balancing the long-term needs of society with business motives, gleaning short-term benefits of ESG data is also possible.
Operational ESG reporting happens at a higher frequency and it is used not only to track progress, but to support cost benefit analysis linked to resource use and management. Indeed, ESG data insights can deliver the same primary value drivers and cost reduction strategies that drive mainstream business decisions. ESG data that can give energy managers and facilities managers the information they need to achieve pragmatic short-term goals linked to the function, purpose and efficiency goals of a commercial space. Environmental data is some of the most valuable data for this purpose.
Indeed, ESG data insights can deliver the same primary value drivers and cost reduction strategies that drive mainstream business decisions. It is this operational, and more utilitarian approach to ESG data that can give energy managers and facilities managers the information they need to achieve highly pragmatic short-term goals. Environmental resource data is some of the most valuable in this regard.
Common types of environmental data
Companies often collect environmental data across environmental metrics relevant to their operations. While the relevant metrics can vary from industry to industry, some of the most popular metrics include:
Carbon emissions: Various greenhouse gases are converted into CO2 equivalents measured in metric tons of carbon dioxide (tCO2), and categorized as Scope 1 (operational), Scope 2 (purchased) and Scope 3 (upstream and downstream emissions) for reporting purposes. These emissions are often generated through the direct consumption and burning of fossil fuels in vehicles, on-site refrigerant leaks and emissions from manufacturing processes.
Carbon emissions directly contribute to climate change. They are also helpful for understanding how business activities and relationships influence your carbon footprint beyond immediate operations, across the value chain. This data can contribute to business decisions related to supply chain management, procurement, transportation and fleet management, investments, sustainable product innovations and more.
Energy usage: Energy use totals are calculated using energy meters and utility energy invoice data, often measured in kilowatt hours (kWh). Totals are compiled by converting measurements into megawatt hours (mWh) or joules. Companies can also use energy usage data to calculate their energy intensity, which normalizes energy use per a business unit such as revenue or total units sold. Energy intensity is used to understand energy use relative to business growth or downsizing.
Energy use is extremely relevant data for energy managers to effectively allocate, optimize and ultimately reduce energy consumption to minimize costs. In addition, on-site renewable energy generation and battery storage can help companies further reduce energy needs. Given the volatility of gas prices, sourcing renewable energy can significantly contribute to a company’s strategic energy management goals.
Water management data: Water data can be collected for total consumption, discharges and total withdrawals. More detailed analyses such as withdrawals from areas with water risks can also contribute business intelligence. Water consumption data is the most common data across most industries and it is often measured in cubic meters.
Water consumption is a direct cost to businesses, making it valuable for interpreting and analyzing for the purpose of operational efficiency. Water withdrawals also present potential regulatory risks. As with energy, direct on-site sourcing of water through activities such as rainwater harvesting can further reduce costs.
Waste management data: Data related to waste and recycling is useful for operations managers to track and monitor. Waste and recycling totals are often measured in cubic meters or metric tons. Waste and recycling can also be measured by specific types such as hazardous waste and recycled e-waste. In addition, some industries may benefit from tracking industry–specific types of waste such as mining tailings or food waste.
Waste managers benefit from monitoring waste data to reduce collection and disposal costs and potentially generate an alternative income stream through recycling opportunities. Large companies wishing to invest further in their waste strategy may partner with composting facilities or generate energy from waste with anaerobic digesters or similar technologies.
Summary of operational use cases for environmental data
- Strategic insights: Environmental data contributes important insights into how, where and when environmental resources are used as inputs into business processes.
- Operational and resource efficiency: Minimizing environmental resource use to improve efficiency and drive down costs is one of the most compelling use cases of environmental data. Energy efficiency improvements also drive job creation, supporting an additional 10 million jobs by 2030, according to the International Energy Agency.
- Supply chain management: Increasing sustainability-linked supply chain risks around the world make it important to embed sustainability considerations into commodities sourcing, procurement, transportation and logistics, and other upstream supplier relationships. Popular sustainability trends for supply chains include onshoring, local sourcing and deforestation-free sourcing.
- Product development and innovation: Significant demand for sustainable products and services from both B2B and B2C consumers has led companies to innovate in this direction. Collecting relevant ESG data on the impacts and sustainable benefits of your products is key to building consumer trust.
- Positive workplace culture: Employees increasingly seek sustainable employers and reporting ESG data can enhance a brand’s internal perception as a positive place to work. A recent survey found 58% of all job seekers consider sustainability commitments as a factor in their decision to choose an employer.
Technology is key to ESG data management
Data management for ESG information can strain resources, due to the time intensive activities that go into effectively collecting, tracking, recording and controlling the data. Technological ESG data platforms like Atrius Sustainability streamline this process, as they are designed for adopting common ESG data methodologies and measurement units without a steep learning curve for facilities managers. This also supports stronger capabilities to analyze and model data according to hypothetical scenarios to support planning and effective ongoing operational needs.
ESG data and digital twins
Today, technology has made it easier to collect ESG Data and automate ESG data analytics to translate into immediate actionable insights. More companies can use ESG data to achieve direct and immediate positive financial impacts that go hand in hand with long-term considerations such as environmental sustainability benefits.
When enough environmental and facilities data is combined into a single system, it essentially creates a real-time model of resource flows and operational processes. This model is known as a digital twin. A digital twin can look like a dashboard with the ongoing energy, water, and materials flows aligned to different business processes.
Energy efficiency through automating ESG improvements
When a digital twin is created to link software analytics and hardware controls through connected devices, operational efficiency improvements can happen instantly based on smart analytics using ESG data. The end result is immediate improvements to resource efficiency and stronger discovery of process changes that can be implemented for further improvements.
GRESB describes how this works in practice: “Optimization algorithms [in connected software suits] significantly reduce HVAC energy consumption by sending temperature, pressure, and speed setpoint adjustment signals to fans, pumps, and chillers every 30 seconds.” The end goal of these processes is efficient operations
Some estimates suggest that energy efficiency improvements can lead to 10% energy savings from optimizing the water of HVAC systems through hydronic balancing. Heat recovery strategies can also make an immediate impact, as 78% of heat demand can be recovered from cooling processes.
Establishing data collection processes with efficiency and results driven outcomes in mind is key to seeing results from ESG data collection efforts. Automating the data analysis is key to move directly from collecting data to reducing energy consumption. In some cases, operational approaches can be applied immediately without any upfront costs.
This requires the use of relevant ESG data software that can minimize the time spent manually data collection systems and control procedures, all of which are directly included in a tool. The Atrius suite of tools is specifically designed to minimize the time and cost it takes to see immediate operational efficiency impacts. Real time analysis means you don’t have to wait a full reporting cycle to plan and implement changes. They can be made faster and reported at the same pace.
