ERP Data Cleansing and Why Clean Data Drives ERP Success
- Sherry Linares
- 4 days ago
- 6 min read
What if the biggest threat to your ERP go-live is not the software, not the timeline, and not even user adoption? What if it’s ERP data cleansing?
As I explored in my first blog of this series, “Why ERP Projects Fail: The Real Root Causes”, ERP challenges are rarely about the software. They usually come down to people and process issues.
Teams can do everything “right” on the surface:
The system is configured.
Testing is scheduled.
Go-live has a date.
But then the first real transactions hit, reporting doesn’t reconcile, and confidence drops... fast.
In many cases, the real issue is simple: data cleanup was delayed, underestimated, or treated like a technical chore instead of a business-critical process.
In this final blog of my series on why ERP projects fail, I’ll focus on the process problems that quietly sabotage ERP success long before anyone blames the technology.
Why ERP data cleansing is the most overlooked process risk
Data work rarely feels urgent. It doesn’t demo well or produce a shiny milestone, yet it’s one of the most time-consuming tasks in the entire project... when done correctly.
That’s why ERP data cleansing is often delayed until late in the timeline, when teams are already juggling configuration, training, and readiness checklists.
The problem? Clean data is not optional. In fact, Microsoft emphasizes that proper data preparation is foundational to successful ERP implementations, because configuration, testing, and reporting all depend on it.
When organizations treat data cleanup as a “later” task, they create ERP process problems that show up as configuration confusion, testing failures, and painful go-live surprises. This is exactly why many ERP teams now treat clean data for ERP implementation as a formal workstream, not an afterthought.
Treating ERP data cleansing as a core process discipline gives teams more control earlier in the project.
How dirty data creates ERP process issues across the project
Dirty data is sneaky... it rarely announces itself early.
It hides inside assumptions that customer records are accurate, vendor terms are consistent, item masters are current, and the chart of accounts reflects how the business actually operates today.
When these assumptions are wrong, ERP process issues surface across the project:
Configuration decisions get slowed down because teams can’t trust what the source data is telling them.
Reports and reconciliations fail because mappings are inconsistent.
“Working” test scripts produce misleading outcomes because the test data doesn’t reflect reality.
This is where the two sides of an ERP project—process and people—collide. If you read my previous post in this series, you saw how testing challenges can quickly undermine user confidence and slow adoption.
Here’s the link: most ERP testing breakdown causes ultimately trace back to data issues.
When your test environment is filled with duplicates, outdated records, or inconsistent values, you’re not actually testing your ERP system... you’re testing how well your team can work around flawed inputs.
Delaying ERP data cleansing turns testing into guesswork rather than true validation.
And that’s how dirty data silently sabotages ERP projects. Not through one dramatic failure, but through a gradual erosion of trust that spreads across the project team and user base.
ERP data quality is a business issue, not an IT issue
One of the biggest friction points I see in ERP projects centers around an unspoken question:
“Who actually owns this?”
That question hides beneath quiet assumptions, like believing customer records are accurate, vendor terms are aligned, item masters are up to date, and the chart of accounts truly reflects how the business operates today.
But the reality is this: business teams are the ones who understand the meaning behind the data. They know which customers are active, which vendors are obsolete, which pricing rules still matter, and which “temporary” workarounds quietly became permanent years ago.
If you want sustainable ERP data quality, you need clarity on who owns ERP data cleansing. (Spoiler: it’s almost never just one person.)
Gartner repeatedly highlights poor data quality as a significant business risk—not just a technical inconvenience.
In most organizations, ownership sits with business process leaders, supported by IT and reinforced through lightweight governance. Without that shared responsibility, data cleanup becomes a vague, low-priority task that no one has time to own.
And that’s how small data issues quietly grow into ERP process problems, often surfacing at the worst possible moment.
Common data migration problems in ERP projects, and why they show up late
Data migration tends to get treated like a single event:
Extract the data.
Move it.
Validate it.
DONE.
But in reality, migration is a sequence of decisions. That’s why common data migration problems in ERP projects often show up late, when the pressure is highest.
