ESG Data and Accountability

This DIXONTECH course equips professionals with structured knowledge and practical frameworks to manage ESG data with accuracy, transparency, and accountability. Participants will explore how high-quality ESG data supports sustainability strategies, regulatory compliance, and stakeholder trust. The program emphasizes governance, controls, assurance, and accountability models aligned with global ESG reporting expectations and best practices from leading institutions.

TRAINING TOPICS

• ESG data foundations and governance
• ESG metrics, indicators, and data quality
• Accountability and ownership structures
• ESG reporting, assurance, and transparency
• Risk, compliance, and continuous improvement

By the end of this training course, delegates will be able to:

• Understand ESG data structures and governance
• Design accountable ESG data ownership models
• Improve ESG data accuracy and consistency
• Align ESG data with reporting standards
• Strengthen transparency and audit readiness

TRAINING IS TAILORED TO

• Sustainability managers and ESG leads
• Risk, compliance, and governance professionals
• Finance and reporting specialists
• Internal audit and assurance teams
• Senior managers overseeing ESG strategy

TRAINING METHODOLOGY

The course combines expert-led presentations, structured frameworks, real-world ESG cases, guided discussions, and practical exercises. Participants apply tools to map ESG data flows, define accountability, and strengthen governance controls, ensuring immediate applicability within their organizations.

DAY 1:
ESG DATA FOUNDATIONS AND GOVERNANCE

• ESG concepts, scope, and data domains
• ESG data lifecycle and information flows
• Governance structures for ESG data management
• Roles, responsibilities, and data ownership
• ESG data policies and internal controls
• Data ethics, integrity, and transparency

DAY 2:
ESG METRICS, INDICATORS, AND DATA QUALITY

• Selecting material ESG metrics and KPIs
• Environmental, social, and governance indicators
• Data collection methods and data sources
• Ensuring data accuracy, completeness, consistency
• Managing estimates, assumptions, and proxies

DAY 3:
ACCOUNTABILITY AND OVERSIGHT MODELS

• Accountability frameworks for ESG performance
• Management accountability versus board oversight
• Linking ESG data to performance management
• Internal controls and escalation mechanisms
• Managing third-party and supply chain data
• Accountability in cross-functional ESG teams
• Aligning incentives with ESG accountability

DAY 4:
ESG REPORTING, ASSURANCE, AND TRANSPARENCY

• ESG reporting principles and structure
• Internal versus external ESG disclosures
• Data traceability and audit trails
• Preparing ESG data for assurance reviews
• Managing stakeholder expectations and trust

DAY 5:
RISK, COMPLIANCE, AND CONTINUOUS IMPROVEMENT

• ESG data risks and control weaknesses
• Regulatory compliance and supervisory expectations
• Monitoring, testing, and data validation
• Continuous improvement of ESG data systems
• Integrating ESG data into strategic decisions
• Building a sustainable ESG accountability culture