Open your inbox. Scroll through the vendor pitches that have landed in the last six months.

Count how many have a .ai domain. Count how many claim to be “the first AI-native [something] platform” or position themselves as the “AI-first” solution in their niche.

This is the current state of B2B software positioning, and it’s working.

Deals are getting done. They’re genuinely impressive in a demo, they move fast, and they’re being funded aggressively.

Fast growing businesses are adopting these new-breed tools and attempting to run critical operations on them.

But there’s a big, unspoken risk attached to such a move…

There are going to be far more venture backed businesses with .ai domains that fail in the next five years than succeed. That’s just how venture maths works at scale. And right now, fast-growing retail brands are considering building their operational backbone around these tools as if that reality doesn’t apply to them.

But it does.

The numbers behind the narrative

BLS (Bureau of Labor Statistics) data shows that 20% of newly created businesses don’t survive their first year. 50% are gone within five. Only 34.7% of businesses born in 2013 were still operating a decade later.

That’s not software-specific. But before you sign a multi-year contract with a company that was incorporated eighteen months ago and has a founder who’s never shipped an enterprise product before, it’s the right place to start.

The instinct is to dismiss this. “We’re not buying from some seed-stage startup. Our vendors have raised serious money.” That’s where the thinking tends to go wrong.

Venture economics are built on extreme skew. Only 1 in 140 VC-backed companies ever becomes a unicorn. The model assumes a small minority of portfolio companies become massive winners and a large majority don’t. That maths works fine for a fund managing across dozens of bets. It’s a terrible basis for choosing the system that runs your inventory, your finance, or your order orchestration.

Fashionable and well-funded is not the same as durable. The more capital floods into a single narrative, the more companies that narrative attracts - including a lot that won’t survive the consolidation that always follows a hype cycle. Funding is not a durability signal. It’s a signal that someone made a calculated bet on upside. Those are different things, and the retail industry keeps confusing them.

The question missing in the evaluation room

Being first to adopt an emergent tool in your marketing stack is a calculated risk worth taking. Being first to run your inventory, your finance, and your fulfilment on one is a different kind of bet entirely.

If it goes wrong, you’re not dealing with a campaign that underperformed. You’re dealing with an operational crisis, a migration under pressure, and a vendor that may not have the resources to support you through either.

The vendor evaluation process at most brands goes the same way. Features. Pricing. Integration complexity. Maybe a reference call with a brand two sizes bigger than yours. Nobody asks whether the company will still exist in three years. Nobody models what a forced migration would cost. Nobody asks what happens to their data if the Series B doesn’t close.

Those are the questions that should be leading the conversation. Especially now.

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Private equity isn’t necessarily the safe alternative you think it is

The counter-argument usually goes: “We don’t buy from scrappy startups. Our vendors are PE-backed.”

Moody’s data shows PE-backed companies defaulted at roughly double the rate of non-PE-backed peers between 2022 and 2024. Even among the largest, most established sponsors, default rates sat around 14%. S&P counted over 80 US PE portfolio company bankruptcies in 2024 alone.

What retail operators should actually be doing

The problem isn’t that brands are buying software from young or PE-backed companies. Some of the best tooling available right now comes from exactly those places. The problem is that the evaluation process doesn’t match the stakes.

If a vendor sits in the control layer of your business - finance, inventory, order management, replenishment - the bar for selection and ongoing management should be different from a tool running your email campaigns or your content.

For the control layer, the questions that actually matter:

On operational continuity. If this vendor ceased trading tomorrow, what’s your data extraction plan? How long would a migration take, and what would it cost? Have you modelled that scenario, or is it just uncomfortable to think about?

On financial durability. When did they last raise, and what does their runway look like? What’s their path to profitability?

Is it really worth the risk. When compared to established vendors in the space, do the feature and speed benefits really justify the inherent risks?

Most brands can’t answer those questions for their current vendors. That’s the real exposure.

The contrarian position

The standard advice is to avoid young vendors and stick to established platforms. That’s not quite right either.

The right frame is: match vendor maturity to workflow criticality. New, AI-native tooling can earn a place in your stack. Just maybe don’t put it at the centre of your entire operation just yet. Run your experimentation, your personalisation, your content tooling on the exciting new thing. Run your finance and inventory on something with a 15-year track record, a deep implementation ecosystem, and a balance sheet that’s survived at least one economic downturn.

The brands getting this wrong aren’t naive or foolish. They’re running an evaluation process that assumes software companies to be more durable than the data suggests they actually are.

Reliability is about to get expensive again. The vendors that survive the next round of consolidation will charge more for it, and buyers will pay, because they’ll have learned the hard way what the alternative looks like.

The uncomfortable truth

Somewhere right now, a founder is in a board meeting celebrating a new ERP go-live. The vendor they chose has eighteen months of runway and a Series B that hasn't closed. Nobody in that room knows. That's the problem.

But when they break, they break in exactly the same places.

That’s one of the more useful findings from our latest research, and it’s worth unpacking because it changes how you diagnose operational problems and where you look for the fix.

Most ecommerce stacks are layered. And the layers don’t fail evenly.

At the surface is what customers see: checkout flows, returns portals, localised pricing, branded experience. These layers tend to work well. They’re visible, well-supported, and heavily optimised for conversion and customer satisfaction. When brands invest in new tools, this is usually where the improvement shows up.

Beneath that sits the logic layer: rules, policies, routing decisions, market configurations, exchange logic, exceptions. This is where complexity starts to compound. Edge cases become day-to-day reality. And the assumptions baked into the platform start to show their age.

Underneath both is the operational core: inventory accuracy, landed cost, duties and tax treatment, margin attribution, financial reconciliation. This layer is the hardest to see, the hardest to change, and the least forgiving when something goes wrong.

When brands add new tools, they usually improve the top layer. When they scale internationally, the strain shows up in the layers below.

The friction points our research surfaced were identical across both returns and cross-border: ERP connections requiring manual reconciliation, WMS integrations that don’t reflect real-time inventory, OMS workflows creating duplicate orders or missing data, Shopify Markets configurations that don’t align with operational reality. It doesn’t matter which part of the operation you’re talking about. The failure mode is the same.

And then there are the workarounds.

Every brand we spoke to has at least one spreadsheet, one Slack channel, or one person who just knows how to fix the thing that should work automatically.

As our co-founder Andy Slater put it: “Every brand has temporary fixes that eventually became permanent. You’ll find that last Black Friday something broke, so a plaster got applied to make it work, and then that plaster just becomes part of the business. No one questions it, no one documents it, and it only surfaces again when something else breaks or the one person who built it leaves.”

That’s not a technology failure. It’s an organisational one. And it’s almost impossible to see from the outside, or even from the inside, until something forces it into view.

The reason this framing matters is that it shifts where you look when something isn’t working. If returns feels broken, the instinct is to evaluate returns platforms. If cross-border margin is leaking, the instinct is to interrogate the cross-border provider. Sometimes that’s the right call. But more often, the problem is in the connective tissue: the integrations, the routing logic, the manual processes that have hardened into infrastructure.

Fixing a layer-one problem when the failure is in layer three doesn’t solve anything. It just gives you a better-looking surface on top of a fragile foundation.

Our full research report maps this in detail across both returns and cross-border operations, including where the shared failure points show up most consistently.

Read the full report

That’s the dangerous bit. ERP can fail without a big bang and an error message. It fails quietly, then becomes the reason teams keep a separate spreadsheet and route workflows around the system instead of through it.

If you’re in that limbo, don’t default to blaming the software. In practice, the problems can be self-inflicted. You can have a great system and a great SI, and still end up with something that technically works but nobody trusts because it doesn’t reflect how the business actually runs.

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The quiet failure pattern

The first sign you’re off track is when the project starts optimising for sign-offs instead of outcomes. Milestones get ticked off, demos look slick, but nobody can walk a real order through the full flow without wincing.

The internal tell is confidence. If every test reconciliation is throwing up surprises, and confidence in the system is evaporating, that’s not teething issues. That’s a project that might not recover.

This is why brands without an in-house ERP operator get caught out. Each partner can genuinely deliver their slice, but if you haven’t got enough internal expertise you don’t know how to challenge it.

And the ugly truth is the in-between bits are where things break. Orders moving from your ecommerce platform into ERP, being picked in the warehouse, and landing back into finance is the chain where issues hide. A missing field, a misaligned mapping, a forgotten checkbox, and suddenly your operation breaks in a place nobody owns.

So if your project status looks green but your team’s behaviour is screaming red, listen to the behaviour. Workarounds aren’t coping mechanisms; they’re your warning system.

The stuff that actually derails go-live

If you’ve effectively outsourced decision-making to your vendor and your SI, you’re already late. Training isn’t the same as confidence, and confidence doesn’t appear by magic. It shows up when someone inside the business has the authority and experience to push the system further, and to keep pushing when it gets uncomfortable.

The pitfall here is thinking you can buy capability. You can’t. You either bring in an in-house operator early, or you choose partners who transfer knowledge rather than hoard it, and you set that expectation from day one.

The next sign is capacity theatre. Everyone says they don’t have time, but the real issue is you haven’t made room for the work.

You can’t implement something like ERP by squeezing it in around the edges. That’s not a time problem. That’s a capacity problem.

If your finance lead is meant to redesign the close, run UAT, and still hit month-end with a skeleton team, you’re not running an implementation. You’re setting yourself up to cut corners, miss issues, and then pay for it later.

Then there’s data. Not data in the abstract. Your product data, your SKUs, your attributes, your categorisation, the stuff merch and product dev live and die on.

If data is incomplete, outdated, or inaccurate, the outputs are useless. And if you’ve got no clarity on who owns that data across the business, you’ll end up duplicating entry, arguing about definitions, and migrating a mess with a nicer UI.

