What is Data Migration?

Data migration is the process of transferring financial and operational data from legacy systems into Workday Finance. This involves extracting, transforming, and loading (ETL) data while ensuring its accuracy, completeness, and security.

Why Migrate to Workday?

Many organisations move to Workday Finance for:

  • Unified financial management – Real-time insights and automation.
  • Scalability – Adaptable to global business needs.
  • Efficiency – Reducing manual processes and reconciliation efforts.
  • Compliance – Ensuring regulatory adherence across multiple regions.

Overview of Legacy Systems

Common financial systems replaced by Workday include:

  • Sun Systems – Used by multinational businesses for financial reporting.
  • Sage – A widely used accounting software for small-to-mid-sized businesses.
  • Netvisor – Popular in the Nordics for automated bookkeeping.
  • Pyramid – A legacy ERP system for manufacturing and distribution.
  • Visma – A Scandinavian financial management tool.

Understanding the Workday Data Model

Financial vs. Operational Data in Workday

Workday structures financial data differently from traditional ERPs. Key categories include:

  • Financial Data – General Ledger (GL), Accounts Payable, Accounts Receivable, Banking.
  • Operational Data – Supplier, Customer, and Transactional Data.

Key Data Categories in Workday

  • General Ledger (GL) – Chart of Accounts, Cost Centres, Financial Statements.
  • Supplier Data – Payment details, tax IDs, banking information.
  • Customer Data – Billing, invoicing, and credit limits.
  • Banking & Payments – Reconciliation rules, payment references.

Mapping Legacy System Fields to Workday

Legacy systems store data in structured but varied formats. Migrating data requires:

  • Aligning Chart of Accounts with Workday’s financial framework.
  • Converting supplier and customer records into Workday’s format.
  • Ensuring currency and tax settings match regulatory requirements.

Common Pitfalls in Data Migration

Many data migration failures stem from avoidable mistakes:

1. Incomplete or Inaccurate Data Mapping

  • Legacy system fields often do not have direct equivalents in Workday.
  • Solution: Conduct a field-by-field mapping and identify gaps early.

2. Lack of Data Cleansing and Standardisation

  • Inconsistent supplier names, duplicate customer records, and outdated data can cause issues.
  • Solution: Standardise data formats before migration (e.g., removing duplicate suppliers).

3. Insufficient Testing and Validation

  • Without thorough testing, errors in GL balances or customer invoicing may surface post-migration.
  • Solution: Perform multiple test migrations and reconcile results.

4. Ignoring Historical Data Requirements

  • Some businesses migrate only current-year data, but audit requirements may need historical transactions.
  • Solution: Define what historical data is essential and implement a structured archive plan.

5. Underestimating Change Management

  • Users expect Workday to function like their legacy system.
  • Solution: Provide training and support to finance teams before go-live.

How to Ensure Data Integrity During Migration

1. Establishing a Data Migration Strategy

  • Define what data will be migrated (active vs. archived data).
  • Identify who owns the data (Finance, IT, Compliance).
  • Set clear reconciliation benchmarks for validation.

2. Data Cleansing and Deduplication Best Practices

  • Remove inactive suppliers and customers.
  • Standardise naming conventions (e.g., all supplier names follow a structured format).

3. Using Automated Validation and Reconciliation Methods

  • Implement automated scripts to compare legacy data against Workday’s structure.
  • Reconcile GL balances pre- and post-migration.

4. Implementing MOD 10/11 Checksums for Payment References

  • Countries like Sweden (OCR), Norway (KID), and Finland (Viitenumero) use checksum validation for banking.
  • Ensure Workday correctly calculates and validates payment references.

5. Post-Migration Data Audits and Quality Checks

  • Run reports comparing legacy trial balances with Workday outputs.
  • Verify customer and supplier data accuracy.

The Role of Data Governance in Transformation Projects

1. Defining Data Ownership and Responsibilities

  • Assign clear roles for data management (Finance, IT, Compliance).
  • Ensure ongoing data stewardship for future system updates.

2. Setting Up Data Governance Policies

  • Define rules for data entry, validation, and archiving.
  • Enforce naming conventions to prevent data fragmentation.

3. Continuous Monitoring and Data Maintenance in Workday

  • Use Workday’s audit tracking to monitor data changes.
  • Automate duplicate record detection.

4. Preventing Data Decay and Stale Records

  • Set periodic data reviews to maintain system integrity.

Real-World Examples of Successful Workday Migrations

Case Study 1: Migrating Financial Data from Sage Line Systems

Challenges:

  • Fragmented financial data across regions.
  • Reconciliation discrepancies between Sage Line Systems and third-party tools.

Solution:

  • Standardised data before migration.
  • Automated validation of ledger balances.
  • Ran Sun Systems and Workday in parallel for two months.

Outcome:
Standardised data before migration.

  • 100% accuracy in GL balances post-migration.
  • Month-end close efficiency improved by 50%.

Case Study 2: Consolidating Multi-Country Finance Operations into Workday

Challenges:

  • Different Chart of Accounts per country.
  • Multiple banking formats (OCR, KID, Viitenumero).
  • Tax compliance for EU VAT and Making Tax Digital (UK).

Solution:

  • Created a single Chart of Accounts across all regions.
  • Integrated banking reference checks for different countries.
  • Configured Workday’s tax compliance tools.

Outcome:

  • Finance consolidation across five countries with real-time reporting.
    ntegrated banking reference checks for different countries.
  • Manual reconciliation efforts cut by 60%.

Lessons Learned from Large-Scale ERP Implementations

1. Data Cleansing is Non-Negotiable

  • Up to 40% of legacy data contains errors.
  • Clean data before migration, not after.

2. Parallel Runs Help Identify Hidden Issues

  • Running both systems in parallel for one financial cycle catches errors.
  • Common issues: Currency mismatches, rounding errors, missing mappings.

3. Financial Reconciliation Must Be a Priority

  • Comparing trial balances pre- and post-migration ensures accuracy.
  • Automate reconciliation scripts to catch discrepancies early.

4. Customisations Should Be Minimized

  • Over-customisation increases maintenance costs.
  • Adapt processes to Workday best practices.

5. Cross-Functional Collaboration is Critical

  • Finance, IT, and Compliance must work together.
  • Ensure finance teams adapt to Workday workflows, not legacy habits.

6. Local Regulatory Compliance Must Be Built-In

  • VAT, EU Making Tax Digital (MTD), and Nordic banking standards must be configured upfront.

Best Practices

  • Plan data migration strategy early.
  • Cleanse and standardise data before loading into Workday.
  • Use automated validation and reconciliation methods.
  • Minimise customisations and follow Workday best practices.
  • Ensure cross-functional collaboration between Finance, IT, and Compliance.

Next Steps

  • Need expert support? Our team can streamline your Workday migration.
Get in touch today!