Episode 4: Why Supplier Data Is Never Usable - And Three Levers to Fix It

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If you work in distribution, retail, or marketplace, you already know the pain: supplier data arrives late, incomplete, inconsistently formatted, and almost never in the shape your systems need. Teams spend weeks chasing, verifying, and manually transforming data before a single product goes live.

What's surprising is how rarely businesses treat this as the structural problem it is. Instead, they buy a supplier portal, build a new onboarding template, or jump straight to automation — and wonder why nothing changes.

Here's a clearer picture of what's actually going on, and what to do about it.

Why the Problem Keeps Getting Worse

The assumption baked into most supplier onboarding processes is that data will arrive in a usable state. It doesn't. It never does. And yet the process is designed as if it will — which is why you end up with large teams doing nothing but transposing and gap-filling data between supplier and system. Human middleware, essentially.

This affects distributors, retailers, and marketplaces in slightly different ways, but the core issue is the same: data is coming in from many different sources, in many different formats, and needs to land in one coherent product model.

What makes this harder is that the data requirements are growing. Compliance pressures, digital product passports, multichannel publishing, and the rise of AI-powered commerce all demand more structured, more complete product data than ever before. And critically, where humans could once fill in gaps — scanning a PDF, making a reasonable assumption — machines can't. AI agents and LLMs need the data to actually be there.

The stakes are also competitive. One real client of ours was averaging 10 to 15 interactions per supplier SKU, two to five hours of verification time per product, and up to a month from initial product introduction to launch. Getting a product into the warehouse is one thing. Getting it live and findable is another entirely — and if a competitor can do it faster, that's a real commercial advantage lost.

The Three Levers: Structure, Usability, Automation

Most businesses try to skip straight to automation, believing a tool will solve the problem. It won't — not without the first two levers in place. Here's what each one actually means.

1. Structure: Decouple Onboarding From Enrichment

The goal of structure is to make supplier data workable without forcing suppliers to reshape it before they send it. That's a critical distinction.

If you're asking a supplier to fill in a 200-attribute spreadsheet with 30 tabs and 15 mandatory fields, you're not going to get timely, accurate, complete data back. You're going to get frustrated suppliers and back-and-forth emails.

The better approach is to separate two things that most businesses have fused together: the onboarding structure (what you actually capture from the supplier) and the presentational structure (what the data needs to look like in your PIM, ERP, or e-commerce platform). If you decouple those two, suppliers can give you what they already have — their existing line card, a product spec sheet, whatever format it's in — and your team or your tooling handles the transformation from there.

This also means being realistic about what suppliers can reasonably provide. Many of the suppliers our clients work with are not digitally mature. Some have a product team of one or two people. Sending them a 200-attribute import template and expecting it back in two weeks isn't a process — it's a fantasy.

2. Usability: Remove Friction Without Dropping Standards

Once the structure is right, the focus shifts to making the process as easy as possible for the supplier to use correctly. The goal is to eliminate the back-and-forth, not just digitise it.

That means every field has a clear name, a clear purpose, and clear guidance on how to fill it in. It means building in flexibility for the reality that suppliers hold data in different formats — some can copy-paste, some can upload a PDF, some need bulk import tools. It means validation rules that catch problems at entry, not after submission.

A common failure mode here is portal rollout: the tool gets deployed, suppliers get a login link, and then nothing happens. One business we spoke to recently had invested in a supplier onboarding tool, run it for nine months, and had three suppliers actively using it out of several hundred — because the tool was too complex and there was no real incentive for suppliers to engage.

The measure of good usability is simple: the easier it is for a supplier to give you the right data, the more complete and timely that data will be. Reducing friction doesn't mean reducing standards. It means removing the barriers that stop suppliers from meeting them.

3. Automation: Only Once the Foundation Is Right

Automation in supplier onboarding can mean many things — template mapping, AI-based data extraction, auto-normalisation of units and formats, consistency checks. Used well, it takes the repetitive, pernickety tasks off human plates and speeds up the whole process significantly.

But automation applied to a broken foundation doesn't fix the foundation. It automates the mess. You might successfully automate 20% of the work, and still have a team manually transposing the other 80%. The investment doesn't deliver because the structural and usability problems haven't been addressed first.

Most vendor portals on the market today are, in reality, not much more than glorified Excel templates with a login screen. They don't automate much — they just move the reconciliation problem into a slightly different format.

A Practical Starting Point

This doesn't have to be a huge program of work. The most effective approach we've seen is to start small, deliberately.

Pick one supplier and one category. Map out the current process end to end. Then sit down with that supplier and ask them directly: what are the friction points from your side? Where does this process break down? That conversation is almost always more useful than another internal process redesign — and it builds the kind of collaborative relationship that makes the whole thing work better over time.

From there, run a small proof of concept. Test the improved process. See what changes. Then roll it out incrementally across other suppliers and categories.

A few principles to keep in mind as you do:

• Don't start by chasing completeness. Define what minimum viable data looks like to get a product live, nail that first, and then build up from there incrementally.
• Match the process to supplier maturity. A small supplier onboarding 50 products needs a simple, guided form. A large supplier onboarding tens of thousands of products needs bulk import tooling and automated mapping. One process doesn't fit all.
• Connect category management and digital teams. One of the most common and costly disconnects we see is between the people defining what data gets collected and the people responsible for the customer experience it drives. The filters, the search results, the product pages — all of it flows from the data captured during onboarding. Those two parts of the business need to be working from the same brief.

The Summary

Supplier data problems aren't going away on their own — if anything, the data requirements are growing and the tolerance for gaps is shrinking. But the fix isn't another portal or another template. It's getting three things in the right order:

Structure — decouple what you collect from what you need to present, and make the collection step realistic for suppliers.

Usability — remove friction at every point in the supplier interaction, with clear guidance, flexible submission formats, and validation that catches errors early.

Automation — once the foundation is solid, automate the repetitive transformation work to speed everything up and reduce manual effort on both sides.

Start with one category, one supplier, and one honest conversation. The improvements are visible quickly — and so is the business case for doing more.

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