An Increff benchmark report · September 2026

Empty Shelves, Full Backrooms

Why U.S. footwear keeps losing margin one size at a time, and what nine live client engagements prove about fixing it.

Every number in the results section came from a live deployment, not a model.

Read this if

You own merchandising, planning, allocation, or supply chain for a footwear or sportswear business selling in the U.S., own retail, outlets, wholesale, or all three.

Time to read

12 minutes

What moved (Increff proprietary data):

65%

Abandoned a shoe purchase because their size wasn't available. Up 91% year over year.

67%

Price sits right next to availability as the leading sale-killer in footwear.

11.6% → 5.4%

Inside 105 days across ~264 doors, with daily size-level replenishment.

18%

Footwear unit sales still grew +3.2% year over year while inventory came down.

Footwear stockout rate

11.6% → 5.4%

in 105 days, ~264 doors

Top-seller complete size availability

67% → 100%

primary revenue drivers

Size-level demand mismatch

87% → 48%

nearly halved

Excess inventory (>120 days)

40% → 19%

of network

Days of holding

314 → 224

~90 days of capital freed

Sell-through margin

46.1% → 54.7%

+8.6 percentage points

Average markdown depth

52% → 45%

less discounting

Replenishment option efficiency

50% → 80%

more productive

And the growth that came with it: +3.2% footwear units on 18% less store stock. +7.3pp full-price sell-through. €3.7M (≈$4.3M) incremental full-price revenue in one season on the same footprint, 204,801 extra units. 26,000 idle pairs redeployed across a 30-store pilot for a 13% availability gain and ~8% revenue advantage over matched control doors, with zero new buying.

Better availability does not require more inventory. It requires putting the right sizes in the right stores.

01 — Three symptoms

One inventory problem, three symptoms

Ask three people in a footwear business what the inventory problem is and you will hear three different answers.

The store manager

Sees a bestseller with missing sizes.

The planner

Sees a DC full of size 6s that will not move.

The CFO

Sees the same problem later, after margin disappears into markdowns.

These are not separate issues. They are the same mistake showing up in three places: decisions made too late, on stale data, at style level instead of size level.

That is the argument in its simplest form. The rest of this report is the evidence.

02 — Board priority

Why footwear inventory accuracy became a board priority in 2026

Two things happened at once- Demand held up. Availability didn't.

After a year of tariff pressure, U.S. footwear retailers bought cautiously. Reasonable call. But caution applied at style level lands as broken size runs on the floor. The Spring 2026 AlixPartners–FDRA survey found 65% of consumers abandoned a purchase because their size was out of stock, a 91% jump year over year, with price still first at 67%. Retailers' wait-and-see approach to inventory is translating into thinner shelf availability exactly when demand is still active.

AlixPartners' Bryan Eshelman put the mechanism plainly: "Demand for footwear remains strong, but consumer tolerance for friction has collapsed." Shoppers research on their phones, walk in decided, and leave the moment their size isn't there. They do not defer. They go somewhere else.

Meanwhile the biggest brands in the category spent four quarters publicly cleaning up the consequences. The commentary below is not from consultants. It is from the operators.

03 — Operators

What the operators said

Meanwhile the biggest brands in the category spent four quarters publicly cleaning up the consequences. This is the part worth sitting with. The commentary below is not from consultants. It is from the operators.

Who	What they said	What it means for allocation
Elliott Hill, CEO, Nike	Nike's biggest action of the quarter was "removing unhealthy inventory of our classic footwear franchises from the marketplace", which cost about five points of reported revenue.	The world's largest footwear company chose to give up revenue to protect full-price realization. Availability alone is not the goal. Healthy availability is.
Bjørn Gulden, CEO, adidas	"The discipline of not overselling into retailers is therefore currently crucial."	Sell-in discipline is now a stated strategy at the #2 brand. Which means every unit you do ship has to land in the right door, in the right size.
Arthur Hoeld, CEO, Puma	"The big cleanup was done primarily during quarters three and four" of last year. He has also flagged "a mid-double-digit decline in our inventory levels at selected wholesale partners."	A full reset year, plus a plan to cut SKU count by a mid-to-high double-digit percentage by Spring 2028. Fewer options makes size accuracy on the survivors non-negotiable.
Ed Stack, Exec. Chairman, Dick's Sporting Goods	"The inventory of Foot Locker is probably cleaner than it has ever been."	It took a $218M gross-profit charge to get there. The clean-up is the expensive way to solve a size-and-store problem.
Oliver Reichert, CEO, Birkenstock	"The ultimate truth for brand health and momentum is sell-through at full price", held above 90%. He calls the model "capacity constrained by design."	Deliberate scarcity works only if the scarce units are in the right place. Scarcity plus bad allocation is just a stockout.
Stefano Caroti, CEO, Deckers (HOKA, UGG)	"High levels of full price sell through underscored our continued focus on quality sales."	Record year, inventory down 2%. The proof that growth and lean stock coexist.
Joe Preston, President & CEO, New Balance	"You're seeing a whipsaw effect in traffic trends", but consumers still show up for the big moments.	If traffic arrives in bursts, availability during those bursts is everything. A broken size run during back-to-school cannot be made up in week nine.

