Connected business operations. Flexible deployment.
Learn how parallel running validates data integrity, process accuracy, and system stability before cutover. This guide covers planning, execution, reconciliation, and risk mitigation for safe ERP migrations.
Parallel running is the practice of operating the legacy ERP system and the new target ERP system simultaneously for a defined period to validate data accuracy, process functionality, and integration stability. This approach is critical for reducing migration risk because it allows organizations to identify discrepancies in financial reporting, operational workflows, and data integrity before committing to a full cutover. By maintaining business continuity in the legacy system while testing the new system with real-world data, organizations can mitigate the risk of data loss, operational downtime, and broken customizations. The primary risks controlled through parallel running include reporting discrepancies, integration failures, and user adoption challenges. This method ensures that the new system can handle production volumes and complex business logic without disrupting core operations.
Effective parallel running requires meticulous planning to ensure that the comparison between the legacy and new systems is meaningful. The first step is defining the scope of the parallel run, which should include all critical business processes such as order-to-cash, procure-to-pay, and record-to-report. It is essential to identify the specific data sets that will be migrated and tested, including master data, transactional data, and historical records. The duration of the parallel run should be sufficient to cover at least one full business cycle, such as a monthly or quarterly close, to validate recurring processes. Stakeholders from finance, operations, and IT must be involved in defining success criteria, which typically include zero critical data discrepancies and successful completion of key business transactions.
Success criteria must be measurable and agreed upon by all stakeholders before the parallel run begins. Key performance indicators (KPIs) should include data reconciliation accuracy, transaction processing time, and user error rates. For example, financial reports generated in both systems should match within a defined tolerance, such as 0.1% variance. Operational KPIs might include the time taken to process an order or the number of failed integration events. These KPIs provide objective evidence that the new system is ready for cutover. Without clear success criteria, the parallel run may fail to identify critical issues, leading to a risky cutover decision.
The technical execution of parallel running involves setting up a representative staging environment that mirrors the production environment. This includes configuring the new ERP system with the same hardware specifications, network topology, and security settings as the production environment. Data migration scripts must be tested and validated to ensure that data is transferred accurately and completely. Integration points, such as APIs and middleware, must be configured to allow data flow between the legacy and new systems without interfering with production operations. It is crucial to ensure that the staging environment is isolated from production to prevent any unintended changes to live data. Regular backups of the staging environment should be taken to allow for quick recovery in case of test failures.
Data migration during parallel running is a critical step that requires careful management. Initial data loads should be performed to populate the new system with master data and historical transactions. Subsequent incremental loads should be scheduled to keep the new system synchronized with the legacy system. Data mapping rules must be validated to ensure that fields are correctly transformed and mapped between the two systems. Deduplication and cleansing processes should be applied to ensure data quality. Reconciliation reports should be generated after each data load to identify and resolve discrepancies. This iterative process ensures that the new system contains accurate and up-to-date data, reducing the risk of data loss during cutover.
Validation and reconciliation are the core activities of parallel running. Financial reconciliation involves comparing trial balances, general ledgers, and financial statements between the legacy and new systems. Operational reconciliation includes verifying order statuses, inventory levels, and customer accounts. Discrepancies identified during reconciliation must be investigated and resolved before proceeding to the next phase. A discrepancy log should be maintained to track issues, their root causes, and resolution status. This log serves as a critical document for the go/no-go decision. Automated reconciliation tools can be used to speed up the process and reduce the risk of human error. However, manual verification is still necessary for complex transactions and edge cases.
User adoption is a significant factor in the success of parallel running. End-users must be trained on the new system and encouraged to use it for non-critical tasks during the parallel run. This helps identify usability issues and gaps in training materials. Feedback from users should be collected and analyzed to improve the system configuration and user experience. Change management initiatives should be implemented to address resistance to change and ensure that users are comfortable with the new system. Regular communication with stakeholders about the progress of the parallel run and any issues identified helps build confidence and support for the cutover decision. User acceptance testing (UAT) should be conducted during this phase to validate that the system meets business requirements.
