Social Criteria
ESRS S1: Working Conditions of Employees → 206 criteria
Main Criteria
1. Identification of Workforce Categories
Criterion: List and describe all employees and non-employees in the company’s workforce.
Type of Data: Semi-narrative.
Example Expected: Categorization of workforce into full-time employees, part-time employees, contractors, and temporary workers.
2. Description of Workforce Types
Criterion: Explanation of workforce types, including roles and nature of employment.
Type of Data: Narrative.
Example Expected: Description of roles such as production workers, administrative staff, and external contractors.
3. Negative Impacts on Workforce
Criterion: Disclosure of any material negative impacts on the workforce caused by the company’s activities.
Type of Data: Semi-narrative.
Example Expected: Instances of workplace accidents or layoffs due to operational restructuring.
4. Positive Impact Initiatives
Criterion: Description of activities aimed at generating positive impacts for the workforce.
Type of Data: Narrative.
Example Expected: Training programs or health benefits offered to employees.
5. Workforce Engagement Policies
Criterion: Disclosure of policies promoting workforce engagement and satisfaction.
Type of Data: Narrative.
Example Expected: Policy to improve employee satisfaction scores by 15% within three years.
6. Diversity and Inclusion Metrics
Criterion: Metrics related to diversity and inclusion across the workforce.
Type of Data: Quantitative.
Example Expected: Percentage of women in management positions or ethnic diversity ratios.
7. Fair Remuneration Practices
Criterion: Disclosure of policies ensuring fair and equal pay for all workforce members.
Type of Data: Narrative and quantitative.
Example Expected: Ratio of average salaries for men and women in similar roles.
8. Workforce Development Programs
Criterion: Information on workforce training and development programs.
Type of Data: Narrative.
Example Expected: Number of training hours per employee annually.
9. Grievance Mechanisms`
Criterion: Availability of mechanisms for employees to report grievances.
Type of Data: Narrative.
Example Expected: Description of anonymous reporting tools for workplace issues.
10. Occupational Health and Safety
Criterion: Measures and initiatives to ensure occupational health and safety in the workplace.
Type of Data: Narrative and quantitative.
Example Expected: Reduction in workplace injuries by 20% compared to the previous year.
ESRS S2: Working Conditions in the Value Chain → 76 criteria
Main Criteria
1. Identification of Value Chain Workers
Criterion: List and description of all value chain workers significantly impacted by the company’s activities.
Type of Data: Semi-narrative.
Example Expected: Categorization of supply chain workers, including contractors and outsourced employees.
2. Description of Value Chain Worker Types
Criterion: Explanation of the types of value chain workers subject to material impacts.
Type of Data: Narrative.
Example Expected: Details on temporary workers, seasonal labor, or subcontracted employees.
3. Assessment of Material Impacts on Workers
Criterion: Identification of material impacts on value chain workers, such as unsafe working conditions or wage disparities.
Type of Data: Semi-narrative.
Example Expected: Instances of human rights violations reported in sourcing operations.
4. Geographic and Commodity Disclosures
Criterion: Disclosure of geographies or commodities associated with significant impacts on value chain workers.
Type of Data: Narrative.
Example Expected: Identification of high-risk regions for labor issues, such as areas with known child labor concerns.
5. Policies Addressing Value Chain Worker Impacts
Criterion: Declaration of policies aimed at managing material impacts on value chain workers.
Type of Data: Narrative.
Example Expected: Policy mandating fair wage practices throughout the supply chain.
6. Stakeholder Engagement
Criterion: Processes for engaging with stakeholders to address impacts on value chain workers.
Type of Data: Narrative.
Example Expected: Regular dialogues with worker advocacy groups or local communities.
7. Tracking and Monitoring Systems
Criterion: Mechanisms for tracking and monitoring labor conditions in the value chain.
Type of Data: Semi-narrative and quantitative.
Example Expected: Annual audits covering 80% of suppliers.
8. Remediation Mechanisms
Criterion: Description of mechanisms for remedying issues faced by value chain workers.
Type of Data: Narrative.
Example Expected: Implementation of grievance redressal systems accessible to all value chain workers.
9. Training and Capacity Building
Criterion: Information on training programs for value chain workers to improve skills or awareness.
Type of Data: Narrative.
Example Expected: Delivery of health and safety training to 10,000 supply chain workers annually.
10. Commitments to Improving Labor Standards
Criterion: Disclosure of commitments or targets to improve labor standards within the value chain.
Type of Data: Narrative and quantitative.
Example Expected: Target to eliminate hazardous labor practices by 2030.
ESRS S3: Relationships with Affected Communities → 75 criteria
Main Criteria
1. Identification of Affected Communities
Criterion: List and description of all communities significantly affected by the company’s activities.