Read that table again and notice what nobody is saying. Nobody is saying "we need more inventory." They are all focused on precision: choosing the right unit, door, size, and week.

The proof point sits inside Dick's Sporting Goods. Its Fast Break remodel format runs a tighter footwear assortment, and those stores delivered double-digit comparable sales growth and higher merchandise margins. Less range, better placed, more money. That is the thesis of this report, tested at scale by someone else.

04 — Constraints

Why managing footwear like apparel costs margin

Most planning systems were built around apparel. Footwear adds five constraints those systems were never designed to handle.

1. There is no substitution

In apparel, customers will often size up or down. A medium tee shopper takes a small or large depending on drape. In footwear, a size 10 customer cannot wear a 9. So the miss costs you twice on the same style: an unrecoverable lost sale in the size you're out of, and dead stock in the size you over-shipped. No other category charges you both ways.

There is a second-order problem that is worse, because it corrupts your data. When a target size is out of stock, some sales shift to the next size up. Point-of-sale research on men's footwear puts that unnatural lift at roughly 23%. Your system reads a forced substitution as a genuine preference, tilts next season's size curve toward the wrong sizes, and locks the imbalance in. You now have a size curve built from your own stockouts.

2. The SKU math is brutal

One silhouette needs 10–13 sizes per gender. Add a second width and three colorways and one design becomes 60+ SKUs. A modest 20-style line is 1,200+ SKUs to forecast, buy, track, and replenish. No planner reviews that weekly in a spreadsheet. Nobody.

3. Boxes don't compress

Apparel folds. Shoes ship in rigid cartons that eat cubic space in the DC and the backroom. Unproductive footwear costs more per square foot to hold than unproductive apparel, and it degrades store handling on top of that.

4. Broken size runs devalue the whole style

Cores, roughly men's 9–11, women's 7–8.5, sell out mid-season. What's left is 7s and 13s on a floor fixture that now reads "picked over." Conversion on the remaining units falls even though those units are still full-price product. The usual response is a markdown on the entire style. You just discounted a silhouette that had pricing power six weeks ago.

5. You commit six to nine months out

Lasts, dies, outsoles, multi-component assembly, MOQs, factory pre-packs. Size curves get frozen long before you can see a trend. If a door's actual demand diverges from the pre-pack, manufacturing cannot help you. Only in-season rebalancing can.

Add returns on top

General retail returns ran about 16.9% in 2024; footwear routinely runs 25–31% because of fit uncertainty and last variation. Returned pairs sit in reverse logistics for weeks, come back in broken assortments, and often miss the full-price window entirely.

None of these are demand problems. All of them are allocation problems.

05 — Measurement

How to measure footwear availability accurately

If you review footwear on style-level KPIs, you will keep approving assortments that look fine and lose money.

