Dead Stock and Markdown Rates by Vertical, 2025

Dead stock is failed demand forecasting showing up as destroyed cash. The margin gap between a well-run inventory operation and a poorly run one lives inside one number: how much of what you bought ended up sold at a discount, or worse, written off entirely. This post sets category-level benchmarks for the three metrics that matter, dead stock on-hand, formal write-off rate, and markdown sell-through, and grounds them in real disclosed figures from public DTC and retail brands. The read is for operators running $5M to $150M in revenue who are deciding their next buy.

The headline benchmark: how much inventory ends up marked down or written off

Start with the stakes. IHL Group and Blue Yonder put combined global overstock and out-of-stock cost at $1.77 trillion a year, of which roughly $562 billion is overstock alone. That is the macro version of the problem sitting in your own warehouse: inventory you paid for that is not selling at the price you planned.

At the brand level, the benchmark splits into two very different numbers. Dead stock on-hand (the share of inventory value that has stopped moving) runs 20-30% in fashion apparel. The share that gets formally written off as a total loss is far smaller, usually 2-5% of inventory value a year in a well-run apparel brand. The gap between those two numbers is the markdown machine: most dead stock never gets written off because it gets discounted out the door first.

When I talk to founders running a brand this size, the number that surprises them is not the write-off rate. They expect that to be small. It is the dead-stock-on-hand figure. A founder who thinks they are running a tight operation is often genuinely shocked to learn that a quarter of their inventory value has not sold a unit in 90 days. The write-off line on the P&L looks clean precisely because the damage already happened one markdown earlier.

The chart makes the structural point: on average across verticals, dead stock on-hand is roughly five times the annual write-off rate. Beauty is the exception: both rates converge near 3-7%, so the bars are nearly equal. Consumer electronics goes the other way, where model-year obsolescence inflates dead stock to 10x or more the write-off rate. The write-off bars are consistently smaller and narrower than the dead stock bars. The dead stock bars are where the real spread lives, and that spread is the rest of this post.

The vertical spread: why apparel and sporting goods look nothing like beauty

The benchmark is not one number. It is eight very different numbers, because the thing that creates dead stock differs by category. Fashion apparel and sporting goods sit at the top (20-30%) because of trend cyclicality, seasonality, and size-color complexity: a single style in five sizes and four colors is twenty SKUs, any of which can strand. Beauty and CPG sit at the bottom (3-15%) because they run replenishment models with narrow, long-lived assortments and predictable reorder velocity.

Two cells deserve a caveat. Consumer electronics shows a high dead stock figure but a low write-off rate because the dead stock there is obsolescence-driven (last year's model) and gets cleared through fast, deep price cuts rather than destruction. Sporting goods spikes to 25-55% of assortment on discount during elevated-inventory periods, which is a point-in-time observation from the post-pandemic glut, not a steady-state average. Read the ranges as operating bands, not single targets.

The driver column is the part operators should internalize. The pattern we see again and again is that brands try to fix a dead-stock problem with a clearance tactic when the real cause is upstream: too many styles, buys sized to a plan instead of to demand, or a markdown taken six weeks too late. Beauty does not have less dead stock because beauty teams are smarter. It has less dead stock because the model creates fewer ways to strand a unit.

What the public company financials reveal

Benchmarks from vendor reports are useful, but you can also read inventory discipline straight off a balance sheet. We computed Days Inventory Outstanding (DIO, the average number of days a brand holds inventory before selling it) from SEC EDGAR 10-K filings for six public DTC and retail brands. DIO is calculated as average inventory divided by cost of goods sold, times 365, with COGS derived from revenue minus gross profit.

The ranking is instructive, and it comes with a trap. The natural read is "low DIO good, high DIO bad," and within apparel that mostly holds: Urban Outfitters at 59 days is turning inventory more than twice as fast as Revolve at 147. But e.l.f. Beauty sits at the top of the chart at 183 days, and that is not a dead-stock signal. e.l.f. is a CPG brand pre-building inventory for mass-retail shelf programs at Walmart and Target. Its turns are driven by retailer point-of-sale velocity, not its own store sell-through, so a long DIO there reflects supply-chain buffer, not failed demand. DIO is a proxy for inventory at risk, not a direct markdown rate. Use it to ask the question, not to answer it.

Carter's is the cleanest example of discipline in the dataset. Across FY2022 to FY2024 the company took absolute period-end inventory from $744.6M down to $502.3M, a 32.5% reduction, while revenue fell only about 12% ($3.21B to $2.84B) over the same window.

That is what a markdown-and-buy-discipline cycle looks like in the financials: inventory falling much faster than sales, which means the company chose to clear stranded stock and buy leaner rather than carry it forward and hope. For a private operator the same move shows up as a quarter of compressed gross margin followed by a much healthier cash position. The brands that refuse to take that hit are the ones still carrying three seasons of dead inventory two years later.

