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TL;DR
Most fashion brands lose margin twice a season, once to markdowns on styles nobody wanted, and once to sales when a bestseller runs out of the right size. Both trace back to the same decision: how wide the assortment is and how deep each option goes. This post walks through how the leading assortment planning platforms approach that call, and where demand-led merchandise planning beats a seasonal template for width and depth decisions.
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At Increff, we've partnered with fashion, lifestyle, and retail brands to help merchandising teams make smarter assortment decisions that balance customer demand with inventory productivity. One challenge we've consistently seen is that determining the right assortment width isn't simply about offering more choices, it's about offering the right choices for every store, cluster, and customer segment. As product portfolios expand and consumer preferences become more localized, successful retailers rely on data-driven option planning to optimize depth, width, and allocation without increasing inventory risk. Understanding these principles is essential for building assortments that maximize sell-through, reduce markdowns, and improve profitability.
What is option planning and assortment width management?
Option planning determines how many different styles and how many size or color variations of each style a retailer should offer across stores, regions, or sales channels for a season.
Assortment width refers to the variety of products offered. A wide assortment includes many different styles but fewer units of each, while a narrow assortment focuses on fewer styles with more inventory available for each one
Flagship stores in dense urban markets can carry broader assortments, while smaller formats perform better with a tighter, deeper mix of proven sellers. Merchandising teams must tailor width and depth to local demand each season.
Why does poor assortment width planning cost fashion brands so much?
Getting the option count wrong shows up in two failure modes, often in the same season:
- Too wide, too shallow: Buying spreads too thin across styles that never build enough velocity to earn full-price sell-through, forcing markdowns to clear them.
- Too narrow, too deep: A handful of styles get overbought in sizes or colors the local customer doesn't want, while other stores run out of the sizes that do sell.
Roughly 44% of fashion retailers report ending a season with excess inventory, and markdowns touch an average of 40% of the goods they carry. That pressure traces back to decisions made months before a single unit reaches a shelf.
Which tools provide option planning and assortment management?
Five vendors come up repeatedly when fashion merchandising and planning teams evaluate assortment software, each with a different view on how width should be decided.
1. Blue Yonder drives assortment decisions through AI-driven localization, reading store-level demographics and sales history to recommend a product mix and size curve per location, tied to shelf capacity. It suits large, multi-format chains, though configuration depth can mean a longer rollout for mid-sized teams.
2. RELEX Solutions builds assortment planning into a unified platform that also runs replenishment, space, and pricing, letting planners set sales, margin, and volume targets and simulate assortments against them. It suits retailers wanting assortment and demand planning on one system, though its breadth leans more toward general merchandise and grocery than fashion-specific size curves.
3. Increff ties width and depth directly to store-level sell-through instead of a seasonal template, using attribute-based demand signals and NOOS classification to set option counts by cluster or channel as in-season sales come in. It suits fashion, footwear, and lifestyle brands wanting assortment calls grounded in daily demand data, built for these categories rather than as a general retail platform.
4. o9 Solutions positions assortment planning as one stage in an end-to-end chain, from Merchandise Financial Planning through range and buy planning to in-season management, all on one data model. It suits large enterprise fashion retailers wanting financial and assortment plans reconciled automatically, though that scale can be heavier than mid-market brands need.
5. Centric Software leans into visual, style-first planning, letting merchandisers build assortments on visual boards tied to its PLM suite. That fits design-led fashion and luxury brands planning alongside product development, though brands wanting tight in-season replenishment often pair it with a separate system.
Each tool handles part of the option planning problem well. Where most fall short for mid-market and high-growth fashion brands is connecting width and depth to daily, store-level sell-through rather than a seasonal snapshot.
How does Increff help fashion brands plan the right width and depth?
Increff's merchandise planning software ties option counts to what each store is actually selling, not a template carried over from last season.
Most “assortment width” issues aren’t really about having too many or too few products. They’re visibility gaps in demand that show up only after the season starts. Increff solves both.
Its attribute-based demand planning groups products by up to 17 attributes, so real demand carries across seasons even when SKUs change. Store DNA profiles capture each location’s demand patterns using past sales and seasonality. And NOOS classification identifies core, best-selling, and seasonal styles, helping you keep never-out-of-stock items available while trimming low-demand, long-tail bets.
Width and depth planning balances style count with proven size curves and live OTB. Range architecture moves these local plans, by cluster or channel, into the buy plan. This keeps option counts tied to real sell-through, not a flat national number.
Conclusion
The right fit depends less on brand size and more on three questions: how granular your store clusters need to be, how tightly decisions must connect to buying and OTB, and how much of your range is style-driven versus attribute-driven. Demand planning teams and merchandising and planning leads evaluating vendors should ask each one to show, with their own historical sales data, how a width and depth recommendation would have changed last season's sell-through.
Frequently Asked Questions
Q: What's the difference between assortment width and assortment depth?
A: Width is how many different styles or categories a store carries. Depth is how many sizes, colors, or other variants exist within each style. A wide, shallow assortment spreads budget across many styles with few options each; a narrow, deep assortment concentrates spend on fewer styles with more variants.
Q: How often should option plans be reviewed during a season?
A: Most fashion merchandising teams review option counts at least weekly once a season is live, using in-season sales and stock data to catch over- or under-performing styles before markdown becomes the only lever left.
Q: Can small or mid-sized fashion brands use enterprise assortment planning tools?
A: Yes, but implementation weight varies. Enterprise platforms built for global retail chains can take longer to configure than tools purpose-built for fashion merchandise planning at a mid-market scale, where merchandising and planning teams often need faster time to value.
Q: Is demand planning the same thing as assortment planning?
A: No. Demand planning forecasts how much something will sell; assortment and option planning decide which styles and variants to buy and stock based on that forecast. They work together, but merchandise planning teams treat them as separate, connected steps.
Q: Does assortment width planning work the same way across all fashion categories?
A: No. Categories with strong core, never-out-of-stock styles need different width strategies than trend-driven categories with short lifecycles, which is why attribute-based and NOOS-style classification matters more in fashion merchandise planning than in general merchandise.
Q: How does option planning connect to markdown rates?
A: Overly wide assortments spread demand too thin across styles, so more of them miss their sell-through window and end up marked down. Tightening width around proven demand and building depth into winners reduces the volume that needs a late-season discount.
Q: What data do I need before building an option plan?
A: Store-level historical sales by style and attribute, current stock positions, size curve performance, and financial targets (OTB and margin goals) for the season.