Harnessing Data and Intelligence for Collective Advantage 2026

From visibility to change Better data alone does not automatically lead to better decisions or outcomes. Impact depends on how information is interpreted, shared and acted upon by different stakeholders. The Partnership therefore creates a platform for discovery, enabling participants to identify both where data generates value for their own efforts and where shared intelligence can unlock collective impact. This collaborative process provides the opportunity to develop impact pathways that link data to practical outcomes, such as improved risk targeting, more consistent remediation and stronger worker protection. Over time, these shared insights can inform responsible recruitment, investment priorities and policy design, allowing both individual organizations and the wider system to make better, more coordinated decisions.As shared visibility grows, incentives can begin to shift across the system. When credible information on risk and response is accessible to multiple actors, lagging performers face reputational and regulatory pressure to improve, while frontrunners gain recognition and reduced compliance burden. Governments and donors can direct enforcement or investment where it will have the greatest effect, and worker organizations can use validated insights to advocate for remedy. Comparable experience from other domains (such as public health, climate action and financial transparency) demonstrates how privacy-preserving data collaboration can raise performance standards without centralizing information.19 By enabling a similar architecture for the forced labour data ecosystem, the Partnership aims to transform disconnected activity into a virtuous cycle of insight, collaboration and coordinated prevention over time. Alignment of incentives, impact and technology case for collective impact FIGURE 2 Collective impact Technology is not viableLimited adoptionNo collective impact and potential harmsIncentives case In addition to impact, delivers clear value and aligns incentives with each stakeholder group: – Business – Government – UN/international organizations – NGOs and civil society – Trade unions Impact case – Data enables interventions that reduce forced labour – Supports enforcement, remedia- tion and worker empowerment – Turns fragmented insights into systemic actionTechnology case – Federated architecture ensures data sovereignty – Multilingual NLP , federated AI for integration – Advanced analytics for actionable insights Source: World Economic Forum Better data alone does not automatically lead to better decisions or outcomes. Impact depends on how information is interpreted, shared and acted upon by different stakeholders. Harnessing Data and Intelligence for Collective Advantage: Ending Forced Labour in Global Supply Chains 12