Navigating Seasonal Slumps: Apparel Production Planning for Low Demand Periods
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The apparel manufacturing industry is beleaguered with challenges on several fronts. Economic uncertainty has led to volatile demand, and wars have clogged important trade routes, plunging the already fragile supply chain into utter mayhem.
Against this backdrop, striking the balance between their own capacities and ever-changing demand continues to elude manufacturers. They must look to digital transformation to compete in these tough times – but this reorganisation isn’t as easy as it seems. It comes with challenges of resistance to change, high capital expenditure costs, and integration nightmares.
The solution is for manufacturers to introduce this transformation, in the simplest way possible. But before we get to that, let’s take a look at the complexities present in manufacturing today.
Today, apparel manufacturing is embroiled in uncertainty. Supply chains that were already fragile are further strained due to ongoing geopolitical tensions in the middle east and Ukraine. Just as the industry was recovering from the logistical clampdowns placed during the COVID-19 pandemic, these crises have impacted international trade routes and rattled entire supply chains connecting manufacturing hubs in Asia to large markets in the West.
Pandemic-related restrictions created a bullwhip effect. Retailers stockpiled to avoid frequent shipments, but were met with poor demand as the pandemic subsided and economic uncertainty arose. Suppliers and manufacturers that had expanded capacities to meet the sudden demand boom from retailers during the pandemic were forced to scale down. However, despite economic stability (and demand) returning, manufacturers remain apprehensive about expanding factory capacities and workforces for fear of demand volatility rearing its ugly head again.
There is indecision – in addition to reluctance – around building capacity, which makes it difficult for manufacturers to reconcile erratic order volumes with static production capacities. They believe shop floors, labour forces, and machinery reinforcements will prove an expensive investment in times of uncertainty.
Technology solutions, however, are an investment that can help manufacturers utilise existing capacities optimally without having to plan risky expansions. These tools not only monitor ongoing activity on the production line, but can forecast future productivity and help plan schedules based on this data generated in factories.
The advance of Industry 4.0 – the fourth Industrial Revolution characterised by the use of software in creating intelligent factories – is nowhere as evident as it is in the manufacture and trade of consumer goods. Consumer goods manufacturers are using the cloud and big data throughout the production chain.
The manufacturing of FMCG products, especially perishable items like food, beverages, and cosmetics, relies on automation technologies across packaging, inventory management, quality control, and supply chain optimization. Smart packaging and inventory management software can generate analytics that help with devising distribution and storage plans. This, coupled with logistics data like road traffic conditions, provides real-time insight into the movement of finished goods.
Just like FMCG manufacturing, inventory, storage, and logistics management solutions can be used in apparel manufacturing. These also have benefits in overall supply chain management as they give visibility into the transition between manufacturing and shipment. However, just like FMCG, the implementation of these technologies is challenging for the apparel industry, too. Small to medium manufacturers might find the cost of technology solutions like MES and ERP to be too high.
Moreover, manufacturers may run into issues of integration with existing systems. For instance, customer relationship management (CRM) software might not be compatible with existing ERP solutions, causing longer turnaround times for integration. Finally, employees’ technical proficiency poses a challenge to usage within the organisation. In factories where digital transformation is being introduced, manufacturers might find resistance from the workforce to adopt new technologies.
Leadership must take these potential roadblocks into consideration and design strategies incorporating a staggered rollout of tech and employee education to ensure successful implementation.
It is an established fact that technology is no longer an option for apparel manufacturers. The next challenge for the industry is to align the adoption of tech solutions with uncertain demand and production requirements, as well as the proficiency of workers on the shop floor.
The solution to the challenge is this – tech solutions need to be made simple. The labour force employed in the garment manufacturing sector is often technically skilled. This means that they may have the know-how required for sewing, garment construction, and even operating machinery. However, automation and cloud based solutions are still developing and new to these workers. Management must design a tech adoption strategy that allows the people who are expected to use these tools every day to do so in a way that fosters repeatability and places minimum cognitive burden on them.
For example, a factory line manager responsible for overseeing daily activities should be able to track the production by monitoring progress made by workers and machinery. This would require a deep understanding of the MES. Such a worker should be trained in optimally utilising the MES to generate reports on real-time progress. Additionally, they should be able to use these solutions to develop weekly or monthly projections on capacities and how they can be utilised for future orders.
Other than user-centricity, the benefits of simple, modular, and scalable tech solutions are far-reaching. A workforce that is familiar with the usage of these tools is better informed about its own capacities. This is crucial for a manufacturing unit to respond to demand fluctuations sustainably.