The pitfall is leaving product data clean-up as an IT workstream you’ll get to later. You won’t. You’ll hit cutover, discover items don’t behave properly, and you’ll be trying to fix it at the exact moment the business needs stability.

Timeline pressure is the other classic. Vendors will happily sell you speed, and the business will happily attach go-live to a milestone because it feels decisive. The cost of that decisiveness lands on you when quality gets traded away to hit a date.

Missing a vendor’s deadline is frustrating. Missing your own readiness is catastrophic.

If you’re hearing “can we go live in 90 days,” you’re asking the wrong question. The right question is what needs to be true for you to go live in 90 days.

That shift matters because it forces the awkward conversation. If sponsor attention, capacity, integrations, and data readiness aren’t there, the answer isn’t cross your fingers. The answer is to move the date.

Testing is where all of this gets exposed. If UAT is mostly happy-path clicking, you’re setting yourself up for the sort of failure that doesn’t even throw an alert.

Integrations can fail quietly. Orders can stop flowing, postings can be incomplete, and you won’t know until someone reconciles properly and realises things don’t tie out. That’s when the panic starts, because you’re now debugging while customers are waiting and finance is trying to close.

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That’s why end-to-end testing beats vendor sign-offs when you’re testing whether your business can trade. You’re not testing modules, you’re testing whether your business can trade.

And don’t kid yourself that some functions can join later. If finance isn’t engaged during implementation, then relies on the ERP for reporting, you can end up with the data wrong because the system didn’t meet their needs and nobody caught it in testing.

By the time you realise, it’s not a quick fix. With a large volume of inaccurate records, you’re into a long slog that could’ve been avoided by involving the right teams from the start.

Why talking to someone who’s done this matters

The difference between a successful project and a rescue mission usually comes down to whether someone in the room knows where the skeletons are buried.

Not theoretical skeletons. The actual ones. The integration that looked fine in the demo but breaks under volume. The data migration that passes validation but lands finance with a reconciliation nightmare. The cutover plan that works on paper but collapses when your warehouse team is still picking orders.

This is what Commerce Thinking’s ERP practice exists for. We’re former brand-side operators from companies like Gymshark, Liverpool FC, and Burberry who’ve run these projects, lived through the mistakes, and know what good looks like when the pressure’s on.

We’re not here to sell you more config or extend timelines. We’re here to tell you what’s actually going to break before it does, challenge the bits that don’t make sense, and make sure your team can own the system when we leave.

Because the goal isn’t dependency. It’s capability. If you need us six months after go-live to run a routine process, we’ve failed.

If you’re mid-project and starting to feel that unease, or you’re about to kick off and want to avoid the traps, talk to us. We know what a good project looks like because we’ve built them. And we know what a struggling project looks like because we’ve rescued them.

If you’ve got that sinking feeling

ERP doesn’t solve problems. People do.

If you’re mid-project and you’ve got that feeling, treat it as a signal. You’ve still got time to fix the fundamentals, make room, clean the data, and force end-to-end ownership before the system becomes a very expensive spreadsheet generator.

You don’t need deeper config. You need broader context, the kind that understands how your teams actually work, not how the process map says they should. If you don’t bake that context into design and testing, you’ll go live and still be arguing about why merchandising missed PO lock dates or why a landed cost update has just blown up reporting deadlines.

None of this is about perfection. It’s about reality.

That’s a different kind of problem. And it’s the one our latest research puts a sharp point on.

15 of 24 brands we spoke to use a dedicated cross-border platform. Of those 15, only three have ever migrated to a different provider. The frustrations are near-universal: cost opacity, rigid workflows, slow iteration, roadmaps that feel disconnected from operational reality. The satisfaction scores reflect it too, with Global-e sitting at 5.6 out of 10 in our research.

And yet the switching rate is remarkably low.

The reason isn’t loyalty. It’s architecture. Cross-border platforms sit deep in the stack. They touch checkout, duties calculation, currency conversion, fraud, logistics, and returns. Ripping one out means re-integrating all of it, often during the same peak periods when the pain is most acute. The risk feels higher than the reward, so brands tolerate. They work around. They accept margin leakage they can’t fully quantify because the alternative feels worse.

One operator captured the sentiment clearly: “They are the market leader, thus regarded as best in class, but we do not regard them as a pragmatic partner.”

That’s a telling quote. It points to a gap between market position and actual operational value that is becoming harder to ignore as international revenue becomes more material and finance teams start asking market-level questions the tooling can’t answer cleanly.

The parallel with returns is striking. Two or three years ago, returns looked exactly like this. High dissatisfaction, low movement. Operators knew something was wrong but couldn’t justify the migration cost. Then platforms like Loop, Swap, and Reveni made it easier to move, and the market shifted. Switching behaviour that looked structural turned out to be situational.

Cross-border hasn’t had that moment yet. But the conditions for it are building.

Macroeconomic pressure is forcing greater scrutiny of international margin. Currency volatility, rising logistics costs, and tighter cash positions are making previously tolerated leakage harder to ignore. At the same time, operating models are shifting. Brands that once ran a single global storefront are experimenting with multi-store setups, regional entities, and more complex Shopify Markets configurations. Those changes surface limitations in cross-border platforms that were designed around simpler assumptions.

The question for 2026 is whether cross-border follows the same arc as returns, or whether the integration depth keeps brands locked in longer. We don’t have a definitive answer. But the brands that are already stress-testing their cross-border setup, mapping their actual margin by market, and building internal clarity on what switching would involve, are going to be better positioned when that moment arrives.

Our full research report covers the cross-border landscape in detail, including adoption patterns, satisfaction scores, and the specific friction points operators flagged most consistently.

Read the full report

In this series, we’ve been following West Park Rovers, the fictional club from Kieran Maguire’s The Price of Football, as they bring retail in-house.

So far, we’ve covered the business case for making the move, the operational reality of running what is effectively a small factory, and in the last piece, The 12-Month Apocalypse, the brutal economics of a catalogue that expires every year.

That piece was about pressure with a fixed horizon. Time you can see running out.

This one is about the opposite.

Moments that arrive without warning. A goal. A farewell. A signing that shifts the mood of a whole city overnight. Demand that exists right now and will be gone by Thursday.

Seasonal retail has a calendar. Sports retail has a pulse.

Catch up on this series:

• Part I - West Park Rovers

• Part II - The Business Case

• Part III - Your Club Shop is a Factory

• Part IV - The 12 Month Apocalypse

Most retail businesses plan in seasons.

Spring drop. Summer sale. Autumn launch. Clearance.

Sports clubs plan in interruptions.

A late winner. A derby goal. A record broken. A captain leaving. A shock signing. A manager sacked on a Tuesday.

These moments do not arrive politely. They do not wait for a range review. They do not care what your production lead time is.

Fans react instantly. Your shop usually doesn’t.

That gap is where the money leaks. It is also where the relationship weakens.

Because in sport, the moment is the product.

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The problem with “seasonal” thinking

When retail is outsourced, the calendar wins.

A licensing partner plans ranges months in advance. Products get approved, produced, shipped, and sold. Everything is built for predictability.

That’s fine for the fundamentals. New kits. Training ranges. Evergreen accessories.

It falls apart the second something unexpected happens.

A goal that goes viral.
A farewell that turns emotional.
A promotion that changes the mood of a whole city.

Fans want to mark it now. They want something that says “I was there” while the story still feels alive.

Outsourced retail rarely moves at that speed. It moves at the speed of contracts, approvals, and shared priorities.

By the time it reacts, the moment has already moved on. The emotion has cooled. Fans have spent elsewhere. Or they have bought something unofficial.

In-house doesn’t just mean “make new products faster”

This is where most clubs get the wrong idea.

They hear “moments” and jump straight to “drops”.

Limited edition tee. Special graphic. Quick turnaround print run.

Sometimes that is the right move. Often it isn’t.

Because the most valuable part of moments-based merchandising is not always new product creation.

It’s attention control.

If a player has a standout performance, you do not always need a new item. You need to make it easier for fans to buy what already exists.

That means:

• Moving relevant products higher up collection pages

• Updating homepage modules while traffic is spiking

• Changing default recommendations to match what fans are searching for

• Making search forgiving when names are hard to spell

• Ensuring the “obvious” products are not buried behind generic navigation

This is not hype. It’s friction removal.

You are not inventing demand. You are stepping out of its way.

That is why bringing retail in-house changes everything. It gives you the ability to re-merchandise in hours, not weeks.

Not loudly. Not desperately. Just intelligently.

Why moments matter more than campaigns

West Park Rovers start by looking at what actually drives spikes in their store traffic.

They expect it to be planned launches. It isn’t.

The biggest surges come from unpredictable events.

A big win.
A controversial result.
A player suddenly becoming a hero.
A goodbye nobody expected to hurt as much as it did.

The club’s current retail setup can’t capture those surges properly because the store isn’t designed to respond to the club’s reality. It’s designed to sell a pre-agreed range efficiently.

That is the difference.

A club does not need a better calendar. It needs an engine that can turn emotion into action.

The line between celebration and cash grab

This is the delicate part.

Moments merchandising can feel cynical if it’s handled badly.

Fans can smell opportunism. They know when something is a cheap grab. They know when a moment is being squeezed for revenue.

But that is not a reason to ignore moments altogether. It’s a reason to build a better approach.

The best moment-based merchandising does three things:

1. It feels like it comes from the club
   The tone, design, and framing matter. Fans are buying belonging, not fabric.

2. It respects timing
   If you show up too late, it feels performative. If you show up too aggressively, it feels exploitative.

3. It offers something real
   That could be a limited item, a numbered run, a commemorative piece, or simply a more thoughtful presentation of existing products.

The point is not to monetise emotion. The point is to give fans a way to participate in it.

If the club does not provide that, someone else will.

The operational truth behind the romance

This is not a creative challenge. It’s an operational one.

If you want to respond to moments, your operations need to be built for volatility.

