3 Crucial Types of Data That Are Ignored in Sustainability Reporting

Written by Mateusz Panek | Jul 16, 2024 7:26:47 AM

Sustainability reporting requires a multidimensional perspective on how environmental, economic, and social issues can affect a company’s bottom line. Companies understandably use widely known data, metrics, and KPIs to measure their sustainability efforts, but there are other types of data that are equally crucial in supporting better decision-making, regulatory compliance, and stakeholder trust.

In this second part of our series on data management for ESG and sustainability reporting, we will focus on crucial sources and types of data that companies often overlook when creating sustainability reports. We also touch on the challenges of collecting and analyzing these kinds of data, which emphasize the need of a system, platform, or solution for gathering them. In turn, companies can utilize these kinds of data more effectively, such as in double materiality assessments or sustainability reporting.

Data that reflects double materiality and attestation

The Corporate Sustainability Reporting Directive (CSRD), which now affects more than 50,000 global companies that have transactions or operations in the EU, reinforced the significance of double materiality and data attestation. Sustainability reporting must now encompass the financial, environmental, and social impact of the company. While they are crucial for compliance, many organizations still struggle with them.

Double materiality is central to the CSRD and other sustainability standards and frameworks. It encompasses two perspectives:

Environmental and social materiality: This entails how the company’s operations affect society and the environment. It includes factors like greenhouse gas (GHG) emissions, resource usage, labor practices, and community engagement.
Financial materiality: This involves how sustainability issues affect the company’s financial performance. It includes risks and opportunities related to regulatory changes, market shifts, and operational efficiencies.

Data attestation involves verifying and validating data to ensure its accuracy, reliability, and completeness. This process typically includes internal audits, third-party verifications, and adherence to standardized reporting frameworks. Attested data enhances the credibility of sustainability reports, giving stakeholders confidence in the reported information. For instance, the International Auditing and Assurance Standards Board (IAASB) is currently developing a global standard for sustainability assurance that aims to provide a comprehensive, standalone framework applicable to all types of sustainability assurance engagements.

Despite their importance, many companies overlook these aspects in their reports. For example, assessing double materiality involves analyzing numerous internal and external factors, making the process complex and time-consuming. Integrating different types of data can be difficult due to differences in data formats, collection methods, and reporting standards. Data attestation also requires significant resources and expertise.

Type of Data	Examples of Data	Why They Are Overlooked	Relation to Double Materiality
Environmental	Energy consumption, waste management, water usage	Detailed environmental data requires extensive monitoring and analysis, which can be resource-intensive.	Direct impact on the environment and society. Regulatory risks, cost of resources, potential savings from efficiency
Social	Employee diversity, labor practices, community investment	Social metrics often lack standardized measurement and reporting protocols, leading to inconsistent data collection.	Affects the workforce’s well-being Employee satisfaction, retention, brand reputation, compliance costs
Economic	Cost savings from sustainability initiatives, revenue from eco-friendly products	The economic impact of sustainability initiatives is often not integrated with financial reporting systems.	Affects society through product choices Direct impact on profitability and regulatory compliance costs
Governance	Board diversity, executive compensation linked to sustainability	Governance data is often siloed in different departments (e.g., HR, legal, compliance) and not consolidated for reporting.	Reflects company values and stakeholder trust Reduces financial risks and improves investor trust
Operational	Material usage, production efficiency	Data on operations can be siloed within departments, making it difficult to aggregate and analyze comprehensively.	Reduces environmental impact through efficient resource use Operational efficiencies that reduce costs and enhance profitability
Supply chain	Supplier sustainability scores, raw material sourcing	Collecting detailed supply chain data requires close collaboration with suppliers, which can be challenging.	Reduces overall environmental footprint Mitigates risks related to supply chain disruptions, enhances cost management
Health and safety	Workplace accidents, occupational health metrics	Health and safety data can be sensitive and subject to privacy regulations, making it harder to collect and report comprehensively.	Enhances employee well-being and health standards Reduces costs related to accidents and improves productivity
Product life cycle	Life cycle assessments, end-of-life disposal plans	Life cycle assessments are complex and require specialized expertise and tools.	Minimizes negative environmental impact and maximizes product stewardship Innovations driving new revenue streams while reducing costs
Customer/Consumer	Detailed consumer satisfaction with sustainability, customer engagement in sustainability initiatives	Customer/consumer data is often qualitative, making it harder to quantify and integrate into reporting frameworks.	Promotes societal engagement in sustainability and enhances public image Drives sales and brand loyalty and reduces risks

Table 1. An overview of some kinds of sustainability-related data and their complexities
that deter companies from including them in sustainability reports

