Why Data Migration in ERP Is the Hardest Step

When businesses plan for an ERP implementation, they usually focus on system features, vendor selection, training, or timelines. But one step often underestimated — and yet the most critical — is data migration. A Hectic Process for vendors of transferring existing business data — such as customers, suppliers, products, transactions, and financial records — from legacy systems, spreadsheets, or older ERPs into the new platform. Sounds simple? In reality, it’s often the most complex, time-consuming, and risky phase of ERP implementation. Let’s explore why data migration is so challenging, what can go wrong, and how to prepare your organization to get it right the first time.

1. Your Data Is Probably Messier Than You Think

Most organizations believe their data is “fine” — until they start the migration process. That’s when hidden issues surface: inconsistent naming, missing values, duplicates, outdated records, or conflicting formats.

Common Problems:

• Duplicate customer or vendor names (“ABC Ltd.” vs “A.B.C. Limited”).
• Missing fields (no GST number, phone number, or address).
• Data spread across multiple systems — Excel, CRMs, accounting tools, or even paper.
• Old or inactive records that clutter the database.

The problem is simple: ERP systems demand structure, accuracy, and consistency. If your legacy data isn’t clean, the new ERP will inherit those flaws — leading to faulty reports, mismatched transactions, and operational chaos. Tip: Before you even start your ERP project, conduct a data health check. Clean, deduplicate, and standardize your records — this can cut migration effort (and frustration) by 30–40%.

2. Data Mapping Is a Complex Puzzle

Each ERP system — including Odoo | SAP | MS Dynamics etc — has its own data structure and relationships. For instance, what you used to call “Client Name” in your Excel sheet might be stored as “Partner Name” in the new ERP system, linked to multiple relational tables (e.g., invoices, orders, payments). Mapping this old data to the new structure is like solving a puzzle — every field must find its exact place in the new environment.

Why It’s Hard:

• Field names, types, and dependencies differ between systems.
• Mandatory fields in ERP may not exist in your old data.
• Relationships between records (like linking invoices to customers) can break if IDs don’t match.
• Some fields (like tax rules or payment terms) must be redefined entirely.

Example: A company moving from Tally to new ERP (eg: Odoo) needs to map its “Ledger Accounts” to “Chart of Accounts” — a one-to-many relationship that requires precision to avoid financial mismatches.

3. Data Volume and Quality Impact Performance

If your organization has been operating for several years, chances are you’ve accumulated massive amounts of data. Migrating everything — including years of historical transactions — can severely affect both timeline and system performance. Typical Challenges:

• Historical data (beyond 3–5 years) may not be relevant but still takes time to migrate.
• Large import files (tens of thousands of rows) slow down migration testing.
• Poor-quality or redundant data can inflate storage and degrade reporting speed.

Best Practice: Don’t migrate everything blindly. Instead, prioritize relevant data:

• Active customers and suppliers.
• Current inventory and open orders.
• Recent transaction history (1–2 years). Archive the rest separately for reference. This keeps your ERP fast, clean, and easy to manage.

4. Lack of Ownership and Responsibility

One of the most common pitfalls in ERP data migration is unclear ownership. Who is responsible for validating customer data? Who verifies product SKUs or accounting balances? Without defined accountability, teams assume “someone else” is handling it — until errors emerge after go-live.

Why It Happens:

• Each department owns different data sets (finance, sales, HR, etc.).
• Data migration is seen as a technical task, not a business responsibility.
• Lack of coordination leads to gaps, duplication, and mismatches.

Solution: Assign data owners for every module — Sales, Inventory, Accounting, HR — responsible for verifying accuracy and approving final uploads. The IT or Vendor manages the technical migration, but business teams must ensure correctness.

5. Data Validation and Testing Take More Time Than Expected

Even after cleaning and mapping, data migration isn’t “done” — it must be tested, validated, and re-tested before go-live.

