29 October 2026International edition
Vol. I · No.
29 October 2026
AI IN FASHION
DAILY
The daily briefing on AI in the fashion business
Where fashion meets artificial intelligence.
Merchandising & Buying · Stories

Pre-season buy sign-off checklist: data and decisions before commitment

Before final commitment, validate forecast assumptions, lock capacity, confirm suppliers, set margin floors, optimise size curves, align launch dates, plan promotions and build contingency scenarios.

hanged black plastic clothes hanger lot
Photo: Artem Beliaikin / Unsplash

KEY TAKEAWAYS Summary by the editors

  1. Wholesale orders typically run March to May for autumn collections, with bulk production lead times of 60 to 90 days and factory capacity booking recommended four to six months ahead.
  2. Apparel gross margins range from 40 to 60 per cent, whilst markdowns consume 20 to 50 per cent of net sales, making margin floor discipline essential to avoid selling at a loss.
  3. AI-powered demand forecasting has the potential to reduce inventory by five to 15 per cent and improve stockouts by 15 to 25 per cent according to McKinsey research.
  4. Size curves built from clean demand data, adjusting for stockouts and using only weeks when all sizes were in stock, prevent core-size shortages and excess fringe-size inventory.

What should buyers confirm before signing off on pre-season orders?

Wholesale buyers typically begin placing orders for Fall 2025 collections immediately following Fashion Week, with most orders submitted between March and May 2025. Before final commitment, merchandisers must validate that forecast assumptions, capacity bookings, supplier agreements, margin targets, size allocation, launch timing, promotional plans, markdown budgets and contingency scenarios all align with the business plan and protect profitability under multiple demand outcomes.

The checklist exists because pre-season sign-off locks in financial exposure months before goods arrive. Bulk production typically requires 60 to 90 days after PP sample approval, with peak season booking recommended four to six months ahead. Brand replenishment requirements have shifted from 12 to 16 week lead times pre-pandemic to four to six weeks in 2025, with the most demanding buyers targeting a four-week ceiling from order placement to shipment. For retailers working with longer lead times, margin protection starts at sign-off, not markdown.

How do you validate forecast assumptions and capacity before commitment?

AI-powered forecasting use cases, as noted in The State of Fashion 2025 by McKinsey and Company, have the potential to reduce inventory by five to 15 per cent and to achieve a 15 to 25 per cent improvement on stock-outs. Yet forecasts only create value when buyers confirm that demand projections reflect clean sell-through data, adjusted for stockouts and promotions, and that supplier capacity is booked to match the commitment.

Booking lead times now run 14 to 18 weeks at tier-1 plants (OneAim 2026 factory survey). Buyers must verify that factory slots are confirmed in writing, that fabric is secured or on order, and that production windows align with in-store launch dates. Converting demand projections into purchase orders through demand planning requires accounting for supplier lead time, minimum order quantities, and vendor reliability. A forecast without a capacity guarantee is a wish, not a plan.

What margin targets and markdown budgets protect profitability?

Apparel and accessories fall in the mid-range, with established brands achieving 40 to 60 per cent gross margins through strategies like vertical integration and targeted pricing. Markdowns consume 20 to 50 per cent of net sales, yet most retailers manage them with outdated tools. Buyers must set margin floors before sign-off to ensure no product can be marked down below break-even.

If your COGS is £18, holding cost £2, and fulfilment £3, your break-even is £23. With a 10 per cent margin floor, you should never mark below £25.30. Given that average retail net margins sit at 3.1 to 3.7 per cent, every pound below floor is real loss, not just lost margin. McKinsey estimates disciplined markdown optimization can improve margin rates by 400 to 800 basis points. Pre-season sign-off is when the markdown budget must be agreed and embedded in the buy plan, not treated as a surprise in-season.

How do you optimise size curves and avoid broken-size losses?

As soon as you have history, every guide says the same thing: work out what percentage of last season's sales each size was, and split the next buy along those shares. If 35 per cent was M, buy 35 per cent M. Build the curve from clean demand, using only weeks when every size was in stock and nothing was on markdown. Static curves contaminated by stockouts lead to core-size shortages whilst fringe sizes accumulate.

Best practice is to segment size curves by product category. Basics (T-shirts, tanks): Standard S/M/L/XL bell curve. Retailers should calculate adjusted demand for each size by identifying the average daily sales rate only during days it was in stock, then multiply by total active selling days. The resulting percentages become the optimal size curve applied to future high-level forecasts, reducing the margin drag from broken assortments.

Why must launch dates, promotional plans and contingency scenarios align?

Retailers generally start to introduce Fall collections in late July, with a full rollout occurring throughout August and September 2025. Early drops usually consist of transitional items like lightweight knits and layering pieces, while heavier apparel such as coats and cold-weather wear follows in early fall. Launch dates must be locked to production calendars, and promotional plans must reflect the markdown budget already embedded in margin targets.

Contingency planning, scenario planning, and operational efficiency reviews should continue to be central to every business in the sector, to ensure they can respond quickly to disruptions while maintaining product flow. Three scenarios (conservative, base, optimistic) let brands pre-decide how to respond instead of reacting in crisis mode. Scenario planning is not about predicting the future, it is about reducing the time between signal and response. At sign-off, merchandisers should document what actions will trigger each scenario, from delaying receipts to accelerating markdown.

What happens when sign-off discipline improves inventory outcomes?

Gap reported in its May 28, 2026 Q1 fiscal 2026 results that ending inventory was flat year over year, while improved inventory management supported underlying merchandise margin expansion even as tariff pressure weighed on merchandise margin. Disciplined pre-season planning, when executed with verified supplier capacity, margin floors and size-curve optimisation, translates into in-season agility and reduced markdown exposure.

The checklist is not bureaucracy. It is the mechanism that ensures every assumption behind the buy has been tested, every commitment is backed by capacity, and every margin target has a floor. Sign-off without the checklist is approval without accountability.

Frequently asked questions

When should wholesale buyers place orders for autumn collections?

Wholesale buyers typically place orders between March and May, immediately following Fashion Week, allowing 60 to 90 days for bulk production and factory capacity booking four to six months ahead of the selling season.

What margin targets should apparel buyers set before sign-off?

Established apparel brands achieve 40 to 60 per cent gross margins, but with markdowns consuming 20 to 50 per cent of net sales, buyers must set margin floors to ensure no product is marked below break-even, typically 10 per cent above cost plus holding and fulfilment.

How should size curves be calculated to prevent stockouts and excess inventory?

Size curves should be built from clean demand data, using only weeks when every size was in stock and nothing was on markdown, calculating adjusted demand by average daily sales rate per size multiplied by total active selling days, then segmented by product category rather than using a single curve across the range.

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