How to Fix Data Discrepancies in Workday: A Step-by-Step Guide

Accurate data is crucial for efficient Workday operations, ensuring business processes run smoothly and reporting is reliable. However, data discrepancies are common and can cause misaligned business processes, payroll errors, and inefficiencies in decision-making. Here’s a step-by-step guide to resolving data discrepancies in Workday, and how SimpliData can streamline this process for you.

1. Identify the Root Cause of Discrepancies

The first step in resolving discrepancies is identifying their source. Common causes include:

• Manual data entry errors.
• Mismatches during data migration.
• Integration issues between Workday and other systems.

SimpliData helps by offering automated data diagnostics that detect discrepancies, whether they stem from integration mismatches or format inconsistencies. This early detection prevents issues from snowballing into larger problems.

2. Standardize Data Formats

Data discrepancies often arise due to inconsistent formatting across systems. To address this:

• Ensure uniform data formats, such as standardizing date formats (MM/DD/YYYY) or employee ID lengths.
• Synchronize naming conventions and field structures between systems.

SimpliData's Blueprint Solutions automatically applies data formatting rules to ensure consistency across all platforms. With real-time data transformations, you’ll minimize manual errors and ensure seamless data flow between Workday and your other systems.

3. Leverage Data Validation Rules

Workday allows for custom data validation rules to ensure data accuracy. These rules can include:

• Mandatory fields for critical data points like employee numbers.
• Set limits or requirements on field formats, such as phone numbers and email addresses.

SimpliData integrates with Workday to automate data validations, flagging errors before they enter the system. This reduces the number of discrepancies at the point of entry and improves overall data integrity.

4. Perform Data Cleansing

Once discrepancies are identified, data cleansing is critical. This involves:

• Removing duplicate records.
• Correcting outdated or incorrect information.
• Filling in missing data fields.

SimpliData’s Data Cleansing Tools offer automated solutions for cleaning data across large datasets. Their intelligent system recognizes and corrects errors, allowing faster and more efficient cleanup efforts without manual intervention.

5. Reconcile Data Regularly

Schedule regular data reconciliations to ensure data remains accurate over time. Comparing Workday data with other systems, such as financial or HR platforms, is essential for consistency.

SimpliData offers automated reconciliation processes that cross-check Workday data against your external systems. By flagging real-time discrepancies, SimpliData helps prevent errors from propagating and affecting business processes.

6. Integrate Data Quality Monitoring

To maintain long-term data accuracy, invest in continuous data quality monitoring tools. These tools:

• Track data integrity in real time.
• Automatically alert teams when discrepancies are detected.

SimpliData’s Data Quality Monitoring Solution integrates seamlessly with Workday to offer real-time alerts, automated reports, and comprehensive dashboards. This proactive approach ensures you maintain high data quality without manual oversight, freeing up resources for other critical tasks.

7. Document and Communicate Changes

As discrepancies are resolved, document the changes and communicate them across teams. This ensures everyone follows updated procedures, and the same issues don’t resurface.

SimpliData’s collaboration features allow teams to share insights, track resolutions, and ensure alignment. This transparency helps promote best practices and prevents recurring discrepancies.