Instead of this	Track this	What the old metric hides
Style-level in-stock %	Size availability %, share of doors in stock on every planned size in a live style	A door with 40 pairs of size 6 reports 100% in-stock while it's out of 10
Bestseller in-stock %	Top-seller complete-size availability %, top-decile styles holding an unbroken core run	Bestsellers can lose up to a third of revenue potential with cores broken and no flag raised
Nothing	Broken size set rate, active styles missing one or more core sizes	You find out a style stopped being viable at full price after the markdown
Blanket size ratios	Size-level demand mismatch %, door-level variance between historical size velocity and what shipped	Flattens real demographic and geographic size differences between a downtown door, a strip center, and an outlet
Blended weeks of supply	Days on hand by size band (core / secondary / fringe)	A bloated fringe cushion masks an imminent core stockout
Campaign fill rate	Core-size in-stock during campaigns (target 95%+)	You paid to drive traffic to doors that can't convert it
Ad-hoc store transfers	Cut-size consolidation velocity, speed and volume of remnants regrouped into complete runs	Single pairs die in backrooms instead of becoming saleable size sets

Recalibrate the financial benchmarks

Apparel numbers will mislead you:

GMROI. Apparel targets 2.5–4.0. Footwear averages closer to 1.86, because carrying extended size runs is structural, not optional. Measure GMROI by size band or you will never see where the capital is actually stuck.
Inventory turns. Apparel runs 4–6x. Footwear runs 2–3x on cube constraints. Evaluate turns per cubic foot, per store format.
Sell-through. 60–80% is not a health check in footwear. An 80% sell-through with a broken curve leaves a clearance tail that eats the season's net margin.
Markdown depth. In footwear, deep markdowns are usually an upstream size-planning error showing up downstream as a price decision. Treat markdown depth as a diagnostic, not a lever.

06 — Tooling

What changed in the tooling

Three shifts, all recent, all relevant.

1. Allocation stopped being about filling shelves

The old mandate was uniform presentation: every door gets the style, spread the units. The new mandate is portfolio margin. Modern engines will deliberately short-ship a slow door to keep a complete size run intact in a high-velocity one. You accept a small, known localized loss to protect full-price sell-through where the volume actually is. Gartner's market guide for short-life-cycle forecasting, allocation and replenishment (Jonathan Kutner) documents this move away from presentation-rule allocation toward margin-led allocation.

2. Store-to-store transfers went from last resort to first move

Retailers historically avoided transfers: admin load, freight cost, no visibility into whether the transfer paid. Predictive demand signals changed the economics. If you can score a transfer's projected margin against its logistics cost, moving 26,000 idle pairs stops being a chore and becomes the cheapest inventory you'll ever buy.

3. AI moved from dashboards into the workflow

The useful version is not a chatbot. It is agents embedded in execution, tuning replenishment thresholds and rebalancing door-level profiles inside merchant-defined guardrails, and escalating only exceptions. In footwear this isn't a nice-to-have. Hundreds of size-color variants across hundreds of doors is past the point where manual review is possible.

07 — Playbook

The six-rule operating playbook

01
Plan size-by-store, not style-by-region
Style averages hide door-level size gaps under a top line that balances on paper. A downtown transit-hub door, a suburban strip center, and an outlet have different size profiles. Kill standardized regional packing ratios.
02
Protect cores before you fund depth
Footwear sizes follow a Pareto curve, four to five core sizes drive up to 70% of revenue. Tier the assortment: cores get deep buffers and a 95%+ availability target through promo windows; secondary sizes get allocated to trailing 30-day velocity; fringe sizes get stocked to minimum presentation only. No speculative buys on extremes.
03
Rebuild size curves from velocity, not raw sales history
Raw history is a record of what you had, not what customers wanted. A stocked-out size records zero, so the system cuts next season's buy on your best size. Use lost-sales imputation and two to three seasons of door-level sell-through velocity by silhouette and gender.
04
Mobilize the network before you cut a PO
The size that's out in one door is usually sitting in another door in the same market. Check backrooms and orchestrate transfers before you place a supplemental order or pull from the DC. You already own the inventory.
05
Replace blanket promotions with size-level, elasticity-driven markdowns
A flat 30% off a silhouette hands margin away on the sizes still selling at full price. Price by inventory health at the store-and-size level. Shallow discounts, targeted at the sizes and doors that actually need them.
06
Rationalize the tail every season
The long tail of slow options ties up open-to-buy and backroom cube. Prune underperforming styles and fringe variants at season end, on purpose, on a calendar. Concentrate capital on proven turnover.

07 — Evidence

Nine real-world cases across six brands

Results from live deployments across six footwear and sportswear brands, full-price networks, factory outlets, and multi-channel wholesale, with engagements running in European, Indian, and multi-region store networks.

