Advancing Living Wage for Garment Workers in Bangladesh

Project Description

Bangladesh is one of the world’s largest garment exporters, with approximately 4.3 million garment workers. Many of them work 50 to 70 hours per week and still struggle to meet their basic needs. Research by Clean Clothes Campaign and Fashion Revolution found that 96.7% of the garment companies surveyed do not pay their workers a living wage. Information on the wages paid in individual factories is rarely available, which makes it harder for brands to assess their own progress, and for trade unions, consumers and policymakers to review what companies report.

The project responds to this lack of transparency by collecting wage data directly from workers. Trade union partners use a secure digital survey tool, designed to work on low-end mobile phones and collects anonymous wage data. The aggregated results are intended for publication on Fashion Checker, an online platform that monitors living wage commitments of garment brands. Trade unions, brands, consumers and the International Accord can then use the evidence in their own work. The data will also be used to discuss wage findings with Dutch garment brands in two roundtable sessions, to report wage violations to the International Accord and the brands concerned, and to support consumer campaigns. Trade unions can also use the data in their own work.

The project is led by Clean Clothes Campaign (CCC), in cooperation with the Bangladesh Centre for Worker Solidarity (BCWS), the Bangladesh Institute of Labour Studies (BILS), WageIndicator Foundation and Wikirate. Its main target groups are garment workers and trade unions in Bangladesh, and brands that source from Bangladeshi factories, with a focus on Dutch brands.

Role WageIndicator

WageIndicator’s contributions are as follows:

• Survey design

WageIndicator developed the questionnaire together with CCC and BCWS, and coordinated the preparation of the survey translations.

• Digital tool

Built the survey in KoboToolBox, which workers answer using KoboCollect, and prepared a survey manual.

• Training

Trained the enumerators who conducted the interviews.

• Data management

Cleaned the data and delivered both a clean and a raw wage dataset.