The channel-chair model
This is what a channel-chair looks like. One person per channel, responsible for everything on that channel: new listings, content updates, error handling, seasonal pushes.
On the surface, this feels like a sensible workflow. Channels have different requirements, someone should own them.
So you hire an Amazon specialist. Then an eBay specialist. Then someone for your website, then for the next marketplace. Each person becomes the expert on their platform. Each person does their job.
The problem is that each person's job overlaps almost entirely with every other person's job. If the company was a garment factory, you would be asking the team to cut the same piece of fabric twice, in order to sew it once. Adding a product to eBay and adding a product to Amazon are the same task performed twice.
The research, attributes, content, images are all done once per channel, not once in total. This means for every channel you add, the same work happens over and over again. You can see this breeds structural duplication, or in other words wasted time at scale.
In smaller catalogs this is fine, it gives fine grained control. But with a large catalog and a high channel count, now here are a few problems brewing. Let's call it a ceiling.
The ceiling isn't failure, it's part of the design. Much like a carpenter makes an amazing cabinet. But if you need speed and volume, you need a factory - not a craftsman.
Where it goes
There is another smaller problem, something slower: listing drift.
Take your eBay operator. They're working hard, listing new products each season, handling errors, fighting mapping issues. But the eBay catalogue sits at 10% of your full range. Not because they're failing. Because the model structurally cannot make room for closing that gap. Every week they reset to the same reactive workload. No ground is gained.
Years of this compound. What does it look like when you check?
- Missing attributes across product types
- Mismatched values between channels
- Weak or absent descriptions
- Multiple SKUs for the same physical product
- Duplicate SKUs created to handle edge cases, without traceability
- No clean view of which products are missing on which channel
The catalogue technically works. Listings are live. But the consistent, optimised, fully-covered catalogue that could exist — and the revenue that goes with it — doesn't.
That's listing drift. Not a failure event. The natural output of the channel-chair model, compounding quietly at scale.
The hiring trap
When the Amazon team can't keep up, the obvious fix is to hire another Amazon person.
Follow me for a minute. From inside the model, the problem looks like "not enough Amazon people." So the solution looks like "more Amazon people." Makes sense.
But this scales the cost without touching the structure. The new hire does the same channel-specific job, preserving the duplication. Now more people are doing the same work twice, or three times, or ten times. And you're still no closer to the 90% of your catalogue that isn't on secondary channels yet.
The Henry Ford shift
Henry Ford didn't fix the craft workshop by hiring more craftsmen. He decomposed the work into stages, put a specialist on each one, and turned craft into factory.
The person who built the whole car became a paint specialist. Or a window specialist. Or an engine specialist. The car got better. Production got faster. Cost per unit came down.
Product operations teams can make exactly the same shift.
Instead of organising by channel, one person per channel responsible for everything on that channel, organise by function. One responsibility per stage of the chain, applied across all channels simultaneously:
- Images
- Attributes
- Content
- Quality control
Each function is owned once. Products flow through the chain. Channels receive the output.
This is the function-chain model.
It reduces the cost per product to go live, speeds up the process and frees up time to optimise listings. These points together are how you make product-data work for you.
What it looks like in practice
A function-chain for product operations could look like this:
Product triage → photography → base properties → market research → attribute population → attribute review → listing content per channel → quality control → fixing listing errors.
One person can cover multiple stages, this isn't a 10-person prescription. It's a structure that scales with your organisation. A small team runs a shorter chain; a larger one adds people to functions, not to channels.
Each stage is a function, not a channel. The attribute reviewer works across all products for all channels. Once. Not per channel. Content is where channel-specific work happens, because channels genuinely need different tone and format. But that content writer depends on clean attributes from upstream. They own the content function. They do not own a channel.
AI agents slot in naturally at the research, attribute population and content writing stages, because those are functions. They don't need to know which channel a product is heading to in order to do their job.
And the scaling equation changes entirely. Adding a new channel adds a destination for the chain's output. It does not require a new parallel chain. Ten channels does not mean ten teams.
The PIM question
This shift tends to happen when teams adopt a PIM system. That's not a coincidence.
A workflow-based PIM can't cleanly replicate the channel-chair model. Its architecture is built around stages, shared product records, and task assignment by role. The tool pushes you toward the question: who actually owns this stage?