All figures are Increff proprietary data™ benchmarked against prior-year like-for-like or matched control doors. Brand names are withheld. The deployments ran in European, Indian, and multi-region store networks; the operating principles are market-agnostic, but U.S. readers should note the deployment geographies.

1) Automated daily replenishment

Outdoor & casual footwear brand, ~264 stores

The problem. Replenishment ran on bi-weekly manual review. The lag between what sold and what shipped kept widening. Cores of fast movers ran dry while backrooms filled with dead styles and extreme sizes.

What changed. Replenishment read sell-through at style, size, and store level and raised recommendations daily. No waiting for a planner to notice a gap.

Availability improved and inventory came down. If you have been told those trade off, this is the counterexample.

Metric	Result	Note
Overall stockout rate	13% → 5%	Inside 105 days of go-live
Footwear stockout rate	11.6% → 5.4%	Deepest size complexity, biggest gain
Footwear unit sales	+3.2%	On 18% less store stock YoY
Footwear sell-through	+7.3 points	More of what shipped actually sold
Days of holding	314 → 224	~90 days of working capital released
Apparel stockout rate	9.9% → 2.6%	Same engine, rest of the range
Accessories unit sales	+17%	Reversed a 10% decline, ~half the network live

2) Size-wise distribution and planograms

Global sportswear brand, factory outlets

The problem. Allocation ran off style totals with generic size ratios. Style quantities looked adequate. Stores drowned in fringe sizes while cores sold out.

What changed. A size-wise model allocated at size level inside each style. Planograms were rebuilt around size velocity, so fast sizes got the shelf visibility to match.

Metric	Result	Note
Top-seller availability	67% → 100%	Complete size sets on primary revenue drivers
Size-level demand mismatch	87% → 48%	Nearly halved
Excess inventory (>120 days)	40% → 19%	Freed DC and backroom cube

3) Full-price network allocation

Sportswear major, European full-price network

The problem. The network was already performing well. That's what made it interesting — allocation was the only lever left. An earlier review had flagged stock sitting in doors where it wasn't selling.

What changed. Automated replenishment and dynamic allocation across the full-price fleet, measured like-for-like. True ROS™ and size-availability signals held days of holding near target.

Metric	Result	Note
Full-price revenue	+4%	€3.7M (≈$4.3M) in a single season, like-for-like
Sales quantity	+12%	204,801 additional units, same store network
True rate of sale	+11%	Each door sold faster on the same footprint
Sell-through	+1 point	Held while volume grew, the harder combination
Days of holding	72 days	Against a 69-day ideal; growth didn't come from carrying more
Earlier review	€1.87M (≈$2.2M)	Rate of sale +6%, size availability +17%, 95% fill rate held, ~18% of non-performing store stock cleared

4) End-of-season sale planning

Same sportswear major, India

The problem. The clearance window is short and unforgiving. Store category mix wasn't built around actual selling speed, so revenue leaked before the sale even opened.

What changed. Forward rate-of-sale analysis drove replenishment down to store, category, gender, and attribute, not broad strokes. Best sellers stayed in stock; store-level category mix stayed aligned to what was selling.

Metric	Result	Note
Average selling price	+12%	Growth from mix and price, not volume
Rate of sale	+13%	Stock moved faster through a short window
Revenue per day	+8%	More out of the same number of selling days
Store inventory health	+5%	Network came out of the sale cleaner than it went in

5) Algorithmic inter-store transfers

International athletic brand, India

The problem. Some doors held size runs that had stopped selling locally while doors a few kilometres away were short of the same sizes. Style health across the network was low, with stock sitting outside any healthy sell-through band.

What changed. Transfer recommendations scored selling velocity, freight cost, and projected margin, then moved stock from where it was stuck to where it would sell. No new buying. Only ~40% of the eligible network was live, so these are partial-rollout numbers.

Metric	Result	Note
Revenue vs. control	~8% better	Pilot doors lost less revenue during a market slowdown
Availability	+13%	Measured against control over the same window
Inventory health	+21%	Pilot network ended the period cleaner than it started
Scale of regrouping	26,000 pairs	Redeployed across pilot doors

In a separate multi-channel deployment, transfers drove 4× sales-quantity growth on previously idle stock, lifted rate of sale 9×, and moved style health from 9% to 52%, all without procuring a single new pair.

