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Updated: Nov 21, 2019

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by: Koh Jia Rong

With the advent of technologies like automated factories, developing countries in the South East Asia region that rely on labour intensive manufacturing are facing the threat of losing a key component of their Gross Domestic Product (GDP). Development begins with industrialisation, with basic and simple industries traditionally taking up the first stage of this process.(1) With the route closed off due to automation, what pathway to a full industrialisation is left for low wage labour?


Technological advancements have allowed developing countries like China to produce goods with staggering quantities at a fraction of the cost due to automated factories, the latest of which is  Tianyuan Garments Co.’s $20 million factory that will produce 23 million t-shirts at 33¢ apiece(2). Whilst the factory is being built in Arkansas (USA), profits from these automations will be kept out of developing countries’ hands, who need it as a crucial step in breaking out of their emerging markets. Along with the loss in GDP, the largely unskilled labour force in these countries will face eroding wages and high unemployment.


What drives the push for automation? Several sports apparel companies, including Nike, in efforts to reduce costs and respond swiftly to consumer demands, have opted to increase automated processes in their production lines. Nike’s partnership with Flex (the producer of the Fitbit trackers) resulted in a factory in Mexico, where laser cutting and automated gluing are streamlining production costs and time.(3) Pulling out of emerging markets also sheds the stigma of exploiting cheap labour and sweat shops.

75% of Nike footwear factory workers are based in Vietnam, Indonesia and China, housed in 566 contractor factories in those countries. Already, executives are looking at costs minimisation, where turning to automation results in a 50% cut in labour costs, and 20% cut in material costs. This translates directly into a higher profit line – one that is already sapped by the onset of competition from other sports apparel brands. The International Labour Organization has reported that at least 2/3 of SEA, 9.2 million textile and footwear jobs are under threat of being replaced by automated processes. This translates to 4 in 5 workers finding themselves out of job as their parent companies pull out and close factories.(4) Whilst the passing of these sweatshop factories is not to be mourned, it is of great concern that the emerging markets will have now lost a valuable source of income, with alternatives rapidly dwindling as automation and robotics become vastly more efficient than a low-skilled employment force.


The risk of automation also varies according the specific labour market structure of the country. The proportion of jobs with the greatest risk of automation (Sewing machine operators, Street Vendors, Sales and Services attendants, Office Clerks) is highest in Vietnam (70%), followed by Cambodia (57%), Indonesia (56%), Philippines (49%) and lastly Thailand (44%). Comparing the countries with the greatest and lowest proportion of at risk jobs, Thailand holds the smallest share of low-skill employment (less than 10%), while Vietnam holds the highest share at 40%.(5) Whilst higher education levels does somewhat insulate against replacement, it is a hard fact that a sizable portion of population in these developing countries are caught in a poverty cycle and rely on subsistence farming and crop labour for a living. Another vulnerability of these countries is the concentration on specific industries which are susceptible to technological substitution (Agriculture, Garment manufacturing, Construction and Tourism).


As the technology for automation is quickly becoming available, it is prohibitively expensive for most and requires a depth of infrastructure not likely found in these developing economies. A likely scenario would be for companies that benefit most from automation to simply place their factories domestically or in a developed country where tech support and maintenance of advanced machinery is readily available, as with the case of Tianyuan Garments Co.’s Arkansas factory. There will be a great decrease in Foreign Direct Investments (FDI), in addition to the loss of available jobs. During the transition of a developing to a developed country, this FDI is all the more crucial as it provides the financial means for a country to build and expand, as well as providing employment and education (in the case of employment that requires skilled labour) opportunities for the local populace. In the case of Singapore, the transition from primary manufacturing and agriculture to more robust, self-sustaining industries(6, 7) which rely less on FDI was well underway before automation became prevalent. But what of the current groups of developing ASEAN countries?

A lack of FDI and glut of unemployment is likely to give rise to civil unrest and political strive, all the more making it difficult for emerging economies to grow, leaving the at risk countries in a rut of slow development all the more whilst developed countries further isolate them by moving further and further away from their traditional reliance on cheap, low wage labour.


As human needs and wants are unlimited, it is a matter of finding a new need to fill the gap left behind by automation. Maintenance work, tech support and infrastructure development are areas that will likely experience a boom / growth, as the machinery that runs in these factories will rely on such supporting equipment and skills. Along with these parallel growth industries, it is important to foster and nurture the sectors that display a low-risk to automation.

These include education and training, human health and social work activities, which rely heavily on human skills that cannot be emulated by machinery as yet. Human heuristics and the cultivation of creativity may lead to novel ideas which will create the important, distinct irreplaceable element that protects against automation. This can be achieved through corporate training and government initiatives.


Technology, once discovered, has the ability to leap-frog through generations. This allows emerging markets to completely bypass outdated technology and immediately acquire the latest generation of tech at a fraction of the cost it took to develop them. This accelerated process allows developing countries to somewhat catch up to their developed counterparts.

We can already observe the benefits automation and robotics have on infrastructure. The Myanmar Automated Clearance System (MACCS) was implemented this year to counter the $2 billion increase in imports, which was straining the outdated port to capacity(8). The system is designed to be as efficient as possible when allocating port resources, and takes care of everything: from cargo logistics to tax collection, increasing productivity. This was a joint venture with Japan, and is exactly the co-operation that allows for both developing and developed countries to reap the benefits of technology sustainably together.

Ironically, at-risk industries are themselves able to benefit the most from automation. Labour intensive agricultural tasks may be delegated to machinery, freeing up human capital, thereby increasing accessibility to education to those that require it the most to break out of the poverty cycle and move into high wage labour.


The onus is on the government to oversee and foster the introduction of technology into their economies to prevent mass disruption and reap the benefits of technology. Diversification of human capital into hard to replicate industries and the identification of new skills sets which represent job opportunities are the best approaches to adopt in the face of automation.


  1. Tim Worstall, (2017). If The Robots Steal All The Sweatshop Jobs Then How Will The Poor Get Rich? [online] Available at: [Accessed 12 Dec. 2017].

  2. Kevin Hamlin, (2017). China Snaps Up America’s Cheap Robot Labor [Online] Available at: [Accessed 5 Dec. 2017].

  3. Adam Minter, (2016). Asian workers need to wake up to automation [Online] Available at: [Accessed 14 Dec. 2017].

  4. Chang, Jae-Hee; Huynh, Phu (2016). ASEAN in transformation: the future of jobs at risk of automation Pg. 12 [Online] Available at: [Accessed 7 Dec. 2017].

  5. Chang, Jae-Hee; Huynh, Phu (2016). ASEAN in transformation: the future of jobs at risk of automation, Pg. 16 [Online] Available at: [Accessed 7 Dec. 2017].

  6. WorldBank. (2017). GDP of Singapore (current US$). [online] Available at: [Accessed 17 Dec. 2017].

  7. (2017). Statistics Singapore. [online] Available at: [Accessed 13 Dec. 2017]. 

  8. Thiha, (2016). Automated system available in border trade camps by 2018. [Online] Available at: [Accessed 15 Dec. 2017]

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