Labour Automation: The Fashion Industry’s Blind Spot

Labour Automation: The Fashion Industry’s Blind Spot

Alysha Parks for Girl Stats | Jan. 26, 2020

Securing female garment workers futures requires increased attention on an important blind spot that must not be dismissed by the fashion industry – labour automation

In our previous Insight piece, Girl Stats’ researcher, E. Fayette Plambeck, highlighted the fashion industry’s role in contributing to global female empowerment by improving its working conditions. Responsible businesses in the fashion industry that place investments for its employees as a priority can accelerate the achievement of the UN’s Sustainable Development Agenda’s Goal 5 (Gender Equality) and Goal 8 (Decent Work and Economic Activity).

While solutions to assuring protection for female workers can be as simple as strengthening the companies’ due-diligence, the ILO’s 2016 ASEAN in Transformation Report signals an important blind spot that must not be dismissed by the fashion industry – labour automation. Labour automation entails replacement of labour intensive methods like sewing and gluing with anything from robotics to artificial intelligence to control the manufacturing. As the mass-market of apparel moves away from labour dependent processes, automation has been praised as the solution to making manufacturing cheaper and faster. However, the adverse and long-lasting effects of automation on current workers have received less attention.

The ILO claims labour automation places 56 percent of all jobs in the ASEAN-5 (Cambodia, Indonesia, the Philippines, Thailand, and Vietnam) at high risk of displacement in the next decade or two. As the world’s main supplier for garment, textile, and footwear (GTF) alternative to China, the ASEAN-5 is left with its GTF industry highly vulnerable to unemployment and rising exploitative standards in an already precarious environment. In other words, in the next decade, improving working conditions in the GTF industry in ASEAN countries, which provides employment for almost 9 million people, most of whom are female, might not be enough. Responsible companies must adopt a future-focused outlook which may potentially imply adopting CSR programs to invest in young women’s education and training in addition to current effort to improve internal working conditions.

The Data Explains it all

ASEAN-5 Risk of Exploitation due to Automation (Verisk Maplecroft)

The fashion industry must then pay greater attention to analysis made by human rights experts providing supporting data on the impact of labour automation. The figure attached illustrates the application of Verisk Maplecroft’ Industry Labour Risk Indices to ILO’s data on 21 sectors. It reveals that in most ASEAN-5 countries, workers with high exposure to labour rights violations – which make up most of the manufacturing industry – face higher risks of automation. For example, in Vietnam, 67% of its workers – 36 million people – who are already working in substandard conditions are highly vulnerable to unemployment due to automation. 39% of Vietnam’s manufacturing industry is employed by the GTF industry, a heightened concern for global fashion companies sourcing from Vietnam.

How is this finding related to gender equality? The issue’s pertinence to women’s deteriorating economic ability is made evident in Vietnam and Cambodia where over 85% of GTF jobs are at high risk of automation when over 76% of GTF workers are women. In other words, about 2.6 million women in Vietnam and 600,000 women in Cambodia may be unemployed, leading to increased competition for jobs within their respective countries or other ASEAN nations (2018 Verisk Maplecroft Human Rights Outlook).

 The Direct Impact of Automation on Women 

Verisk Maplecroft and the ILO both address the negative impact of automation in the GTF industry: large amounts of unemployed women may start to lower their own labour standards for employment. As many of these women are low-skilled workers, a lack of employment opportunities may lead women to work in substandard conditions, where working conditions are not in line with national or international standards. In the worst cases, mass unemployment may lead to many women being trafficked into sexual exploitation or forced labour.

Women have also reported negative influence automation can have on the current employees who work alongside the machines. For example, a female garment worker from Indonesia, which is home to factories supplying companies like H&M, Zara, Adidas, and Nike, reports via Huffington Post that while machines have improved working conditions such as safety, she faced pressure from employers to work longer hours with higher quotas. The article quotes, “They wanted us to become machines.” 

Solution: What’s Next? 

The solution is not as simple as eliminating machines and rejecting labour automation. Labour unions in the GTF industry, such as Indonesia’s Garteks Federation of Textile and Garment Workers Union, claim dangerous exposure to harmful chemicals has been greatly reduced due to automation. However, they also suggest that planning and informing workers ahead of automation is necessary, as companies usually take two years to prepare for a new machine adoption. While this would not resolve the long-term decrease in employment for women, it at least leaves the women with a few years for preparation. During this time, companies can also focus on educating and training their female employees for newly needed roles in the automated factory or for their exit opportunities.

The long-term solution, however, does exist. The ILO claims in its report the core issue of automation displacing massive amounts of workers in the GTF industry has to do with a lack of skilled talent. ILO reports the immense impact education levels can have on the risk levels of an individual’s career. For example, in the Philippines and Thailand, primary school graduates were 90 percent more likely to be at high risk jobs compared to post-secondary graduates. However, countries in ASEAN-5 have not only lagged behind providing training for unemployed workers post-automation but also failed to solve issues of poverty that have increased barriers to education for low-skilled workers.

In order for businesses to contribute to the SDG Agenda’s Goals, responsible companies in the GTF sectors operating in places like ASEAN must realise that internal audit of working conditions will not be enough. Women’s empowerment in the GTF industry within the next decade entails companies investing in women’s education and skills to prevent women from entering work detrimental to their social and financial status. It also involves companies working in collaboration with local NGOs and advocacy groups focusing on women’s education to develop comprehensive and impactful CSR programmes.