Most product and data teams eventually run into the same wall. The ERP holds all the "real" data: SKUs, pricing, stock levels, supplier codes. But when someone from marketing asks for enriched product descriptions, or a channel manager needs localized attributes for a new market, the ERP either can't deliver them or delivers them badly.
That gap is not a bug. It's by design. ERP systems were built for operational efficiency, not product content management. This article maps which product data belongs in ERP, which doesn't, and what to put in its place.
Which Product Data Is Managed in ERP?
In an ERP system, product data refers to the structured, transactional attributes tied to a product master record. This is the product master: SKU, unit of measure, pricing, inventory levels, supplier references, bill of materials, cost codes, and lifecycle status. In SAP, this is the material master. In Microsoft Dynamics 365 or Oracle NetSuite, the equivalent is the item master or product catalog record.
The product master in an ERP is the single source of truth for operations. Procurement, manufacturing, finance, and logistics all depend on it.
ERP product data management is tightly governed by design. ERP systems enforce validation rules, approval workflows, and field-level controls because errors in the product master have direct financial consequences. A wrong unit of measure on a purchase order creates real problems. A missing image on a product listing is annoying, but it won't stop a production run.
That distinction matters when you're deciding what should live where.
Product Data That Doesn't Belong in ERP and Where It Does
A large share of product information has nothing to do with operations. ERP data models are built around transactions. Every field in a product master record exists because a purchase order, production order, or stock movement needs to read it. Marketing copy, CAD files, and translated channel content don't serve any transaction. Storing them in the ERP adds weight to a system built for speed and operational consistency, and creates data governance problems when marketing, engineering, and product teams share the same records.
The product information that falls outside ERP and the systems that handle it better:
- Marketing descriptions, digital assets, localized content, and channel-specific product attributes belong in a PIM (Product Information Management) system. PIM handles product data enrichment, multi-channel distribution, and product taxonomy. It takes the core product record from ERP as a starting point and builds the commercial layer on top.
- Engineering data, such as CAD models, technical specifications, design revisions, and component-level material data, belongs in PLM (Product Lifecycle Management). PLM manages the upstream product information before it enters the ERP as a manufacturable item.
- Version-controlled engineering documents such as drawings, release packages, and specifications are the domain of PDM (Product Data Management), which is often embedded within PLM or sits alongside it.
ERP is the operational core. PLM and PDM manage the engineering layer. PIM manages the commercial layer. Problems arise when companies try to collapse these layers into one system, usually the ERP, because it's already there.
The problematic pattern is consistent. A manufacturer stores everything in the ERP because it's the system everyone has access to. Over time, the product master gets cluttered, product data quality degrades because nobody owns it clearly, and the digital sales team builds a parallel spreadsheet because the ERP can't output what they need. The fix is always the same: separate product information by purpose, assign clear data ownership, and integrate the systems rather than merging them.
Where ERP Product Data Management Breaks Down
ERP works well within its operational scope. The problems start when product data has to do more.
Data governance at scale across markets. When a company operates across multiple regions, maintaining consistent ERP product data often requires multiple ERP instances: one per country or business unit, each managing product master records independently. The result is a fragmented data landscape with no unified visibility across the enterprise. The ERP stops being a single source of truth for product information and becomes one of several competing ones.
Product data quality at the master record level. Data accuracy, user experience, and analytics capabilities are the top three areas where ERP systems fall short for users. Product data quality problems — duplicate records, inconsistent naming conventions, missing product attributes — are common and expensive to fix after the fact.
Time-to-market pressure across channels. When a product needs to go live across a webshop, a marketplace, and a print catalog simultaneously, ERP has no native mechanism to manage that. Each channel needs differently formatted product information. Without a system designed for that distribution, the work falls to manual exports, spreadsheets, and copy-paste. That slows launches and multiplies errors.
Our customers have come to us with exactly this problem. One mid-size electronics manufacturer had product master records spread across two ERP instances after an acquisition, with no reliable way to tell which system held the authoritative data for a given SKU. Procurement was ordering against one price, and finance was reporting against another. The fix required a product data governance layer outside the ERP, because the ERP itself had no mechanism to resolve conflicts between its own instances.
ERP-Only, ERP and PIM, or ERP and MDM: Which Fits Your Situation
The right approach depends on product catalog complexity, channel count, and how much of your revenue depends on rich product information.
For companies with simple catalogs and limited channel exposure, ERP product data management is often sufficient. Clean data governance, consistent naming conventions, and a well-maintained product master handle a lot.
For companies with large or complex product catalogs, multiple sales channels, or global operations, a dedicated PIM system typically makes more sense alongside the ERP. The PIM handles product data enrichment, channel-specific formatting, and content distribution. The ERP remians the source of truth for operational product data. The two systems sync on the shared attributes: SKU, pricing, and inventory signals.
The difference becomes concrete with something like "material composition." That attribute might need to appear as a short procurement code in the ERP, a full technical description in a product datasheet, and translated marketing copy in a French-language catalog. An ERP stores one value in the product master. A PIM stores all three, manages the relationships between them, and routes each to the right destination. SAP, Oracle NetSuite, and Microsoft Dynamics 365 have all attempted this with built-in content modules, but these additions sit on top of an operational data model. Teams typically end up maintaining parallel product records anyway.
For large enterprises dealing with multiple ERP instances, post-merger product data conflicts, or complex regulatory environments, MDM (Master Data Management) is a third option. Where PIM enriches and distributes product content, MDM governs the product master record itself: enforcing consistent definitions, resolving conflicts between ERP instances, and serving as the authoritative source that feeds all downstream systems, including the ERP. The two are not interchangeable. MDM addresses data consistency at the master level. PIM addresses content quality at the channel level.
Fix the Right Problem First
Before picking a tool, assess where the actual problem sits.
If your issues are in channel readiness: incomplete product listings, slow time-to-market, and localization bottlenecks, that's where ERP structural limits are costing you, and a PIM ERP integration is worth evaluating. If the problems are in the operational records themselves — duplicates, wrong units of measure, conflicting product master data across systems — no amount of additional tooling fixes that. ERP data governance has to come first.
Getting the diagnosis right matters more than picking the tool. ERP product data management problems often get misattributed. Teams add systems when they should fix processes, or fix processes when the product data architecture is the actual constraint.
The product master in your ERP is load-bearing. Whatever sits alongside it needs to treat it that way.
*AtroPIM and AtroCore support flexible PIM and data management architectures that integrate with existing ERP systems.