Typical patterns include:
Duplicate records that were never merged because “we can deal with it later”
Outdated fields and values that don’t align with the new ERP structure
Inconsistent naming conventions that break reporting logic
These problems are beyond inconvenient. They create rework, slow adoption, and undermine trust.
This is the impact of poor data on ERP success.
Even if the go-live date holds, the organization pays for it in operational friction.
What “clean data” really means for ERP
Clean data doesn’t mean perfect data. It means the data supports today’s business reality and the workflows being implemented.
Clean data for ERP typically means:
Accurate records that reflect current customers, vendors, items, and terms
Consistent definitions across departments
Standardized formats that support reporting and automation
Retired clutter that no longer belongs in the new system
This is also where governance matters. Teams don’t need bureaucracy. They need clear decision rights, definitions, and accountability.
That’s what data governance for ERP provides: a practical framework for deciding what is “clean,” who approves changes, and how to maintain quality after go-live.
Skip this critical step, and you may still migrate, but not with confidence.
A practical approach: ERP data migration best practices that won't stall the project
A common fear is that data cleanup will slow the project down. Often, the opposite is true.
When incorporated carefully, ERP data migration best practices accelerate progress because they reduce rework and prevent late-stage surprises.
Here’s a practical approach that works without bringing the project to a halt:
Start early and prioritize critical data first. Focus on customers, vendors, items, and the chart of accounts before you tackle less critical lists.
Clean in phases. DO NOT wait for a single “cleanup sprint” at the end.
Define quality standards. This is where ERP data validation and quality checks come into play. Agree on what “valid” means and measure against it.
Use testing cycles as verification. Migration and testing should reinforce each other. If the data fails validation, fix the data and rerun, rather than accepting flawed results.
This is one of the clearest ways to reduce ERP data migration issues while also strengthening go-live readiness.
Why data cleansing is critical in ERP testing and adoption
At some point, every team hits the same moment: the system looks ready, but the business experience does not.
Users don’t judge the ERP by its menu options. They judge it by whether it works with the information they rely on every day. If their customer lists are wrong, if their items are duplicated, if reporting totals don’t tie out, confidence wanes—and fast.
That loss of confidence becomes a people problem, even though the root cause was process.
So “why data cleansing is critical in ERP projects” isn’t a technical argument. It’s a business argument. ERP data cleansing protects credibility, adoption, and momentum.
It also reduces the need for workarounds—one of the fastest ways new systems start reverting to old habits.
Bringing the series together: people and process still win
Across this series, one message has remained consistent: ERP success is not built by software alone. It depends on people and processes working together.
When teams invest in both, they reduce preventable problems and improve the odds that the ERP delivers real value. When they don't, projects become harder than they need to be.
The takeaway is simple:
Treat clean data for ERP implementation as a core success driver, not a late-stage task. Starting earlier buys time and reduces go-live surprises.
What’s next
If you’re planning an ERP move, or maybe you’re already midstream and feeling the data pressure build, a light reset can help.
That usually means getting clear on data ownership, agreeing on quality standards, and identifying the highest-impact cleanup priorities first.
You don’t have to make it perfect to make it successful, but you do have to make it intentional.
If you’d like to explore how these concepts apply to your own organization, you can reach out here – I'd love to chat!
About the Author
Sherry Linares is the President of SL Dynamic Global Solutions LLC, where she helps organizations navigate ERP and IT transformations with a focus on practical solutions and empathetic leadership.
She brings a rare blend of technical insight and real-world experience, built from her years as an end user in Finance and IT and from leading Microsoft Dynamics NAV implementations across the U.S., Europe, and Japan.
Her work as NAVUG Director at Dynamics Communities strengthened her commitment to advocating for users and bridging the gap between business needs and technology.
Sherry’s curiosity for technology began early when she tested Windows 3.1.1 and early versions of CorelDRAW, Word, and Excel.
Today, that same curiosity shapes her people-first approach to helping businesses adopt better processes, not just new systems.
Connect with Sherry on LinkedIn.
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