Seven interdependent principles for fashion supply chains built for volatility, grounded in a decade of investor questions, a 47-company benchmark and field research inside demand-driven networks.
Executive summary
Across the past decade most segments of the fashion industry grew revenue while profits did not follow. Premium operating margins halved as revenue rose by nearly a third. Sportswear margins fell despite a doubling of revenue. Luxury margins slipped from a 27% peak in 2022 to 24% in 2025.
Investors have already located the cause. Inventory overhang, gross-margin compression and markdown dependency together account for over 40% of all problem-related questions put to management every year since 2018. These are the signatures of a long-lead-time, large-batch model that is systematically destroying a growing share of the value revenue growth creates.
The report’s core argument: agility is an infrastructure and a mindset, not a speed setting.
Revenue grew. Operating margin mostly did not.
Operating margin by segment, 2014 vs 2025, 47 listed fashion and apparel companies
| Segment | Revenue growth | Op. profit growth | Margin 2014 | Margin 2025 |
|---|---|---|---|---|
| Premium | +30% | -41% | 13.2% | 6.1% |
| Sportswear | +103% | +81% | 11.1% | 9.9% |
| Mass | +71% | +55% | 13.1% | 11.9% |
| Luxury | +140% | +194% | 19.6% | 24% |
Source: Hyran / Swanstant financial benchmark of 47 listed companies, 2014–2025
Why now
Tariff volatility makes diversification urgent while climate risk constrains where companies can credibly diversify. Regulation demands traceability across whichever new geographies are chosen. Demand volatility shortens the window in which all of these decisions must be made.
Consumer trend cycles have compressed from years to weeks. Investor questions about forecast failure went from near zero in 2014 to a sustained 20–30 per 1,000 since 2022.
Landed cost has become a moving target. China-specific apparel surcharges peaked at 145%, and investor concern about geographic concentration rose to roughly seven times its prior-decade average in 2025.
The EU ban on destroying unsold apparel took effect in July 2026, the Digital Product Passport lands in 2028–2029, and California's textile EPR scheme is phasing in.
Extreme weather is disrupting raw-material availability and quality, while heat and water scarcity pose physical risks to the hubs that dominate apparel exports.
Investor attention shifted
Mentions per 1,000 analyst questions on fashion and luxury earnings calls, 2020–2025
Inventory overhang
Gross margin compression
Supply chain disruption
Geographic / geopolitical
| Signal | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 |
|---|---|---|---|---|---|---|
| Inventory overhang | 161 | 149 | 192 | 170 | 123 | 110 |
| Gross margin compression | 88 | 110 | 112 | 118 | 128 | 115 |
| Supply chain disruption | 29 | 58 | 61 | 39 | 27 | 23 |
| Geographic / geopolitical | 30 | 10 | 7 | 13 | 29 | 129 |
Source: Analysis of 36,036 analyst questions across 1,000 earnings calls, Appendix A.5
The core argument
Demand signals, sell-through velocity and reorder probability flow down to the mill and factory. Capacity and material positions flow up to the brand, on standardised fields with clear governance over who sees and decides what.
Pre-positioning fabric, adjusting capacity and triggering replenishment against demand signals. This needs payment terms that align with fast turnover, the capability to act on a signal, and technology built as a functional asset for the supplier.
An initial run of 80–100 units looks irrational through a unit-cost lens. Once markdowns, unsold stock and disruption risk are counted, it looks very rational. Buyers need to be measured on full-price sell-through and inventory days, not cost per unit alone.
The evidence
An analysis of days inventory outstanding against operating margin across ten listed brands over 2013–2025 reveals a consistent inverse relationship. Correlation is not causation, but the pattern holds across segments and over a decade.
Lower inventory days, higher margins. Sportswear brands with faster turns operate at materially higher margins (r = −0.60, stable 2013–2024). The pattern holds in mass-market apparel (r = −0.37).
Figure from the report. Source: Swanstant PCI database, periods ending Nov 2024–Aug 2025.
The framework
They are not a checklist and they are not sequential. Each one amplifies or constrains the others: digital infrastructure enables agility, transparency makes climate risk visible and circularity possible, and fair value distribution is the financial condition under which suppliers can build the capabilities the others depend on.
Move the production decision from forecast to signal. Commit small, observe what sells, scale behind real demand, and defer each irreversible step to the last responsible moment.
Redesign the process first, then build the infrastructure that lets it run at speed across tiers. Visibility is not coordination; signals must reach the people who act on them.
One capability, two returns. The multi-tier connectivity that lets a brand reallocate production is the same capability regulators now demand.
Design waste out rather than manage it away. Overproduction is the single largest value leak, and demand accuracy is the most effective circularity tool.
A factory borrowing at double-digit rates while waiting months for payment cannot fund the capabilities the brand is asking for. Payment architecture must match the operating model.
The hubs that dominate apparel exports are among the most climate-exposed geographies. Network design choices that cut emissions also reduce concentration risk.
A supply chain can be outsourced. An ecosystem has to be built, with governance, investment and incentives that reward execution with orders, speed and payment.
The principles as a system
Taken together, they distribute risk more openly across the chain, replacing a model in which forecast error cascades downstream with one in which information and the ability to act on it are shared across tiers.