That means:

• Stock strategy that supports late-stage customisation

• Clear processes for prioritising what gets promoted and when

• Fast changes to storefront merchandising without breaking everything

• Systems that can handle sudden spikes without collapsing

• A decision-making model that doesn’t require six sign-offs

Moments do not wait for internal alignment.

West Park Rovers realise that “being agile” is not a marketing aspiration. It is a capability. And capabilities are built, not wished into existence.

You either have the muscle to move quickly, or you don’t.

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Why outsourcing struggles here

It’s not because third parties are incompetent.

It’s because they are optimised for a different game.

A licensing partner is built to deliver a stable operation at scale. They plan ranges, manage inventory, fulfil orders, and protect margin through predictability.

They are rarely built to:

• Drop everything for one club’s unexpected moment

• Take creative risks on short-run products

• Re-merchandise a site in line with match-day emotion

• Deal with chaos without renegotiation

Their job is to run a retail business efficiently.

Your job is to run a club that generates constant, unpredictable stories.

When the store isn’t connected to the story, it becomes generic. Fans feel it. And they shop accordingly.

Treat moments as signals

The real shift for West Park Rovers is how they think about their retail calendar.

They stop treating it as fixed.

Instead, they plan the season like a framework with space for signals.

Signals like:

• A player spike in popularity

• A sudden increase in searches for a specific name or item

• A viral clip driving traffic to the store

• A surge in demand for a certain product line after a match

The club does not need to guess perfectly.

It needs to be able to notice, respond, and capitalise without panic.

That means building the store to be rebalanced continuously, not refreshed occasionally.

The short version

Sports retail is not seasonal retail.

It’s reactive retail.

The most valuable moments are unpredictable. That is exactly why they are valuable.

Clubs that run commerce in-house don’t win because they can print a t-shirt quickly. They win because they can move attention quickly. They can make the obvious products easier to find. They can respond to demand while it still exists. They can show up in the moment without making it feel like a scheme.

Fans will always buy around moments.

The only question is whether they buy from you.

That’s the data point our latest research leads with in its chapter on switching behaviour, and it’s worth sitting with for a moment. This isn’t normal SaaS churn. Most software categories don’t see this level of movement at this stage of market maturity. What it tells you is that the returns platform market is still finding its shape, and that the fit between platform and operator breaks more often than anyone building the original business case probably expected.

The more interesting question, though, is why.

When we dug into the reasons behind platform switches, it wasn’t feature gaps or platform failures doing the damage. It was context shifts. The business changed shape, and the platform didn’t change with it.

New markets were the most common trigger. A platform that worked cleanly for UK-only operations doesn’t necessarily scale to EU or US without significant friction. Additional warehouses created similar pressure: routing logic that made sense when inventory lived in one location starts to break when it’s spread across multiple sites. Finance scrutiny drove switches too, particularly when leadership started asking margin questions the current setup couldn’t answer. And volume growth exposed the difference between a platform that works at 5,000 returns a month and one that holds up at 25,000.

There’s an implicit promise in most SaaS relationships: implement once, optimise occasionally, move on. Returns doesn’t work that way. Every new market, warehouse, or carrier relationship introduces friction. Every peak season stress-tests the setup. Every finance review surfaces questions the platform wasn’t designed to answer.

Operators aren’t disloyal. They’re pragmatic. When the fit breaks, they move.

What’s also interesting is the direction of movement. Most switching isn’t happening between modern platforms. It’s happening away from older, more rigid setups. And once that first move is made, appetite for further switching drops significantly. Platforms don’t need to be perfect. They just need to feel directionally right.

This changes how competitive pressure shows up in the market. Modern platforms aren’t winning by pulling customers from each other. They’re winning by being the obvious next step once legacy setups break. That makes switching events rarer but more decisive. When a brand is ready to move, they usually know where they’re going.

For brands, the practical implication is straightforward: budget for re-evaluation. Returns infrastructure isn’t a one-time decision. It’s something that needs to be revisited as the business changes shape, not just when something breaks.

The brands that treat their returns setup as a living part of the operation, rather than a problem that’s been solved, tend to be the ones that don’t end up in crisis mode when volume spikes or a new market goes live.

Our full research report covers this in more detail, including the specific triggers that tend to drive migration decisions and what the switching patterns tell us about where this market is heading.

Read the full research

That changes now. And AI gives us the perfect reason to start.

The pace of change hitting back-office functions right now is unlike anything most brands are prepared for. The operators who figure it out early, together, in the same room, without a sales pitch in sight, are going to be miles ahead. That’s what Operator Experience is built for. And OX1 Manchester on 16th April is where it begins.

What’s Happening

12:30 – 17:00 | Hallé St Peters, Manchester M4 6BF

The afternoon is structured around a single, practical question: what if your brand challenged itself to automate 30% of all operational tasks by 2030?

Working in small squads, you’ll map end-to-end processes, hunt for automation opportunities, and identify the highest-value targets, prioritising quick wins you can actually take back to the office on Monday. You’ll leave with a concrete initiative in hand, not a deck to file away.

The session opens with AI Essentials and How to Use It Safely, covering real-world use cases across product, ecom, finance and ops, alongside risk, governance, and compliance guidance you can apply immediately. Special guests will share AI-era org structures and practical safety frameworks.

What you need to bring: a charged laptop. We’ve got everything else.

17:00 – Late | The Castle, 66 Oldham St, Manchester M4 1LE

After the workshop, the evening continues at The Castle, a proper pub, a proper crowd. Strictly brand-side operators. No selling, no pitching. Just the kind of honest conversations you rarely get to have when everyone else in the room has a commercial agenda.

And fashion photographer Nathan McDowell will be capturing the day, so you’ll get professional shots afterwards.

You’re in Good Company

The brands already confirmed are ones you’d know; fast-growing, operationally serious, and brand-side through and through. But more than the names, it’s the people in the room that matter. Directors and heads of function dealing with the same challenges you are. No hierarchy, no agenda. Just people who get it.

Who Is This For?

If you’re a director, head, or senior leader in:

• Operations or supply chain

• Finance and back-office technology

• Ecommerce

• Merchandising or buying

• Product data or tech

...and you work brand-side at a fast-growing fashion, apparel, or consumer brand, this is for you.

The agenda has been built by the community itself: Lauren, Robbie, Ewan, Robin, Roberta, Kya, Paul and Luke. People who’ve sat in your seat and know exactly what’s useful and what’s a waste of time.

Made Possible By Our Partners

OX1 Manchester is free to attend for brand-side leaders and operators. That’s only possible because of our partners, who are here to support the community, not sell to it.

Headline: Dema
Event: Emfas, Loop, Torque
Community: Whanau, Vervaunt, Commerce Thinking, Centra, High Cohesion, Resourced

They’ve committed to making this a no-promotion, no-posturing environment. If you’re here, it’s because someone thought you’d fit.

How to Join

Places are limited. This is a curated event, size is deliberately kept small so the conversations are real and the workshop actually works.

To register or express interest in joining the Operator Experience community:

operatorexperience.ai

If you want to know more about what Operator Experience is building, a peer community for brand-side operators, events across the UK, and a space where the people doing the work can actually learn from each other, that’s the place to start.

Save the date: 16th April 2026. Manchester. See you there.

So why does the returns process still feel, for so many teams, like a constant source of pain?

That’s the question our returns and cross-border research puts at the centre of its second chapter. And the answer is one of the more useful distinctions in the whole report: the gap between tool satisfaction and operational confidence.

Operators like their platforms. They do not necessarily trust their returns operation.

That gap, between “I like my returns platform” and “I trust my returns process end to end,” is where margin leaks. It’s where manual workarounds live. It’s where the spreadsheet that someone built eighteen months ago becomes quietly load-bearing infrastructure.

The pain, when you dig into it, isn’t in the platform itself. It’s in everything the platform has to connect to.

Integrations with WMS, ERP, and OMS systems that half-work or require constant maintenance. International routing logic that doesn’t flex cleanly across markets, carriers, and cost structures. Reporting that’s fragmented across three systems and reconciles in none of them.

As one operator put it during our research: “The returns portal is great. The returns process is a nightmare.”

That sentence captures something important. It tells you that the product problem in returns has largely been solved. The platforms are good. The interfaces are clean. The customer-facing experience has improved significantly. What hasn’t improved at the same rate is the operational infrastructure those platforms sit inside.

Our research surfaces a consistent set of operational failures that show up not as edge cases but as default behaviour across brands. Returns being routed to the wrong warehouse because the logic doesn’t reflect actual cost or inventory. Duties being paid twice, or not reclaimed at all, on international returns. Exchanges requiring manual intervention despite available stock. Customer service teams overriding policies to unblock customers, creating inconsistency and margin leakage downstream. Finance teams reconciling returns and refunds weeks later, outside the core systems.

None of those are platform failures in isolation. They’re symptoms of systems that weren’t built to work together at this level of complexity.

The other area the research flags is recovered revenue. Almost every brand we spoke to is capturing some value through exchanges and store credit. Very few feel confident they’re maximising it. The mechanics exist in most modern platforms. The strategic clarity doesn’t. Teams aren’t sure what good looks like, how much they’re actually retaining, or where the biggest opportunities sit.

What this means practically is that if you’re evaluating your returns setup and the platform scores well, you’re asking the right question in the wrong place. The platform isn’t the bottleneck. The bottleneck is the system around it: the integrations, the routing logic, the reporting, and the manual workarounds that have quietly become part of how the business operates.

Good tools don’t fix broken systems. That’s the takeaway from this part of the research, and it’s a useful frame for any team that’s wondering why their returns operation still feels harder than it should.

Read the full research

That’s the thing that keeps coming up when you talk to mid-market ecommerce operators about international revenue. There was no board-level decision, no market entry strategy, no dedicated team assembled to manage cross-border complexity. There was a product that went viral in Germany. A TikTok that landed in the US. A marketplace that opened up in France. And then, somewhere between the excitement of the numbers and the reality of the fulfilment queue, 40% of orders were shipping overseas.