The operator read: what actually drives the spread

Once you know your number and your vertical's band, the question is what to change. Five levers move dead stock and markdown rates, in roughly the order of their impact.

Buy discipline. The single largest cause of dead stock is buying to a plan instead of to demand. Smaller initial buys with planned replenishment, and shorter production lead times, cut dead-stock risk at the source. When we have worked through this with operators, the brands that moved from one big seasonal buy to a tighter initial order plus reorders saw dead stock fall without touching their markdown strategy at all.

Style count. SKU proliferation is the apparel-specific multiplier. Every additional style is another way to strand inventory across sizes and colors. Narrow assortments are the structural reason beauty and CPG sit in single digits.

Markdown timing. The stated planning benchmark is to sell roughly 70% of a collection at full price before the first markdown, then clear the rest. Most brands wait too long, hoping a slow style turns, and end up taking a deeper discount later than a shallow one earlier would have cost them.

Pre-order and drop structure. Pre-selling even 15-20% of a buy removes that share from dead-stock risk entirely and gives you a demand read to size the rest. This is the highest-impact front-end fix available.

Clearance channel access. Liquidation, off-price, and B-grade sales recover cost. A write-off recovers nothing. Brands with real clearance channels keep their write-off rate near the bottom of the band even when their dead-stock-on-hand runs high.

How to use this in your own model

Turn the benchmark into a three-step diagnostic you can run this quarter.

First, calculate your own three numbers: dead stock as a percent of inventory value, write-off as a percent of inventory value, and markdown or clearance dollars as a percent of revenue. Second, compare each to your vertical's band from the table above. Third, trace any gap back to one of the five levers: buy volume, style count, markdown timing, pre-order structure, or clearance access.

The payoff is real. Reducing dead stock from 30% to 15% on a $2M inventory base frees roughly $300K in cash, all else equal, plus the markdown losses you avoid on the inventory you never bought. Building that discipline into your buy plan is exactly what a fractional CFO does. For more on the markdown side specifically, see our guide to apparel markdown strategy; on the write-off mechanics, how to take inventory writedowns; and on turns, how to improve inventory days.

Dead stock on-hand runs on average five times your formal write-off rate across most verticals. The write-off line on your P&L looks clean because the damage already happened one markdown earlier. If you only watch the write-off number, you are reading the financial statement of a problem you solved badly, not preventing the next one.

Sources and methodology

Category dead stock and write-off benchmarks come from published practitioner and vendor data. Category-specific dead stock percentages (apparel 18.7-30.4%, beauty 3-6.5%) are from Cart.com's 2025 inventory management metrics, split by SMB, mid-size, and enterprise. Annual write-off and obsolescence rates by vertical are compiled from Alexander Jarvis's 2025 ecommerce inventory benchmarks. These are practitioner aggregates, not formal surveys, and are presented as operating bands.

The markdown sell-through figure traces to fashion-industry research. The shift from a 70-75% historical full-price sell-through norm to roughly 50% in recent seasons is described in McKinsey's "Hitting the mark: Why markdowns matter more than ever" and the McKinsey / Business of Fashion State of Fashion series. The 20-50% of net sales consumed by markdowns figure is a fashion markdown-management benchmark and should be read as directional.

The global inventory distortion figure is from a retail benchmark report. The $1.77 trillion combined overstock and out-of-stock estimate, and the ~$562 billion overstock component, are from the IHL Group / Blue Yonder Retail Inventory Distortion Report (2023). It is a global figure with no U.S.-only breakout in the public materials.

DIO figures are computed from primary SEC filings. Days Inventory Outstanding, gross margin, revenue, and average inventory were calculated from SEC EDGAR 10-K filings for American Eagle (CIK 919012), Urban Outfitters (CIK 912615), Revolve (CIK 1746618), Carter's (CIK 1060822), Lands' End (CIK 799288), and e.l.f. Beauty (CIK 1600033), for fiscal years ending Q4 2024 or Q1 2025. DIO = (average inventory / COGS) x 365, with COGS derived from revenue minus gross profit. Average inventory is the mean of beginning and ending period inventory.

Limitations. Dead stock and write-off bands are compiled from vendor and practitioner sources whose sample sizes are not fully disclosed; treat them as ranges, not precise targets. DIO is an inventory-efficiency proxy, not a markdown rate: a high DIO flags inventory at risk but does not by itself mean more markdowns, and for replenishment-driven CPG brands it can reflect supply-chain buffer rather than dead stock. Footwear and children's apparel dead-stock ranges are inferred from apparel benchmarks where no category-specific source exists.

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