Stock simulator for fashion stores

The average fashion store sells only 60% of its inventory at full price. The rest is lost margin.

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  • Deterministic calculation

In 30 seconds: Simulate demand by SKU and find the ideal composition of your buy so you sell more at full price and less on markdown. Deterministic calculation with auditable formulas. The result is indicative — adjust the assumptions to reflect your real operation.

Fashion is one of the toughest inventory challenges: long lead times (60-90 days from Asia), high variability by size/color and strong seasonality. This calculator gives you a baseline — complement it with SKU-level analysis for top sellers vs long tail.

Methodology

Average daily demand = Annual demand ÷ 365

EOQ = √((2 × Annual demand × Order cost) ÷ Holding cost per unit/year)

Safety Stock = Z × σ × √Lead time (days)

Reorder Point (ROP) = (Daily demand × Lead time) + Safety Stock

Total annual cost = (Demand ÷ EOQ × Order cost) + (EOQ ÷ 2 × Holding cost) + (Safety Stock × Holding cost)

Variables

Annual Demand
Units sold or consumed in a year for the SKU.
Order Cost
Administrative and logistics cost of placing an order (regardless of size).
Holding Cost
Annual cost of keeping one unit in stock (storage, tied-up capital, insurance, obsolescence).
Lead Time
Days between placing the order and receiving it.
Daily Standard Deviation
Observed variability in daily demand — how much it fluctuates day to day.
Service Level
Target probability of not stocking out during lead time (90%, 95%, 97.5%, 99%).

Practical example

Women's fashion boutique in Guadalajara importing from Asia: annual demand 6,000 pieces of the base SKU (16/day), unit cost $420, order cost $2,500 (customs broker, consolidated freight, quality inspection), holding cost $35/piece/year (capital + climate-controlled warehouse + markdown risk), 60-day sea lead time, daily deviation 6 pieces.

EOQ = √(2 × 6,000 × 2,500 ÷ 35) = √857,143 = 926 pieces per order. Frequency: 6.5 orders per year, one every 56 days.

Safety stock for 92% service level (z = 1.41): 1.41 × 6 × √60 = 66 pieces. Reorder point = (16 × 60) + 66 = 960 + 66 = 1,026 pieces.

Caution: theoretical EOQ of 926 pieces equals 56 days of inventory, but the fashion cycle is only 90 days on the sales floor before 30-40% markdown. If the SKU is purely seasonal, DON'T use EOQ — use a 'production pull' rule in two waves (50% initial, 50% reorder at day 30 based on sell-through).

By size/color: the base SKU typically splits 10% XS, 25% S, 30% M, 25% L, 10% XL. Applying EOQ per individual size generates excess SS at the extremes. Apply EOQ to the family and use allocation rules across the size curve.

Operating recommendation: the 92% level (not 95%) is deliberate in fashion — an 8% stockout on extreme sizes costs less than a 30% markdown on 200 unsold pieces. If your historical sell-through drops below 70% in weeks 1-4, lower the level to 88% and work size-by-size with supplier buyback in China.

Interpretation

EOQ minimizes the total cost between ordering and holding. Orders below EOQ raise ordering cost; above EOQ raise holding cost.

Raising the service level from 95% to 99% usually increases safety stock 30-50%. Only worth it if the cost of a stockout (lost sale + lost customer) exceeds the extra inventory cost.

Long or variable lead time is the main driver of safety stock. Cutting supplier lead time in half can reduce your safety stock by 30%.

If your calculated ROP is above the inventory you usually carry, you're at recurring risk of stockout. If it's much lower, you're over-stocking.

Assumptions and limitations

  • Assumes independent, normally distributed demand (valid for SKUs with a stable history; fails for new or highly seasonal products).
  • Assumes a fixed, known lead time (lead-time variability can also be modeled but needs more data).
  • Assumes constant ordering and holding costs — no volume discounts or warehouse capacity limits.
  • The Wilson EOQ model doesn't consider warehouse capacity constraints or product shelf life (perishables need different models).

When to use this calculator

  • For A-class SKUs (high volume, high rotation): the difference between theoretical EOQ and operating EOQ translates directly into thousands in avoidable cost.

  • When a supplier changes price, lead time or minimum order — recalculate EOQ and ROP to adjust the purchasing policy.

  • Before negotiating annual contracts: EOQ tells you the optimal order size to use as an anchor in negotiations.

