The workforce in the clothing and footwear manufacturing sector is often mostly made up of female workers. Though these jobs require a high degree of skills, they are often underpaid, insecure and characterized by an uncertain future, in particular because of the risk of being replaced by automated equipment. So, how are women in the apparel and footwear manufacturing sectors affected by automation and technological upgrading? And do these factors favour men over women? In this podcast, ILO’s Valeria Esquivel, Employment Policies and Gender Specialist, and Senior economist David Kucera will help us examine these issues as guests.
Impact of automation on employment in the apparel and footwear industry
Unlike any other manufacturing industry, apparel and footwear industry is both labour-intensive and female intensive. While the industry has a strong potential to create jobs, they're often not decent jobs. They're commonly characterized by low pay, long working hours, and limited prospects. Now combined with that, recent studies have also argued that the jobs in these industries are at high risk of automation in coming years because many of the tasks within them are considered to be routine. David Kucera, in a research paper with Sheba Tejani, has shown that automation is often associated with the defeminization of employment, meaning falling shares of women's employment.
David’s research was based on the combination of three elements, namely, the strategic role of the industry in economic development, concerns about automation and technological upgrading in the industry, and studies on how technological upgrading across manufacturing, for the most part, lead to defeminization. This was done through case studies of factories in two countries, Mexico and Indonesia, and their two quite important apparel and footwear exporters. More specifically then in terms of method, what they did was we based our study on interviews with employers, with technology specialists, with women and men production workers, as well as with worker representatives.
Drivers and bottlenecks to automation
Valeria’s study focused on the technological bottlenecks associated with automation. For example, fabrics are difficult to handle and there is a wide range of products and size to be produced. So, they wanted to address technological bottlenecks at the level of factories. Other studies done studies also tend to underestimate how much skill is involved in production work in apparel and footwear, particularly in sewing where most of the jobs are. Though commonly classified as “unskilled” or “semi-skilled work,” many of these workers are in fact very skilled and the factories need them.
Valeria said that one of the reasons that women's skills were underappreciated and undervalued is because women often learnt how to sew as girls in their homes. So, the training they received, in fact, before joining the firm, was invisible. Thus, they focused in our case studies, not on jobs and their technological feasibility, but also on the economic feasibility. It is important to bear in mind that these investments are typically made by supply factories in the lower tiers of the global supply chain. So, the firms must bear the cost and the risks of investing in technology that is often new and relatively untested.
Particular gender impacts in Indonesia
David said that one of the things that distinguished Indonesia from Mexico was that three of the four firms they looked at in Indonesia were Better Work Factories. Better Work is a joint program of the ILO and the International Finance Corporation. What is known from prior studies is that participation in that program is associated, for the most part, not just in Indonesia, but a number of other countries, with better economic performance, but also reduced gender inequality by several measures, including gender pay gaps. What they found was that there was not a lot of strong evidence of, or even anecdotal evidence, of differences in the impacts of automation on men and women’s employment.
One of the things they were able to find is that technological upgrading has led to labour displacement at the level of the task. For example, in terms of fabric cutting, there were fewer workers per machine with higher output, but there wasn’t any labour displacement at the factory levels. Because of demand expansion in the sector, the demand for apparel and footwear is expanding, they saw in some firms of growth of employment during this period of technological upgrading. David concluded that technological upgrading from the point of view of the firms is as much about improving product quality and lowering rejection rates than dealing with issues of labour costs.
David went on to add that labour costs also played a role. In Indonesia, there were strong regional differences in the level of minimum wages. There was no national minimum wage there. It plays a key role in how firms locate their factories. It also means that firms who are in higher wage areas, they have this greater incentive to automate.
David’s final point was that, bringing in the gender dimension again, working on these automated or semi-automated machines was not necessarily associated with wage increases. What they saw in the factors used at was that there’s was very compressed wage structure. However, he said that some of those aspects might be unique to Indonesia itself and not general.
Gender impacts of automation and technological upgrading in Mexico
According to Valeria, what came as a departure from Indonesia was the fact that labour shortages in the industry and difficulty to attract young workers was consistently reported to be a driver of automation in Mexico. On challenges, she said that automation comes along with lots of changes in the system of production to adequate it to the automated or the new equipment, so it’s not an easy change to put in place. In terms of barriers, one firm told them that it doesn't make sense to automate more than they've already done because they sell artisanal parts which are done in the traditional way.
Valeria’s study also identified the persistence of gender segregation. Most female workers were still in sewing, and cutting was disproportionately male-dominated in the case of apparel. In footwear, the majority of workers in finishing were women, whereas the majority of workers shaping heels were men. They heard that there were no gender limitations in the hiring and placements of workers across tasks, but they saw the persistence of traditional patterns. Thus, it is not that gender segregation patterns are broken by technological upgrading, or the idea that tasks are less hard or strenuous. But on the other hand, that the automation happens but it is filtered through traditional gender patterns.
Valeria and her team did not see in Mexico what David observed in Indonesia as a process of defeminization of the industry, at least not in the short term as a response to automation.
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