The growth was real. The infrastructure to support it was not.

In our latest research, 71% of brands reported that 30% or more of their revenue comes from international sales. At the sharper end, six brands sat between 70% and 90% international. These aren’t global enterprises with regional teams and dedicated localisation budgets. They’re mid-market operators, often with lean teams, domestic systems, and workflows that were designed for a single market.

The phrase that keeps coming back is this: technically global, operationally domestic.

It’s a useful way to think about where a lot of brands currently sit. The revenue is international. The returns logic, the customer service setup, the finance reconciliation, the carrier relationships, the duties handling: mostly not. And for a while, that works. Orders go out. Customers receive them. Revenue goes up.

Then the cracks appear.

Returns from international customers become more expensive and harder to route. Cross-border costs start eating into margin before anyone is measuring them properly. Finance teams begin asking questions that operations teams can’t answer. And suddenly the gap between revenue growth and operational capability becomes impossible to ignore.

The important thing to understand is that this isn’t a failure of ambition or planning. It’s a structural pattern. Paid social doesn’t respect borders. Organic demand doesn’t wait for you to build a cross-border strategy before it shows up. The platforms that brands use to grow, Shopify, Meta, TikTok, don’t have a “domestic only” setting.

What this creates is a very specific kind of operational challenge. The brand looks international from the outside. The infrastructure, if you dig into it, is still built around assumptions that made sense when 90% of customers were in the same country.

The first step toward fixing it is recognising it. And for many brands, that recognition is still catching up with the reality of their revenue mix.

We spoke to 24 fast-growing ecommerce brands for this research, primarily in fashion and consumer goods, with revenues ranging from approximately £10m to £100m. The full report is worth reading if you’re running or advising a brand at this stage of growth. Not because it has all the answers, but because it makes visible a set of problems that most teams are quietly navigating without a shared language for them.

If your international revenue is growing faster than your operational capability to support it, you’re not alone. You’re the norm.

Read the full research

If you’re a parent, you know what that means. The same episode of your child’s favourite show. On repeat. Over and over again.

In our house it’s Bluey, The Sign. I’ve lost count how many times we’ve watched this 30 mins episode.

In global commerce, it’s tariffs. And the three year old is the US President.

Trump is not considered a serious person by most of the world. But the consequences of his actions are.

Another threat. Another headline. Now a proposed 10% global tariff.

Rather than write another long explainer, here’s the short version.

If you’re an overseas brand selling into the US, these are the decisions you should make now. And stop procrastinating on.

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1. Model the Numbers Properly

Not high-level margin. Not blended averages.

Build a SKU-level landed cost model under both a 10% and 25% scenario. Know your true duty exposure, margin by channel, break-even thresholds, and cash impact.

If you haven’t modelled it, you’re operating on hope.

2. Import at Cost, Not Retail

If you’re shipping DTC cross-border and importing at retail value, you are voluntarily inflating your duty base.

Fix your transfer pricing, importer of record setup, and merchant of record structure.

3. Move Inventory into the US (If Volume Justifies It)

Stop treating the US like just another international market.

Bulk import at cost. Hold inventory in a US 3PL. Ship domestically.

Lower duty base, faster delivery, lower friction, more control. This isn’t just tariff mitigation. It’s operational maturity.

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4. Clean Your Product Data

Tariffs expose weak foundations.

You need accurate HS/HTS codes, clear country of origin, a clean item master, and SKU-level cost integrity.

If your ERP can’t tell you margin by SKU by market with confidence, that’s a real problem.

5. Build Pricing Agility

Decide now where you absorb, where you pass on, and what your threshold triggers are. Static global pricing is fragile in a volatile political environment.

6. Decide What the US Actually Is to You

Is it a strategic growth market, a profitable channel, or just incremental revenue?

If it matters, operationalise it properly. If it doesn’t, stop pretending.

7. Stop Delaying

Every time tariffs are mentioned, brands say the same thing: let’s wait and see.

We’ve been waiting and seeing for years.

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The bottom line

You can’t control Trump’s next outburst. He has the temperament of a three-year old.

You can control your landed cost model, your operating structure, your pricing logic, and your data integrity.

Stop kidding yourself.

Just like Bluey will play on my TV, this tariff episode will play again. So stop procrastinating on big decisions, just get on with it.

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• mostly fashion

• mostly UK-headquartered

• mostly between £10m and £100m

• and asked questions about returns, cross-border, margin visibility

• and the gap between what tools promise and what teams actually experience

We expected to find brands at various stages of deliberate international expansion. What we actually found: international revenue has already arrived, and for most it wasn’t a carefully thought out strategy.

67% of the cohort reported 30%+ of revenue from international sales. Six brands sat between 70% and 90%+. These aren’t global enterprises with regional teams. They’re operators with domestic systems and workflows scaling beyond a single market.

The growth is real. The margin pressure that follows is also real.

What the report covers

The full report goes deep across six areas. Here’s enough to frame the conversation, not enough to replace reading it.

Returns tooling has improved dramatically. Returns operations haven’t. The gap between “I like my platform” and “I trust my setup” is where the margin leaks live.

16 of 24 brands have switched returns platforms at least once, and the triggers are rarely about the tool itself.

Cross-border remains the problem everyone tolerates. Universal frustration, almost zero switching. The report explores whether that’s about to change.

And underneath all of it: the same integration pain, manual workarounds, and analytics gaps showing up in every conversation regardless of category or vendor.

Why now

Tighter margins, rising logistics costs, and sharper finance scrutiny are making previously tolerated leakage harder to ignore. The window where international complexity could be treated as a future problem has closed.

The report maps where that pressure is showing up, and what operators are actually doing about it.

Read the full report

Independent research. No vendor sponsorship. First in an ongoing series. If you’d like to participate or just tell us we’ve got something wrong: research@commercethinking.com

But what starts as a physical extension of the brand quickly becomes a merchandising, ops and stock management headache. And that’s the part nobody warns you about in a POS demo.

Here’s what digitally-native teams miss: a store isn’t a vibe. It’s inventory, data, people, and a stack of decisions that compound daily.

And the compounding is the killer.

Every physical location adds complexity to your operation. More SKUs. More touchpoints. More ways for stock to end up in the wrong place at the wrong time.

We’ve delivered these retail expansions in brand, from merchandise planning through to setting up the stock room and everything that breaks in between.

It’s never easy. But it is predictable.

Inventory stops being a number and becomes geography

In the main, ecommerce has the luxury of tidy pools of stock. Retail is different. The moment stock leaves the DC, it becomes harder to control.

Once you’ve pushed units into a store, you’ve turned them into a local bet. If you guessed wrong on depth, size curve, or timing, you can’t just fix it with a Shopify tweak.

This is why stores create strange new ways for it to break. Stock can sit in the wrong location simply because it isn’t that store’s pick day.

You start learning that allocation is never just allocation. It’s also delivery schedules, labour in the DC, and how fast you can move product without breaking the maths.

The trap for DTC brands is treating store stock like marketing inventory. Something you place beautifully and then let it do its job.

In practice, stock decisions are as strategic as store design, because the moment you go physical your stock stops being numbers in a system. It becomes geography, weather, timing, and people.

If you want a simple operator test, go look at how often you can rebalance stock today. Not theoretically, actually. If the answer is weekly or rarely, you’re about to feel it.

Omnichannel can act like a release valve, but only if you build it properly. The whole point is making stock fluid again, shipping from stores, fulfilling locally, and moving it at the pace of demand, not delivery schedules.

That’s also where some DTC teams get annoyed. They wanted a store. They accidentally signed up for a supply chain node.

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The boring data stuff will stop your store trading

Most DTC teams can tolerate messy product data for longer than they should. A dodgy size value here, a duplicate SKU there, a naming convention that only one person understands. Online, you can often ship anyway.

In a store, those little inconsistencies turn into hard stops. This can happen when the size format in the warehouse system doesn’t match the labels on the physical products. A shipment lands but can’t be received.

This is why store number two hits like a brick. The jump from one to two physical locations is less of a step and more of a chasm, like going from one child to two.

At one location, problems get fixed in real time. At two, they scale.

Brands end up thinking they need to switch POS or layer on another tool. Sometimes they do. But the harder truth is usually integration and someone owning it.

You need everything feeding into one view of stock everyone trusts, rather than stacking system on top of system. And you need to treat product data like an asset, not an afterthought.

If you’re firefighting at store two, store three is going to tip members of your team into madness. That line’s dramatic, but it’s also accurate.

The numbers start lying and you pay for it in working capital

Multi-location retail doesn’t just add admin. It messes with your confidence in the numbers.

One location can be messy and still survivable. Add more nodes and suddenly you’re dealing with timing gaps, transfers, delayed receipts, and teams making decisions off different versions of the truth.

That’s when you see the quiet behaviour change. People start over-ordering, holding extra, and pushing problems into next month because nobody trusts what’s on the screen.

Finance and merchandising end up talking past each other. Buying can’t buy confidently if stock, inbound, returns, and sales aren’t landing in one view quickly enough.

Meanwhile the store team sees it the simple way. Customers want the thing, it’s not there, and everyone looks at everyone else.

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A store is also a people business and the first year isn’t glamorous

DTC brands are used to scaling with code, media, and a few more warehouse pickers. Stores scale with rotas, training, and managers who can run a tight ship on a Tuesday morning, not just launch parties on a Saturday.

This is where a lot of digitally-led teams get caught out. You can’t A/B test your way to consistent store operations if you haven’t built proper training and clear ways of working.

If you’re going to do this properly, you need staff who understand operations, not just merchandise. You need processes that connect physical and digital inventory, and data that can be trusted by finance, fulfilment, and commercial teams alike.

