For decades, most apparel brands and retailers across the world have relied on a two-season cycle, Spring/Summer (SS) and Autumn/Winter (AW), under which brands design, manufacture, and launch collections aligned to specific seasons. The process begins nearly a year in advance, with design teams forecasting trends and studying runway shows in fashion capitals like Paris, Milan, and New York and fabric mill trade shows. These events involve significant costs, including travel, sourcing discussions, and vendor negotiations. Once trends are identified, designers create collections that move through sampling, sourcing, production planning, and bulk manufacturing. After six to nine months of preparation, the collections reach stores, where retailers coordinate synchronised launches, so the entire assortment arrives together to present a cohesive visual story to customers.

What it Entails
Because lead times can stretch up to nine months, brands must forecast demand across markets well in advance. However, forecasts often miss the mark, so brands have made peace with 50–60 per cent sell-through at full price, with the rest getting cleared through end of season discounts. Such markdowns erode margins and expose the risks of long-range forecasting. In 2018, H&M’s operating profit tumbled by 62 per cent while grappling with ~$4.3 billion of unsold inventory after overestimating demand for certain collections.

The Operational Complexity
Seasonal, forecast-based planning creates several inefficiencies that brands must constantly correct. First is the challenge of unsold inventory management at store level, which must be transferred between stores, discounted, or cleared through outlet channels or online. In 2022, Gap Inc.’s merchandise margin fell by five per cent, with more than half the decline attributable to higher discounting.

Second, because the entire supply chain, from yarn manufacturers to fabric mills, follow the same calendar, factories and brand team face intense bursts of activity followed by periods of underutilisation, leading to capacity wastage and operational instability.

Third, to ensure coordinated collection launches, production timelines are locked months in advance, elongating lead times, and leaving little room to respond to emerging trends.

This rigidity also forces brands to adopt a ‘spray and pray’ approach: produce a wide variety of styles and hope that some will resonate with customers.

Over time brands have faced disastrous consequences of this rigidity: ASOS missed a key demand window due to delayed inventory arrivals, while Under Armour was slow to respond to the shift from performance wear to casual streetwear. Long time-to-market was one key factor attributed in Forever 21’s bankruptcy as it failed to meet customers’ demand for constant newness.

Why the Model Exists
The two-season model originated in Western markets where sharp weather shifts made clothing strongly climate-driven. Indian brands continued this practice assuming that trends evolved slowly, and customers demand freshness every six months. The industry also assumed most fashion products shared similar lifecycles, i.e., about six months of spring-summer or autumn-winter.

The Indian Fashion Cycle
In tropical climates like India, only ~15 per cent of apparel assortments like heavy winterwear or peak summer garments, are truly weather-driven, and even these are relevant to barely six per cent of the country. The remaining 85 per cent, like T-shirts, shirts, dresses, and denim, sell year-round. Also, in India, festivals and marriage dates influence purchases more than climate. Yet the two-season model persists, creating commercial and operational challenges.

Moreover, in the last few years social media has increased exposure to emerging trends and created a need to update wardrobes frequently. On the distribution side, online marketplaces have enabled brands to do multiple, even weekly drops of new styles with low inventory risk.

As consumer behaviour evolves, the future lies in flexible assortment strategies aligned with customer demand rather than rigid seasonal calendars. While winter jackets, swimwear, or monsoon-specific clothing remain seasonal, most categories can shift to dynamic, trend-driven release cycles.

Trends will differ: something like Oversized T-shirts will follow short trend cycles driven by youth culture and social media, requiring rapid design-to-store timelines while the wardrobe must-haves like denim, basic tees and formal wear will have longer lifecycles.

Rethinking the Model
Ultimately, brands must shorten the design-to-store lead time and align assortment strategies with customers’ buying pattern.

Brands like Shein are adopting advanced systems to detect emerging trends faster through monitoring of online searches, social media sentiment.

Brands like Zara and Boohoo reduce the development to store lead time through vertical integration by platforming fabrics, and owning the supply chain, accelerating time-to-market to as little as 15 days.

Brands like Athleisure Basics, Stitch Fix etc facilitate low MOQs per style to facilitate smaller experimental production runs, while D2C brands are pioneering online-first product testing to validate demand digitally before physical store rollout.

In the Indian market, Snitch launches new styles every 25 days, while Zudio conducts 52 micro-launches annually, aiming towards sustained inventory velocity and reduced obsolescence risk.

The real lesson is not that one should adopt fast fashion nor stick to the two-season cycle. Brands should define how their product offering drives customer purchase behaviour—seasonality, trends, or core wardrobe needs, and align their organisational processes and supply chains accordingly.