Parallel Run

Intro to Parallel Run?

A Parallel Run is a critical implementation strategy used when transitioning from an existing system to a new one, particularly in HR and payroll contexts. This approach involves running both systems simultaneously for a designated period to compare outputs, identify discrepancies, and ensure the new system functions correctly before fully decommissioning the legacy solution. As organizations increasingly modernize their HR technology stacks, understanding parallel run methodology becomes essential for ensuring smooth transitions that maintain data integrity and operational continuity.

Definition of Parallel Run

A Parallel Run is an implementation methodology where an organization operates both a new system and an existing (legacy) system simultaneously for a defined period, processing the same data inputs through both systems and comparing the outputs to validate the new system’s accuracy and functionality before fully transitioning.

This approach is typically employed during significant system migrations or upgrades, especially for business-critical functions like payroll, where errors can have serious financial and compliance implications. The parallel run period allows organizations to:

• Verify that the new system produces the same or expected results as the legacy system
• Identify and resolve discrepancies or configuration issues
• Train users on the new system while maintaining operational continuity
• Build confidence in the new solution before full cutover
• Establish a fallback option if significant issues are encountered

Parallel runs can vary in duration depending on the complexity of the system and organizational risk tolerance, ranging from a single processing cycle to multiple months of side-by-side operation. While this definition provides a general understanding of parallel runs, specific implementations may vary based on industry, system type, and organizational requirements.

Importance of Parallel Run in HR

Parallel runs are particularly important in HR technology implementations for several critical reasons:

Payroll Accuracy and Compliance: Payroll errors can have severe consequences, from employee dissatisfaction to regulatory penalties. Parallel runs help ensure the new system correctly calculates wages, taxes, deductions, and benefits before it becomes the system of record.

Data Integrity Validation: HR systems manage sensitive employee information that affects numerous downstream processes. Parallel runs verify that data has been correctly migrated, transformed, and processed in the new environment.

Confidence Building: Successful parallel runs build stakeholder confidence in the new system, reducing resistance to change and increasing adoption rates among HR staff and employees.

Risk Mitigation: By identifying and addressing issues before full implementation, parallel runs significantly reduce the risk of major disruptions to critical HR functions like benefits administration, time tracking, and employee records management.

Process Adaptation: Parallel runs allow HR teams to adapt their operational processes to the new system while still maintaining the security of established workflows, creating a smoother transition period.

Compliance Verification: HR systems must adhere to various labor laws and regulations. Parallel runs help verify that the new system properly implements compliance requirements across all jurisdictions where the organization operates.

Examples of Parallel Run

Here are practical examples of parallel runs in HR and payroll contexts:

Example 1: Payroll System Migration
A manufacturing company with 2,000 employees is transitioning from a legacy on-premises payroll system to a modern cloud-based solution. The company implements a three-month parallel run strategy where payroll administrators process each bi-weekly payroll in both systems. Each cycle involves entering time data, processing payroll calculations, and generating reports from both systems. The payroll team then conducts a detailed reconciliation to identify any variances in gross-to-net calculations, tax withholdings, benefit deductions, and other components. In the first cycle, they discover that the new system calculates overtime differently for certain job classifications, allowing them to correct the configuration before affecting actual employee payments. By the end of the three-month period, all discrepancies have been resolved, giving management confidence to proceed with the full transition.

Example 2: Benefits Administration Platform
A healthcare organization implements a new benefits administration system during its annual open enrollment period. They conduct a parallel run by having employees make their benefit selections in both the legacy and new systems. The HR team then compares enrollment data, premium calculations, and eligibility determinations between both systems. This parallel process reveals several discrepancies in how the new system handles domestic partner coverage and age-based premium adjustments. The implementation team addresses these issues before finalizing elections in the new system, ensuring employees receive the correct coverage and deductions when the new plan year begins.

Example 3: Time and Attendance System
A retail company with multiple locations is replacing its time and attendance tracking system. They implement a phased parallel run approach, starting with headquarters staff and gradually adding store locations. For each location, employees clock in/out using both the old badge system and the new mobile app for two pay periods. The HR team compares the recorded hours, break times, and calculated work durations between systems to identify discrepancies. This approach reveals configuration issues with different shift premiums and scheduling rules at various locations. By addressing these issues incrementally, the company avoids widespread problems and builds expertise in troubleshooting the new system before completing the full rollout to all 50 store locations.