Overcoming these challenges need a strategic approach that capitalizes on the synergy of modern technology, best data management practices, and investment in technical and domain expertise:

Integrated reporting systems that combine financial and nonfinancial data as well as support data validation and attestation processes
Advanced analytics that automate data collection, validation, and analysis as well as analyzes material issues
Data integration platforms that can handle different data types and formats and support real-time processing and analysis
Standardized data collection across all departments and regions and adoption of recognized frameworks like the GRI

In 2024, our Sustainability Analytics Practice engaged with a global retail company in getting their sustainability data attestation-ready. It covered social sustainability across their global value chain, addressing new reporting requirements under the European Sustainability Reporting Standards (ESRS), which is the framework behind the CSRD. Our engagement also included data assessments to tackle data quality issues in reporting as well stakeholder workshops that would address the concerns of their stakeholders — their workforce, workers in the value chain, local communities, and consumers.

Sustainability data beyond Scope 1, 2, and 3 GHG emissions

Scope 1, 2, and 3 GHG emissions are well-known and widely reported categories of GHG emissions. While they are critical for understanding a company’s carbon footprint, there are additional kinds and types of data that extend beyond these categories. These include Scope 4 emissions, sometimes referred to as “avoided emissions,” and governance-related data.

Scope 4 emissions, coined by the World Resources Institute, is an emerging concept that considers the emissions savings that are achieved using a company’s products or services. For example, renewable energy solutions provided by a company can help avoid emissions that would otherwise be produced using fossil fuels. There are several standards and methods for calculating Scope 4 emissions, but they share the common aspect of evaluating the difference between the emissions of the low-carbon/eco-friendly solution and the emissions that would be generated if the new solution didn’t exist.

Governance-related data include corporate practices that affect sustainability, such as policies on executive compensation linked to sustainability targets, board diversity, and compliance with environmental regulations.

Depending on the nature of the company’s business, how and where it operates, and who it transacts with, several other kinds of data can be incorporated in the company’s sustainability reports beyond Scope 1, 2, and 3:

Type of Sustainability Data	Overview of the Data	Examples of Data	Sample Data Source
Scope 4 emissions	Emissions avoided through the use of a company’s products or services	GHG emissions reductions from solar panel installations Energy savings from LED lighting upgrades GHG emissions avoided by electric vehicles Renewable energy credits purchased Reduction in GHG emissions from telecommuting policies	Renewable energy project reports Product life cycle assessments Customer usage data Energy audits
Governance	Data related to corporate governance affecting the company’s sustainability	Percentage of executive compensation tied to sustainability targets Diversity of board members (e.g., gender, ethnicity), Compliance with environmental regulations Policies on anticorruption and bribery Transparency in political contributions	HR records Board meeting minutes Compliance reports Corporate governance documents
Social impact	Data on social sustainability aspects such as labor practices and community engagement	Employee satisfaction scores from surveys Amount invested in local community projects Number of human rights training sessions conducted Fair trade certifications for products Impact of employee volunteer programs	Employee surveys Community investment report Training records CSR reports
Extended value chain	Data from the extended value chain, focusing on product life cycle impact and end-of-life disposal	Carbon footprint of supply chain Percentage of materials recycled at end of life Emissions from transportation of raw materials Sustainable sourcing certifications Water usage across the supply chain	Supplier reports Life cycle assessment studies Logistics records Sustainability audits
Biodiversity and Ecosystem Impact	Data on initiatives to protect and restore biodiversity and ecosystem	Number of trees planted Area of habitat restored Species population changes in areas where the company operates Partnerships with conservation organizations Impact of agricultural practices on local ecosystems	Conservation project reports Environmental impact assessments Biodiversity monitoring programs NGO partnerships
Health and safety	Data on workplace health and safety as well as employee well-being initiatives	Number of workplace accidents reported Percentage of employees participating in wellness programs Results of product safety tests Employee health data Compliance with workplace safety regulations.	Incident reports Wellness program participation records Product testing reports OSHA records
Financial impact	Data on the financial implications of sustainability practices.	Costs saved through energy efficiency measures Amount raised through green bonds Revenue from eco-friendly product lines Cost of compliance with environmental regulations Savings from waste reduction programs	Financial reports, Sustainability bond documentation Sales records Green finance reports
Innovation and R&D	Data on research and development projects focused on sustainability.	Number of sustainable technology patents file Investment in R&D for renewable energy Partnerships with universities or NGOs for sustainability research Development of biodegradable materials Advancements in carbon capture technology.	Patent filings R&D budget reports Collaboration agreements Grant reports

Table 2. A list of sample important sustainability-related data that might be used in sustainability reporting

Metrics and KPIs aligned with the principle of materiality

With the CSRD emphasizing better transparency and accountability, companies must adopt a more rigorous approach to sustainability disclosures. Incorporating specific KPIs and metrics ensures that the sustainability report is both relevant and actionable.

