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
Sector: Technology
Employees: 3.300
“To achieve success in the coming decade, investors and companies must adopt forward-looking and proactive approaches to materiality.”
Source: Embracing the new age of materiality: harnessing the pace of change in ESG,
World Economic Forum
Strategic Question
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.
Objectives
Strengthen Barco’s governance processes
Inform corporate strategy
Prioritise sustainability commitments, targets and programmes
Enhance and integrate reporting
Challenge
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.
Solution
Trensition performed an AI-driven analysis of Barco’s materiality matrix. Based on AI and big data, its technology automatically scanned and analysed millions of data points from a wide range of sources to identify and predict ESG topics and score them on the industry context of Barco and its stakeholders.
Impact
While a dynamic materiality assessment – and the dynamic ESG mindset that accompanies it – cannot be used to predict the future, it can strengthen a company’s understanding of stakeholder needs and improve its ability to forecast risk. Because a dynamic materiality assessment is future-focused and risk-conscious by nature, it can serve as an effective precursor to more dynamic corporate ESG actions – such as governance or risk management – that enhance resilience and build stakeholder trust. As such, we observed that dynamic systems are not isolated to the topic of the materiality assessment, but can serve to achieve more integrated reporting.
Our analysis offered in-depth detail on how these material topics would most likely evolve in the coming years.
The most significant rises expected for the coming year are:
• Learning and development
• Diversity and inclusion
• Climate change and energy
The rise in the importance of people-related materiality topics could be explained as a result of the Covid-19 pandemic. On top of that, COP26, the UN Climate Change Conference in Glasgow, was a catalyst for the growing significance of climate change as a topic.
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