The fashion industry is going through a massive transformation. What used to be business driven by seasonal collections is now dictated by ever-changing trends fuelled by social media and fabric innovations. Styles that once lasted an entire season now come and go within months. Platforms like Instagram and TikTok have sped up this cycle, forcing brands to react faster than ever. But there is a major roadblock – traditional supply chains take too long. The typical process from concept to store still takes 6-9 months, making it hard for brands to keep up.

The Challenge: Slow Supply Chains and Missed Trends

One of the biggest issues in fashion today is the gap between fast-moving design teams and sluggish supply chains. The current system involves too many steps, and by the time a product finally hits the shelves, the trend might already be fading. This leads to smaller windows for selling at full price, cutting into profits. And even with the best forecasting, there is no guarantee of getting it right, some stores end up with too little stock, while others are left with piles of unsold inventory, forcing brands to slash prices and lose money.

Right now, most brands rely on spreadsheets and reactive strategies to fix these issues mid-season, but this approach is slow and outdated. The industry needs a smarter, more flexible way to operate.

Gen AI: A Partial Fix, But not the Whole Answer

Generative AI (Gen AI) is being hailed as a game-changer, helping brands predict trends and design more sellable products. But AI alone is not enough. If a brand still follows a long production cycle, even the most accurate trend forecasting would not help, it will be too late. Take the oversized T-shirt trend of early 2023-24 as an example. By the time many brands caught on and launched their own versions, demand had already dropped. AI is useful, but unless supply chains speed up, brands would not see real benefits.

Breaking Old Habits: What Needs to Change

To stay competitive, fashion brands need to rethink how they operate. Here are three key changes they should make:

  1. Fixing the seasonal calendar approach: Many brands believe that carefully planning out each step in a seasonal calendar ensures everything gets done on time. But teams juggle multiple styles at once, constantly switching between tasks. This stretches out development time, causing a bottleneck at the final stage. By the time the garments are produced, there is little room left for adjustments or early launches. A more streamlined, focused approach, working on fewer styles at a time, can help speed things up.
  2. Adapting to local markets: India follows the same Spring-Summer and Autumn-Winter collection cycle as Europe and the US, but the country’s weather patterns do not align with these seasons. Instead of copying Western models, brands should focus on what their customers need. A more tailored approach to product planning, based on real demand rather than outdated industry norms, would be far more effective.
  3. Shortening supply chain timelines: Brands may not have full control over their supply chains, but that does not mean they cannot optimise them. Instead of treating manufacturers as mere vendors, brands should build closer partnerships with them. When manufacturers have a stake in the brand’s success, not just in delivering orders at the lowest cost, they can work more collaboratively to ensure faster, more efficient production.

The Way Forward: Agile Fashion with Real-Time Tracking

The solution is to categorise products based on how long they stay in demand. Basics like white shirts, black dresses, and seasonal staples (e.g., winter coats) do not change as quickly as trend-driven items. These can be stocked in key locations to allow for quick replenishment to the store and warehouse of the brand. For such styles, there can be strategic tie-ups with the vendors who will maintain fabric stock as well.

Another shift is adopting a ‘one-in, one-out’ workflow in the season calendar planning cycle, meaning teams only take a certain number of open tasks at any point in time and add new tasks when previous ones are completed. Using digital workflow management systems, brands can track progress in real time, allowing for faster decisions and quicker production cycles.

Even with these improvements, challenges will persist during periods of stockouts and surpluses, as the lead time cannot be reduced beyond a point—typically 3 to 4 months. Brands must be prepared to adjust during the season, whether it is reorganising store layouts, shifting stock between locations, or restocking fast-selling items. Machine Learning (ML) can help by analysing sales data and suggesting the best course of action, ensuring the right products are in the right places at the right time and in the apt quantity.

Is This Really New?

Not entirely. Brands like Zara, Shein, and Zudio already follow many of these agile practices. However, larger, more established companies have been slow to adapt, mainly because it is tough to change from long-standing processes and mindsets. The key is to shift from seeing how the supply chain needs to change to changing consumer trends and treating suppliers to treating them as long-term partners.

Another game-changer is rethinking inventory management. Instead of sending all stock to stores upfront, brands should hold some back in warehouses and replenish it as they sell. This allows for better control and faster reactions to trends, ensuring the right products reach consumers before the next wave of styles takes over.