  • To set reorder points in WMS or ERP systems: many businesses operate with inherited ROPs with no statistical basis.

  • When evaluating a supplier with a shorter lead time: quantify the safety stock savings that could justify a higher unit cost.

Common mistakes

  • Using average demand without measuring the standard deviation. Without volatility, safety stock is zero and stockout risk is huge.

  • Ignoring the cost of capital when calculating holding cost. In high-rate environments, tied-up capital can represent 60% of holding cost.

  • Applying EOQ to perishables without adjusting for shelf life — you'll end up ordering quantities that expire before selling.

  • Defaulting service level to 99%. Low-contribution products don't justify such expensive safety stock; segment by margin.

Industry use cases

Fast fashion

Short cycles (4-6 weeks) and SKUs with short life. EOQ applies at base SKU; use allocation rules for size/color. A 90-92% service level helps avoid mass markdowns.

Boutique / designer

Limited production, lead times of 90-120 days. EOQ is less relevant; the right model is season-based ordering with partial supplier buyback.

Footwear

Size variability creates a U curve: central sizes turn fast, extremes slowly. Apply EOQ by size family, not individual SKU.

Accessories

Shorter lead times (30-45 days) and lower seasonality. Traditional EOQ works well with a 95%+ service level.

Methodology and assumptions

How results are calculated, what we assume when modeling, and where the method loses precision.

Formula

EOQ = √(2·D·S ÷ H) · ROP = d × LT + Safety stock

Assumptions

  • Annual demand D known and reasonably stable.
  • Order cost S and holding cost H expressed in the same currency and time unit.
  • Deterministic lead time LT; safety stock covers variance.

Applicability limits

  • EOQ assumes instant replenishment — for in-house production use the EPQ variant.
  • When demand is seasonal the formula understates peak inventory.
  • Volume discounts are not included: evaluate the quantity discount separately.

Sources

  • Harris, F.W. (1913) — How Many Parts to Make at Once (origin of the EOQ formula).
  • APICS / ASCM — CPIM Body of Knowledge on inventory and demand.

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Complete guide

Fashion inventory: when every collection is a bet with an expiration date

In fashion — fast fashion, mid-market, emerging brands — inventory is not an asset you hold; it is an asset on a clock. An autumn-winter collection has 12-16 useful weeks at full price, after which markdowns begin. Residual stock that crosses into the next season loses 50-70% of value and competes with fresher new product. The difference between a brand that pays its investment fund and one that goes bust is measured in end-of-season sell-through rate and in the discipline of the markdown cadence — not in designer creativity.

Sell-through rate: the metric the buying committee lives by

In fashion, sell-through rate is the ratio of units sold to units received in a given period:

Sell-through = Units sold ÷ Units received × 100

Industry benchmarks (BoF State of Fashion 2024, Retail Dive):

  • Week 1-4 (soft launch + first markdown-free): healthy sell-through 15-25%.
  • Week 8 (mid-season): 50-65%.
  • Week 12 (end of full-price): 70-80%.
  • End of season (week 16-20): 85-92% target.

Below 70% at close indicates structural overbuying: either real demand was below forecast or the product had the wrong fit/color/price. Above 95% — paradoxically — is stockout leaving sales on the table; best-sellers that sold out in week 6 could have kept selling at full price for six more weeks had replenishment been in place.

SKU depth and breadth: the strategic trade-off

SKU depth is the quantity purchased per SKU. SKU breadth is the total count of distinct SKUs in the collection. Fast fashion (Zara, H&M, Shein) operates with high breadth and low depth — thousands of styles with few units each, fast rotation, weekly readjustment. Premium or niche brands operate with low breadth and high depth — few styles, more units each, 16-20 week cycle. A common mistake for emerging brands is copying fast-fashion breadth without the operational capability to rotate that many SKUs — result: 55% sell-through and 35-45% dead stock at season close.

Size and color mix: where most lose margin

The optimal size curve varies by channel, country, and product type. A typical adult-female curve in LatAm (XS-XL): S 18%, M 32%, L 28%, XL 14%, XS 8%. Deviating 3-5 points in a critical size (M or L) creates a double problem: stockout in the missing size and dead stock in the oversized one. The simulator models lost conversion from size stockout: when a customer cannot find their size, 40-55% do not buy another size or wait for replenishment — they leave to a competitor. That cost appears in no report but is the #1 margin-erosion factor in fashion.