KPIs aligned with materiality help organizations address the most pressing environmental, social, and governance issues affecting their business. This also enables companies to efficiently allocate resources, drive performance improvements, and meet regulatory requirements.

Materiality entails aspects of sustainability that are most significant to the company’s business model and stakeholders. Some KPIs, such as GHG emissions, energy and water consumption, and waste management, are obvious examples. However, there are also other crucial metrics that have a direct impact on a company’s sustainability performance that tend to be overlooked.

Stakeholders, too, are multifaceted, including investors, customers, consumers, suppliers, employees, regulators, and the broader community. Meeting their diverse expectations requires a comprehensive set of KPIs that provide a clear and accurate picture of the company’s sustainability efforts.

Stakeholders	Examples of Materiality-Related Sustainability Data	Sample Data Source	Why They’re Overlooked in Sustainability Reports
Investors	Scope 3 emissions from product use and disposal ROI on sustainability initiatives Climate risk assessments Environmental compliance costs	Carbon footprint assessments Financial impact studies Climate risk analysis Environmental compliance reports	Complexity and resource intensity Lack of standardization Data integration challenges Limited expertise Inadequate data collection systems
Customers	Life cycle emissions of products Customer satisfaction with sustainable packaging Data security incidents related to product use Transparency in product ingredients Product recyclability rates	Life cycle assessment reports Customer feedback surveys Data protection incident logs Ingredient transparency disclosures Recycling program records	Focus on simpler metrics Data collection challenges Lack of standardization Privacy concerns Insufficient tracking systems
Consumers	Toxicity levels in product materials Impact of end-of-life product disposal Ethical sourcing of raw materials Consumer health impact Packaging waste reduction	Product safety testing reports End-of-life impact assessments Ethical sourcing audits Consumer health studies Waste management reports	High complexity Lack of standardization Difficulty in quantification Inadequate data collection systems Privacy concerns
Suppliers	Carbon footprint of supplier operations Compliance with labor standards Use of renewable energy by suppliers Supplier diversity metrics	Supplier sustainability reports Labor compliance audits Renewable energy usage reports Supplier diversity records	Data collection challenges Lack of supplier transparency Resource intensity Inadequate data management systems Limited expertise
Employees	Mental health and well-being metrics Gender pay gap analysis Impact of work policies on productivity Employee turnover rates Participation in sustainability training programs	Employee health surveys HR compensation reports Work productivity rates HR records Training attendance records	Data sensitivity Lack of standardization Resource constraints Privacy concerns Insufficient tracking systems
Regulators	Compliance with new environmental regulations Third-party audits of human rights practices Transparency in political contributions Adherence to anticorruption policies Impact assessments for new projects	Regulatory compliance reports Human rights audit reports Political contribution disclosures Anticorruption compliance records Environmental impact assessments	Evolving regulation Complexity of compliance Limited resources Lack of independent verification Data integration challenges
Community	Impact of community development projects Effectiveness of educational outreach programs Local air and water quality measurements Community health initiatives Contributions to local infrastructure	Community development impact studies Educational program assessments Local environmental quality reports Public health reports Infrastructure investment records	High complexity Resource constraints Difficulty in measurement Lack of standardization Inadequate tracking systems

Table 3. Examples of materiality-related sustainability data that could be overlooked in sustainability reporting

Depending on the company, external data sources might also be needed to generate more insights, provide benchmarks, and enable trends to be analyzed and predicted. In 2023, for example, we engaged with one of the world’s leading CPG companies to develop and activate use cases for sustainability analytics for their recycling program. We were able to come up with use cases that not only helps the CPG company comply with regulations but generate business value from their sustainability efforts:

Predictive analytics for optimizing sorting rates in waste production
Streamlining design for recycling (DfR) and material use to improve recyclability
Analytics that use third-party data to understand recycling behaviors among consumers
Supply chain analytics for promoting responsible production, sourcing, and material use as well as improving the use of recycled materials that, in turn, reduces costs
Third-party data from reputable partners such as Closed Loop Partners, the World Bank, and Ellen MacArthur Foundation combined with internal datasets to generate actionable insights on the global recycling ecosystem

While there might be challenges in collecting and analyzing these kinds of data, the best data management practices, an appropriate tech stack, and the right domain expertise can help in having a more holistic view of the company's sustainability performance.

In the next part of our series, we will explore how data and analytics platforms can support comprehensive and compliant sustainability reporting.

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