Connected business operations. Flexible deployment.
Discover why parallel running is critical for ERP migration success. Learn how to validate data integrity, process accuracy, and system stability before cutover to minimize risk and ensure operational continuity.
Parallel running is the process of operating the legacy ERP system and the new target ERP system simultaneously for a defined period to validate data integrity, process accuracy, and system stability before cutover. This phase is not merely a testing step; it is the primary risk mitigation strategy that ensures the new system can handle real-world business operations without disrupting critical workflows. The main risks to control during this phase include data loss, financial reporting discrepancies, broken integrations, and performance regressions that may not surface in isolated unit or integration tests. By comparing outputs from both systems against the same input data, organizations can identify gaps in configuration, custom code, or data mapping. This validation step provides the confidence needed to proceed with cutover, ensuring that the migration does not compromise operational continuity or financial accuracy. Without parallel running, organizations face significant exposure to undetected errors that can lead to costly post-go-live fixes, regulatory non-compliance, and loss of stakeholder trust.
Before initiating parallel running, it is essential to define a clear scope that aligns with the migration's critical business processes. Not every module or transaction type requires the same level of validation. The scope should focus on high-volume, high-risk processes such as order-to-cash, procure-to-pay, and financial closing. Objectives should be measurable, such as achieving 99.9% data reconciliation accuracy or zero critical defects in core workflows. Defining the scope also involves selecting the appropriate data set for comparison. Using representative production data, rather than synthetic test data, is crucial for identifying real-world issues. The duration of the parallel run should be sufficient to cover at least one full business cycle, including month-end or quarter-end closing processes if applicable. This ensures that time-dependent processes and batch jobs are validated under realistic conditions.
Identify the top five to ten business processes that have the highest impact on revenue, compliance, or operational efficiency. These processes should be the primary focus of the parallel run. For example, in a manufacturing environment, production planning and inventory management might be critical, while in a service business, project billing and resource allocation might take precedence. Document the expected outcomes for each process in both the legacy and new systems. This documentation serves as the baseline for comparison. It is also important to involve key business stakeholders in this selection process to ensure that the chosen processes reflect actual business priorities and pain points.
Define clear, quantitative success criteria for the parallel run. These criteria should include data accuracy thresholds, performance benchmarks, and defect severity limits. For instance, a success criterion might be that all financial reports match within a 0.1% variance, or that system response times do not exceed 2 seconds for critical transactions. Defect severity should be categorized into critical, major, and minor, with clear definitions for each. Critical defects, such as data loss or system crashes, must be resolved before cutover. Major defects, such as minor reporting discrepancies, should be resolved or have a documented workaround. Minor defects can be deferred to post-go-live if they do not impact core operations. These criteria should be agreed upon by all stakeholders, including IT, finance, and operations, to ensure alignment on what constitutes a successful migration.
A robust parallel run requires a well-prepared environment that mirrors production conditions as closely as possible. This includes setting up a staging environment for the new ERP system that is identical to the production configuration in terms of hardware, software, and network settings. The legacy system should remain in production, while the new system operates in a parallel mode, receiving the same data inputs. Data synchronization is a critical component of this preparation. Mechanisms must be in place to ensure that data entered in the legacy system is accurately replicated to the new system for comparison. This may involve real-time data feeds, batch transfers, or manual data entry, depending on the complexity of the integration. It is also important to ensure that both systems are running on the same time zone and date settings to avoid discrepancies in time-stamped data.
Data synchronization between the legacy and new systems is the backbone of parallel running. The method of synchronization should be chosen based on the volume and frequency of data transactions. For high-volume, real-time transactions, an API-based integration may be necessary to ensure immediate data availability in the new system. For lower-volume, batch-oriented processes, scheduled data transfers may be sufficient. The synchronization process must be monitored closely to detect any data loss or corruption during transfer. Logging and error handling mechanisms should be in place to capture and report any synchronization issues. Additionally, data mapping rules must be validated to ensure that fields in the legacy system are correctly mapped to the corresponding fields in the new system. Any discrepancies in data mapping should be resolved before the parallel run begins.
Comprehensive monitoring and logging are essential for tracking the performance and accuracy of both systems during the parallel run. Monitoring tools should be configured to capture key performance indicators (KPIs) such as transaction processing times, error rates, and system uptime. Logging should capture all data transactions, user actions, and system events in both the legacy and new systems. This data will be used for reconciliation and analysis. It is also important to set up alerts for any anomalies or deviations from expected behavior. For example, an alert should be triggered if the error rate in the new system exceeds a predefined threshold. This proactive monitoring allows the team to identify and address issues in real-time, minimizing the impact on the parallel run.