On color, the operational rule is: 1 core (black, white, beige) with 35-45% of the buy, 2-3 seasonal colors with 35-45%, and 1-2 experimentals with the rest. Overweighting experimentals is the trap of creative teams that confuse 'what they love' with 'what sells.'

Markdown cadence: the discipline that separates winners from losers

Markdown cadence is the pre-set schedule of price reductions across a collection's useful life:

  • Week 0-8: full price, no visible discounts (loyalty member exceptions, early access).
  • Week 8-12: first markdown 20-30% on SKUs with below-corridor sell-through.
  • Week 12-16: second markdown 40-50% on residual.
  • Week 16-20: clearance 60-70% + outlet movement.
  • Beyond week 20: outlet destination, closeout wholesaler, or write-off.

Breaking the cadence — for example, pushing a 30% discount in week 4 to 'drive sales' — destroys the pricing power of the entire collection. Customers learn that if they wait 4 weeks, the product drops; full-price sales collapse across the next 3 collections. Zara operates with a famous cadence discipline: no markdowns before week 10-12, which sustains its 56-58% gross margin against 38-45% for competitors that cave to early discounting (McKinsey Apparel Economics 2024).

Fast-fashion cycle vs traditional collections

The traditional fashion cycle runs 2-4 collections per year (spring/summer, fall/winter, resort, pre-fall). Fast fashion runs 52 micro-collections — one per week. Ultra-fast fashion (Shein) runs 2,000-10,000 new SKUs per day, supported by an on-demand manufacturing model where 80% of inventory is produced in small batches (~100-500 units) and only best-sellers are scaled up. Implication for mid-market brands: you cannot compete with Shein on speed, but you can compete by rotating faster than the traditional cycle — monthly or bi-monthly drops instead of 2 large collections per year cut obsolete-inventory risk by 40-60%.

GMROI and Open-to-Buy: the tools the professional buyer uses

GMROI (Gross Margin Return on Inventory) measures the margin return on every dollar invested in inventory:

GMROI = Gross margin ÷ Average inventory cost

A healthy GMROI in fashion is 2.5-4.5 (2.5-4.5 dollars of gross margin per dollar of average inventory). Benchmarks: fast fashion 4-6, mid-market 2.5-3.5, premium 2.0-3.0, luxury 1.5-2.5 (BoF + McKinsey).

Open-to-Buy (OTB) is the budget available to purchase future inventory given the sell-through, residual, and target margin plan. Running without a formal OTB is buying by instinct — the direct route to overbuying.

6-week buying calendar: planning before the season begins

Professional fashion buyers operate on a buying calendar — a structured 6-week process that maps supply chain lead times against the season open date:

  • Week 1–2: trend analysis, competitive review, open-to-buy budget confirmed with CFO.
  • Week 3–4: supplier selection, style finalization, sampling and price negotiation. OTB allocated by department and category.
  • Week 5: purchase orders submitted. Lead time for overseas production (Turkey, Bangladesh, Brazil): 12–16 weeks; domestic/nearshore: 4–8 weeks.
  • Week 6: order confirmations, logistics booking, delivery windows agreed.

Brands that skip this discipline submit orders based on intuition and gut feel — resulting in the classic overbuying-on-favorites error: 60% of the budget into 5 hero styles that end up duplicating each other's demand, with the long tail of the collection understocked. The buying calendar forces budget allocation before emotional attachment to specific styles sets in.

Dead stock channels: how to exit residual profitably

When sell-through at season close is below target, residual inventory needs a structured exit ladder. The priority sequence:

  1. Own online clearance sale: highest margin recovery (40–60 cents on the dollar). But needs to be executed before the next season's new arrivals compete for the same customer attention.
  2. Own outlet / physical sample sale: for brands with physical presence. 50–70% recovery depending on traffic.
  3. B2B closeout wholesaler / jobbers: firms like B-Stock, Direct Liquidation, or regional LatAm closouteros buy residual lots at 15–35 cents on the retail dollar. Recovery is low but immediate — cash today vs storage cost tomorrow.
  4. Discount marketplace (factory outlet channels): Gilt, Vente-Privée, Privalia, Dafiti Outlet. Recovery 25–45% of original retail. Requires brand approval in most cases.
  5. Donation with tax deduction: for US brands, IRS enhanced food/inventory donation deduction. For Mexico, LISR Article 27 covers eligible inventory donations. Tax recovery 15–30 cents on the dollar depending on bracket.
  6. Liquidation/write-off: last resort. Physical destruction for luxury brands protecting brand equity (LVMH writes off Burberry-style); write-off at cost for mid-market.

