Connected business operations. Flexible deployment.
Parallel running is a critical validation strategy in ERP migrations. This guide explains how to execute dual-system operations to verify data integrity, process accuracy, and system stability before cutover.
Parallel running is the most effective method for validating ERP migration accuracy because it allows the legacy and target systems to operate simultaneously, enabling direct comparison of outputs, data integrity, and process flows. This dual-system operation is critical for identifying discrepancies that static testing or unit tests often miss. The primary risks controlled by parallel running include silent data corruption, broken business logic, integration failures, and reporting inaccuracies that could compromise financial compliance or operational continuity. By executing real business transactions in both systems, organizations can verify that the new ERP behaves exactly as expected under production-like conditions. This approach provides measurable evidence that the migration is ready for cutover, reducing the likelihood of costly post-go-live failures. It is not merely a testing phase but a strategic validation step that protects business data and ensures operational stability.
Successful parallel running begins with rigorous preparation. The first step is defining the scope of the parallel run. Determine which business units, processes, and data sets will be included. Typically, this includes core financial processes, inventory management, and customer order processing. The next step is establishing a representative staging environment. This environment must mirror the production infrastructure in terms of hardware, software versions, and network configuration. Any deviation can lead to false positives or negatives in validation results. Data preparation is equally critical. The target system must be loaded with a complete and accurate copy of the legacy data. This includes master data, transactional data, and historical records. Data cleansing and mapping must be completed before the parallel run begins to ensure that discrepancies are due to system behavior rather than data quality issues.
Before initiating the parallel run, define clear success criteria. These should include specific metrics for data accuracy, process completion rates, and performance benchmarks. For example, financial reports must match within a defined tolerance, such as 0.1%. Process completion rates should be 100% for critical workflows. Performance benchmarks should ensure that the new system can handle peak loads without degradation. These criteria serve as the go/no-go decision points for cutover. They must be agreed upon by all stakeholders, including IT, finance, and operations. Documenting these criteria ensures that the validation process is objective and defensible.
The execution phase involves running both the legacy and target systems in parallel for a defined period. This period should be long enough to cover a full business cycle, such as a month-end close or a complete order-to-cash cycle. During this time, all transactions are entered into both systems. Users must be trained to perform their tasks in both systems, ensuring that the same data is entered in both. This requires careful coordination to avoid data entry errors. The target system should be configured to capture all logs and audit trails. These logs are essential for troubleshooting discrepancies. Integration points must be monitored closely. Any failures in data exchange between the ERP and external systems must be logged and analyzed. The parallel run should be conducted in a controlled environment where changes to the production system are frozen. This ensures that the comparison is valid and that any issues are isolated to the migration process.
Real-time monitoring is essential during the parallel run. Automated tools should be used to compare data between the two systems. These tools should flag discrepancies in real time, allowing for immediate investigation. Discrepancies should be categorized by severity. Critical discrepancies, such as financial mismatches or failed integrations, must be resolved before the parallel run can be considered successful. Minor discrepancies, such as formatting differences, can be documented and addressed post-cutover if they do not impact business operations. A dedicated team should be assigned to monitor the parallel run and manage the discrepancy log. This team should include representatives from IT, finance, and operations to ensure that all perspectives are considered.
Data reconciliation is the core of parallel running validation. It involves comparing data between the legacy and target systems to ensure accuracy and completeness. This includes master data, such as customer and vendor records, and transactional data, such as invoices and purchase orders. Reconciliation should be performed at multiple levels. At the record level, each record in the legacy system should have a corresponding record in the target system with matching values. At the aggregate level, totals and subtotals should match. For example, the total accounts receivable in the legacy system should match the total in the target system. Reconciliation reports should be generated daily during the parallel run. These reports should highlight any discrepancies and provide details for investigation. The reconciliation process should be documented to ensure auditability and traceability.
| Validation Area | Key Metrics | Acceptance Criteria | Responsible Role |
|---|---|---|---|
| Financial Data | General Ledger Balance, Accounts Receivable, Accounts Payable | 100% Match or within 0.1% tolerance | Finance Controller |
| Inventory Data | Stock Levels, Valuation, Movement History | 100% Match in quantity and value | Operations Manager |
| Customer Data | Customer Records, Order History, Credit Limits | 100% Match in key fields | Sales Director |
| Integration Points | API Success Rate, Data Latency, Error Logs | 99.9% Success Rate, No Critical Errors | IT Director |
Discrepancies found during the parallel run must be managed systematically. Each discrepancy should be logged in a defect tracking system. The log should include details such as the date, time, user, transaction ID, and description of the issue. Discrepancies should be triaged based on severity and impact. Critical defects, such as those affecting financial reporting or system stability, must be resolved before cutover. High-severity defects, such as those affecting key business processes, should be resolved or have a documented workaround. Low-severity defects can be deferred to post-go-live if they do not impact critical operations. The defect resolution process should involve root cause analysis. This helps identify whether the issue is due to data mapping, system configuration, or custom code. Resolving the root cause prevents similar issues from recurring in the future.
Root cause analysis is essential for effective defect management. It involves investigating the underlying cause of a discrepancy. This may require reviewing data mapping rules, system configuration, or custom code. For example, if financial reports do not match, the root cause may be a difference in accounting rules between the legacy and target systems. Corrective actions should be implemented to resolve the root cause. These actions may include updating data mapping rules, adjusting system configuration, or modifying custom code. After corrective actions are implemented, the discrepancy should be re-tested to ensure that it is resolved. This iterative process ensures that all critical issues are addressed before cutover.
