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Forced Labour Risk Detection Methodology

Completed

Developed a methodology to detect and remediate forced labor more effectively by targeting higher-risk locations with better data.

Guatemala
India
Kenya
Orange Chrysanthemums

Project Highlights

Funders

ISEAL Innovations Fund

Partners

UTZ, Ergon Associates and SAN Technical Partners IMO India, Africert and FIIT.

Implementation dates

November 2017
-
October 2018

Commodities

Not Crop-Focused

Beneficiaries

Standards systems and certification schemes (stronger detection/remediation playbook); sourcing companies and auditors (targeted risk assessments); and affected workers (more effective, victim-centered responses).

About the project

Forced labor in agriculture often remained hidden, and audit-only approaches struggled to detect it. In partnership with UTZ, SAN designed a methodology that better leveraged existing knowledge and new data to target higher-risk locations and improve assessment and detection across supply chains. The project also compiled initial, locally appropriate, victim-centered considerations for remediation, helping standards systems and organizations understand their role in responding effectively when forced labor was identified.

Outcomes

In the long term, the project improved how supply chains assessed vulnerability and detected forced labor. By equipping standards systems and other organizations with a practical methodology—and supporting its adoption—the work led to more effective, targeted identification of risks and cases across agricultural sourcing.

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