The most common mistake: waiting too long before moving to step 3. Each additional month of holding costs storage + capital — on a $50K residual lot at 18% inventory holding cost, delay costs $750/month. Moving to a wholesaler at 25 cents in month 3 is better than 25 cents in month 9 after $6,750 in holding cost.

B2B vs DTC inventory economics: different models, different math

Fashion inventory management looks fundamentally different depending on the sales model:

  • Wholesale / B2B (selling to retailers): the brand buys inventory and ships to retail accounts. Sell-through risk transfers to the retailer — except when consignment or markdown support arrangements exist. The brand's inventory problem is primarily around initial buy size and collection depth.
  • DTC (direct-to-consumer online): the brand owns inventory and ships to end consumers. Returns (25–40% in fashion) come back to the brand. Size and color mix risk is fully on the brand. But the brand also captures full retail margin, typically 2.5–4× the wholesale margin.
  • Omnichannel: the complexity of maintaining shared inventory visibility across retail wholesale, own stores, and DTC channels. The largest brands (Zara, Mango) use unified ATP (Available to Promise) pools where the same unit can be allocated to any channel based on real-time demand — reducing dead stock risk by 25–35% vs siloed channel inventory.

2026 industry context: sustainable fashion and pricing power

Two forces are reshaping fashion inventory economics in 2026:

  1. Shein and ultra-fast fashion disruption: Shein's on-demand manufacturing model (small initial batch, scale winners instantly) is being partially copied by mid-market brands as a dead-stock mitigation strategy. Brands with domestic or nearshore suppliers (Mexico's textile cluster in Jalisco, Colombia's Medellín garment district) can now operate 4-week test-and-scale cycles that were previously only available to Shein's Guangdong supplier network.
  1. Sustainable fashion premium: a growing segment of consumers (23% of US millennial shoppers, per McKinsey 2025) actively seeks certified sustainable brands and demonstrates price inelasticity of -0.4 to -0.8 vs -1.5 to -3.0 for fast fashion — meaning sustainable brands can hold higher prices without proportional volume loss. This shifts the inventory calculus: fewer SKUs at higher margin per unit, longer useful life per style, and better gross margin for the same sell-through rate.

Common mistakes and red flags

  • Overbuying hero colors: buying 45% of the collection in one 'breakout' color and then losing at markdown when the trend fades in week 6.
  • No size data by channel: DTC and wholesale customers have different size curves; applying the DTC curve to wholesale creates systematic mis-sizes.
  • First markdown too late: discount after week 14 instead of week 8-10 means clearing at 60% instead of 30%, destroying margin.
  • No OTB discipline: buying above OTB 'because the style is great' is the direct path to over-inventory and cash squeeze at season end.
  • Counting last-season styles as current inventory: last season's residual in the same store competes with the new collection and confuses both the customer and the sell-through report.

Conclusion

In fashion, operational discipline — weekly sell-through, size curve, markdown cadence, GMROI, OTB — is more decisive than design creativity for economic survival. Brands running these metrics in a weekly cockpit scale; those running on the founder's intuition end up liquidating closeouts and shuttering stores. The simulator turns your ERP + POS into the weekly cockpit the buyer, the planner, and the CFO need to share.

Illustrative case

Composite case for instructional purposes: combines sector dynamics with realistic figures. Names are fictional and do not represent a specific company.

Aldara Studio is an emerging mid-market women's-wear brand with 4 stores plus an online channel, launched in 2021. 2024 revenue: USD 380K. The founder — a designer by training, no retail background — was operating with two large annual collections (spring/summer, fall/winter) of 450 SKUs each and single-shot purchasing from Turkish and Brazilian suppliers with 14-18 week lead times.

The visible problem: autumn-winter 2024 closeout sell-through was 62%, leaving 38% residual valued at USD 95K at cost. Forced liquidation in January-February 2025 at an average 50% discount recovered only USD 28K in cash — a USD 67K loss versus a healthy 88% sell-through scenario.