Type of Data: Semi-narrative.
Example Expected: Identification of indigenous communities impacted by resource extraction or development projects.
2. Description of Community Types
Criterion: Explanation of the types of affected communities subject to material impacts.
Type of Data: Narrative.
Example Expected: Differentiation between urban communities impacted by air pollution and rural areas affected by deforestation.
3. Assessment of Material Community Impacts
Criterion: Identification of material impacts on affected communities, such as displacement or health hazards.
Type of Data: Semi-narrative.
Example Expected: Instances of community relocation caused by mining activities.
4. Occurrence of Negative Impacts
Criterion: Disclosure of occurrences where the company caused or contributed to negative impacts on communities.
Type of Data: Semi-narrative.
Example Expected: Reports of water contamination incidents affecting local populations.
5. Policies to Address Community Impacts
Criterion: Declaration of policies aimed at managing and mitigating impacts on communities.
Type of Data: Narrative.
Example Expected: Policy committing to free, prior, and informed consent for projects affecting indigenous peoples.
6. Stakeholder Engagement with Communities
Criterion: Description of engagement processes with affected communities.
Type of Data: Narrative.
• Example Expected: Record of consultations conducted with local residents on project developments.
7. Monitoring and Reporting Mechanisms
Criterion: Systems in place to monitor and report on the impacts of operations on communities.
Type of Data: Semi-narrative and quantitative.
Example Expected: Annual monitoring of air quality in areas surrounding manufacturing plants.
8. Grievance Mechanisms for Communities
Criterion: Availability of mechanisms for communities to report grievances.
Type of Data: Narrative.
Example Expected: Establishment of a community hotline to address environmental complaints.
9. Programs for Community Development
Criterion: Description of programs aimed at supporting community development and well-being.
Type of Data: Narrative and quantitative.
Example Expected: Investment in education and healthcare infrastructure in affected regions.
10. Commitments to Respect Human Rights
Criterion: Disclosure of commitments or targets related to respecting and promoting human rights in affected communities.
Type of Data: Narrative.
Example Expected: Goal to achieve zero human rights violations in all operations by 2030.
ESRS S4: Consumers and End-Users → 74 criteria
Main Criteria
1. Identification of Affected Consumers and End-Users
Criterion: List and description of all consumers and end-users significantly impacted by the company’s activities or products.
Type of Data: Semi-narrative.
Example Expected: Identification of user groups exposed to product safety risks or misleading information.
2. Description of Consumer and End-User Types
Criterion: Explanation of the types of consumers and end-users subject to material impacts.
Type of Data: Narrative.
Example Expected: Differentiation between individual customers, business clients, and vulnerable groups such as children or the elderly.
3. Assessment of Material Impacts on Consumers and End-Users
Criterion: Identification of material impacts, such as health hazards, data privacy breaches, or product quality issues.
Type of Data: Semi-narrative.
Example Expected: Reports of adverse effects linked to product usage or service delivery.
4. Occurrence of Negative Impacts
Criterion: Disclosure of occurrences where the company caused or contributed to negative impacts on consumers and end-users.
Type of Data: Semi-narrative.
Example Expected: Instances of data security breaches affecting customers.
5. Policies to Protect Consumers and End-Users
Criterion: Declaration of policies aimed at safeguarding consumer and end-user interests.
Type of Data: Narrative.
Example Expected: Policy ensuring transparent product labeling and compliance with data protection laws.
6. Engagement with Consumers and End-Users
Criterion: Description of engagement processes to address impacts on consumers and end-users.
Type of Data: Narrative.
Example Expected: Regular surveys or focus groups to understand consumer satisfaction and concerns.
7. Monitoring and Reporting Mechanisms
Criterion: Systems in place to monitor and report on the impacts of operations on consumers and end-users.
Type of Data: Semi-narrative and quantitative.
Example Expected: Metrics on product recall rates or customer complaints.
8. Grievance Mechanisms for Consumers and End-Users
Criterion: Availability of mechanisms for consumers and end-users to report grievances.
Type of Data: Narrative.
Example Expected: Dedicated support channels for addressing consumer complaints.
9. Programs for Consumer Education and Awareness
Criterion: Description of programs aimed at educating consumers and promoting responsible use of products or services.
Type of Data: Narrative and quantitative.
Example Expected: Campaigns on safe product usage or data protection practices.
10. Commitments to Consumer Protection
Criterion: Disclosure of commitments or targets to enhance consumer protection and satisfaction.
Type of Data: Narrative and quantitative.
Example Expected: Goal to resolve 95% of consumer complaints within 48 hours by 2025.