You also need patience. The first year isn’t glamorous. It’s systems work. It’s process work.

This is the bit that frustrates a lot of founders. They wanted a store to make the brand feel more real. Instead, they get a new category of daily work that doesn’t show up on Instagram.

Physical retail has physical failure modes

The biggest one is brutally simple. The cost base doesn’t care how good your brand deck looks.

Online, you can often dial spend up and down with demand. In stores, rent turns up every month, payroll turns up every week, and the inventory you bought to make the shop look full is now sat somewhere specific.

That’s why so many DTC store rollouts look fine in the first few openings and then start to get ugly. When the economics don’t hold, you don’t just turn it off; unwinding stores can be expensive and public.

So what do far too many DTC brands overlook? It’s not the shopfit. It’s the operating model.

They underestimate how quickly inventory becomes a local replenishment problem. They underestimate how frequently messy product data will block trading. And they assume that if one store works, two stores will work, when two stores is the point where the cracks widen.

If you’re going into stores, treat it like you’re changing the shape of the business. Because you are. Build the unsexy parts early, especially data discipline and integration, and you’ll give yourself a much better chance to make the fun bits pay off.

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Happy Monday everyone. Why not stick on some Joy Division and settle in for an uplifting article…

The efficiency case for AI in brands isn't debatable anymore. Automate repetitive work, reduce headcount, protect margin. The tools work, the ROI is clear, and your competitors aren't waiting for permission.

So brands will do this. They’re already doing it.

What nobody’s pricing in is the leadership deficit we’re sleepwalking into.

The tasks AI automates best sit disproportionately in entry-level roles. Weekly trade packs, routine reporting, first-pass copy. The structured, repeatable work that happens to be where people learn how brands actually operate.

Automate those tasks away and you don’t just trim payroll. You collapse the apprenticeship. And without the apprenticeship, you don’t get the next generation of leaders who know what good looks like and can actually scrutinise and manage the machines.

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The pipeline breaks quietly

The hypothesis is simple.

If the number of entry-level roles shrink. Hiring slows. The juniors you do bring in spend their time monitoring AI outputs instead of doing the actual work. They learn to approve, not to judge. To trust the model because they’ve never lived through what happens when the model is subtly, expensively wrong.

Give it 10 to 15 years and today’s assistants should be your managers. Today’s coordinators should be your directors. Instead you’re staring at a gap.

A shortage of people who can interrogate what the automation is doing. Who’ve built the pattern recognition and muscle memory that only comes from years of reps. Who know how the business works when the systems don’t agree and the customer does something annoying right on the cutoff.

That knowledge doesn’t come from courses or observing. It’s earned through doing the work, making mistakes, and gradually building an “in the bones” understanding.

With AI, we’re doing away with the opportunities to develop knowledge in the next generation of brand leaders.

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The competitive failure mode

Here’s where it gets worse. Every brand faces the same pressure to automate. So every brand will. And every brand will end up competing for the same tiny pool of people who actually came up doing the work.

Costs spike. Churn accelerates. You lean harder on consultants and external hires because the institutional knowledge isn’t sitting inside the business anymore.

Worse, you get slower and more fragile. You’ve got excellent tools and not enough people who can tell you when the tools are lying. When the forecast is off, the copy doesn’t sound like your brand, or the operational decision will create problems three steps downstream.

The more you automate, the more you need humans with deep context to scrutinise what you automated. But those humans don’t magically appear. They’re grown through years of doing the work you just removed from the business.

We’re trading short-term efficiency for long-term fragility, and we’re all doing it at the same time.

We’re not prepared for this

The brutal part is that brands will make the rational choice at every stage. Automate or fall behind. The market punishes hesitation faster than it punishes deferred talent problems.

But rational individual decisions can still create collective problems. And we’re sleepwalking into one.

In 10 to 15 years, we’ll have a generation of “leaders” who’ve never done the work they’re leading. Who can’t sense-check AI outputs because they never built the judgement. Who’ve only ever approved, never created.

Now the optimists will say “well the AI will be so good in 10 years that it’ll paper over the gaps in individual understanding”. Totally fair, but doesn’t that feel pretty bleak for the next generation of school, college or university leavers? Is that really the extent of our ambition?

Without new pathways and different approaches, we’ll break the talent market.

The leadership deficit is coming. Not because anyone intended it, but because nobody stopped to ask what happens when an entire industry automates away its training ground at the same time.

If we don’t intervene now - if brands don’t deliberately rebuild pathways for early-stage talent, create new apprenticeships, make space for real practice and feedback - we’ll get the efficiency today and the crisis tomorrow.

Our small attempt at not just being part of the problem

AI is moving too fast to navigate all the implications alone, and there’s nowhere dedicated to retail brands solving the adaptation problem together.

Whether that’s practical use of the tools, to managing the org design shifts it’s prompting.

So I’ve created an invite-only community where brand leaders and operators learn, share and build AI-era capabilities as a peer group.

We're deliberately mixing senior leaders with ambitious junior talent. Systems admins with merch managers, ops specialists with analysts. Different experience levels, same challenge: learning to work with AI without losing the fundamentals that made us good at this in the first place.

If you’re interested then apply at Operator Experience.

Between November and December 2025, I interviewed 40+ leaders and operators at consumer brands. I spoke with people at different levels within brands turning over £10m to £250m.

I asked really straightforward questions about AI: their attitudes, confidence levels, practical usage, and what pressure they’re feeling.

One trend dominated each conversation.

Nearly everyone, from CEOs to early-stage operators, was certain AI would reshape how they work day-to-day and how their business operates. But they didn’t know where to start. Most didn’t trust the noise they heard online. And most were trying to figure it out alone.

The pressure is real

There’s another layer to this. Nearly every operator I spoke to admitted feeling insecure about their competition moving faster on AI. The fear isn’t abstract.

It’s that a rival brand is already automating processes, improving margins, or accelerating decision-making while they’re still figuring out where to begin.

That stress compounds when owners, investors, and board members keep (unhelpfully) asking “what’s your AI strategy?”

It’s a question that sounds reasonable but often creates paralysis. Most operators don’t need an AI strategy, they need to identify specific tasks worth automating and start building capability around those. But when you’re being asked for a strategy deck while trying to run the business, the gap between expectation and reality gets uncomfortable fast.

This is exactly why isolation doesn’t work. When you learn with peers who are facing the same questions and the same pressure, you realise you’re not behind, just figuring it out like everyone else. And that shared context accelerates everything.

The L&D gap

AI literacy was a top priority for every People and HR leader I spoke with.

Then I asked the follow-up: what programmes exist to solve this? What are you actually doing about it?

The answer was almost always the same. Not much. A few vendor webinars. Maybe some online courses that nobody finishes. But nothing credible. Nothing structured. Nothing that actually builds capability across the business.

There’s a clear gap between what brands know they need and what’s available to them. And it’s not for lack of trying.

I think we need to approach AI literacy differently. Traditional L&D (courses, one-size-fits-all training) isn’t fit for purpose. AI is moving too fast. The day someone creates a definitive course on leveraging AI inside a fast-growth brand is the day it’s out of date. The technology shifts rapidly, and the applications are nearly infinite.

So the questions I keep asking myself are: How do we help operators understand where automation creates leverage in their specific role? And how do they learn to apply it alongside peers facing similar problems?

Right now, that doesn’t really exist at scale.

What we’re creating

Operator Experience is a small, invite-only community for people running complex parts of modern businesses: operations, finance, commercial, merch, product, tech, logistics, growth.

It’s launching publicly this month with the support of a group of brilliant partners. The group will meet four times per year. Our first workshop is in Manchester on 16th April, with London following in July and more cities through 2026 and beyond.

We’re intentionally keeping this tight-knit, capping the number of brands but encouraging each to bring multiple people from across their business. The biggest winners in the AI era will be brands that organise cross-functionally to automate and augment work. We’re practising what we preach.

If this sounds relevant to you or your team, get in touch with me directly on luke@commercethinking.com

More at operatorexperience.ai

You get twitchy. Someone suggests a chatbot. Someone else suggests hiring a head of AI. IT talks about vendors. Finance asks about ROI. Then you all go back to moving data between spreadsheets like it’s the default setting.

The problem with that question is it invites performance. You get decks. You get demos. You get everyone doing their bit to sound strategic.

What you don’t get is actual work being automated.

AI isn’t the destination. It’s a tool, and it’s getting baked into a lot of the stuff you already pay for. The better question is boring but that’s why it works.

How are we going to automate 30% of tasks by 2030?

The only target that matters

Pick a target that forces choices, and is close enough to feel uncomfortable. Put a date on it, even if it’s a rough date, not a perfect number.

30% of tasks by 2030 is a clean target. If you get to half that, you’d still have taken a big chunk out of the grind.

And it’s not a random number. It’s a simple target that’s big enough to change how work gets done.

It’s tasks, not jobs.

If you’re running a retail brand, you’re already running a service business internally. Merch serves trading, and finance serves everyone. Tech and systems teams serve everyone too. And no, this isn’t about cutting heads.

The point is to redesign how the work gets done. A lot of effort goes into moving data around, updating numbers, and reconciling systems.

That cost adds up. And in the AI-era, that work can be done differently.

A vague AI strategy doesn’t force any of that work to happen but a hard automation target does.

It makes you pick. It makes you prioritise. It makes you admit where ops are creaking.

It also makes board conversations easier. Despite the question “what’s your AI strategy?” coming up all the time. The board doesn’t actually need an AI strategy (and most wouldn’t recognise one that’s legit from one that’s bullshit anyway). It needs a decision framework for when automation is worth doing.

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Where the real work is hiding

Go look at the places where teams hand over to each other. That’s where data gets copied, double-checked, and re-entered.

Look between merch and logistics. Between systems that were built for different decades.

