The fast fashion industry in India is experiencing a remarkable growth trajectory, with the market projected to expand by 30-40% in 2024. Currently valued at $10 billion, it is expected to reach $50 billion by FY31. Despite this rapid progress, fashion companies face significant challenges, particularly in maintaining profit before tax (PBT) margins, which remain in the single digits despite high markups. The extended lead times required to create and deliver new collections are a primary obstacle, leading to financial risks such as stockouts and excess inventory.
The Indian fast fashion market’s impressive growth comes amid increasing consumer demand and evolving fashion trends. However, the inability to keep up with ever-changing trends and promptly replenish stores with new collections hampers the industry’s potential. The prolonged lead times force brands to make design and production decisions based on future fashion forecasts rather than current trends, often resulting in a disconnect between market demand and store offerings. This disjoint can have substantial financial ramifications for fast fashion retailers, as incorrect predictions can lead to surplus stock or, conversely, empty shelves.
The Challenge of Extended Lead Times
One of the most pressing issues in the fast fashion industry is the extended lead times necessary to design and manufacture new collections. Brands aim to quickly capture and introduce current fashion trends into their stores. However, the protracted lead time mandates designing and manufacturing collections well in advance—around 7-9 months before they hit the market. This incredibly long pre-planning period often results in a mismatch between what is trending and what is available in stores.
This misalignment carries significant financial risks, leading to two critical issues: stockouts and excess inventory. Stockouts result in lost sales and unsatisfied customers, while excess inventory, which ties up capital, often necessitates substantial end-of-season discounts to clear stock, thereby eroding profit margins. For instance, imagine a brand with 1,000 stores eliminating excess inventory; it could hypothetically free up resources to stock over 250 additional stores using the same working capital. This demonstrates the potential for improving both top and bottom lines through more effective inventory management.
The consequences of an inefficient supply chain are evident. When collections hit the stores long after trends have shifted, retailers face difficulties in moving products off the shelves. This increases the need for markdowns to clear outdated stock, impacting profitability. Additionally, stockouts result from the lengthy design-to-shelf process, leading to missed sales opportunities and diminished customer loyalty. Therefore, brands must innovate their supply chains to streamline operations and align more closely with consumer demands.
Flexible and Adaptive Supply Chain Strategies
To combat these challenges, the article proposes a more flexible and adaptive supply chain strategy. While improving forecasting by employing AI and ML is a common approach, its limitations are evident through examples such as the failure of the ‘wedge’ sneaker trend and the ‘micro handbag’ trend. A more effective strategy involves drastically reducing lead times to allow for collections to launch closer to the season. This requires challenging current assumptions about lead times and exploring ways to reduce them significantly, necessitating calculated risks in stocking raw materials.
Reducing lead times can be achieved by adopting practices such as on-demand manufacturing and nearshoring production. By producing closer to the market, brands can significantly cut down transit times and respond more swiftly to shifting consumer preferences. Without the need to predict trends far in advance, brands can produce smaller, more targeted runs of collections based on real-time data. Additionally, aligning with agile supply chain partners who prioritize speed over traditional bulk manufacturing could make a substantial difference in the fast fashion industry.
Another key aspect of flexible supply chain strategies is the segmentation of the product portfolio by shelf life. This involves categorizing products into perennial items, short product lifecycle items, and very short product lifecycle items. Each category demands a tailored supply chain approach to maximize efficiency and responsiveness. Perennial items, those with longer lifecycles, benefit from steady, demand-driven supply chains, while items with shorter lifecycles require more dynamic and reactive systems.
Optimizing Supply Chains for Perennial Items
Longer product lifecycle items, such as classic white shirts, are always in demand. Their supply chain should be optimized by moving from pushing inventory to a demand-driven system, emphasizing reduced lead times, centralized stock at aggregated locations, frequent replenishments, and strategic partnerships with garment and fabric vendors to reserve production capacity. This strategy increases product availability, improves inventory turnover, and enhances sales without the reliance on heavy markdowns.
By focusing on a demand-driven system, brands can ensure that perennial items are always available to meet customer demand. This approach not only improves inventory turnover but also enhances sales and reduces the need for heavy markdowns, ultimately leading to healthier profit margins. Establishing strong relationships with suppliers and leveraging advanced inventory management tools enables brands to monitor stock levels accurately, order replenishments just in time, and maintain a balanced inventory without overstocking.
