When river starts running dry, start looking for water elsewhere.That’s what the global readymade garment (RMG) industry has been doing lately—reimagining apparel production line-ups and integrating technology for cutting cost and competition. Technological advancement and better efficiency are what the Bangladeshi RMG industry needs. This can be done with Artificial Intelligence (AI). The RMG industry in Bangladesh is celebrated as its leading (and dominating) source of export earnings. Our position in the global market as the second-largest manufacturer of garments is an accolade that we wear proudly, and the industry has provided immense support to the economic development of the country. AI, opposite to what is feared to be replacing people in the industry, can be used to embrace and create new opportunities. As far-fetched as it sounds, AI is a part of our daily lives: from Siri to Google search engine, to self-driving cars, customer service chat boxes and much more. Bangladesh is becoming a more popular apparel sourcing destination for western retailers thanks to the ongoing US-China trade war. Geographical diversification of sourcing is underway, driven by the need for cost optimisation that predates the current tariff battles. Up to three-quarters of businesses said they were already looking for suppliers in new countries or had plans to do so in 2018 and some of China’s long-standing competitors are emerging as their top choices. A notable portion of companies working in the cost-sensitive textile sector has mentioned plans to expand their sourcing to other Asian manufacturing hubs such as Bangladesh. Brands in this modern-day market stay on the lookout for super vendors who have smaller lead times, shorter order runs, more styles and produce high fashion. In order to keep competing in this in-season change and highly competitive sector and hold their position, manufacturers in Bangladesh need to start embracing digital transformation and transform themselves into super vendors. Bangladesh, according to an ILO report, has the lowest gender pay gap in the world. We have more than three million female garment workers who have graduated from abject poverty to a position of economic empowerment. The report also refers to “impossible” targets being set for workers. In compliant factories, the targets are set by industrial engineers and workers often find them hard to accept. But with time, most factories can explain that there is a clear relationship between wage and efficiency. Bangladesh, limping at a national average of 40 percent efficiency has a long way to go compared with other factories in the world sporting an easy 70 percent mark. When compared to 2016, there has been a 300 percent percent growth in investments in Artificial Intelligence capability in 2017 globally, as predicted by Forrester Research. An IDC research has predicted that the AI market will become worth more than USD 47 billion in 2020 growing from an USD 8 billion market in 2016. In case of Bangladesh, re-branding and digitisation of the RMG industry to meet the global sourcing requirements will also require successful adoption on industry automation. For this purpose, specific cases must be reviewed with an objective yardstick. Apparel retail, specifically, e-commerce, is driven by the fashions trending globally. AI can help computers identify images and recommend those products online which the customer is more likely to buy. E-commerce and M-commerce platforms, through AI capabilities, are able to leverage the information available about the customers and their inclinations, similarities and differences in the kinds of applications and products they seek. AI intervention in merchandising can help companies to not just analyse large data volumes, but also predict consumer trends, making merchandising operation error free, and more aligned to the customer needs. Apart from the capabilities discussed above, there is a sea of technologies that are already being offered by vendors like Amazon, Artificial solutions, Google, Creative virtual, Assist AI, etc. that apparel industry can use to improve its operating efficiency and gain cost advantages across the supply chain. Things like natural language generation, virtual agents, machine learning platforms, AI-optimised hardware, decision management, biometrics, robotic process automation and the list goes on. An average order planning time with manual systems is 35-40 minutes. Average order planning time with an automated system takes up to 7 minutes, giving vendors an 80 percent time reduction in order planning. With this improvement, if a factory produces 10 styles/day the lead time will be reduced by 5 hours in a day, 125 hours in a month and over 1,500 hours in a year. With the amount of time saved, more styles of clothing can be planned in a year with existing manpower. With order quantity shrinking per style and number of styles increasing, vendors can ensure that their costs don’t suffer. In order to survive, vendors need to reduce lead time so that they can handle more style changes, cater to in-season change and reduce the cost to bid for more orders. Thus, the industry is ripe to be disrupted by digital transformation. However, just like in a zero-sum game, what benefits business and industry, harms poor and marginal income groups. We will also have to take into consideration the possibilities of increased job loss and job replacement. Policymakers and industry practitioners will also have to adopt innovative measures to address these issues. In the competitive era of globalisation, the question is not whether or not we can sustain this position and adapt to the changing trends. The question is whether we are ready to embrace the technological change for a bigger gain.
