Overview

SESAMm structures ESG controversies into Events and Cases to transform fragmented media coverage into clear, decision-ready ESG signals. Rather than treating each article independently, this methodology enables users to track how ESG issues emerge, evolve, escalate, and resolve over time, while reducing duplication and noise.

This methodology is applied across one of the largest data lakes in the industry, comprising over 30 billion documents from more than 4 million sources across 100 languages, with 10 million new documents processed daily. Sources span premium news outlets, NGO websites, company websites, blogs, and discussion forums, with deep coverage across Europe, Asia, and emerging markets, providing insight into controversies that may not surface in mainstream international media. For a full overview of data sources, see Data Lake Sources Overview.

How This Supports Decision-Making

By structuring ESG controversies into Events and Cases, and then enriching them with intensity scores, risk categorization, and UNGC screening SESAMm transforms fragmented media coverage into clear, actionable ESG signals. This enables users to:

• Separate isolated incidents from persistent, escalating ESG risks
• Track how controversies emerge, develop, and resolve over time
• Support due diligence, ongoing monitoring, and comparative risk analysis
• Maintain transparent audit trails from high-level signals back to underlying source articles

Taken together, the methodology ensures that users are not simply seeing more data, they are seeing the right data, structured in a way that supports faster and more confident decision-making.