But the tool alone doesn't make the shift.
Teams that adopt a PIM and continue working channel-by-channel end up using it as a glorified listing app. Products reach more channels faster, but the underlying data quality and team structure problems stay in place. The mess grows faster, now efficiently distributed to more places.
The workflow redesign is the actual intervention. Teams that get this right usually arrive at the function-chain structure themselves, as part of designing their PIM workflow. It's not imposed from outside. It emerges once you're thinking in stages rather than channels.
What changes
When the function-chain works, most "Amazon problems" (or other marketplace issues) turn out to be data problems.
A suppressed listing or a listing rejection usually traces back to a missing attribute, a wrong value, or unmapped content. The PIM surfaces the error. The person who owns that data function fixes it. The Amazon specialist's job shrinks to what genuinely requires their expertise:
- Brand registry disputes
- Account-level restrictions
- Policy appeals
That is a much smaller job than it looks from inside the channel-chair model.
One team that made this shift in early 2026 predicted more than 50% improvement in new-product throughput. That's a prediction, not a measured result. Implementation began May 2026. But the mechanisms are concrete:
- Less coordination overhead between channel people
- AI-generated research and content instead of manual copy-paste
- Pre-populated attributes reducing per-product effort
- Better channel mapping producing fewer downstream errors
- Faster flow from intake to live listing
Five compounding improvements, not one.
Teams that have made the shift describe it the same way: you can't see how much faster it goes until you've had it. It's like hot water: nobody needs it until they've had it, then they can't imagine going back.
The channel-chair model wasn't wrong to try. It's the intuitive response to multi-channel operations, and almost everyone ends up there. But the function-chain makes the duplication visible for the first time.
Once you've seen it, you can't unsee it.
The model is not a software problem. It is not a coordination problem. It is a design problem.
You are not hiring more craftsmen. You are building the factory.
FAQ
Why does duplicate work happen in multi-channel ecommerce teams?
Duplicate work is a structural consequence of organising by channel rather than by function. When each person owns a channel, they independently perform all the same product management tasks: listing, content, attribute updates, error handling. The person on the next channel does the same. The work is not shared; it is repeated. Adding a new channel adds a new person doing the same tasks, not a new stage in a shared process.
How do you scale a multi-channel ecommerce team without hiring more people per channel?
Organise by function instead of by channel. When responsibilities are structured as a shared production chain, each function is owned once and the output flows to all channels. One person owns images, another owns attribute review, another owns content. Adding a new channel adds a destination for the chain, not a new parallel chain. This is what allows teams to expand channel count without expanding headcount proportionally.
What is the best ecommerce team structure for managing many sales channels?
A function-chain structure: each team member owns a function (images, attributes, content, quality control) applied across all channels, rather than owning a single channel across all functions. This eliminates the duplication built into the channel-by-channel model, creates clear ownership at each production stage, and makes it possible to add AI agents and automation at specific functions without disrupting the rest of the workflow.
What is listing drift and how does it affect ecommerce operations?
Listing drift is the gradual degradation of product catalogue quality that results from independent, channel-by-channel management over time. It shows up as missing attributes, mismatched values between channels, weak descriptions, multiple SKUs for the same product, and no clear view of which products are missing on which channel. It is not a single failure event. It is the natural long-term output of the channel-chair model, compounding quietly until it becomes a growth ceiling.
How does a PIM system change how your ecommerce team works?
A workflow-based PIM cannot cleanly replicate a channel-by-channel team structure. Its architecture is built around stages, shared product records, and role-based task assignment. This creates pressure to rethink team structure at the point of adoption. Teams that adopt a PIM without changing how they work end up using it as a glorified listing app. The structural redesign is the actual intervention; the PIM is the tool that makes it sustainable.
What is the function-chain model in ecommerce product operations?
The function-chain model is a product operations structure where each team member owns a function in the production process (photography, attribute review, content writing, quality control) rather than a sales channel. Products move through the chain sequentially; each function is applied once across all channels simultaneously. It is the ecommerce equivalent of Henry Ford's assembly line: craft (one person manages one channel end-to-end) becomes factory (each person specialises in one stage of the shared chain).