Once the environment is prepared, the parallel run can begin. During this phase, business users continue to operate in the legacy system, while the new system processes the same transactions in the background. The primary task is to reconcile the outputs of both systems. This involves comparing financial reports, inventory levels, customer balances, and other key data points. Reconciliation should be performed at regular intervals, such as daily or weekly, depending on the volume of transactions. Any discrepancies identified during reconciliation must be investigated and resolved. The root cause of each discrepancy should be documented, and corrective actions should be implemented. This iterative process of reconciliation and correction continues until the success criteria are met.
Financial reconciliation is a critical component of parallel running, as it ensures that the new system produces accurate financial reports. This involves comparing general ledger balances, trial balances, and financial statements from both systems. Any variances must be investigated to determine whether they are due to data mapping errors, configuration issues, or process differences. It is important to involve the finance team in this process, as they have the expertise to identify and resolve financial discrepancies. Financial reconciliation should be performed at the end of each accounting period to ensure that the new system can handle month-end closing processes accurately. This step is crucial for maintaining regulatory compliance and ensuring that financial reports are reliable.
In addition to financial data, operational data such as inventory levels, order statuses, and production schedules must be reconciled. This ensures that the new system can accurately track and manage operational processes. Discrepancies in operational data can lead to stockouts, delayed orders, or production bottlenecks. The operations team should be involved in analyzing these discrepancies and implementing corrective actions. It is also important to validate that the new system can handle peak loads and high-volume transactions without performance degradation. This can be done by simulating peak load scenarios during the parallel run and monitoring system performance.
Discrepancies and defects are inevitable during parallel running. The key is to manage them effectively to ensure that they do not compromise the migration timeline. A defect management process should be established to track, prioritize, and resolve issues. Each defect should be assigned a severity level, a responsible owner, and a target resolution date. Critical defects must be resolved before cutover, while major and minor defects can be deferred if they do not impact core operations. Regular defect review meetings should be held to discuss the status of open defects and agree on resolution strategies. It is also important to document all defects and their resolutions to provide an audit trail and to inform future migration projects.
Defect prioritization should be based on the impact of the defect on business operations and the risk of proceeding with cutover. Critical defects, such as data loss or system crashes, should be resolved immediately. Major defects, such as minor reporting discrepancies, should be resolved within a defined timeframe. Minor defects, such as cosmetic issues, can be deferred to post-go-live. The prioritization process should involve input from all stakeholders, including IT, finance, and operations, to ensure that the most critical issues are addressed first. It is also important to consider the effort required to resolve each defect and the availability of resources. This helps in creating a realistic resolution plan that aligns with the migration timeline.
Documenting the root cause of each defect is essential for preventing similar issues in the future. The root cause analysis should identify whether the defect was due to a data mapping error, a configuration issue, a custom code bug, or a process difference. Corrective actions should be implemented to address the root cause, and the fix should be validated in the staging environment before being deployed to the production environment. This documentation also serves as a knowledge base for the project team and can be used to inform future migration projects. It is important to ensure that all documentation is accurate, up-to-date, and accessible to all stakeholders.
Parallel running is also an opportunity to validate integrations and customizations in the new system. Integrations with third-party systems, such as CRM, e-commerce, and supply chain management, must be tested to ensure that data flows correctly between systems. Customizations, such as custom reports, workflows, and user interfaces, must be validated to ensure that they function as expected in the new system. Any issues with integrations or customizations must be identified and resolved before cutover. This is particularly important for organizations with complex integration landscapes or extensive customizations, as these areas are often the source of migration failures.
Third-party integrations should be tested end-to-end to ensure that data is transmitted accurately and in a timely manner. This involves validating data formats, authentication mechanisms, and error handling. Any discrepancies in data transmission must be investigated and resolved. It is also important to test the resilience of integrations by simulating failure scenarios, such as network outages or system downtime. This ensures that the integrations can handle unexpected events without causing data loss or system failures. The integration team should be involved in this testing process to ensure that all technical aspects are covered.
Custom code and reports must be validated to ensure that they function correctly in the new system. This involves testing custom workflows, user interfaces, and reports to ensure that they produce accurate results. Any issues with custom code must be identified and resolved before cutover. It is also important to validate that custom reports are generated accurately and in a timely manner. The development team should be involved in this validation process to ensure that all technical aspects are covered. This step is crucial for ensuring that the new system meets the specific needs of the organization.
Performance and scalability are critical considerations during parallel running. The new system must be able to handle the same volume of transactions as the legacy system without performance degradation. This involves monitoring system response times, throughput, and resource utilization. Any performance issues must be identified and resolved before cutover. It is also important to test the scalability of the new system by simulating increased load scenarios. This ensures that the system can handle future growth without requiring significant infrastructure upgrades. The IT team should be involved in this assessment to ensure that all technical aspects are covered.
