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Learn how to plan and execute parallel runs to validate new ERP systems against legacy data, ensuring data integrity, process accuracy, and operational continuity before cutover.
A parallel run is a critical validation phase in ERP migration where the new system operates simultaneously with the legacy system for a defined period. This approach allows organizations to compare outputs, reconcile data, and verify business processes without interrupting daily operations. The primary goal is to ensure that the new ERP system produces accurate, consistent, and reliable results that match or exceed the legacy system's performance. By validating the new system against legacy data, organizations can identify discrepancies, data mapping errors, and process gaps before cutover. This reduces the risk of data loss, financial inaccuracies, and operational disruptions. The main risks to control during this phase include data integrity issues, process misalignment, user adoption challenges, and integration failures. A well-planned parallel run provides a safety net, allowing teams to refine configurations, fix defects, and build confidence in the new system before decommissioning the legacy platform.
Before initiating a parallel run, it is essential to define a clear scope and set measurable objectives. This involves identifying which business processes, data sets, and modules will be included in the validation. Not all processes may need to be run in parallel; focusing on high-risk, high-volume, or financially critical processes can optimize resources. Objectives should include specific criteria for success, such as data reconciliation accuracy thresholds, process completion times, and user acceptance rates. Responsible roles must be assigned, including data owners, process owners, IT leads, and business stakeholders. Dependencies, such as data cleansing completion, integration setup, and user training, must be mapped and addressed. A detailed plan should outline the duration of the parallel run, the frequency of reconciliation, and the escalation path for issues. This preparation ensures that the parallel run is focused, efficient, and aligned with business goals.
Selecting the right processes and data sets is crucial for a meaningful parallel run. Prioritize processes that are complex, high-volume, or have significant financial impact, such as order-to-cash, procure-to-pay, and financial closing. Data sets should include master data (customers, vendors, items) and transactional data (invoices, purchase orders, journal entries). Ensure that the data selected is representative of real-world scenarios, including edge cases and historical data. This helps in identifying potential issues that may not surface in controlled testing environments. Collaboration between IT and business teams is essential to ensure that the selected processes and data sets cover all critical business functions.
Defining clear success criteria is vital for evaluating the parallel run's effectiveness. These criteria should be measurable and agreed upon by all stakeholders. Examples include data reconciliation accuracy of 99.9%, process completion within defined timeframes, and zero critical defects. Financial reconciliation should match legacy system reports within a predefined tolerance. User acceptance should be measured through feedback and adoption metrics. These criteria serve as go/no-go indicators for cutover. If the new system fails to meet these criteria, the parallel run should be extended, and issues must be resolved before proceeding.
The technical execution of a parallel run requires a robust staging environment that mirrors the production setup. This environment should include the new ERP system, integrated applications, and data migration tools. Data from the legacy system must be migrated to the new system using validated mapping and transformation rules. Ensure that the data is cleansed and deduplicated before migration to avoid carrying over errors. Integration points, such as APIs and middleware, must be configured and tested to ensure seamless data flow. Security controls, including user roles and permissions, should be replicated to maintain compliance. Performance monitoring tools should be deployed to track system response times and resource usage. This setup ensures that the parallel run is conducted in a realistic and controlled environment.
Data migration is a critical component of the parallel run. Accurate data mapping ensures that legacy data is correctly transformed into the new system's structure. This involves defining field-level mappings, handling data type conversions, and managing referential integrity. Data cleansing should be performed to remove duplicates, correct errors, and standardize formats. Transformation rules must be documented and tested to ensure consistency. Audit trails should be maintained to track data changes and enable traceability. Regular data validation checks should be performed to ensure that migrated data matches the source data within defined tolerances.
Integrations between the new ERP system and other applications must be configured and tested during the parallel run. This includes APIs, middleware, and data exchange protocols. Ensure that authentication, data contracts, and error handling mechanisms are in place. Test integration scenarios, including normal flows, error conditions, and retries. Monitor integration logs to identify and resolve issues promptly. Configuration of the new ERP system, including workflows, approval processes, and reporting templates, should be aligned with business requirements. This ensures that the system operates as expected and supports business processes effectively.
Validation is the core of the parallel run, involving the reconciliation of data and processes between the legacy and new systems. Data reconciliation compares key data points, such as financial balances, inventory levels, and transaction counts, to ensure consistency. Process validation involves executing business processes in both systems and comparing outcomes. Discrepancies should be documented, analyzed, and resolved. Root cause analysis helps identify whether issues stem from data mapping, configuration, or process design. Regular reconciliation reports should be generated and reviewed by stakeholders. This iterative process ensures that the new system is accurate and reliable before cutover.
Financial reconciliation is a critical aspect of parallel run validation. It involves comparing financial reports, such as trial balances, income statements, and balance sheets, between the legacy and new systems. Discrepancies in financial data can have significant implications for compliance and decision-making. Reconciliation should be performed at regular intervals, such as daily or weekly, to identify and address issues promptly. Tolerance levels should be defined to account for minor differences due to timing or rounding. Any significant discrepancies must be investigated and resolved before cutover. This ensures that the new system provides accurate financial information.