The simulator analysis exposed three operational problems. First, over-breadth in experimental SKUs: 140 SKUs (31% of the collection) were experimental colors/prints that contributed only 11% of sales. Second, wrong size curve — the buy reflected 22% XS and 22% S against real LatAm demand of 12-15% in XS; result: 42% of dead stock came from XS and small S. Third, no markdown cadence: the first discount came only in week 16 when industry corridor demands the first markdown in week 8-10 on underperformers to free cash and launch the next drop.

2025 plan: (1) reduced breadth to 280 SKUs per collection with 70% core + seasonal and 30% experimental; (2) size curve recomputed with 24 months of POS data by channel; (3) formal markdown cadence implementation with 20% in week 10, 40% in week 14, 60% clearance in week 18; (4) transition from 2 large collections to 6 bi-monthly drops with staggered purchases of 180 SKUs each.

First 8 months of 2025: sell-through on the 3 closed drops was 84-89%, average residual at 14%, gross margin up from 48% to 55%. The founder describes the shift in one sentence: 'before, I designed and prayed; now, I design and measure every week.'

From theory to calculation

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Sector reference ranges

Indicative ranges based on public sector literature and operational observation. Your business may differ — use the numbers as a starting point, not as a target.

MetricValueSource
Target sell-through at end of season — mid-market fashion70-80%BoF State of Fashion 2024 + McKinsey Apparel Economics
Gross margin — fast fashion (Zara, Inditex)58-62%Inditex Annual Report 2024 + McKinsey 2024
Healthy GMROI — mid-market fashion2.5-3.5NRF Retail Benchmarks Apparel 2024
Customers abandoning due to size stockout25-40%Euromonitor Fashion Consumer Behavior Survey 2024
Obsolescence risk reduction with monthly drops vs 2 collections/year20-40%BoF + McKinsey State of Fashion Technology 2024
New SKUs per day — Shein (ultra-fast fashion)2,000-10,000Jungle Scout Ultra-Fast Fashion Market Report 2024

Frequently asked questions

1What is sell-through rate in fashion?
The percentage of received units that sold in a period: sales ÷ receipts × 100. Healthy end-of-season benchmark: 85-92%. Below 70% signals overbuying; above 95% signals structural stockout. Measured by collection, drop, style, and individual SKU.
2How do I calculate the optimal size mix?
Start from the last 12-24 months of POS data by channel and demographic segment. A typical adult-female curve in LatAm: XS 8%, S 18%, M 32%, L 28%, XL 14%. Adjust to your real customer — mature-range fashion skews toward L/XL; youth brands concentrate on S/M. Deviations of 3+ points in a critical size generate stockout AND dead stock simultaneously.
3When should fashion markdowns begin?
Standard markdown cadence: week 8-10 first markdown 20-30% on underperforming SKUs; week 12-14 second markdown 40-50% on residual; week 16-20 clearance 60-70%; week 20+ outlet or write-off. Discounts before week 8 erode pricing power for the whole collection — customers learn to wait.
4What is a healthy GMROI for a clothing store?
GMROI (gross margin ÷ average inventory at cost) healthy: fast fashion 4-6, mid-market 2.5-3.5, premium 2.0-3.0, luxury 1.5-2.5. Below-corridor values indicate too much capital tied up in low-return inventory — review SKU mix, replenishment cadence, and OTB.
5How many collections per year is optimal?
Depends on the model. Traditional: 2-4 large collections (spring/summer, fall/winter, resort, pre-fall). Modern mid-market: 6-12 drops. Fast fashion (Zara, H&M): 52 weekly drops. Ultra-fast fashion (Shein): daily. More drops reduce obsolescence risk but require operational capability — do not copy Shein without on-demand manufacturing infrastructure.
6What do I do with end-of-season residual?
Ladder the exit: (1) online clearance 60-70% on your store; (2) physical outlet if available; (3) B2B closeout wholesaler; (4) discount marketplace (factory outlet channels); (5) tax-deductible donation; (6) write-off plus destruction. The goal is to free cash before the cost of holding exceeds residual value — typically weeks 20-24 after the drop.
7What is Open-to-Buy and why does it matter?
The budget available for future inventory purchases, calculated as OTB = projected sales + target end-of-period inventory − beginning inventory − orders already placed. Running without a formal OTB is buying by intuition, which almost always generates overbuying. It is the professional buyer's daily tool and the foundation of any serious fashion financial plan.

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Last updated: April 30, 2026 · Reviewed by the Simúlalo editorial team. Figures and benchmarks are indicative; verify with your own data before deciding.

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