7 Manufacturing Master Data Problems Causing Production Delays (And How to Fix Them)

When a production line stops, the first question is always operational. Wrong components. Late delivery. Equipment failure. And nine times out of ten, the investigation stops there. Rarely does anyone connect it to manufacturing master data management problems sitting quietly in the background.

What should be getting asked is: Why did the wrong components get ordered? Why wasn’t the delivery right? Why did the equipment record show the wrong maintenance schedule?

The answer, more often than you’d think, is bad master data. Not a dramatic system failure. Not human incompetence. Just a data record somewhere in your ERP that was wrong, duplicated, or out of date, and nobody caught it before it became a production problem.

We see this constantly. So here are the seven master data problems that cause the most damage in manufacturing and what actually fixes them.

1. Duplicate material records

Picture this: a buyer can’t find a material in the system. It’s there. It was created two years ago by someone in a different plant, but the description doesn’t match what they searched for. So, they create a new one. Now you have two records for the same material, sitting in the same ERP, slowly diverging.

This happens everywhere. And it compounds. One duplicate becomes five, five becomes fifty, and before long your procurement team is ordering against the wrong record, your inventory counts are split across multiple entries, and nobody really trusts the data anymore.

The solution to this isn’t a one-off data cleanse. That’s just treating the symptom. The fix is a governed creation workflow that checks for duplicates before approving a new record. Stop them getting in rather than chasing them once they’re there.

2. Inconsistent units of measure

This one sounds trivial until it isn’t.

The same material. Kilograms in one plant, grams in another. Or ordered as individual units but received as boxes of 12. It gets entered in a way that makes sense to the person who created the record, with no enforced standard across the business.

In food and beverage or pharmaceuticals, a unit of measure error in a product formulation isn’t just an operational headache. It’s a potentially catastrophic quality and safety issue. In any manufacturing environment it causes miscounts, incorrect ordering quantities, and production runs that fall short mid-shift. You can imagine the potential negative impact on customers.

We can’t stress enough how important it is to standardise units of measure centrally. Enforce them with validation rules that won’t let a non-compliant record be saved. It sounds boring, but in the long run prevents a lot of pain.

3. BOM changes that don’t reach the shop floor

Engineering updates a bill of materials. A new component, a changed quantity, a revised specification. The change gets approved internally, emails confirmed, spreadsheet updated, and everyone moves on. Except… the production team is still working from the old version. All because the change was never formally pushed to the systems they actually use.

This is one of the most common and most costly master data failures in manufacturing. Products get built incorrectly. Wrong components get consumed. Rework piles up. And when you dig into why, it always comes back to the same thing: an engineering change process that relied on people manually communicating updates rather than a system that automatically propagates them.

BOM changes need a governed workflow that doesn’t consider a change complete until it has reached every downstream system that depends on it. Not an email chain. A process.

4. Supplier data owned by nobody and everybody

These are classic manufacturing master data management problems that compound over time. Finance has the supplier set up one way. Procurement has their own version. Neither team knows what the other has, and there’s no single governed record that both work from.

So, payments go to outdated bank details. Purchase orders get raised against the wrong contact. New supplier onboarding takes twice as long as it should because the same information is being collected in two places by two teams that don’t talk to each other.

It also means your spending data is fragmented. If the same supplier exists as three different vendor records, your total spend with them is invisible, and so is your negotiating position.

One governed vendor record. One workflow. Both departments work from the same source, managing their relevant fields, with full visibility of each other’s data. That’s what good looks like.

5. Anyone can change anything, and nobody knows they did it

This is the one that surprises people when we point it out. In most ERP systems, including SAP, users with the right access level can change a master data record directly. No approval. No notification. No audit trail that’s easy to follow.

A field gets updated. A value changes. Production sees something different to what was there last week and has no idea why.

When something goes wrong (and it will), there’s no clean way to find out what changed, when it changed, or who changed it. Root cause analysis becomes guesswork. Compliance audits become a scramble.

Every change to a critical data record should go through a formal request, be routed to an appropriate approver, and be logged with a full timestamp and change history. This isn’t bureaucracy. It’s basic governance, and most manufacturers don’t have it.

6. Manual data entry at an industrial scale

Spreadsheets, emails and people typing values into ERP screens by hand, at pace, while managing six other things. No, it’s not the worst idea for a Guy Richie film ever. It’s how most manufacturing master data gets created and maintained. And this is fine for a while… Until you’re running hundreds of data requests a month across multiple plants and data objects, and the error rate starts to show up as operational problems downstream.

The 70% reduction in manual data entry that Maextro customers typically see isn’t a product stat plucked from thin air. It reflects the scale of the manual effort most manufacturers are currently carrying and didn’t realise was costing them.

Automate where you can. Enforce validation where you can’t. Catch errors before they’re saved, not after they’ve already caused a problem three steps down the line.

7. The ERP migration that was never properly cleaned up

When manufacturers go live on a new ERP or migrate from one system to another, data often comes across as-is. This means the duplicates, abandoned records and material codes nobody has used since 2017 all migrate. cleaning it up properly before go-live would have taken too long. That’s what we hear the most.

“We’ll sort it out after.” That was three years ago.

This is data debt. And unlike financial debt, it doesn’t sit still. It compounds. More transactions run against bad records. More duplicates get added because the originals are hard to find. More workarounds get built because the data can’t be trusted. The longer it’s left, the more embedded it becomes.

Retroactive remediation is possible and for a lot of manufacturers we work with, it’s where the journey starts. Tools like Maextro’s Align capabilities are built specifically to identify and fix this kind of historical mess at scale, without someone having to manually correct records one by one. It’s not a small job. But it’s a finite one, and the improvement on the other side is immediate.

So, what’s the common thread?

Every single problem above happens because data enters or changes within a system without validation, without a clear owner, and without governance.

None of this is inevitable. All of these manufacturing master data management problems are structural with a structural fix.

The purpose of Manufacturing MDM software isn’t to replace your ERP. It’s to sit alongside it, controlling what goes in, tracking what changes, and making sure that procurement, production, finance and supply chain are all working from the same accurate data. When that’s in place, the operational problems that felt random start to disappear because the root cause is finally being addressed.

If any of these problems sound familiar, see how Maextro solves and mitigates manufacturing master data management problems in practice and what that looks like for manufacturers like Carlsberg, BAE Systems, WaterWipes and SHS Group who are already trusting it to increase agility in their manufacturing operations.