Parallel running is not just about data validation; it is also about validating business processes. Users must perform their daily tasks in both systems to ensure that the new ERP supports their workflows. This includes order processing, inventory management, and financial reporting. User acceptance testing (UAT) should be conducted during the parallel run. Users should provide feedback on the usability and functionality of the new system. Any issues with user experience should be documented and addressed. This ensures that the new system is not only technically accurate but also user-friendly. User adoption is a critical factor in the success of an ERP migration. Parallel running provides an opportunity to identify and address adoption barriers before cutover.
Performance and stability are critical aspects of ERP migration validation. The new system must be able to handle the same load as the legacy system without degradation. Performance testing should be conducted during the parallel run. This includes load testing, stress testing, and endurance testing. Load testing ensures that the system can handle normal transaction volumes. Stress testing ensures that the system can handle peak loads. Endurance testing ensures that the system remains stable over extended periods. Performance metrics, such as response time, throughput, and resource utilization, should be monitored and compared to the legacy system. Any performance regressions must be investigated and resolved. This ensures that the new system can support business operations without disruption.
The parallel run culminates in a cutover decision. This decision is based on the validation results and the resolution of critical defects. Go/no-go criteria should be defined in advance. These criteria should include data accuracy, process completion, performance benchmarks, and user acceptance. If all criteria are met, the cutover can proceed. If any critical criteria are not met, the cutover should be delayed. The go/no-go decision should be made by a cross-functional team, including IT, finance, and operations. This ensures that all perspectives are considered. The decision should be documented and communicated to all stakeholders. A clear communication plan is essential to manage expectations and ensure a smooth transition.
| Go/No-Go Criterion | Threshold | Status | Action Required |
|---|---|---|---|
| Financial Data Accuracy | 100% Match | Met | None |
| Critical Defects Resolved | 0 Open Critical Defects | Met | None |
| Performance Benchmarks | Within 10% of Legacy | Met | None |
| User Acceptance | 95% Positive Feedback | Not Met | Additional Training Required |
After the parallel run, the focus shifts to stabilization and support. The new system should be monitored closely during the initial post-go-live period. This includes monitoring system performance, data integrity, and user activity. Any issues that arise should be addressed promptly. A dedicated support team should be available to assist users and resolve issues. This team should include representatives from IT, finance, and operations. The support team should have access to the defect tracking system and the ability to escalate issues as needed. Post-go-live support is essential for ensuring a smooth transition and addressing any residual issues. It also provides an opportunity to gather feedback and make continuous improvements.
Parallel running is a key risk mitigation strategy. It allows organizations to identify and address issues before cutover, reducing the risk of post-go-live failures. However, a rollback strategy should still be in place. A rollback plan should define the conditions under which the organization will revert to the legacy system. These conditions should include critical system failures, data corruption, or significant business disruption. The rollback plan should be tested during the parallel run to ensure that it is feasible. This includes testing the process for restoring data from backups and reconfiguring the legacy system. A well-defined rollback strategy provides a safety net and ensures that the organization can recover from unexpected issues.
Parallel running is an indispensable component of ERP migration validation. It provides a comprehensive assessment of data accuracy, process integrity, and system stability. By executing real business transactions in both systems, organizations can identify and address issues before cutover, reducing the risk of post-go-live failures. The process requires careful planning, execution, and monitoring. It involves data reconciliation, business process validation, performance testing, and defect management. The go/no-go decision is based on predefined criteria, ensuring that the cutover is only proceeded with when the new system is ready. Post-go-live support and a rollback strategy provide additional layers of protection. Parallel running is not just a technical exercise; it is a strategic validation step that protects business data, ensures operational continuity, and supports long-term ERP success.
Common questions on this topic. Talk to our team for anything specific to your business.
Parallel running is a validation strategy where the legacy and new ERP systems operate simultaneously. Transactions are processed in both systems to compare outputs and verify data accuracy and process integrity before cutover.
The duration depends on the complexity of the business processes. Typically, it should cover at least one full business cycle, such as a month-end close or a complete order-to-cash cycle, to ensure comprehensive validation.
All critical data should be reconciled, including master data (customers, vendors, items) and transactional data (invoices, purchase orders, general ledger entries). Financial reports and inventory levels are particularly important.
Yes, data reconciliation and comparison can be automated using specialized tools. However, business process validation and user acceptance testing require manual involvement to ensure that workflows are correctly supported.
Skipping parallel running increases the risk of undetected data errors, broken business processes, and integration failures. This can lead to financial discrepancies, operational disruptions, and costly post-go-live fixes.
Discrepancies should be logged, triaged by severity, and investigated for root cause. Critical discrepancies must be resolved before cutover. Corrective actions should be implemented and re-tested to ensure resolution.
Learn how to design, test, and execute a reliable rollback strategy for ERP migrations. This guide covers data preservation, cutover triggers, and risk mitigation to ensure business continuity.
Learn how to structure a distribution ERP for multi-entity operations. This guide covers inventory visibility, order allocation, master data governance, and integration strategies to eliminate silos and improve operational control.
Discover how professional services firms can leverage ERP transformation to standardize project operations, improve financial visibility, and achieve sustainable scalability without excessive customization.
Discuss your workflows, modules and deployment options with our team.
Back to resources