That’s where the opportunity is. Not in a shiny demo. Not in a brainstorm about the future of AI. It’s in the grim, daily stuff that good people hate doing.

If you want a simple start, hunt for tasks with these tells. They’re boring, but they’re reliable.

• The same data is typed twice, usually in two different systems.

• The output is a spreadsheet someone emails round to get approved.

• Nobody can agree who owns the step, so it sits in limbo.

Finding the tasks and fixing them across teams is the job. It’s more people than tech.

You can often buy tools that sync product data across systems and cut manual re-entry. Buying the tool is the easy bit.

The harder part is agreeing what good data looks like, who signs it off, and what changes when you stop relying on heroic manual checks. This is why brands chase the wrong stuff.

The flashy customer-facing thing is easier to show progress on. It looks good in a deck. Meanwhile, the wins are in clear workflows and taking friction out. That’s the stuff that cuts cost, moves faster, and stops trading teams firefighting.

We’ve been saying this in retail for ages. Doing the boring implementation work, getting workflows clear, and protecting the brand is what separates the ones that get value from the ones that don’t.

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Your hot new AI hire won’t save you

Here’s the thing. AI skills will get cheaper and easier to pick up over time.

It’s easier learning how to vibe code than to grasp the full reality of running an inventory based, fast growing business.

What’s scarce is context. The people who understand how an inventory-based retail brand really works, and can sanity-check what the machine got right or wrong.

You can’t learn that in a course. It’s lived experience. It’s knowing where the bodies are buried in your allocation logic, your size curves, and your month-end close.

So don’t build your plan around hiring a handful of specialists and hoping they’ll fix it for you.Get the leadership team clear on where work actually happens, how it flows, and why it breaks down. Then use AI and automation to remove the drag.

Think about it like spreadsheets. Most of your business doesn’t need to become a spreadsheet wizard.

But everyone should know what spreadsheets can do, and when to pull in the person who’s good at automating the button-clicking.

AI is the same…

What to say to your teams

The biggest thing I tell leadership teams is this. Stop pretending you’ve got it all mapped. Tell the truth, and set a direction.

AI’s going to change how we run this business. It’s going to change how we work.

We don’t know exactly how yet, but doing nothing isn’t an option. So we’re going to talk about it head-on, and we want everyone calling out where AI and automation can take busywork off people’s desks.

We’ll get better at it as we go.

It calms things down. It tells people you’re not outsourcing the future to a vendor. And it makes it okay for people to bring messy, boring problems to the surface.

Then you make it real.

You don’t need a big bang programme. You need a rhythm.

Pick a painful process. Map it end to end. Put the person who does the work in the room.

Bring someone who can configure the system and someone who can wire it up without breaking anything. Ship something small.

Share what worked and what didn’t.

If you want real automation by a deadline that matters, you won’t get it from one tool.

You’ll get it from a steady run of unsexy fixes that remove friction and stop good people spending their week doing admin.

And when someone asks what’s our AI strategy, you’ll have a better answer.

We’re aiming to automate 30% of tasks by 2030. Here’s where we’re starting.

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That’s the real scaling story. Growth makes ops messy, and inventory is where it shows up first, because it’s cash you’ve already spent.

Here’s the bit people miss. These moments aren’t gradual. They’re step changes.

You can feel fine for 12 months, then one launch, one new channel, one extra warehouse and suddenly buying the right amount of stock at the right time turns into a scrap.

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The early crunch comes sooner than you think

The first tipping point is when you can’t hold the whole assortment in your head anymore. Often that’s when you’ve gone from a tidy range to hundreds of SKUs with variants.

At that point, buying stops being something you can run on intuition and a spreadsheet. You’re now managing lead times, supplier constraints, replenishment, and all the knock-on effects. Forecasting errors stop being small rounding issues and start turning into proper mistakes.

This is also when you learn product data isn’t admin. If your SKU setup is inconsistent, or costs aren’t kept clean, everything downstream lies to you. You’ll think you’ve got stock, you won’t. You’ll think you’ve got margin, you don’t.

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Channel expansion isn’t just more demand

The next tipping point is when you add a second proper channel. Usually it’s wholesale, marketplaces, or stores.

Now you’re not just forecasting demand. You’re allocating stock across channels where demand behaves differently, and the rules change. Wholesale pulls volume and cash forward, but it also locks in commitments, changes pack sizes, and makes late delivery far more painful.

If you don’t have one stock view you trust across channels, you’ll get hit twice. You’ll be out of stock on the thing that’s working, while last season’s ideas pile up in the wrong place.

Multiple locations is where the numbers start lying

One warehouse can be messy and still survivable. Two warehouses, a new 3PL, or one international node is where the wheels come off.

You get phantom inventory, slow inventory updates, transfer problems, and teams start adding safety stock buffers at each location because nobody trusts the numbers. That feels like risk management, but it’s really a cash bleed.

This is where integrations stop being optional. Not in some slide-deck architecture way, but in a brutal operational way. If orders, stock, inbound, and returns aren’t landing in one view of stock that everyone trusts quickly enough, you can’t buy confidently.

Volume turns small mistakes into company-threatening ones

Even if you don’t add channels or warehouses, sheer volume will do it. A brand can grow a lot and still be running the same buying process and the same reporting setup.

The problem is the costs that were previously background noise become the whole song. Freight, duties, and fulfilment costs. If finance and merchandising don’t have a clean view of landed margin, you’ll keep buying like the unit economics are better than they really are.

There’s a reason we bang on about stock turn. It’s the fastest tell of whether your inventory is working for you or sitting there eating your cash.

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What goes wrong commercially when you miss these moments

If you keep scaling without changing how you plan and buy, the outcomes are boring and brutal.

You tie up cash in inventory you can’t shift. Dead stock isn’t just a merchandising embarrassment, it’s cash that can’t fund marketing, product development, or the boring bills.

You erode margin in ways that don’t show up in the headline gross margin. Excess stock turns into more discounting and a longer clearance hangover, and it’s happening everywhere right now.

You miss revenue because you’re out of stock at the wrong time. Stockouts take a painful chunk off your sales, and it’s never the slow movers that disappear first.

Then there’s the self-inflicted stuff that makes operators wince. Poor forecasting leads to urgent fixes, and urgent fixes are expensive. Air freight is far more expensive than ocean freight per unit, which means you can turn a great product into a marginal one simply through panic.

The final one is the one everyone pretends isn’t happening until it is. Growth stalls because operations can’t keep up. People spend their days firefighting, which means you’ve got no bandwidth to make the changes that would stop it.

What the prepared brands do differently

They don’t wing it through tipping points. They build a little ahead of the business, not miles ahead.

It’s always the same pattern.

They get the data right before they buy software. Clean product setup, consistent costing, someone owns the data, and a way to stop bad data from creeping back in.

They fix the system that gives them one view of stock they trust, and ties buying back to reality. Sometimes that’s the ERP. Sometimes it’s inventory and planning first. Sometimes it’s order management, if the core pain is allocation and oversell.

They run the business on a small set of numbers they trust. Stock turn, sell-through, and in-stock on key lines. Then margin after the costs that actually land, not just what’s on the supplier invoice.

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If you’re already late, stop digging

If you’ve read this with a sinking feeling, you’re not alone. Plenty of brands blast past two or three tipping points on heroics.

The fix won’t be pretty, but it can be fast if you’re decisive.

Start by getting the basics stable. Stabilise product and inventory data. Audit the mess, clean it, and set rules and ownership so new SKUs are created correctly from now on.

Then pick a place to start and move fast. For many brands, that means getting purchase orders, inventory and landed cost into one place that finance and merch both trust. Don’t aim for the perfect setup on day one. Aim to stop the bleeding, then keep improving.

Be honest about capacity. If nobody in the business has implemented an ERP, planned inventory across channels, or built integrations properly, you can’t magic that skill up while everyone’s already drowning.

This is where you either hire someone who’s done it, or you bring in experienced help for a stint and give them room to do it properly. Your team will not magically find time for a major systems programme while also running launches, trading, and wholesale deliveries.

One last thing, because it matters. Going earlier doesn’t mean buying the biggest system you can afford. A badly rolled out platform on top of messy data is just a faster way to get the wrong answers.

Quick gut check

Go look at your own buying and inventory process. If you can’t answer these quickly, you’re near a tipping point already:

• What do we actually have available to sell, by channel and location, right now?

• What do we have inbound, and when will it really land?

• What is our true margin after freight, duties, and fulfilment on the things we’re about to reorder?

Scaling brands don’t fail from lack of ambition. They fail because they scaled the exciting bits and left the unsexy ops behind.

Get ahead of the inventory tipping points, and you buy yourself something that’s hard to put on a slide. Control. And right now, that’s what keeps growth profitable.

Why this series?

Most sports clubs still outsource retail. A licensing partner runs the store, ships the orders, and pays a royalty. It works, but it keeps commerce at arm’s length.

This series explores what happens when clubs bring retail and e-commerce in-house, and what that decision really involves once you move past the headline business case.

We’re using West Park Rovers, the fictional club from Kieran Maguire’s The Price of Football, as a reference point. They’re a stand-in for any club trying to modernise how it sells to fans, from merchandise to collectibles.

If you’re new here, it’s worth starting at the beginning:

• The Business Case looks at why clubs are making this shift.

• Your Club Shop Is a Factory explores the operational reality that follows.

This article builds on those foundations and looks at one of the least discussed challenges of in-house retail: running a business where the entire product range effectively expires every year.

Most retail businesses think in seasons.

Sports clubs think in deadlines.

There is a difference.

For a fashion brand, a product can linger. It might be discounted. It might be pushed to an outlet. It might quietly sell through over time. The tail is long, even if the peak is short.

For a sports club, the tail is brutal.

At a certain point each year, the entire catalogue effectively expires. Not gradually. All at once.

That reality shapes everything, whether the club acknowledges it or not.