6) Replenishment, transfer, and markdown as one workflow

Athletic brand, factory outlets

The problem. Discounts went out broadly instead of by how a style was actually performing, so margin disappeared even on styles that needed no push. Stock sat unevenly, so a top seller could be unavailable in one door and idle in another at the same moment.

What changed. Markdown, transfer, and replenishment ran on the same network at once, as one connected decision instead of three separate projects. Performance signals decided where discounts landed, where stock moved, and which local top sellers got replenishment priority.

Metric	Result	Note
Sell-through margin	46.1% → 54.7%	+8.6pp
Average markdown depth	52% → 45%	~€259K (≈$300K) gross margin preserved
Overall inventory health	+~18%	Example doors moved from 66–70% to 81–85%
Markdown incremental sales	₹9.13L in 12 days	Worth 8% of turnover on the discounted style set
Markdown margin gain	₹5.73L	Recovered by discounting less deeply, not less often
Transfer	+26%	Growth in average per-day sale quantity
Replenishment option efficiency	50% → 80%	More of the range earning its place in each door
Healthy local top sellers	+~31%	Each door carried more of what sells in its own catchment

Two more, briefly

Multi-channel heritage footwear enterprise

150 distributors, 400 exclusive showrooms, 6,000+ multi-brand doors. Cut overall inventory 8% through True ROS™ replenishment, grew sales 10.46% with a 1.0% margin gain, lifted core style health 30%, and raised daily sales velocity 26% through algorithmic transfers.

Premium comfort footwear brand

Ran the same combination and grew sales quantity 13% and revenue 18%.

08 — For U.S. leaders

How U.S. footwear leaders can improve availability and margin

Improve availability without adding stock

The industry assumption is that better on-shelf availability requires bigger buffers. The data says otherwise: stockouts 11.6% → 5.4% with 18% less store stock and 90 fewer days of holding. Deckers just posted a record year with inventory down 2%. Move capital strategy from safety stock toward daily responsiveness.

Track availability by size and store

Retire style-level in-stock from leadership reviews. Replace it with Top-Seller Complete Size Availability %, Size-Level Demand Mismatch %, and Broken Size Set Rate. Then align planner incentives to complete size-set preservation rather than departmental unit volume. People manage what gets reviewed.

Rebalance stock continuously

Transfers should run continuously, scored against freight and margin, regrouping single-pair remnants into complete runs in your highest-velocity doors. This is revenue from inventory you already own and open-to-buy you don't have to spend.

Use margin to guide allocation

Prioritize net portfolio profitability over uniform store presentation. That means accepting deliberate short-ships to keep high-velocity doors unbroken through peak windows. And it means letting agents handle the high-volume size decisions inside guardrails, so merchants spend their time on the exceptions that need judgment.

09 — FAQ

Frequently asked questions

How do I measure footwear lost sales?

Estimate expected sales for each size during the period it was unavailable. Use its in-stock rate of sale, comparable stores, similar products, seasonality, and promotional activity. The gap between expected demand and recorded sales gives you a more accurate estimate than treating zero sales as zero demand.

When should I transfer store inventory?

Transfer inventory when a product is selling slowly in one store but has unmet demand in another. The expected full-price margin at the receiving store should exceed the cost of freight and handling. Prioritize transfers that restore complete size runs on fast-selling styles.

Which stores need inventory rebalancing?

Look for stores with excess days of holding, slow-selling sizes, and incomplete size runs. Compare them with stores that have strong sales velocity but are missing the same sizes. That identifies where inventory is trapped and where it has a better chance of selling.

How do I protect full-price sell-through?

Keep core sizes available through the main selling window and respond before size runs break. Replenish fast sellers, transfer idle stock, and avoid discounting an entire style because a few sizes are overstocked. The earlier the imbalance is corrected, the less margin is lost.

Why is footwear inventory data inaccurate?

Recorded sales show what customers bought, not everything they wanted. Stockouts suppress sales for unavailable sizes, substitutions can make adjacent sizes appear more popular, and inventory may be misplaced in stores or reverse logistics. These gaps can distort forecasting, allocation, and replenishment decisions.

How should I split inventory by channel?

Build separate demand profiles for owned stores, ecommerce, outlets, and wholesale. Each channel has different customers, return patterns, selling windows, and fulfillment options. Allocate shared inventory according to expected sales and margin rather than applying one size and quantity mix across every channel.