Let’s take modularity for example – manufacturing technologies like MES and ERP span the entire production cycle. MES systems monitor and document everything on the shop floor from order receipt and raw material processing to the finished product. However, as important as it is for all these pieces to speak to each other, tech solutions should be able to perform monitoring, analysis, and reporting on each process separately.
Such modularity allows manufacturers to break down and get deeper insight into each step of the manufacturing process. This helps structure the shop flows better, and allows workers to take ownership of the segments they work in.
Manufacturers’ choice of tech solutions should also account for scalability. It is essential that technology used in garment manufacturing can be scaled up or down to make the most of factory capacities, irrespective of changing demand volumes.
Convenience is an important factor to consider when investing in a piece of technology that is meant for a large workforce. Simplified technology solutions are easier to use, and therefore, are quicker to adopt. Workers trained in operating software that is intuitive to manoeuvre can leverage it to increase productivity and efficiency.
Software solutions geared towards apparel manufacturing are designed to cover end-to-end production processes. However, modularity within these all-encompassing systems can spur adoption and productivity, especially in a production line. For example, an individual working in packaging is only interested in when a finished garment is expected to arrive before them, the availability of packaging materials, and the time to shipment. S/he cannot be expected to understand the operations of the entire MES. On the other hand, if they are trained in using only pieces of the software relevant to their role, it would result in increased efficiency without overwhelming them.
The benefits of adopting tech solutions in garment manufacturing are numerous, but disrupting decades of production practices isn’t easy. As manufacturers look to bring the benefits of Industry 4.0 to fashion, they are met with a unique set of challenges. Let’s take a look at these hurdles and how manufacturers across various consumer goods segments overcame them:
Most factories manufacturing consumer goods operate on legacy systems. The cost of digital transformation, especially for small-scale players, can be extremely high. McKinsey estimates that most companies have over 20% of their tech assets in the tech debt category, and 60% of CIO estimate that this rise has occurred over recent years.
Factory owners are expected to burn thousands of dollars to digitise their shop floors with MES, ERP, and data analytics solutions. This prospect is daunting for manufacturers to the extent that they often decide against digitising at all.
However, investment in these pieces of technology is essential to stay competitive in present times. So, instead of planning a complete overhaul from manual or analogue production, they may consider taking a staggered approach to tech adoption. Software solutions are often bundled together, but manufacturers may work out deals to purchase tech products required on priority. They may scale up their tech suites as and when production demands, thus saving on huge capital investment and enjoying faster ROIs.
The beauty of tech solutions for apparel production is that several pieces of software can be integrated with each other to create a neural system that acts as the factory’s brain. But integrating these diverse software with one another is a common roadblock that often requires up to weeks for resolution. Factory leadership must appoint a team of tech experts to carry out these integrations by working closely with the vendors providing these various services.
Often the challenge is that factories might be working with dated, on-site IT systems. However, cloud-based solutions are the future – they are flexible, can allow manufacturers to modernise financial records, and make the most of reliable data services. A digital overhaul is required that enables a switch to cloud-based solutions. The benefits of this would be far-reaching – with data and insights at their fingertips, manufacturers can make quicker decisions around capacity planning.
The garment manufacturing workforce might be skilled, but they are seldom tech savvy. In fact, years of working in assigned roles on the production line might create a culture that encourages comfort with analogue production and resistance to change. The challenge is reversing this culture to make way for adoption and usage of software by employees in house.
Manufacturers may consider constituting a small cross-functional team to address workers’ needs and hesitations with adoption of new tech solutions. Moreover, such a team should be empowered to focus on innovation – through experimentation, safe failures, testing, and iterative refining – to align available tech solutions more closely with the needs of individual factories. Making technology central to everyday functioning would bring in a mindset shift more attuned to tech adoption and foster dexterity with its usage.
Factory leadership may educate workers on the benefits of such tech like boosting efficiency and productivity. They may schedule routine training and refresher sessions aimed at teaching them how to use software resources. In fact, if certain repetitive tasks can be carried out by machines powered with intelligent software, workers must be upskilled and employed in positions that require concerted human efforts.
Software, as they say, is eating the world. The market is flooded with bespoke solutions for each industry – and they just keep on getting better. But all businesses are built differently, and are at varying stages of maturity. This means they need not give in to the false sense of urgency to stay ahead of the curve.
What most small to medium businesses in apparel manufacturing require is simple and effective software solutions, purchased and deployed on an as-needed basis. Especially in times like these, their focus should be on tackling uncertainties by making optimum use of their resources which can only be achieved through user-centricity, modularity, and scalability in tech solutions.