Master data is the DNA of an ERP system. Customers, suppliers, items, cost centers, bills of materials — when this foundational data is inconsistent, outdated, or incomplete, every process built on it is compromised. Invoices go to the wrong addresses. Orders get created twice. Reports become impossible to compare.
This problem exists in almost every mid-sized company, yet it is rarely prioritized until the next ERP migration forces the issue.
The 6 most common signs of poor master data
Duplicate customer numbers
The same customer has 3 different numbers, created by different departments at different times. There is no single, complete view of the customer.
Outdated supplier data
Contacts have left the company, bank details have changed, and addresses are no longer correct. Payments get sent using outdated information.
Inconsistent item master data
The same item exists under different names, units, or prices. Accurate inventory valuation becomes impossible. Procurement orders items that are already in stock.
Outdated price lists
Old pricing structures remain in the system because no one has maintained them. Invoices are issued using incorrect prices. Manual corrections become a daily task.
Missing required fields
Records have no category, no owner, or no defined validity period. Reports can't be filtered properly. Compliance requirements can't be met.
No data owner
No one is accountable for the quality of a given record. Everyone can make changes, but no one is responsible for maintaining it. Chaos is the predictable result.
The 6 master data categories and who owns them
Customer master data
Owner: Sales / CRM
Contains: contact details, terms, segmentation
Supplier master data
Owner: Procurement
Contains: terms, banking details, lead times
Item master data
Owner: Product Management / Procurement
Contains: names, units, prices, categories
Cost center / organizational master data
Owner: Finance / Controlling
Contains: posting logic, reporting structure
Bills of materials / recipes
Owner: Engineering / Production
Contains: components, quantities, versions
Employee master data
Owner: HR
Contains: roles, permissions, cost center assignments
How to build master data governance in 5 steps
Assign a data owner
Assign one accountable person or role to each master data category. That person has final responsibility for data quality and approval, not "everyone."
Clean up existing data
Start with an audit: what exists? What is outdated, duplicated, or incomplete? Define rules for merging duplicate records. Establish an archiving process.
This is a project with a beginning and an end, not an ongoing cleanup exercise.
Define data entry standards
Which fields are mandatory? What naming conventions apply to items? How are customers belonging to the same corporate group handled?
Document the rules and make them mandatory.
Enforce access and approval controls
Who can create master data? Who can edit it? Who can delete it? Critical data should require a second-person review or approval.
Enforce these controls in the system, don't rely on trust alone.
Introduce data quality monitoring
Create a monthly report covering the completeness of required fields, records without an owner, and inconsistent categorization.
What gets measured tends to improve.
An ERP running on poor master data is like a precision instrument calibrated using the wrong inputs. The result is precisely wrong.
Master data quality isn't an IT problem, it's an organizational and leadership problem.
Without clear ownership, standards, and controls, the chaos will keep coming back no matter how often the data gets cleaned up.
Governance beats cleanup.