AI intervention in merchandising can help the company to not just analyse large data volumes but also predict consumer trends, making merchandising operation error-free, and more aligned to the customer needs
When the river starts running dry, start looking for water elsewhere. This is 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 the needs of the hour for Bangladeshi RMG industry which can be reintroduced by Artificial Intelligence (AI).
The RMG industry in Bangladesh is celebrated as the leading and dominating source of export earnings for Bangladesh.
Our position in the global market as the second-largest manufacturer of garments is an accolade that we wear proudly, and the industry has been immensely supportive for the economic development of the country.
AI as the daily driver
Artificial Intelligence, contrary to what was feared to be replacing people, can be used to embrace and create new opportunities. As far from reach 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.
Need for industry automation
Bangladesh is becoming a 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. To keep competing in this in-season change and highly competitive sector and hold their position, the manufacturers in Bangladesh needs to start embracing digital transformation and transform themselves into super vendors.
Concerns over socio-economic diaspora
The charity to which the money is being donated pledges equality for women. I cannot but agree to the cause, especially because in Bangladesh, according to the 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, (interstoff is certainly one of them), 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 is limping at a national average of 40 percent efficiency has a long way to go with other factories in the world sporting an easy 70 percent mark.
Meet the competition
When compared to 2016, there has been a 300 percent growth in investments in Artificial Intelligence capabilities development in 2017 globally, as predicted by Forrester Research. An IDC research has predicted that the AI market will become worth more than $47 billion in 2020 growing from an $8 billion market in 2016.
In the case of Bangladesh, re-branding and digitisation of the RMG industry to meet the global sourcing requirements will also require successful adoption on industrial 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, can leverage the information available about the customers, and their inclinations, similarities, and differences in the kinds of applications and products they seek for.
Merchandising in the apparel industry is a functional area that has to deal with large volumes of data. AI intervention in merchandising can help the company 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 set 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 1500 hours in a year.
With the amount of saved time, more styles of clothing can be planned in a year with existing manpower. With order quantity shrinking per style and number of styles increasing, the vendors can ensure that their costs do not suffer.
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.
As the former central bank governor, Atiur Rahman aptly put, "Collaboration of human and robot (cobots) could be a pathway towards integrating technological innovation in the apparel industry in Bangladesh."
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.
The writer is a development sector research professional. Her areas of interests includes RMG Automation, Energy & Environment, Green Finance and Sustainable Development. She can be reached at firstname.lastname@example.org