System response times should be monitored closely during the parallel run to ensure that the new system meets performance benchmarks. Any delays in response times must be investigated to determine whether they are due to system configuration, network issues, or data volume. Corrective actions should be implemented to address any performance issues. It is also important to monitor resource utilization, such as CPU, memory, and disk I/O, to ensure that the system is not under excessive load. This helps in identifying potential bottlenecks and optimizing system performance.
Simulating peak load scenarios is essential for validating the scalability of the new system. This involves generating a high volume of transactions to test the system's ability to handle peak loads. The results of these simulations should be compared to the performance of the legacy system to ensure that the new system can handle the same load without degradation. Any performance issues identified during these simulations must be resolved before cutover. This step is crucial for ensuring that the new system can support the organization's growth and operational demands.
Once the parallel run is complete and all success criteria are met, the organization can proceed with cutover. Cutover is the process of switching from the legacy system to the new system. This involves finalizing data migration, configuring the new system for production use, and training users. A detailed cutover plan should be developed, including a timeline, responsibilities, and rollback procedures. The cutover plan should be reviewed and approved by all stakeholders before execution. It is also important to communicate the cutover plan to all users to ensure that they are prepared for the transition.
Finalizing data migration is a critical step in the cutover process. This involves transferring all remaining data from the legacy system to the new system. Data migration should be performed in a controlled manner, with validation checks at each step to ensure data integrity. Any discrepancies identified during data migration must be resolved before cutover. It is also important to perform a final reconciliation of data between the legacy and new systems to ensure that all data has been migrated accurately. This step is crucial for ensuring that the new system has a complete and accurate data set.
Executing the cutover plan requires careful coordination and communication. The cutover should be performed during a planned downtime window to minimize the impact on business operations. All stakeholders should be informed of the cutover schedule and any potential disruptions. The cutover team should follow the cutover plan step-by-step, with checkpoints to ensure that each step is completed successfully. Any issues encountered during cutover must be addressed immediately, and the rollback procedure should be initiated if necessary. This step is crucial for ensuring a smooth transition to the new system.
Post-go-live stabilization is the final phase of the ERP migration. This involves monitoring the new system for any issues, providing user support, and making necessary adjustments. A hypercare period should be established, during which the project team provides intensive support to users and addresses any issues that arise. This period typically lasts for two to four weeks, depending on the complexity of the migration. During this time, the team should monitor system performance, user feedback, and error rates to ensure that the new system is stable and reliable. Any issues identified during the hypercare period must be resolved promptly to maintain user confidence and operational continuity.
Providing user support is essential for ensuring a successful transition to the new system. This involves helping users resolve any issues they encounter, providing training and guidance, and addressing any concerns. The support team should be available during the hypercare period to provide real-time assistance. It is also important to collect user feedback to identify any areas for improvement. This feedback can be used to make necessary adjustments to the new system and to inform future migration projects. User support is crucial for ensuring that users are comfortable and confident in using the new system.
Monitoring system stability is essential for ensuring that the new system is reliable and performant. This involves tracking key performance indicators (KPIs) such as system uptime, error rates, and user satisfaction. Any anomalies or deviations from expected behavior must be investigated and resolved. The monitoring process should continue beyond the hypercare period to ensure that the system remains stable over time. This step is crucial for maintaining operational continuity and ensuring that the new system meets the organization's long-term needs.
Common questions on this topic. Talk to our team for anything specific to your business.
The duration of parallel running depends on the complexity of the migration and the volume of transactions. Typically, it should last for at least one full business cycle, including month-end or quarter-end closing processes. For complex migrations, it may last several weeks to ensure that all issues are identified and resolved.
Key data points such as financial reports, inventory levels, customer balances, and order statuses should be compared. The focus should be on high-volume, high-risk processes that have the greatest impact on business operations.
Yes, parallel running can be partially automated using data synchronization tools and reconciliation scripts. However, manual validation is still necessary to interpret discrepancies and make informed decisions.
Skipping parallel running increases the risk of data loss, financial reporting discrepancies, broken integrations, and performance regressions. These issues can lead to costly post-go-live fixes and operational disruptions.
Discrepancies should be investigated to determine the root cause, and corrective actions should be implemented. Critical discrepancies must be resolved before cutover, while minor discrepancies can be deferred if they do not impact core operations.
Yes, even for minor upgrades, parallel running is recommended to validate that the new version functions correctly and that data integrity is maintained. The scope and duration may be shorter, but the process is still essential for risk mitigation.
Discover how manufacturing ERP systems enhance procurement accuracy and material availability through integrated BOMs, MRP logic, and robust data governance.
Discover how to manage complex data mapping in multi-entity ERP migrations. Learn strategies for handling legal entities, currency conversions, and data integrity to ensure a successful cutover.
Discover how construction ERP transformation eliminates duplicate data entry by connecting field operations with financial systems. Learn the architecture, integration strategies, and business outcomes for reducing manual work and improving project visibility.
Discuss your workflows, modules and deployment options with our team.
Back to resources