Business Situation
In a complex and rapidly evolving environmental, social, and governance (ESG) landscape, the client, a France-based sustainability platform, sought to elevate the quality, relevance, and accuracy of ESG data being delivered to its end users. The objective was to improve the platform’s overall performance through:
- Structured ESG data gathering and validation
- Refined survey frameworks and taxonomy aligned to multiple ESG standards
- Robust verification of key performance indicators (KPIs) using primary disclosures and credible external sources
The client required an expert partner who could blend technical rigor with domain expertise and navigate the nuances of evaluating private market entities, often characterized by fragmented reporting and minimal public disclosures.
SGA Approach
SG Analytics (SGA) deployed a hybrid delivery model, combining sector-specific ESG subject matter experts (SMEs) with artificial intelligence (AI)-assisted data extraction, tagging, and verification tools, enabling the client to operate with both speed and depth across global coverage.
Integrated Solution Framework
1. ESG Survey and Framework Assessment
- Conducted an in-depth review of ESG surveys aligned to frameworks such as the Sustainable Finance Disclosure Regulation (SFDR), Global Reporting Initiative (GRI), Sustainability Accounting Standards Board (SASB), and Principles for Responsible Investment (PRI)
- Identified gaps, redundancies, and unclear taxonomies to refine and optimize data capture
- Streamlined KPIs to better reflect relevance for private market entities
2. SME-Driven FTE Model Deployment
- Assembled a dedicated team of ESG SMEs across 10+ sectors, including financial services, energy, technology, healthcare, and manufacturing
- Trained SMEs on the client’s platform to ensuring familiarity with workflow logic, scoring standards, and source hierarchies
3. AI-Enabled Data Extraction & Validation
- Deployed SGA’s internal platform Intelligent Data Extraction and Tagging Tool (IDEAT) to auto-extract data from uploaded documents, including:
- Sustainability reports, policy disclosures, governance charters
- Employee handbooks, diversity, equity and inclusion (DEI) frameworks, and health & safety policies
- Leveraged IDEAT-QA, our AI-driven validation engine, to flag anomalies, missing data points, and inconsistencies across similar disclosures
- Verified all data points by analysts to ensure contextual relevance and clarity
4. Indicator-Level KPI Analysis
- Assessed performance across ESG themes such as:
- Greenhouse gas (GHG) emissions, renewable energy use, and biodiversity initiatives
- DEI metrics, whistleblower policies, and employee turnover
- Data privacy incidents, governance structure, and board independence
- Tagged and scored indicators based on industry materiality, regional expectations, and portfolio risk thresholds
5. Documentation and Process Standardization
- Created role-specific standard operating procedures (SOPs) and guideline documents for extraction, scoring, and annotation
- Developed standardized frameworks to enable scalable team ramp-up, ensure consistency across research cycles, and minimize analyst bias
6. Milestone-Driven Engagement Delivery
- Structured delivery in sprints across portfolio company clusters to provide timely insights for each customer
- Included transparent source referencing and confidence-level tagging for every data point extracted
Business Impact
- Strengthened ESG Performance Visibility
Delivered deeper, clearer, and more reliable insights into the ESG practices of private portfolio companies
- Improved Survey Optimization and Framework Clarity
Refined and streamlined ESG surveys to reduce confusion and enhance the relevance of captured data
- Tech-Validated, Human-Refined Data
Combined AI validation with expert oversight to reduce time-to-insight and boost confidence in data used for investor reports
- Standardized Workflows for Scale
Enabled operational scale-up through SOP-driven execution without loss of quality, critical for covering global private entities
- Enhanced ESG Advisory Support
Equipped the client’s customers with actionable ESG insights, sector benchmarks, and strategic recommendations to improve responsible investment alignment
Key Takeaways
- Human-in-the-Loop Architecture The project exemplified how human expertise complements AI tools, especially when navigating fragmented disclosures from private companies.
- Built for Scale and Accuracy By integrating a modular full-time equivalent (FTE) model with SOP-based workflows, the engagement enabled consistency, quality, and growth readiness.
- Reliable ESG Performance Insights Standardized data tagging, source referencing, and validation protocols ensured decision-grade intelligence.
Improved Client Value Delivery The client was able to offer more meaningful and timely ESG evaluations to customers, improving the credibility and performance of their platform.
