Client Success Story
Automated and data-driven materiality reporting
Trensition takes an AI-driven approach to analyse Barco’s ESG topics leveraging big data and artificial intelligence (AI) to create real-time insights that assess the materiality of known and emerging issues.
Case Study: Barco
Identify and prioritise the company’s most relevant environmental, social and governance (ESG) topics, considering each topic’s impact on the organisation and its stakeholders.
Strengthen Barco’s governance processes
Inform corporate strategy
Prioritise sustainability commitments, targets and programmes
Enhance and integrate reporting
Continuous monitoring of material issues is critical to stay on top of emerging risks and opportunities. A materiality assessment helps organisations understand what topics matter most to their business and stakeholders. Every three to four years, Barco conducts a comprehensive materiality assessment to make sure the latest developments are reflected in its business and external environment.
The most recent assessment, which was performed in 2020, was based upon and aligned with its integrated reporting approach and looked at six domains.
One hundred and eleven stakeholders participated in the surveys and interviews. The resulting materiality matrix has three categories: low, medium and highly material topics.
Historically, the outputs of these assessments are static in nature, capturing a moment in time and often resulting in a backwards-looking view of business priorities. This static perspective quickly loses its value as organisations seek to develop strategies and disclosures that anticipate future conditions and business needs. However, the advent of dynamic materiality is highly likely to change this static perspective and disrupt the future of sustainability and enterprise risk management.
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