Furthermore, centralized stocking and omitting intermediaries can yield significant benefits. By holding centralized stock, brands can redistribute inventory swiftly across various locations in response to local demand patterns. This ensures quick replenishment and reduced lead times. Predictive analytics can further bolster these efforts by identifying trends in perennial item demand, enabling brands to optimize their inventory levels effectively.
Strategies for Short Product Lifecycle Items
Short product lifecycle items, typically made from popular fabrics, need to be quickly converted to new styles to match consumer preferences. Brands can stock undyed greige or dyed fabric to quickly create and replace sold-out styles from a design bank. This approach significantly reduces lead times, making it possible to react faster to store-level demand. By stocking undyed greige or dyed fabric, brands can quickly create new styles to replace sold-out items, ensuring that they can respond to consumer preferences in a timely manner. This strategy not only reduces lead times but also helps brands stay ahead of trends and maintain customer satisfaction.
The ability to pivot quickly in response to consumer preferences is vital for maintaining relevance in the fast fashion market. By retaining a versatile inventory of raw materials, brands can swiftly adapt their product offerings without the cumbersome delays associated with traditional manufacturing cycles. Utilizing a design bank allows for rapid style updates based on real-time sales data and fashion trends, ensuring that brands can avoid stockouts and excess inventory. This lean approach to manufacturing not only minimizes financial risk but also maximizes the utility of available working capital.
In addition to stocking versatile materials, implementing an agile design and production process is critical. Collaborating with design teams to create customizable templates and modular components that can be quickly assembled into new products saves time and resources. This system also enables designers to incorporate feedback rapidly, ensuring the final products align with consumer expectations. Such agility in production supports a just-in-time inventory model, minimizing the risk associated with long lead times and seasonal fluctuations.
Managing Very Short Product Lifecycle Items
Very short product lifecycle items cover true fashion items with very short lifecycles. The supply chain operates like a relay race, requiring efficient multi-project management. Issues such as starting tasks without complete information and shifting between projects cause inefficiencies. Implementing a flow system helps align team priorities with final due dates and controls work-in-process. This ensures focus on tasks that need immediate attention, avoiding bad multitasking and maintaining clear priorities.
Managing very short product lifecycle items demands a high degree of coordination and real-time communication across the supply chain. By employing flow systems and prioritizing tasks based on urgency and final due dates, companies can reduce the inefficiencies usually caused by juggling multiple projects. This strategic approach enables businesses to maintain focus and clarity, preventing the pitfalls of multitasking and ensuring that production stages are completed on time and without unnecessary delays. Enhanced coordination ensures that items with the shortest lifecycles are still produced and delivered promptly, minimizing the risk of missing market opportunities.
Given that 40-50% of items in a typical store’s portfolio fall into the core and short product lifecycle categories, differentiating between core styles and very short supply chains can help reduce management burden. Nevertheless, forecasting errors are inevitable; hence, in-season activities play a critical role in course correction. Implementing a proactive merchandise management system based on data analysis can trigger necessary retail planning actions, inter-store transfers, display assortment fulfillment, and decisions on style adjustments to maintain profitability.
Proactive activity during the season is essential to correct any forecasting inaccuracies. Employing merchandise management systems that monitor and analyze sales data allows for real-time adjustments in stock levels and product assortment. This dynamic approach aids in redistributing inventory between stores, optimizing display assortments, and making timely decisions about product modifications or markdowns. Such in-season adjustments maximize profitability by enhancing operational efficiency and responding effectively to the real-time demand of the consumer base.
The Role of Business Intelligence in Fast Fashion
The fast fashion industry in India is witnessing significant growth, with the market projected to expand by 30-40% in 2024. Currently valued at $10 billion, it is anticipated to hit $50 billion by fiscal year 2031. However, fashion companies face notable challenges, particularly in maintaining profit before tax (PBT) margins, which remain in the single digits even with high markups. One of the primary hurdles is the extended lead time necessary to create and deliver new collections, posing financial risks such as stockouts and excess inventory.
This impressive growth stems from rising consumer demand and changing fashion trends. Nonetheless, the industry struggles to keep pace with these trends and rapidly restock stores, hampering its potential. The prolonged lead times compel brands to base design and production decisions on future fashion forecasts rather than current trends, often causing a discrepancy between market demand and store offerings. Consequently, this misalignment can have significant financial impacts on fast fashion retailers, as incorrect predictions can result in either surplus stock or empty shelves.
