Episode 16: Mastering Product Data in Industrial Solutions and Electro Components

Manufacturers make the products, so they must hold the product data. Distributors sell those products, so they must be able to get hold of it.

Both statements are true. Neither one helps.

In industrial solutions and electro components we see the same bottleneck year after year, and the thing that makes it hard to solve is that it looks like two different problems. It is one problem viewed from opposite sides of the same trading relationship.

The same problem from two sides

On the manufacturer side, the data almost always exists. It is just buried. Deep in the ERP, on PDF spec sheets nobody ever transposed into a digital format, or in the head of somebody experienced on the shop floor. Getting it out and into something you can share with trading partners is the job, and it rarely has an owner.

Meanwhile the same business is planning regional or global expansion, which means multilingual content, and actively recruiting new distributors to sell through.

On the distributor side, the job is acquiring that content from a supplier base that can run to thousands. Which is why industrial supply websites so often have missing data, on exactly the sort of attribute-heavy products where the specification is the purchasing decision.

Line the two lists up and they are nearly identical. Missing images, specs and documents. Manual onboarding that eats the week. Time to market. Compliance. ERPs that were never built to hold product information, which businesses outgrow quickly and then tolerate for years. Disconnected systems and websites with no single source of truth anywhere.

Only one item sits on a single side. Inconsistent supplier data belongs to the distributor alone. Everything else, both parties are already paying for.

The numbers behind the bottleneck

In B2B generally, launching a product takes around 30 days. In this vertical it usually takes longer.

Underneath that sit two figures worth knowing. Getting the information you need from a supplier takes 10 to 15 separate interactions per SKU. Verifying it takes two to five hours per SKU. Multiply either by the range growth your business has committed to this year.

The consequences are not subtle. Launches slip. Incomplete listings get de-categorised on websites, so the product is live and invisible at the same time. And customers cannot see, touch or handle anything, so without images, specs, data sheets and compliance material you simply do not stand next to the competitor who has them.

The harder part is that the requirement keeps growing. One SKU with one attribute becomes one SKU with ten attributes, then ten attributes across ten languages. That is a thousand pieces of data for a single product. Specification depth is rising, language coverage is rising, and unless the process gets fixed you are chasing a tail that moves faster every year.

Regulation is moving the same way. Digital Product Passport requirements begin rolling out in 2026 and broaden across more industries in 2027, and without the underlying product data to generate the digital identifier, selling into Europe stops being an option.

How easy are you to do business with?

That is the question we would put to both sides, and it reframes the whole thing usefully.

For a manufacturer it means getting the right data to the right trading partners at the right time. Do that and you sell more, because you are easier to range. It applies well beyond ecommerce: your field sales team needs the same material, and most manufacturers have not yet treated digital trading as the commercial function it now is.

For a distributor it inverts. Make it easy for suppliers to work with you and you onboard more products, and suppliers choose you over the competing distribution partner who makes it painful.

Which is why supplier data onboarding deserves its own work stream, and why it is not a PIM question. It is workflows, approvals, vendor portals and data standards. This part of the market remains strikingly immature and under-serviced, and without somebody owning it you will keep chasing your tail.

Distributors also carry more than classic master data. Lead times, pricing and inventory are all high volume, change frequently, and slow everything down when they are not handled properly. And on compliance, remember who is showing the end customer the data. It is you, not your supplier, so it needs to be traceable and validated.

We used to say in retail that a retailer is just a shop window for a supplier's products. A distributor is the same. The only question is how well you want to show a range of millions of products to the people buying them.

A real example

One global distributor we support introduces 25,000 products a month across a supplier base in the thousands. When we started working together, launching a product took around 130 days. It is now under a week.

At the other end of the scale, a small distributor in Western Australia could only range about 15% of the SKUs on their website, for the straightforward reason that the images and documents did not exist.

A building supplies business asked us to run their data and content work. Doing it internally would have taken their team an estimated two and a half years. That is not a timeline, it is a decision not to sell those products.

One manufacturer saved £130,000 on content creation by automating data sheet production alone.

The most useful thing any of them did, though, was arithmetic. One distributor calculated their cost per SKU introduction across the whole end to end process. Somebody in the business is managing those 10 to 15 supplier interactions and drawing a salary for it, which puts the figure in the tens of pounds per SKU. Multiply by thousands of SKUs and you have the business case, already sitting in your P&L.

Ten things you can do without buying anything

None of this needs a platform, a budget request or a transformation programme. Pick two or three and start.

Score what you actually hold. Take your top 100 SKUs and review them for missing images, specs and documents. Expect not just gaps but inconsistencies and outright wrong values. Then formalise it: mark 10 to 15 SKUs for completeness as a scorecard, and treat anything below about 75% as not ready to range.

Fix the cheap inconsistencies first. Agree a standard naming convention and concatenation rules for titles and descriptions, because product title formats are usually a mishmash. Then run filters or conditional formatting over an export to surface duplicates and blanks. Duplicates you can clear immediately. Missing values take longer.

Consolidate your assets without buying a DAM. A shared drive is enough to start building a central repository. While you are there, draft a product data sheet template in Word or Excel and decide what a product actually needs in order to sell.

Do one supplier properly. List your top 10, choose one reasonably mature partner, take their top 100 SKUs, and run a real cleaning and enrichment exercise with them. Then measure it once the new data is live. That measurement is what funds the next one.

Restructure one category, and talk to the people who sell. Take a single super category and break it into a better taxonomy as a test. Separately, audit your hazardous or standards-bound categories for non-compliant SKUs. Then sit down with sales and customer support, who are a gold mine: what frustrates them, and what do customers ask for that they cannot find on your site?

Half of this list can now be done with an AI assistant sitting alongside you, which changes the effort calculation considerably.

The takeaway

There is not a distributor anywhere that is not trying to grow its offer. Almost none of them are limited by willingness. They are limited by their capacity to onboard products, which is a process constraint wearing a commercial disguise.

The encouraging part is that the fix is rarely a major upheaval. The customers who get results run incremental data and content enrichment over a reasonable period, and the uplift is demonstrable as they go.

As a floor rather than a forecast, expect around 30% off time to market and around 20% sales growth from doing this properly. Those are minimums, not best cases.

So take the 100 SKUs and look at them this week. Whatever you find is already costing you, whichever side of the relationship you sit on.

Listen to the full episode

Episode 16 of Product Data Weekly is available now. For more episodes and the weekly newsletter on operational issues inside product data and ecommerce teams, visit productdataweekly.com.