Effective due diligence through data-driven risk analysis
Global value chains often have negative impacts on the environment and human rights. Emerging regulations for due diligence intend to address these impacts by requiring companies to conduct business responsibly.
The range of topics, business activities and value chain stages to be considered increases complexity, making due diligence a challenge for many companies. To minimize negative impacts and develop adequate measures, focus and prioritization are essential success factors. Within this process, companies also need to consider the changing risk landscape and aim for dynamic solutions for their due diligence systems that reflect the current situation.
In light of these trends, BSD Consulting has developed an approach for effective due diligence through data-driven risk analysis. Thereby, BSD is providing a solution that can help companies to identify key risks for negative impacts, convince decision-makers and credibly meet the due diligence requirements of the guiding principles of the United Nations and the OECD.
The methodological foundation of the risk analysis is audit-based risk information from ELEVATE EiQ and other publicly available sustainability risk databases. EiQ is the comprehensive supply chain intelligence tool by ELEVATE, the parent company of BSD Consulting, which uses proprietary and annually updated risk data on sustainability issues in the supply chain. The EiQ database is built on over 12,500,000 audit data points and 500,000+ index values from more than 5 years and covering 200+ countries, regions and provinces as well as 13 key sectors.
BSD Consulting has implemented and customized the approach for data-driven risk analysis together with Swiss retailer Migros, in the form of a human rights risk assessment, and a food processing company, in the form of a comprehensive sustainability due diligence impact assessment. An overview of the results of these assessments has been presented in the BSD Webinar: Effective due diligence through data-driven risk analysis, on June 16, 2020.