In today’s ESG landscape, we are seeing more companies setting new carbon emissions reductions targets, such as committing to net-zero targets and science-based targets (SBTs). In fact, the number of companies committed to SBTi targets grew by nearly 65% in 2021. As more companies commit to these ambitious targets, data quality and accuracy is becoming an increasingly important topic. Complete and accurate data is the foundation of a successful emissions management program and a robust emissions inventory. However, improving data quality within an organization can present many challenges. Although it can be a significant lift, data collection is one of most important steps in beginning to track an organization’s complete greenhouse gas (GHG) emissions footprint, which has become an essential driver of investor and consumer decision-making. With a carefully and strategically executed data collection and management plan, businesses can confidently and accurately report on their ESG performance.
Challenges to data quality
To understand how to report the most accurate ESG performance, businesses must first identify the challenges they face regarding data management. For most companies, especially those with a large reporting footprint or complex portfolios, the decentralized storage of invoice data can complicate data access and consistency. A frequent issue that companies face is the inability to collect data for leased spaces from property owners or utilities. For instance, in the case of an office space shared among multiple tenants, landlords will pay the complete electricity bill and may not break down the usage information for its tenants. Since data can be difficult, or in some cases impossible to access, a business may be required to estimate a potentially large volume of data in their portfolio. Thus, having quality data from previous months will be integral in calculating accurate estimations.
Furthermore, data from certain GHG streams, such as refrigerants, can also be a challenge to collect due to the irregularity of their service schedule, the inconsistency of the billing cycle, and the lack of exact measurement information. Emissions calculations for Scope 3 categories, such as Use of Sold Products or Investments, can be difficult to quantify without contextual data. Additionally, supply chain data-sharing for Scope 3 emissions is often a complex task as companies must engage with their suppliers for a sum of their emissions. While these data sources can sometimes be immaterial in relation to a company’s overall footprint, organizations must have quantitative evidence to support the immateriality of any sources. It is important to recognize these potential roadblocks in advance of the reporting season and allow enough time to consider solutions for gathering quality data.
The three C’s of improving data quality
To ensure quality data, we propose assessing GHG data in terms of the following three “C’s”:
- Collection: Often, companies can struggle to identify what data sources to track, where to find the data internally or externally, and who should be involved within the organization. This is particularly true of companies calculating a GHG inventory for the first time. Having a digitized and centralized platform to streamline data collection, such as Schneider Electric’s Resource Advisor platform, can help overcome the challenge of collecting data from multiple parties within an organization, and standardize data storage over time. In addition, as GHG data is attracting more attention from stakeholders and regulators, there is a growing importance for strong data governance and oversight into data collection processes and controls. Companies should educate internal stakeholders and implement internal processes to oversee data collection and control from internal groups including IT, Internal Audit Committees, Board Members, and others.
- Consistency: Once the sources of data are defined, organizations should constantly improve their data collection processes and granularity of data. For companies with complex portfolios, data aggregation and consistency over time can be a challenge. Implementing automation to create complete data sets and consistently track data for sites and sources can free up resources for other activities and ensure data is reported consistently. For companies with fluctuating portfolios, consistent and organized tracking of site and source changes will allow for complete data collection and confidence in the metrics reported.
- Confidence: As more frameworks and agencies are incentivizing or requiring companies to audit their GHG data, it is important to have strong data controls in place to ensure accurate information disclosure and reporting methods. Third-party verifiers for GHG metrics will request evidence from the data sources, such as an electric power invoice image or PDF, from which the company captures its monthly energy usage. Additionally, running quality controls and variance testing on monthly energy, fuel, water, or waste consumption will strengthen confidence in data collection and help to proactively identify any outliers that could signal data errors.
Modern trends in data
One of the most exciting modern trends in data is the coupling of data capture and storage to tools that transform raw data into visual formats. This pairing opens the door for organizations to take any number of data streams and, at a glance, reveal trends, outliers, and opportunities. The energy management and sustainability spaces are also benefiting from this development, as companies are eager to turn these tools on their utility usage and emissions data to find opportunities for actionable changes, improved efficiencies, and increased profitability.
As many countries are making the change from voluntary to mandatory reporting/disclosure, ensuring the data system that a company has in place is responsive to an evolving regulatory environment is critical. Schneider Electric’s Sustainability Business can help companies overcome this challenge by providing them with a global team of sustainability experts augmented by our turnkey platform, Resource Advisor, which allows for end-to-end aid in a company’s energy and sustainability journey. As reporting frameworks, like GRESB, evolve their disclosures to encompass the multifaceted climate impacts of company’s operations, a comprehensive platform to track these metrics is extremely valuable.
Data quality is at the heart of an organization’s ability to set and achieve ambitious targets of any kind. By following the three C’s of data quality – collection, consistency, and completeness – organizations can ensure that their ESG data is accurate and comprehensive. Moreover, by using digital energy management platform like Schneider Electric’s Resource Advisor, organizations can leverage data visualization tools and analytics to transform their raw data into actionable insights and strategies for energy management and sustainability. With the help of these solutions, companies can not only meet their regulatory and stakeholder expectations, but also contribute to the global fight against climate change and the transition to a net-zero future.
Written by Olivia Hill, Senior Sustainability Associate for Schneider Electric, Emily Xue, Sustainability Analyst for Schneider Electric, and Marshall Doty, Sustainability Analyst for Schneider Electric.
This article first appeared in the GRESB newsroom. To view, click here.