A hard reset, every season

A football shirt is not just a product. It’s a timestamp.

It’s tied to:

• A specific season

• A specific sponsor

• A specific manufacturer

• A specific squad

• A specific competition context

When any of those change, the product loses relevance. Sometimes overnight.

When several change at once, it becomes unsellable.

West Park Rovers learn this early in their planning. The new season launch feels exciting. New kit. New energy. New momentum.

What gets less airtime is what happens just before that launch.

Because when the new kit goes live, last season’s shirt doesn’t just become less desirable. In some cases, it becomes contractually impossible to sell.

Sponsor changes.
Manufacturer changes.
Competition badges change.

The clock doesn’t tick down gently. It hits zero.

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Underbuying is visible. Overbuying is expensive.

This is where the pressure builds.

If a club underbuys, fans don’t wait. They go elsewhere. Sports retailers, brand websites, marketplaces. The sale still happens, just not with the club.

If a club overbuys, the consequences land internally. Stock sits. Cash is tied up. Margin evaporates through discounting or liquidation.

There is no comfortable middle ground. Only trade-offs.

West Park Rovers run their first full buying model and realise something uncomfortable. They are trying to predict demand months in advance for products that will be irrelevant in a year, in a context where demand is influenced by variables they don’t control.

Team performance.
Injuries.
Transfers.
Manager changes.
Fan sentiment.
Design reception.

Even timing matters. A strong finish to a season can rescue a slow launch. A poor run can stall demand regardless of how good the product is.

Buying for sports retail isn’t forecasting. It’s risk management.

When performance becomes inventory risk

Few industries have this problem.

If a fashion brand misjudges a trend, it absorbs the loss quietly. If a club misjudges its squad or its season, the consequences show up in the warehouse.

A shirt printed with a player name that leaves suddenly doesn’t just lose appeal. It becomes a liability.

That’s why most well run clubs don’t preprint names at scale. They hold blank stock and customise late. It’s not about flexibility for the fan. It’s about protecting the balance sheet.

West Park Rovers debate this internally. Printing early simplifies operations. Printing late increases complexity.

But the alternative is worse. Overcommit early and you risk holding stock that can never be sold at full value.

In a business where the catalogue expires annually, optionality matters more than efficiency.

Liquidation is not a failure. It’s a system.

This is the part most clubs avoid talking about.

Every season ends with unsold stock. The question isn’t whether liquidation happens. It’s whether it’s planned.

There are established paths:

• Discounting through owned channels

• Selling through third-party retailers

• Moving stock into specialist resellers

• Donating through foundations or community programmes

• Auctioning signed or rare items

Handled well, liquidation is controlled. Handled poorly, it’s reactive and value destroying.

West Park Rovers initially see liquidation as a worst-case scenario. Something to avoid. Something that signals failure.

That changes once they understand the economics.

A planned exit is not defeat. It’s part of the operating model.

Trying to avoid liquidation entirely usually leads to worse outcomes. Late discounting. Panicked promotions. Stock sitting too long and losing relevance altogether.

In a 12-month catalogue, liquidation is not the exception. It’s the final stage.

When contracts dictate commerce

Retailers rarely have to turn products off completely.

Clubs do.

A manufacturer change can make entire categories unsellable overnight. What was valid yesterday can be contractually blocked today.

West Park Rovers model a hypothetical supplier switch and immediately see the risk. Stock that looks healthy in March could be forbidden by August.

That reality changes how you buy, how you time promotions, and how aggressively you clear stock.

It also changes how you think about partnerships. A kit deal isn’t just about price or design. It dictates the lifecycle of your entire retail operation.

The emotional layer

There’s another complication that spreadsheets don’t capture.

Fans attach emotion to products in a way most retail businesses never experience.

A shirt isn’t just apparel. It’s memory. A season. A moment. A campaign. A story.

That cuts both ways.

It can sustain demand long after logic says it should fade. It can also evaporate demand instantly when sentiment turns.

West Park Rovers see this when a slow start to the season affects early sales. The product hasn’t changed. The mood has.

Buying for sports retail means accepting that demand is emotional, volatile, and only partially rational.

That’s not a flaw. It’s the nature of the relationship.

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Why this changes how clubs should think

The biggest mistake clubs make is treating this like normal retail.

It isn’t.

When your entire catalogue expires annually, everything shifts:

• Cashflow planning

• Stock risk tolerance

• Discount strategy

• Promotional timing

• Supplier negotiations

• Operational flexibility

Clubs that succeed don’t try to eliminate risk. They design for it.

They buy late where possible.
They customise as close to sale as they can.
They plan liquidation paths before the season starts.
They accept that not every unit is meant to sell at full price.

Most importantly, they stop expecting certainty.

What West Park Rovers take away

By the end of their first full planning cycle, West Park Rovers stop thinking about the shop as a collection of products.

They start thinking about it as a timeline.

Every item has a beginning, a peak, and an end. The mistake is pretending the end won’t arrive.

In a business where the catalogue resets every year, success doesn’t come from perfect forecasts.

It comes from building an operation that can absorb volatility, respond to change, and exit cleanly when the clock runs out.

That’s the real challenge of in-house retail.

And it’s one most clubs underestimate until they’re already living it.

For years, doing kits and bundles properly meant hacks, phantom SKUs, inventory syncs, and someone in ops quietly hating everyone. Now it’s Shopify’s problem. To the customer, it’s a tidy bundle, and your warehouse and ERP still deal in normal SKUs.

That last bit is the whole point. Bundling isn’t a merchandising trick, it’s an ops decision. Here’s what your back-office teams like merch, finance & ops, and leadership need to prepare for your business to nail bundles.

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Start by deciding what kind of bundle you’re actually selling

Most teams talk about bundles like it’s one thing. It isn’t, and the wrong choice shows up later as stock errors, messy reporting, and returns chaos.

It’s always the same three patterns.

1 - Promo bundles. No bundle product, no new SKU, just existing products with an automatic discount like 3 for 2. It’s easiest on ops, but it’s also the least curated experience.

2 - Virtual bundles. The customer browses and buys a set, but the order is exploded into the component SKUs for checkout and fulfilment. This is what Shopify Bundles does, and most bundle apps do the same cart swap.

3 - Physical kits. You pre-pack and stock a kit SKU, often because it’s gift wrapped, it’s sold wholesale too, or you need pick speed. This is a real manufacturing and inventory problem, not a website problem.

Here’s the awkward bit. You can run a lot of virtual bundles with very few operational headaches.

You can run physical kits too, but only if your back office can do kitting, assembly, and clean stock movements.

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What changed on Shopify and why it’s different now

Shopify’s own Bundles app has been around for a while, but the bigger win is Shopify getting out of its own way. The variant limit bump means you can build proper choices without hitting a wall on day one.

In the cart, Shopify can swap the bundle for the components. That means inventory gets checked and comes off the component SKUs, not on some made-up kit item you have to babysit.

So your warehouse doesn’t need to learn what a bundle is. It just sees pickable SKUs like normal.

Keep the truth at component level in your core systems

Here’s where brands still mess it up. They get excited, they create bundle items in the ERP, and now they’ve invented a parallel product universe.

So start there. Shopify can own the bundle definition and the customer experience. Your ERP and planning tools should just see the component SKUs, and you tag the lines so you can tell they came from a bundle. That usually means tagging it, not creating new stock items.

If you want bundle-level reporting, push a bundle ID into line item properties, or whatever field your connector gives you. Then pull the exploded lines back together in reporting. Track it, but don’t stock it.

This is where forecasting turns into chaos. If your plan only watches top-line bundle sales, you’ll miss the real story, which is which component SKU is getting pulled forward and which one is quietly becoming the constraint.

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Warehouse and your 3PL are where bundles either sing or fall over

Virtual bundles are simple only if pick and pack is dead clear.

If your bundle needs special packaging, don’t rely on someone reading order notes. Add the packaging as its own component line, like Gift Box, so it appears on pick lists and packing slips. If the bundle must ship together, check your OMS rules and your 3PL SOPs. They need to match that.

Keep an eye on multi-location stock. Shopify bundles don’t always track bundle stock per location cleanly. You can end up with bundles that look available because total stock exists, but the components are split across sites.

Either restrict bundles to items in the same warehouse, or accept that you’ll be splitting shipments and paying for it.

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Finance needs a heads up because the numbers will look weird at first

Shopify typically spreads the bundle discount across the components based on their price. Good. It keeps tax and refunds consistent, and it means you can still see net sales at SKU level.

It’s also the bit that spooks finance if you don’t warn them. Your core SKUs will suddenly show a lower net ASP because they’re being sold inside a set, and it can look like margin is collapsing when it’s actually just mix.

Decide how you’ll report it before you launch. Do you want to report bundles as their own products, or are bundles just a way of selling and you only care about component sell-through and margin. Either works. Pick one and build your reporting that way.

Also, do the boring maintenance. Shopify bundle pricing doesn’t always update when component prices change, so someone has to own regular bundle price checks or you’ll wake up with accidental discounts.

Returns is the bit no one thinks about until it’s on fire

Bundle returns are where it gets messy. Customers will return one item out of a discounted set, and if you leave it alone they effectively keep some discount on the item they kept.

You’ve got options:

• Keep it simple. Refund each item at its net paid price and move on.

• State clearly that bundle pricing applies only if you keep the full set, and refunds will be adjusted if you break it.

• For the small minority of bundles where it’s justified, require the full set back for a full refund.

Don’t over-engineer for the odd chancer. If your bundle savings are modest, and paid returns are increasingly normal, the incentive for customers to run clever schemes is usually lower than the effort it takes to police it.

The real operational work is making sure your returns portal and CS team can spot when an item was bought as part of a bundle, and follow whatever policy you picked without someone living in a spreadsheet.

