by Evelyn Donatelli
Case Study: Bangladesh. The world’s second largest garment exporter, behind the Chinese mainland, is being impacted by the transition from human factory workers to automated robots and machines within the textile, clothing and footwear (TCF) sector, the sector within ASEAN states to be most affected by automation, according to a recent ILO report. Technology lagging after the Industrial Revolution automated sewing and material production includes stitching and final assembly (“cut and sew”), which until recently required large numbers of human workers. New jobs added in garment and textile sector has fallen new jobs added by the garment and textile trades has decreased to +60K a year, just 20% of the 300K new jobs added annually between 2003 and 2010, according to World Bank data. Textile production is already experiencing an outright decline in jobs.
In Bangladesh, workers in the garment industry earn > 82% of the nation's overall export income. The main export “product” is “cut and sew” labor, which is now being automated. Zahid Hussain, the World Bank’s lead Bangladesh economist refers to the nation’s capacity to pivot these 4M workers to a new industry as “a social time bomb.”
However, if companies can’t sustain themselves, where will fair wages come from? Companies must automate to reduce costs and maintain margin profit while offering competitive prices. Somewhat positively, the jobs that are being automated come with little quality of life for employees, such as physical injury endemic to the working environment. However, not having these jobs means not to have a source of income.
Perhaps the “automation apocalypse”, where humans are out of work due to the superiority in cost-effectiveness and accuracy of our own inventions, will create room for growth in Bangladesh. The historied “low labour cost” advantage held by Bangladesh is costing workers quality of life. Embracing automation in order to offer higher value-added products and services which require higher skills and wages would benefit both workers and the economy as a whole. The pivot will depend on the training factory workers receive and seek out following job losses to automation.