Human trafficking is a gross human rights violation that requires multifaceted and systemic interventions to combat. People of all ages are exploited into forced labour and commercial sex in each of the 34 provinces of Indonesia, which is a major source country and, to a lesser degree, a transit and destination country for human trafficking. Indonesian migrant workers can be vulnerable, and we observe many cases of human trafficking in domestic work, factories, construction, manufacturing, on palm oil plantations, and on fishing vessels. Domestic trafficking, including into sexual exploitation, is also a significant problem.
As with any problem, successful interventions must be based on solid, reliable evidence about what is happening, to whom, where, why, and how. Quite simply, without good data, we will never be able to put a stop to this problem. To be most effective, prevention strategies must be targeted on communities where victimisation is more likely to occur, protection efforts must be tailored to the stated needs of survivors, and prosecutions must rely on solid, reliable evidence.
Getting to Good Human Trafficking Data: A Workbook and Field Guide for Indonesian Civil Society complements Getting to Good Human Trafficking Data: Everyday Guidelines for Frontline Practitioners in Southeast Asia. These two documents should be referenced together as much as possible. This Workbook outlines critical ideas, questions, and exercises for you to work through with your team, while the Guidelines provide more background information and justifications.
The Workbook is intended to help frame an internal discussion around data in your organisation, to ensure you get the most out of the data you already collect, and to proactively address potential challenges you might face as a team in understanding or implementing these approaches. This workbook aims to be practical and actionable; think of this workbook as giving you the building blocks to create or enhance your organisation’s internal protocols and systems, particularly around data issues.
See the full guideline here.