How does the future of manufacturing look like? Some may envision a factory equipped with high-tech, fully automated production line controlled through a centralised dashboard, automated detection of defects powered by artificial intelligence and autonomous drones in moving materials in warehouses. Such a factory of the future promises higher levels of production, greater efficiency, lower error rates and optimized use of workers skills in less repetitive areas — leading to greater profits and less waste.
The manufacturing sector has always been innovating and adopting new technologies. However, the rise of these new technologies, often labeled as a key part of Industrial Revolution 4.0 (Kagermann et al. 2016), has been touted by some as general purpose technologies that will fundamentally transform the sector. This has led to excitement and urgency amongst the private sector and governments to accelerate the adoption of these new technologies, with national policies rolling out a variety of incentives, policies and grants to encourage greater adoption.
However, this dream is littered with many potential obstacles and risks that potentially lead to the waste of capital and government funds. This fear is not unwarranted. For the manufacturers, many of these technologies have to be highly customised to fit the highly specific production lines of each factory — thus expensive to implement (Autor, Mindell, and Reynolds 2020). For example, the same automated robotic arms in a production line that requires more human intervention will need additional safety sensors to prevent accidents compared to one that requires fewer human interventions (Sanneman, Fourie, and Shah 2020) — thus the machine cannot be just bought off-the-shelf and used immediately in any production line. The high up-front cost also deter small- and medium- sized manufacturing companies to adopt technology, as observed in the US (Berger 2020). Successful adoption also depends on the collaboration between workers on the ground and factory/capital owners — a “bottom-up” approach have been proven to be more successful in driving technology adoption than a “top-down” approach (Autor, Mindell, and Reynolds 2020).
Manufacturing firms can learn from these lessons and craft the right technology adoption strategies — both in terms of technology adoption and skills upgrading. Similarly, policymakers can use these evidences to strategize national policies, incentives and grants to improve long-, medium- and short-term growth of the sector through technology adoption, increasing the productivity of the sector while ensuring continuous training opportunities for current and future workers.
Lessons for Malaysia?
Many of these studies mentioned are done in developed countries. The question is, will they apply for emerging economy countries which generally occupy a different part of the global supply chain? The needs of manufacturers in a country like Malaysia might be different from a country like the US. For example, many Malaysian manufacturers are OEM manufacturers that produce parts for products which are ultimately owned by large multinationals or foreign companies. Indeed, the heavily export-led electrical and electronics subsector dominates the total export for Malaysia, many of which produce parts for the major electrical and electronics globally. Electronic integrated circuits alone occupy 20.5% of total export value for Malaysia in 2018 (“The Atlas of Economic Complexity” n.d.). However, no comprehensive study on IR4.0 technology adoption in manufacturers and it’s effects on workers has been done in Malaysia today — a gap that is urgently needed for manufacturers, manufacturing associations and government policymakers to drive greater technology adoption.
Some manufacturing subsectors have higher rates of direct research and development intensity on average compared to others others (OECD Directorate for Science, Technology and Industry 2011). For example, the electrical and electronics subsector are in the high-technology manufacturing compared to textile manufacturers which are in low-technology manufacturing. When comparing the share of high, medium-high, medium-low and low technology intensity manufacturing, Malaysia’s share of high-tech manufacturing industry per national GDP (which includes electronics manufacturing) increased up to 11.9% in 1999, reducing down to roughly 7% in 2020 (Chart 1). In comparison, medium-low manufacturing industries (which includes refined petroleum products) increased up 7.3% in 2020.
The share of high-technology intensity manufacturing employees increased from 37% of all manufacturing employees to 42% in 2000, before decreasing to 33% in 2016 (Chart 2). In comparison, medium-low technology intensity manufacturing employees increased from 21.9% to 29% of manufacturing employees in 2016.
When put together, this seemingly indicating that high-tech manufacturing is slowly losing it’s importance in the economy compared to the other lower technology intensity subsector.
Does this mean that there has been a slowdown in technology adoption in Malaysia? Perhaps not — these categorisation makes assumptions that the inherent R&D intensity across an subsector is lower than another. Technology adoption in any subsector can improve productivity and increase efficiency. An in-depth study on the ground is important to fully capture technology adoption here.
Thus, as part of the “Work of the Future — Global Research Network” research in collaboration with MIT, we seek to understand technology adoption and it’s implications for workers in manufacturers in emerging economies such as Malaysia. Preliminary interviews have found that technology adoption, with the right ecosystem, skills, management and funding can boost productivity in a wide variety of manufacturing subsector. This can only more effectively happen when workers are involved in the process of technology upgrading. Understanding the needs of the different industry is key to identify the success factors for technology adoption and the right policies for Malaysia.
To do that, we seek to interview manufacturers across Malaysia. We would love to hear from a diverse group of manufacturers in different technology. If you would like to be part of our effort to understand how Malaysian firms can successfully adopt technology and inform policy, happy to get in touch through my email at zhai.gen@asb.edu.my.
Appendix
Reference
Autor, David, David Mindell, and Elisabeth Reynolds. 2020. “The Work of the Future: Building Better Jobs in an Age of Intelligent Machines.” MIT Work of the Future. November 17, 2020. https://workofthefuture.mit.edu/research-post/the-work-of-the-future-building-better-jobs-in-an-age-of-intelligent-machines/.
Berger, Suzanne. 2020. “Manufacturing in America: A View from the Field.” MIT Work of the Future.
Kagermann, Henning, Reiner Anderl, Jürgen Gausemeier, Günther Schuh, and Wolfgang Wahlster. 2016. “Industrie 4.0 in a Global Context.” acatech STUDY.
OECD Directorate for Science, Technology and Industry. 2011. “ISIC Rev. 3 Technology Intensity Definition.”
Sanneman, Lindsay, Christopher Fourie, and Julie Shah. 2020. “The State of Industrial Robotics: Emerging Technologies, Challenges, and Key Research Directions.” MIT Work of the Future.
“The Atlas of Economic Complexity.” n.d. Accessed June 3, 2021. https://atlas.cid.harvard.edu/.