Don’t get cute with bundle complexity unless you’re ready to pay for it

Shopify’s native tooling is good for fixed sets, multipacks, and choose-one-from-each style bundles. It’s still not magic for pick-any-X-of-Y bundle builders, and it’s not a clean answer for subscription bundles.

If marketing is pushing a build-your-own bundle builder, treat it like a proper product build. Budget for build, testing, and ongoing maintenance.

Either buy a specialist bundle app or build it.

Or simplify the offer so it fits what Shopify can do reliably.

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How to run bundles like an operator

Go look at your own bundle launch checklist. If it’s just merchandising and site changes, you’re already in trouble.

Make it clear who owns Shopify.

Merch decides the offer. Ops checks pick and pack. Finance signs off how revenue and discounting will land. Whoever owns the integrations makes sure the data stays clean all the way through.

Bundles should feel like a win, not a new category of firefighting. Make the customer experience slick on Shopify. Keep core systems grounded in the component SKUs.

Do the unsexy process work on inventory, fulfilment, reporting, and returns. That’s how you get the upside without the chaos.

We covered the brand implications when the news broke Saturday. Now it’s Monday morning and your team needs answers.

Here’s a concise briefing for your leadership team on how to respond.

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Context

The detail will move around, but the shape of it’s familiar. Trump has been talking about imposing new tariffs on imports into the US from a set of eight European countries.

But what does this mean for brand’s in affected company selling things like clothing, footwear and other consumer products.

If you ship real volume into the US from Europe, that’s not a politics story. It’s unit economics, cash, and planning risk landing on your desk.

This memo is the fact sheet that stops you panicking. Get these definitions straight and you can work out if you’re exposed to Trump’s announcements, and by how much.

The four inputs that decide your import bill

1 - Classification. This is your HS or HTS code. It decides the duty rate, and it often decides what extra paperwork and controls show up.

2 - Country of origin. Origin is where the product is considered made, not where it ships from. In some cases, changing where the last substantial step happens can legally change origin and change duty outcomes, but it has to be real processing and you need to be able to evidence it. For the majority of European based brands, the bulk of their products are made outside of the affected tariff zones - so this gives everyone reasons to be calm.

3 - Customs value. Duty is calculated on the customs value, not your retail price. If your intercompany setup bakes in a markup before goods hit customs, you can end up paying duty on value you never planned to be taxable.

4 - Route to market. How the goods enter a country changes both cost and admin. The classic trap is duty being assessed on a higher value when you ship direct to the consumer versus when you import in bulk at your cost into a local warehouse or 3PL.

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Landed cost and margin

Landed cost is what you actually run the business on. It’s the supplier price plus freight, duties, tariffs, customs fees, and everything it takes to get the unit into a saleable place.

If duty and freight sit elsewhere in the P&L, your merch margin is lying to you. Finance might tolerate that classification, but buying and pricing decisions won’t.

A landed cost flow that holds up when policy swings looks like this.

• Start with the true unit cost tied to your incoterm.

• Allocate freight, insurance, clearance, and inbound handling down to unit level.

• Add duty and any import taxes driven by classification, origin, and customs value.

Then rerun margin from the landed number, by channel.

Gross margin % is net sales minus landed cost, divided by net sales.

Tariffs can move fast. We’ve already seen duty rates jump hard enough to turn a profitable buy into a margin hole while the stock is still on the water.

Data and identifiers

You can outsource customs brokerage. You can’t outsource product truth.

Rules are tightening in a lot of places, and that usually means more declarations, more scrutiny, and less tolerance for vague product info. If you don’t have consistent classification, origin, composition, and values at SKU level, you’ll feel it as delays, rework, and unpleasant surprises on the invoice.

This is where UPC and EAN stop being retail plumbing and start being ops control. Barcodes only help if they point to clean, complete product records, and in most brands data completeness slips through the cracks because nobody’s accountable.

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The quick drill when the next headline lands

You don’t need a war room for every tariff threat. You need a repeatable check that tells you if you’re affected.

• Pull your next inbound and your top sellers, then confirm classification, origin, customs value, and route to market.

• Rebuild landed cost per SKU and rerun margin by channel using the new tariff assumptions.

• Decide fast on the few levers you can actually pull, purchase order timing, inventory placement, and pricing.

You don’t need to become a customs lawyer. You do need to stop being surprised by costs you could’ve modelled in an afternoon.

It’s surreal, but it’s not abstract. If you ship real volume into the US from Europe, you’ve got a commercial problem on your hands.

The mistake now is treating this like a politics story. For brand operators, it’s a unit economics story, a cash story, and a planning story.

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Here’s the bit that matters. Trump has announced (threatened) a 10% tariff on all goods imported into the US from eight European NATO countries starting 1 February, with a move to 25 percent from 1 June.

Denmark, Norway, Sweden, France, Germany, the United Kingdom, the Netherlands, and Finland. The stated condition is that the tariffs stay in place until a deal is reached for a total US purchase of Greenland.

If you’re waiting for this to make sense, don’t. Your job is to assume it’s operationally real until you see otherwise, because the start date is days away.

What’s actually at risk

A 10 percent duty can look manageable on a spreadsheet, especially if you’ve got room in gross margin or you can nudge pricing without destroying demand. The risk is the step-up, and the admin friction that comes with it.

A smaller tariff for a short window is a headache. A bigger tariff, if it sticks, is a strategic change for a lot of categories.

There’s a useful reality check from last year’s tariff drama. Trump imposing a 20 percent tariff and then dialling it back to 10 percent within hours, tells you everything you need to know about planning on vibes.

That volatility is a cost in its own right. It wrecks buying calendars, it makes pricing decisions feel temporary, and it pushes teams into constant re-forecasting.

Now go look at how you currently serve the US. If you’re relying on cross-border parcel shipping to keep inventory centralised, that model only behaves when the border is forgiving.

When tariffs tighten, the failure mode is never just the rate. It’s brokerage fees, clearance delays, bad customer experience, and finance teams trying to explain why the landed cost changed after the sale.

The other thing that catches people out is the customs value, not the retail price. If your structure means goods pick up internal markup before they hit US Customs, you can end up paying duty on value you didn’t intend to be taxable.

The genuine risk for EU brands isn’t one headline. It’s a multi-month squeeze on margin and demand, plus a structural push toward running the US like its own operating unit.

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How to respond without losing your head

You don’t need to panic. You do need a plan, and you need to make decisions with dates in mind.

Treat the initial 10 percent as the opener, and plan like the 25 percent escalation happens. If it gets paused or watered down, fine. If it lands and you’re not ready, you’ll spend the spring firefighting instead of trading.

This week, do three things:

• Model landed cost for a 10 percent case and a 25 percent case by SKU and channel, including brokerage and likely clearance delays.

• Agree what happens to US pricing in each case, and be honest about where you’ll absorb margin versus pass it on.

• Decide whether you’re committing to a US operating model, or accepting that the US channel shrinks for a while.

That last decision is the one most teams dodge, because it feels dramatic. It’s also the one that stops you wasting time on half-measures.

Internally we’ve boiled it down pretty brutally in previous tariff rounds. For a lot of brands, it eventually becomes two options, turn off the US channel or open a US distribution set-up.

If the US matters, act like it matters. Split inventory properly, bulk import into US stock, and fulfil domestically through a 3PL or your own warehouse.

You’re not doing that to get cute with customs. You’re doing it because paying duty once on a planned inbound is operationally saner than paying it again and again on retail-facing parcels, with a customer-service mess bolted on.

If the US doesn’t matter, stop bleeding time and margin trying to keep it alive through clever shipping gymnastics. One internal anecdote from last year was a brand asking whether it could serve the US via Dubai to dodge duties, and being told straight that duties would kill profitability anyway.

There’s a middle ground, but it’s still work. Keep hero lines flowing, pause long-tail SKUs that become unviable in the 25 percent scenario, and make the channel smaller on purpose rather than by accident.

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The levers big players will pull and what you can copy

Some of the big groups will use legal and structural levers that smaller brands just can’t justify. That doesn’t mean you’re stuck, but it does mean you should be realistic about complexity.

One example is the US First Sale rule. Reuters reporting last year said companies including L’Oréal, Moncler and Ferragamo were exploring it to reduce the dutiable value.

The upside is obvious if you can do it cleanly. The downside is also obvious, it’s paperwork-heavy, it comes with audit risk, and it only works if your supply chain and documentation discipline are tight.

If you can’t do that safely, don’t. Do the basics well instead.

Get your HS code assignments checked. Get crystal clear on importer of record by channel, and don’t let wholesale and DTC quietly run on different assumptions.

If you sell direct, fix the customer experience before the chargebacks arrive. Make sure checkout doesn’t surprise customers with fees you already knew were coming, and prep customer-service scripts for why delivery timelines and costs may change.

If you sell wholesale, start the conversation now on who wears the tariff, because someone will. Leaving it until after the goods are on the water is how relationships get wrecked.

And watch competitors, not just politicians. Fortune’s AP reporting highlighted Campari thinking about holding US prices steady if competitors raise theirs, to grab share. That’s the game that starts when tariffs hit, and it’s why you need your numbers per SKU, not just in aggregate.

The bit nobody wants to admit

This isn’t just about Greenland. It’s another reminder that geopolitics is now a direct input into your P&L.

Bruegel estimated that tariffs in the 10 to 25 percent range could shave around 0.3 percent off EU GDP and 0.7 percent off US GDP. You don’t need to be a macro nerd to translate that into your world, it means weaker demand, more noise, and less patience from boards.

Treat this like a drill. The brands that win aren’t the ones with the cleverest statement, they’re the ones that can rework their operating model quickly and keep serving customers without chaos.

If you do the unsexy work now, SKU exposure, landed cost, fulfilment split, you’ll be calmer when the next policy lands. And if this one gets delayed or watered down, you haven’t wasted time. You’ve just tightened the part of your business that was going to get stress-tested anyway.

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