How often should store size profiles change?

Review store size profiles after every season and update them sooner when demand changes significantly. New stores, launches, local events, promotions, and demographic shifts may require more frequent adjustments. Stable, evergreen products can use a longer history than seasonal or trend-led footwear.

How do I test footwear allocation software?

Run a pilot across a matched group of stores. Compare size availability, stockouts, full-price sell-through, markdown depth, inventory health, and transfer costs against similar control stores. The software should also explain its recommendations and work within your existing operational constraints.

Who should own footwear availability?

One team should be accountable for the availability metric, even though merchandising, planning, and supply chain all influence it. Shared ownership without clear accountability often leaves size-level gaps unresolved. The accountable team should have the authority to coordinate allocation, replenishment, transfers, and markdown decisions.

10 — Sources and notes

Third-party sources

1AlixPartners with FDRA. Spring 2026 U.S. Consumer & Executive Footwear Survey, April 23, 2026. https://www.alixpartners.com/newsroom/alixpartners-spring-2026-footwear-survey/
2Nike Inc.. Q3 FY2026 earnings call transcript, March 2026. https://www.investing.com/news/transcripts/earnings-call-transcript-nike-beats-q3-2026-forecasts-stock-rises-93CH-4591828
3adidas AG. Q1 2026 results commentary, April 29, 2026. https://frontofficesports.com/adidas-earnings-q1-beat-expectations-yeezy-soccer-performance/
4Puma SE. Q1 2026 press conference, April 30, 2026. https://wwd.com/footwear-news/shoe-industry-news/https-wwd-com-business-news-financial-puma-q1-2026-sales-fall-1-percent-1238933264/ and https://www.rte.ie/news/business/2026/0430/1571069-puma-quarterly-results/
5DICK'S Sporting Goods. FY2025 and Q1 2026 results, Foot Locker inventory optimization and Fast Break format. https://www.sgieurope.com/financial-results/dicks-closes-year-with-17bn-and-a-foot-locker-bet/120010.article and https://www.sgieurope.com/financial-results/foot-locker-us-comps-rise-6-in-dicks-first-full-quarter-post-deal/121363.article
6Birkenstock Holding plc. Q2 and Q1 FY2026 commentary. https://wwd.com/footwear-news/shoe-industry-news/birkenstock-ceo-oliver-reichert-brand-health-full-price-1238953104/ and https://shop-eat-surf-outdoor.com/news/birkenstock-shares-wholesale-growth-plans-as-q1-revenue-jumps-18/616577
7Deckers Brands. Q1 and Q4 FY2026 earnings commentary. https://stockstory.org/us/stocks/nyse/deck/news/earnings-call/5-revealing-analyst-questions-from-deckerss-q1-earnings-call and https://finance.biggo.com/news/US_DECK_2026-05-21
8New Balance. Joe Preston interview, Semafor, November 2025. https://www.semafor.com/article/11/28/2025/how-joe-preston-got-new-balance-back-in-the-race
9Aldo Group. Inventory and fulfillment logic. https://www.mcgill.ca/bensadoun-school/article/mmr-program/open-conversation-david-bensadoun-come-back-canadian-giant
10Gartner. Market Guide for Retail Forecasting, Allocation and Replenishment Solutions: Short Life Cycle Products (Jonathan Kutner). https://www.gartner.com/en/documents/7591433

Increff data

All figures labelled Increff proprietary data™ are measured outcomes from live client engagements across six footwear and sportswear brands and nine client engagements, benchmarked against prior-year like-for-like performance or matched control store groups. Brand names withheld. The deployments ran in European, Indian, and multi-region store networks; the operating principles are market-agnostic, but U.S. readers should note the deployment geographies. USD conversions are approximate and indicative only. INR figures use lakh (L = 100,000) and crore (Cr = 10,000,000).

Figures requiring internal verification before publication: the ~23% adjacent-size substitution lift, 25–31% footwear return range, 16.9% general retail return rate, GMROI ~1.86 footwear average, and 2–3x footwear inventory turn benchmark are carried over from Increff's internal Footwear & Sportswear Merchandising Industry Report. Confirm the primary citation for each before external release.

The full report

Empty shelves are a choice. Full backrooms are a choice. They don't have to be the same choice.

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