The Employers' Confederation of Thailand (ECOT), in collaboration with the Social Security Office (SSO) and the ILO, has launched a pilot project to support efforts to extend social protection coverage to migrant workers. A planning meeting held in Bangkok on 15 September presented initial results from the pilot and discussed next steps.
Thailand is a major destination for migrant workers from neighbouring countries, with nearly four million registered workers (Ministry of Labour, 2025). While most are eligible to enrol in the Social Security Fund, only about 25% are actually covered. As a member of the Social Security Office Board, ECOT has highlighted significant gaps in the registration and data management of migrant workers. These discrepancies mean that many migrants, despite being legally employed, remain outside the social security system.
A key challenge is the lack of accurate and integrated data to inform policy decisions. Currently, data on migrant workers is scattered across multiple agencies, each with its own system and little exchange or coordination. To address this, the pilot project in Kanchanaburi province tested practical models for inter-agency collaboration and data integration. The results are highly encouraging, providing evidence on feasibility, costs, and benefits for possible nationwide rollout.
Next steps from the pilot include:
- Establishing a permanent provincial coordination mechanism for data management.
- Finalising a "Migrant Worker Journey" visual tool.
- Developing an ECOT policy brief for submission to the Ministry of Labour and other relevant agencies.
The pilot culminated in the Kanchanaburi Sandbox National Expert Forum, co-hosted by ECOT, the ILO, and the Social Security Office, with senior participation from Ms. Xiaoyan Qian, Director of the ILO Country Office for Thailand, Cambodia and Lao PDR, and Ms. Nongluck Korvorakul, Deputy Secretary-General of the Social Security Office. The forum highlighted the importance of integrated labour migration data and its role in strengthening the Social Security Office's Big Data system-helping ensure inclusive, accurate, and sustainable outcomes for policy and practice.
