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Automation and robotics may squeeze Asia’s garments industry

Advances in robotics and process automation aided by emerging technologies like artificial intelligence may negatively impact the ready-made garments industries of the world’s largest textile exporters like China, Bangladesh, Vietnam, Cambodia, etc over the next 5 to 10 years.

Bangladesh is the second largest garments exporter in the world after China, and over 80% of Bangladesh’s total export earnings come from the garments sector, which also employs about 3.5 million people. Vietnam gets 15% of its total export earnings from the garments industry, while employing about 2.5 million people in the sector.

Both Bangladesh and Vietnam exports about $30-$35 billion of garments annually, but Bangladesh relies more on the sector for its overall export earnings, and therefore, Bangladeshi GDP relies more on garments than Vietnam. This makes Bangladesh vulnerable to any major negative shift in the garments manufacturing industry such as a reduction in the required labor force or a reduced export volume.

A recent study by McKinsey’s illustrates the prospect that with changing dynamics of product marketing along with recent advances in manufacturing through automation, garments importers from Europe and the US may find it attractive to produce a good portion of their imports closer to home within the next decade. About 25% of global sourcing executives in McKinsey’s survey said they believed that by 2025 more than 50% of their imported ready-made garments will be manufactured near Europe and the US, away from Asia. About 42% of the respondents believed that more than 30% of the imported volume will come from sources near Europe and America by 2025. This may mean a significant loss of business and employment reduction for many garments manufacturing nations.

Shifting Changes in Fashion Marketing and Demand Generation

There is a tectonic shift taking place regarding how clothing is marketed and how demand for fashion is generated. Gone are the days when major brands had a linear process-flow, where few designers designed the next round of fashion based on their sense of consumer appetite, orders were placed, and the wait for 30-60 days to bring the final product to the destination markets began. Also gone are the days when major brands could generate fashion trends and shape consumer demands by mass marketing alone.

Today’s high-fashion has transformed into fast-fashion, where consumer demand evolves fast and is fickle. Celebrities and social media influencers are generating today’s fashion concepts, as they are often accidentally ending up creating the latest fashion trends, forcing major brands to react and follow. Such fast-paced fashion trends and marketing mechanism rewards niche, small-sized, and internet-based fashion brands or retailers who can quickly transform a concept from its first sight to replication and a finished final product within a short product cycle.

Such quick and reflexive product cycles are now catching up with the major brands, who are exploring agile production processes, where they can quickly react to a fast emerging fashion trend and immediately market a smaller volume of product, instead of waiting for millions of pieces of garments to arrive via an ocean-going vessel in bulk.

Rising Labor and Transport Costs Dent Asia’s Edge in Manufacturing

Over the last two decades, the fashion industry was “cost focused”, helping several Asian countries with the cheaper labor to win orders. Today’s importers now have the luxury to charge consumer some extra premium if they can market fast-fashion items within the shortest period of their discovery.

Labor cost in Asia is rising. China is already more expensive than Mexico for specific expertise. In light of these two majors trends: availability of a moderate premium for faster delivery of latest fashion and rising labor costs in Asia, it now makes economic sense to bring some garments manufacturing near to the destination markets of Europe and America. This is what the industry refers as “near-shoring”, which is an off-shoot of “off-shoring”.

Take for example the case of a pair of jeans. Including 30 days of sea-based container shipment time and cost, a pair of jeans costs $10.68 to bring from Bangladesh to the US market. Manufacturing the same pair of jeans in Mexico, with 2 days of land-based transport cost included, costs $10.57 — just marginally lower than Bangladesh. Producing the same unit currently in the US will cost $14.05.

Automation and Robotics may dramatically reduce garments employment in Asia

Now enter the future where automation, robotics, and artificial intelligence will dramatically reduce both manufacturing costs and time over the next decade.

Sewing is the most costly and labor-intensive process in garment manufacturing, accounting for more than half of the total labor input per garment. Sewing also remains the most difficult part of the process to automate or robotize, given the difficulties in handling fabric using robotic arms.

However, there are several recent ground-breaking innovations in sewing technology enabling robots to easily handle fabric for producing simple garments like t-shirts. Existing technology now, in fact, makes it possible to automate 90% of the sewing for a t-shirt.

With newer technologies being developed, it will be possible to automate sewing for even complicated clothing like a collared shirt or a pair of fancy-dress pants over the next decade. Warehousing, fabric handling during sewing, shipping, and storing of readymade garments is the next most labor-intensive process within the garments life-cycle. Given their more predictable nature, warehousing of fabric is an easier process to automate. Therefore, significant cost savings are assumed to be already on their way over the next few years coming from robotic picking, packaging, boxing, storing etc.

Emerging technologies like gluing instead of stitching of fabrics are also progressing fast. Once the gluing technology is perfected, robotic manufacturing of clothing will make major leaps forward, because it is much easier to glue fabric with mechanical arms rather than stitching. Gluing is currently used for sports and performance clothing mostly, but the use of this technology is expected to expand into other types of regular wear over time.

Automation in sewing and warehousing over the next 5 to 10 years alone can materially alter the profitability and sourcing calculus of major importers in Europe and the US.

As shown earlier, a pair of jeans already costs almost the same to produce in Bangladesh and Mexico, when shipping is factored in.

In a conservative future scenario, if sewing and warehousing costs are reduced by 20% through automation, near-shoring of clothing will make a ton of sense for the American and European brands.

Countries like Turkey, Mexico, Morocco, and several South American nations and Islands will benefit from near-shoring, at the expense of Asian garments powerhouses like China, Bangladesh, and Vietnam.

In a more optimistic scenario, if someday robotics and artificial intelligence reduce garments sourcing costs by 50% to 70% through automation of sewing and warehousing, then not only near-shoring but also bringing the entire garments manufacturing to the destination homelands in Europe and America may also make sense.

Such a scenario is probably 10 to 15 years away with just some stroke of luck, and with no unforseen hindrance towards the current break-neck speed of innovation.

Future automation in garments manufacturing does not necessarily mean the total collapse of garments exports for the current garments power-houses like Bangladesh or Vietnam. These countries that relied mostly on cheaper labor for garments have already started automating their manufacturing process using robotics and machine arms. Given the expanding economies of the Asia region, there will be ample scope for exporting clothing within the expanding Asian markets for Bangladesh and Vietnam.

One thing is certain, though, the number of total labor force employed in the garments sector is more than likely to go down with automation, creating major challenges for the employment sector of countries like Bangladesh. If Bangladesh cannot replace such lost employment by finding other productive reallocation of the excess labor, there will be huge geopolitical and economic consequences, to say the least.

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