Process validation involves executing business processes in both systems and comparing outcomes. This includes order processing, procurement, and financial closing. Performance validation measures system response times, throughput, and resource usage to ensure that the new system meets performance requirements. User acceptance testing (UAT) should be conducted to gather feedback from end-users and identify usability issues. Performance benchmarks should be established and monitored throughout the parallel run. This ensures that the new system can handle real-world workloads and supports business operations effectively.
Discrepancies and defects are inevitable during a parallel run. A structured approach to managing these issues is essential. Discrepancies should be logged in a defect tracking system, categorized by severity, and assigned to responsible teams. Root cause analysis should be performed to identify the underlying issues. Fixes should be implemented, tested, and verified. Regression testing should be conducted to ensure that fixes do not introduce new issues. Regular status updates should be provided to stakeholders. This proactive approach ensures that issues are resolved efficiently and does not delay the cutover.
Defect triage involves prioritizing issues based on their impact on business operations and data integrity. Critical defects, such as data loss or financial inaccuracies, should be resolved immediately. High-priority defects, such as process delays or reporting errors, should be addressed before cutover. Low-priority defects can be scheduled for post-go-live resolution. A clear escalation path should be defined for unresolved issues. Regular defect review meetings should be held to track progress and make decisions. This ensures that resources are allocated effectively and issues are resolved in a timely manner.
Documentation is crucial for maintaining transparency and accountability during the parallel run. All discrepancies, defects, and resolutions should be documented in a central repository. Regular communication with stakeholders, including business users, IT teams, and management, is essential. Status reports should include progress, issues, and risks. This ensures that all parties are informed and can make informed decisions. Clear communication helps build confidence in the new system and supports user adoption.
Cutover is the transition from the legacy system to the new ERP system. It should be planned meticulously to minimize downtime and disruption. A detailed cutover plan should include tasks, responsibilities, timelines, and rollback procedures. Freeze windows should be established to prevent changes to the legacy system during the cutover period. Final data loads should be performed to ensure that the new system has the most up-to-date data. Go/no-go criteria should be defined and reviewed before cutover. Communication with users and stakeholders should be clear and timely. This ensures a smooth transition and minimizes risks.
A cutover runbook provides step-by-step instructions for the transition process. It should include tasks, owners, and timelines. A rollback plan should be defined in case the cutover fails. Rollback triggers should be established, such as critical defects or data integrity issues. The rollback plan should include steps to restore the legacy system and recover data. Regular testing of the rollback plan should be performed to ensure its effectiveness. This ensures that the organization can recover quickly in case of issues.
Effective communication is essential for a successful go-live. Users should be informed about the cutover schedule, expected downtime, and support channels. Training and support should be available during the go-live period. A dedicated support team should be on standby to address issues promptly. Regular updates should be provided to stakeholders. This ensures that users are prepared and supported during the transition.
Post-go-live support is crucial for stabilizing the new ERP system. A hypercare period should be established, during which the support team provides intensive assistance. Issues should be tracked and resolved promptly. Performance monitoring should continue to identify and address bottlenecks. User feedback should be collected and used to improve the system. Regular reviews should be conducted to assess the system's performance and user adoption. This ensures that the new system operates smoothly and meets business needs.
Hypercare is a period of intensive support following go-live. It involves monitoring the system, resolving issues, and providing user support. A dedicated team should be assigned to handle issues during this period. Issues should be logged, prioritized, and resolved quickly. Regular status updates should be provided to stakeholders. This ensures that the system is stable and users are supported during the transition.
Continuous improvement is essential for maximizing the value of the new ERP system. User feedback should be collected and analyzed to identify areas for improvement. Performance tuning should be performed to optimize system efficiency. Process improvements should be implemented based on user feedback and business needs. Regular reviews should be conducted to assess the system's performance and user adoption. This ensures that the system evolves to meet changing business requirements.
Common questions on this topic. Talk to our team for anything specific to your business.
The duration of a parallel run depends on the complexity of the migration and the number of processes involved. Typically, it lasts from one to three months. It should be long enough to cover at least one full business cycle, including month-end or year-end closing, to ensure comprehensive validation.
Key data sets should be validated, including master data (customers, vendors, items) and transactional data (invoices, purchase orders, journal entries). Financial data, such as trial balances and income statements, should be reconciled to ensure accuracy.
Financial reconciliation involves comparing financial reports, such as trial balances and income statements, between the legacy and new systems. Discrepancies should be investigated and resolved. Tolerance levels should be defined to account for minor differences.
Skipping a parallel run increases the risk of data loss, financial inaccuracies, and operational disruptions. It may also lead to user resistance and low adoption rates. A parallel run provides a safety net to identify and resolve issues before cutover.
Discrepancies should be logged, analyzed, and resolved. Root cause analysis helps identify the underlying issues. Fixes should be implemented, tested, and verified. Regular status updates should be provided to stakeholders.
Even for small ERP upgrades, a parallel run is recommended to validate data integrity and process accuracy. It helps identify issues that may not surface in controlled testing environments and builds confidence in the new system.
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