In the face of the escalating risk of modern slavery across different regions and sectors around the world, there is a growing demand for robust data among various stakeholders, including buyers and investors. While corporate social responsibility (CSR) and other sustainability reports provide large-scale data on business and human rights reporting requirements, much of it is simply ‘dumped’ without offering meaningful insights into the actual impact of business activities. Additionally, reporting does not equate to progress and according to the World Benchmarking Alliance,[1] as of 2024, 90% of the world’s 2000 most influential companies were not even halfway to meeting fundamental societal expectations on human rights, decent work and ethical conduct. Effective human rights due diligence and risk assessment requires greater transparency and access to reliable data for business and human rights requirements. This remains challenging for businesses sourcing from hard-to-reach contexts (such as those operating in remote locations, in marginalised communities, conflict zones or digitally excluded groups). A collective response and action from governments in origin and sourcing countries, businesses and civil society organisations is needed to create an effective data ecosystem that enhances data availability, accessibility, and interoperability.
Key conclusions:
- In order to be actionable, data must be robust, cross-referenced and validated from various sources; collected at multiple levels, from worksites and communities to industry and country-wide aggregations; and informed by worker voice, local conditions and risks in high-risk contexts.
- There are serious data gaps, particularly in informal sectors, lower-tier supply chains, and as regards gender-disaggregated data. Corporate data on its own is not sufficient to combat modern slavery; data from trade unions, civil society, survivors, and government sources is critical for designing and implementing effective interventions. A sustainable funding model is needed to ensure equitable cost-sharing in data collection, processing, analysis, and providing support to on-the-ground teams. Government action is needed to support data governance efforts at both national and local levels, including sustainable data collection and equitable cost-sharing.
- Data on modern slavery is highly fragmented across and within different sources, sectors, organisations and departments and is exacerbated by different regulatory frameworks, guidelines, and norms within and across countries, sectors, and organisations. Data standards need to be harmonised in cooperation and collaboration with EMDE stakeholders, including businesses, governments, unions, civil society, workers, and survivors; this can help avoid duplication of efforts and improve the reach and impact of data.
- Clear data-sharing agreements and processes, as well as robust security and privacy safeguards, would help build trust among stakeholders, addressing concerns about costs and confidentiality. A range of actors, including businesses, worker voice initiatives, labour inspectors and third-party platforms are collecting data for human rights compliances, but it remains siloed, inconsistently formatted, and often inaccessible due to proprietary concerns. Government should lead a data management approach, coordinating efforts across various entities to ensure effective data collection and sharing learnings, providing a clearer understanding of key issues and promoting concerted, aligned action to address them.
- The development of open-access data platforms could enhance transparency and accountability, facilitate informed decision-making and broader access to information among companies, sectoral-level organisations and trade unions.
- Continued investment in the use of emerging technology and other data solutions, including Earth observation, blockchain, artificial intelligence, and data analytics, can play a crucial role in building an effective data ecosystem for collecting, integrating, analysing and sharing reliable, actionable data, thereby reducing costs and enhancing transparency.