How HRMS platforms like Asanify support Parallel Run

Modern HRMS platforms like Asanify offer several features to facilitate effective parallel runs during implementation:

Data Import/Export Capabilities: Advanced HRMS systems provide robust data exchange functionality, allowing organizations to easily move information between legacy and new systems during parallel runs for comparison and validation.

Comparison Reporting: Comprehensive platforms include reporting tools that can highlight discrepancies between legacy and new system outputs, making it easier to identify and troubleshoot differences during parallel processing.

Expense Management Software Integration: Leading HRMS solutions ensure that expense tracking and reimbursement processes remain consistent during transition periods, maintaining seamless operations while validating new system functionality.

Configurable Calculation Rules: Flexible HRMS platforms allow administrators to adjust calculation rules and business logic during the parallel run period to match legacy system outputs when discrepancies are identified.

Audit Trails: Robust tracking of all system changes during the parallel run period helps document configuration adjustments and provides a historical record for compliance purposes.

User Access Controls: Sophisticated HRMS systems offer granular access permissions that can be adjusted during parallel runs to control which users can view and modify data in the new system while maintaining operational stability.

Test Environments: Leading platforms provide separate test and production environments, allowing organizations to practice and refine their parallel run processes before executing them with live data.

FAQs about Parallel Run

How long should a parallel run last?

The duration of a parallel run depends on several factors including system complexity, processing cycles, risk tolerance, and available resources. For payroll systems, organizations typically conduct parallel runs for 2-3 complete processing cycles (e.g., 2-3 months for monthly payroll). More complex implementations or those with seasonal variations may require longer periods to validate all scenarios. For less critical HR functions, shorter parallel runs might be sufficient. The key is to ensure you’ve tested all relevant business scenarios and processing variations before ending the parallel period. It’s better to extend a parallel run than to discover major issues after full cutover.

What are the common challenges encountered during a parallel run?

Common challenges include: resource constraints, as staff must operate both systems simultaneously; data synchronization issues when maintaining consistent inputs across systems; reconciliation complexity when identifying the root causes of output discrepancies; timing differences in how systems process certain transactions; reporting format variations that complicate direct comparisons; resistance from users who must double their workload during the parallel period; and deciding which discrepancies are acceptable versus those requiring resolution before cutover. Organizations can address these challenges through careful planning, clear acceptance criteria, automation where possible, and adequate staff support during the parallel period.

How do you effectively analyze and reconcile differences identified during a parallel run?

Effective reconciliation requires a structured approach: first, establish materiality thresholds to determine which variances warrant investigation; second, categorize discrepancies by type (e.g., calculation differences, data mapping issues, timing differences); third, trace each significant variance to its root cause through systematic analysis; fourth, document whether differences represent errors in the new system or intentional improvements over legacy functionality; fifth, develop and implement resolution plans for true errors; and finally, maintain a comprehensive log of all identified differences and their dispositions. Clear documentation is essential, both for resolving current issues and for future reference if questions arise after full implementation.

Should all discrepancies be resolved before ending a parallel run?

Not necessarily. While critical discrepancies affecting accuracy, compliance, or core functionality must be resolved before ending the parallel run, some differences may be acceptable or even expected. Expected differences might include intentional improvements in calculation methodology, enhanced precision in the new system, or differences in reporting formats. The key is to document all discrepancies, understand their causes and impacts, and make deliberate decisions about which require resolution. Each organization should establish clear acceptance criteria at the beginning of the parallel run process, defining the types and magnitudes of acceptable variances for different data elements and processes.

How can organizations optimize resources during a parallel run period?

To optimize resources during parallel runs, organizations should: automate data entry whenever possible to avoid duplicate manual work; prioritize reconciliation efforts based on risk and materiality; implement phased approaches focusing first on core functions before expanding to peripheral processes; cross-train team members to distribute workload and build system knowledge; leverage system integrators or consultants for specialized expertise; temporarily adjust operational schedules to accommodate the additional workload; use workflow tools to track reconciliation activities and avoid duplication of effort; and clearly communicate timeframes and expectations to all stakeholders. Additionally, outsourcing work to USA or other regions can help distribute the workload during intensive parallel run periods.