HR data cleansing and HRIS data validation services UK
We prepare legacy HR and payroll data for new HRIS and analytics so it is clean, complete, standardised and ready to load without disrupting go live or payroll.
- Current HR data quality and source system audit
- Deduplication of employees, positions and org units
- Field normalisation aligned to target HRIS structure
- Data validation rules for payroll, leave and benefits
- Data dictionary and ownership model for HR and IT
- Pre migration test loads and error resolution
Request data review
Share system names and data volumes and we will map cleansing scope.
HRIS data cleansing that makes migration predictable
HR data cleansing and HRIS data validation is the work of finding bad, missing, duplicate or non standard people data before it reaches the new system. It matters because most HRIS delays come from data, not from configuration. If you load inconsistent job titles, expired contracts, wrong leave balances or duplicate workers, HR and payroll will not trust the new platform. With deduplication, field normalisation and a clear data dictionary, go live becomes faster and reporting becomes reliable.
Â
HR Data Quality and Source System Assessment
We start by finding out where your people data actually lives today. That can be in legacy HR, payroll, time, recruitment, spreadsheets or shared drives. We profile the data to see completeness, format issues, conflicting codes, historic employees and non employees stored as employees. We also check statutory and UK specific fields such as NI number, tax codes, right to work and pay elements. This gives you a transparent view of your HR data cleansing need.
From this assessment we create a data quality report sorted by impact. It shows what must be fixed before migration, what can be defaulted, and what can be handled post go live. This stops the project team arguing about data and lets them focus on the highest value corrections first.
Deduplication and Field Normalisation
Duplicate people and unstandardised fields are the main reason mappings fail. We run deduplication logic across person IDs, national IDs, email addresses and employment records to find real duplicates. We agree business rules with HR to decide which record is the master. We then normalise key fields such as job title, department, grade, location, employment type, manager and cost centre to match the target HRIS picklists.
This normalisation is not just technical. We work with HR and Finance to keep naming and structures meaningful for reporting. When field normalisation is done well, data loads cleanly, workflows route correctly and analytics such as headcount or cost by function are accurate from day one.
HRIS Data Validation Rules and Exception Handling
Every HRIS has rules on what data it will accept. We build HRIS data validation rules outside the target system so you can check data before you load it. Typical rules include mandatory fields, valid date ranges, valid manager relationships, numeric fields, payroll balance rules, and matching of codes across HR and payroll. Exceptions are flagged in a log with the exact reason.
We then define how exceptions are fixed. Some can be auto corrected, some need HR to review, some need the business to confirm values. This exception handling makes your data cleansing repeatable and makes test cycles much faster.
Data Dictionary, Ownership and Governance
Data problems come back when nobody owns the definitions. We create an HR data dictionary that defines each field, what it is used for, which system is the source, allowed values, and who is responsible for keeping it clean. We map this to HR and payroll processes such as onboarding, transfer, promotion, absence, variable pay and leavers so people know when data must be updated.
We also define a light data governance rhythm. That can be monthly HR data quality checks and quarterly reviews with HR and IT. This keeps the new HRIS clean even after go live when teams are busy.
Pre Migration Test Loads and Reconciliation
Before the real migration we run controlled test loads. We take a cleansed data set, load it to the target structure, and then reconcile counts, key fields and payroll relevant data. We check for records that failed to load, orphaned dependents, missing managers and incorrect dates. Where issues arise we update the cleansing rules and run again.
This pre migration loop is what makes the actual go live weekend smooth. It also gives your HR team a safe space to practice corrections. By the time you move for real, you will know exactly what to expect.
Make HR data load clean
Tell us which HR or payroll systems you are moving from and we will send a data cleansing checklist.
Talk to us
Discovery and data profiling
We collect sample extracts from your HR, payroll and related systems. We profile the data to spot missing fields, duplicate people, non standard values and outdated records. We map sources to the target HRIS model and highlight where HR data cleansing and HRIS data validation are essential to avoid migration failure.
What We Offer: - HR data quality and completeness report
- Source to target field mapping draft
- List of critical cleansing actions by owner
- Exception log and validation rules catalogue
- Data governance and dictionary starter pack
Schedule data discovery
Cleansing execution and test loading
After discovery we run the actual cleansing cycles. We deduplicate, normalise, enrich and validate the data, then perform test loads into the target structure. We reconcile counts, resolve exceptions and prepare final load files for the implementation team. We also train HR on how to keep data clean after go live.
What We Offer: - Deduplicated and standardised HR data sets
- Validation ready files for the new HRIS
- Test load support and error remediation
- Data dictionary and ownership documentation
- Post go live data quality review plan
Talk to data team
Our Process
Scan sources
Identify all HR, payroll and spreadsheet sources and assess data quality.
Define rules
Build deduplication, field normalisation and validation rules for the target HRIS.
Clean and test
Run cleansing cycles, fix exceptions and test load into the new structure.
Govern data
Hand over dictionary, ownership and review cadence to HR and IT teams.
Why choose Us?
Process led
Cleansing aligned to onboarding, changes, payroll and leavers.
Platform neutral
Works across multiple HR, payroll and talent tools.
Audit friendly
Logs, rules and owners for every data change.
Migration ready
Outputs structured for implementation partners.
Frequently asked questions
About Our HR Data Clensing Services
What is HR data cleansing?
HR data cleansing is the process of fixing, standardising and removing incorrect or duplicate HR and payroll data so it can be safely used in a new HRIS or analytics platform. It makes migration faster and reduces post go live issues.
Why is HRIS data validation important?
HRIS data validation checks that your data meets the rules of the new system before you load it. It prevents failed imports, broken workflows and payroll errors. It is cheaper to validate before migration than to fix thousands of records after go live.
Can you help if our HR data is in spreadsheets?
Yes. Many UK organisations keep parts of HR data in Excel. We can profile, deduplicate and standardise spreadsheet data and merge it with system data so the new HRIS has one consistent employee record.
What is field normalisation?
Field normalisation is the practice of making values consistent. For example, turning HR, Human Resources and People into one value, or making locations, job families and cost centres match the target HRIS picklist. This improves reporting and integrations.
What is a data dictionary in HR?
A data dictionary explains every HR field, what it means, allowed values, which system is the source and who owns it. It helps HR, IT and payroll to speak the same language and keep data clean over time.
Do you support data cleansing before payroll migration?
Yes. For payroll migration we pay extra attention to pay elements, tax, NI, pensions, leave balances and bank details. We validate these to reduce pay day issues.
How many cleansing cycles do we need?
Most projects run 2 to 3 cleansing cycles and the same number of test loads. Complex estates or multiple countries may need more. We keep each cycle short and focused.
Can you work with our implementation partner?
Yes. We can align our HR data cleansing outputs to the templates and load formats your implementation partner needs. That keeps the project moving.
What happens after go live?
We hand over a data quality review plan. HR can run regular checks, fix new issues and update the data dictionary so the HRIS stays clean.
Will this help reporting and analytics?
Yes. Clean and validated data means HR, Finance and leadership can trust headcount, cost, turnover and diversity reports because the underlying data is standardised.
Got more questions?
Feel free to reach out to us for more details & also get a free consulting session with our experts.
Contact Us
Recent Case Studies
We Offer A Wide Range Of HR Consulting Services Tailored To Your Business Needs.
Get A Free Consultation
Our team of experts respond within one business day with the next steps.