Typical Stages:

1. Test Migration: Import a sample dataset into a sandbox (test environment).
2. Validation: Verify that all data appears correctly and behaves as expected.
3. Adjust Mapping: Fix issues and repeat testing.
4. Final Migration: Migrate full, cleaned data into the live database before launch.

Why It’s Hard:

• Errors discovered late in testing can delay go-live.
• Certain data (like balances or open transactions) can’t be validated automatically — they require manual checks.
• Multi-branch or multi-company data adds another layer of complexity.

Pro Tip: Plan at least two rounds of test migrations. It’s better to spend extra time validating than to fix errors after go-live, which can disrupt operations.

6. Different Departments Have Different Data Priorities

Your finance team may care deeply about precise balances, while your sales team wants all customer records imported — even if some are outdated. When departments don’t agree on what’s important, data migration becomes a tug-of-war.

Why It’s a Problem:

• Conflicting definitions (e.g., “active customer” or “valid lead”).
• Departments pushing for more data than necessary.
• Unclear decision-making hierarchy for what to keep, clean, or discard.

Solution: Create a cross-functional migration committee including representatives from each department. Define clear rules — what data is mandatory, what can be archived, and how discrepancies will be resolved.

7. Migration Tools and Formats Can Be Limiting

Not all systems export data in easily usable formats. Some legacy tools only generate reports or unstructured files (PDF, CSV with merged cells, etc.), making conversion difficult. Even with modern software, data often requires significant transformation and normalization before import.

Why It’s Challenging:

• Data exported from older systems may have encoding errors.
• Merging files from multiple sources introduces inconsistencies.
• Complex dependencies (like foreign keys) may not be preserved.

Pro Tip: Use ETL (Extract, Transform, Load) tools or scripts to automate the cleaning and mapping process. For Odoo specifically, partners often use import templates to standardize migration and minimize human error.

8. The Risk of Losing Critical Historical Data

Data migration isn’t just about moving information — it’s about preserving business history. Losing even a small subset of data, like past invoices or employee records, can have regulatory or operational consequences.

Risks Include:

• Missing invoices affecting audit trails.
• Unmatched balances between ledgers.
• Lost customer interactions or payment records.

Best Practice: Always perform data reconciliation after migration. Compare trial balances, stock quantities, and customer balances between old and new systems to ensure accuracy.

9. The Impact of Poor Data Migration Can Be Long-Lasting

A poorly executed data migration can cripple your ERP from day one. Incorrect data leads to wrong reports, frustrated users, and loss of confidence in the new system.

Common Aftereffects:

• Users revert to Excel to “fix” data manually.
• Reports and KPIs show inaccurate figures.
• Financial audits become complex and error-prone.
• Re-migration (fixing data post go-live) becomes expensive and disruptive.

Pro Tip: Treat data migration as a core phase, not a side task. Allocate enough time, budget, and resources to do it right the first time.

10. Successful Data Migration Requires Collaboration, Not Just Tools

At its core, data migration is not just an IT process — it’s a business-wide collaboration. Technology handles the “how,” but people define the “what” and “why.”

Keys to Success:

• Early involvement of all departments.
• Clear communication between business teams and ERP consultants.
• Strong data governance and documentation.
• Adequate time for review, testing, and sign-off.

Tip: Don’t wait until the end to start migration. Begin cleaning and preparing your data as soon as the ERP project kicks off. This proactive approach prevents last-minute surprises.

Conclusion: Data Migration — The Foundation of ERP Success

Your ERP system is only as good as the data inside it. Entering current data as your process flow is one part and having legacy data in the system gives you a foundation to decision making on each transactions that happens in your business. While ERP implementation is often seen as a technology upgrade, data migration is where the real transformation happens. It’s the bridge that connects your company’s past to its digital future. By giving data migration the attention, time, and resources it deserves — cleaning, mapping, validating, and reconciling carefully — you set the foundation for a smooth ERP rollout. In short, good data migration equals a successful ERP implementation. Skip the effort, and you’ll spend months fixing the fallout.