Principle 1 in practice
For a high-risk SKU, material can be held in the yarn or greige state. As confidence in the demand signal grows, dyeing, cutting and sewing follow. Early commitments buy speed to market but lock in cost and remove flexibility.
The risk escalation pyramid
Top: highest risk, fixed commitments. Bottom: lowest risk, maximum flexibility.
Hyran's agentic orchestration layer sits between brand planning (materials, capacity, costing) and factory operations (knits, wovens, dye house, RMG), turning demand signals into material and production decisions.
Figure from the report case study: Hyran Technologies.
Case study · Hyran
A demand-driven model only works if demand signals can be converted into operational decisions across the chain: how much material to commit, what stage to hold it in, when to move from greige to colour, and how suppliers should plan capacity. Planning that would otherwise take days can be updated in seconds.
Hyran internal client data, 2023–2025
Interdependencies
The 2021 semiconductor shortage cost the automotive industry an estimated $210 billion. Automakers lacked visibility beyond Tier 1, had no shared early-warning mechanisms and could not re-coordinate capacity. The principles are a supply chain resilience framework, not a fashion-specific one.
Demand signals only create value if they reach the actors able to respond in time. Infrastructure without an operating model that acts on it produces dashboards, not decisions.
Climate exposure, material provenance, working conditions and constrained capacity cannot be managed while they remain invisible below Tier 1.
Faster changeovers, reserved capacity and digital readiness need investment. Payment terms and order stability decide whether suppliers can make it.
Producing fewer unwanted products prevents economic waste and its footprint. Recovered materials reduce exposure to volatile virgin inputs.
Compliance and operational transformation rely on the same data: supplier identity, material composition, production status and cross-tier visibility.
One brand, one platform, many Tier 1 and Tier 2 suppliers. Orders, demand signals, capacity and status flow in both directions so every supplier plans against the same live picture.
Figure from the report, Principle 7: Ecosystem building.
The operating decisions leaders must optimise
Producing close to demand cuts overproduction and the inventory that weighs on margins. Combined with long-distance air fulfilment, carbon can shift from inventory to freight. Four levers compound to close that gap: modal split, geographic diversification, volume consolidation and sustainable aviation fuel.
Leaner inventory, higher transport carbon. The navigator shows where an operating model sits on air-freight intensity and overproduction, and which way to move. A clear carbon benefit opens up at low overproduction.
Figure from the report. An orientation tool, not a precise benchmark; methodology in Appendix B.
Modal split is the largest carbon lever
Blended transport emissions intensity by sea/air mix, tCO₂e per €m revenue
| Modal split | Intensity (tCO₂e/€m) | Reduction vs all-air |
|---|---|---|
| 0% sea / 100% air | 243 | — |
| 30% sea / 70% air | 176 | −28% |
| 40% sea / 60% air | 153 | −37% |
| 50% sea / 50% air | 131 | −46% |
| 80% sea / 20% air | 65 | −74% |
Source: Hyran analysis. Illustrative; actual reductions depend on route, load factor and product weight
Concrete application
Each is answered with case studies drawn from the research: an on-demand inventory system across 7,500+ suppliers, margin protection at Rise & Fall, Asphalte and Maria Grachvogel, and the Ellen MacArthur Foundation's Jeans Redesign.
How can we reduce inventory risk and the associated working capital trap?
How can we protect gross margins from the pressures of markdown dependency?
How can we build a business model that is compliant with, and benefits from, the transition to a circular economy?
Where to start
Stable, replenishment-driven styles can stay on automated reorder triggers. New, trend-driven styles are where small-batch, test-and-respond disciplines return the most.
Connect the top 20% of suppliers on a shared platform. Prioritise frequent demand signals, material pre-positioning with postponement, and inventory levels across Tier 1 and Tier 2.
Asking suppliers to hold less inventory and respond faster while keeping extended payment terms is contradictory. Suppliers should not bear both payment and order uncertainty.
Factory-floor responsiveness is the rate-limiting step between a demand signal and replenished stock. Supporting variable-order, fast-turnaround workflows unlocks the model.
What to monitor
Full-price sell-through
Industry 60–70%. Agile models target 90%+.
Weeks of cover at reorder
Measures response to real demand, not safety stock.
Markdown rate as % of gross margin
The direct financial cost of overproduction.
Reorder fulfilment lead time
From confirmed signal to goods available for sale.
Initial batch-to-reorder ratio
How well test-and-respond filters demand.
Regulatory readiness score
Share of volume that can already generate DPP and EPR data.
About the report
This report was led by Hyran, with analytical support from Swanstant and with support from SHEIN. The core research team comprised Ahmed Zaidi, François Souchet and Ankit Tejpal, with Ahmed Zaidi and François Souchet as lead authors.
Editorial control rested with Hyran and Swanstant throughout. SHEIN contributed funding and provided access to its internal supply chain and sustainability functions and external manufacturing partners, including site visits and interviews. No company financial data were furnished for inclusion. Where the evidence raised tensions or left questions open, the report says so.
External experts from Shahi Export, Matrix Sourcing, MAS ACME USA, the Smart Freight Centre, Textile ETP and the Otto Group stress-tested the analysis. Their participation does not imply endorsement of its conclusions. Responsibility for the final text rests with Hyran alone.
Hyran
Research lead and editorial control
Analytical support and financial benchmark
SHEIN
Research funding and field access
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