Parallel running is an opportunity to test and refine the rollback plan. The rollback plan should outline the steps to revert to the legacy system if critical issues are identified during the parallel run or after cutover. This includes restoring data from backups, disabling integrations, and communicating with stakeholders. The rollback plan should be tested to ensure that it can be executed within the defined downtime window. Risk mitigation strategies should be documented for common issues such as data loss, integration failures, and performance degradation. Regular risk assessments should be conducted during the parallel run to identify new risks and update the mitigation plan. This proactive approach ensures that the organization is prepared to handle unexpected issues and maintain business continuity.
The cutover decision is based on the results of the parallel run and the achievement of predefined go/no-go criteria. These criteria should include the resolution of all critical discrepancies, successful completion of UAT, and validation of integration points. A formal go/no-go meeting should be held with key stakeholders to review the results and make the final decision. If the criteria are not met, the cutover should be delayed, and additional testing should be conducted. The decision should be documented and communicated to all stakeholders. A clear communication plan should be in place to inform users and customers about the cutover schedule and any potential impacts. This ensures that the organization is aligned and prepared for the transition to the new system.
Post-migration stabilization is the final phase of the ERP migration project. It involves monitoring the new system for performance issues, data discrepancies, and user errors. A hypercare period should be established where additional support is provided to users and IT teams. Incident management processes should be in place to quickly resolve any issues that arise. Regular reviews should be conducted to assess the stability of the system and identify areas for improvement. Lessons learned from the parallel run and cutover should be documented and shared with the organization to improve future migration projects. This phase ensures that the new system is stable and reliable, providing a solid foundation for long-term success.
| Phase | Key Activities | Responsible Roles | Success Criteria |
|---|---|---|---|
| Planning | Define scope, KPIs, and success criteria | Project Manager, Business Analysts | Agreed-upon KPIs and scope |
| Execution | Set up staging environment, migrate data | IT Team, Data Engineers | Accurate data load and system configuration |
| Validation | Reconcile data, test integrations | Finance, Operations, IT | Zero critical discrepancies |
| Cutover | Go/no-go decision, switch to new system | CIO, Project Manager | All go/no-go criteria met |
| Stabilization | Monitor system, provide hypercare support | IT Support, Business Users | System stability and user satisfaction |
Common pitfalls in parallel running include insufficient duration, lack of stakeholder involvement, and inadequate data reconciliation. To avoid these pitfalls, ensure that the parallel run covers a full business cycle and involves all relevant stakeholders. Use automated tools for data reconciliation but supplement with manual verification for complex transactions. Clearly define success criteria and track progress against them. Regular communication with stakeholders helps maintain alignment and address concerns early. By avoiding these common pitfalls, organizations can maximize the benefits of parallel running and reduce migration risk.
Parallel running is a critical component of a successful ERP migration. It provides a safe environment to validate data integrity, process accuracy, and system stability before cutover. By following a structured approach to planning, execution, validation, and stabilization, organizations can significantly reduce migration risk and ensure a smooth transition to the new system. The key to success lies in clear success criteria, thorough data reconciliation, and active stakeholder involvement. Parallel running not only mitigates risk but also builds confidence in the new system, paving the way for long-term success and operational efficiency.
Common questions on this topic. Talk to our team for anything specific to your business.
Parallel running is the process of operating the legacy and new ERP systems simultaneously to validate data accuracy, process functionality, and integration stability before cutover.
The duration should cover at least one full business cycle, such as a monthly or quarterly close, to validate recurring processes and ensure comprehensive testing.
Key data sets include financial reports, trial balances, general ledgers, order statuses, inventory levels, and customer accounts to ensure data integrity and accuracy.
No, parallel running should be conducted in a staging environment with a copy of production data to prevent any unintended changes to live operations.
Skipping parallel running increases the risk of data loss, operational downtime, broken customizations, and reporting discrepancies, leading to a risky cutover decision.
Discrepancies should be logged, investigated, and resolved before proceeding to the next phase. A discrepancy log tracks issues, root causes, and resolution status.
Discover why post-migration performance tuning is critical for ERP success. Learn practical strategies to optimize database queries, manage load, and ensure system stability after migration.
Discover how to prioritize retail ERP transformation to unify store operations, inventory, and financial reporting. Learn key architectural decisions, integration strategies, and governance models for scalable retail growth.
A practical guide for CIOs and IT leaders on managing vendor contracts, licensing models, and compliance risks during ERP migrations, upgrades, or replacements.
Discuss your workflows, modules and deployment options with our team.
Back to resources