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Learn how to design, execute, and validate parallel run periods to minimize risk, ensure data integrity, and guarantee operational continuity during complex ERP migrations or upgrades.
Planning parallel run periods for high-stakes ERP migrations requires a rigorous, phased approach that validates data integrity, process accuracy, and system performance before fully decommissioning the legacy system. The primary objective is to operate both the source and target ERP systems simultaneously for a defined period, allowing stakeholders to compare outputs, identify discrepancies, and confirm that the new system meets business requirements without disrupting daily operations. This strategy mitigates critical risks such as data loss, financial reporting errors, and operational downtime. Key risks to control include synchronization failures between systems, user confusion due to dual data entry, and performance degradation in the target environment. A successful parallel run is not merely a technical exercise but a business validation process that ensures the new ERP can handle real-world transaction volumes and complex business logic. By establishing clear go/no-go criteria, defining reconciliation protocols, and assigning specific ownership for data validation, organizations can reduce the uncertainty associated with major system transitions. This approach protects business continuity and provides a safety net for rollback if critical issues are discovered late in the migration cycle.
Before initiating the parallel run, it is essential to define the precise scope of operations that will be duplicated in both systems. Not all business processes may need to run in parallel; typically, core financial, inventory, and order management processes are prioritized. The objective is to verify that the target ERP produces identical or acceptable results compared to the legacy system for these critical functions. Stakeholders must agree on what constitutes a 'successful' parallel run. This includes defining acceptable variance thresholds for financial reports, inventory counts, and customer balances. For example, a variance of less than 0.1% in general ledger balances might be acceptable, while any discrepancy in customer credit limits must be zero. Clear objectives prevent scope creep and ensure that the parallel run remains focused on high-risk areas. Additionally, the scope should include the specific modules, entities, and integrations that will be tested. This includes third-party add-ons, custom reports, and external API connections. By narrowing the focus, the project team can allocate resources more effectively and avoid the complexity of validating every single transaction in the system.
Critical business processes are those that have a direct impact on revenue, compliance, or operational continuity. These typically include accounts payable, accounts receivable, inventory management, and order-to-cash cycles. The project team should map these processes in both the legacy and target systems to identify where data flows and where decisions are made. This mapping helps in designing the reconciliation checks. For instance, if the legacy system uses a specific rounding rule for currency conversion, the target system must be configured to match this rule, or the variance must be documented and accepted. Identifying these processes early allows for the creation of specific test cases that mimic real-world scenarios. It also helps in training users on how to handle discrepancies when they occur. The goal is to ensure that the target system can handle the complexity of the business without requiring significant workarounds that could introduce errors or inefficiencies.
Variance thresholds are the predefined limits within which differences between the legacy and target systems are considered acceptable. These thresholds must be agreed upon by finance, operations, and IT leaders before the parallel run begins. For financial data, variances in total balances, sub-ledger details, and tax calculations are common areas of concern. For operational data, variances in inventory quantities, order statuses, and shipping dates are critical. The thresholds should be based on the materiality of the data. For example, a small variance in a low-value inventory item might be acceptable, while any variance in high-value assets must be investigated. Documenting these thresholds ensures that the project team has a clear standard for success. It also provides a basis for decision-making when discrepancies are found. If a variance exceeds the threshold, it triggers an investigation to determine the root cause. This could be a data mapping error, a configuration issue, or a difference in business logic. By setting these thresholds early, the organization avoids subjective debates during the parallel run and maintains a data-driven approach to validation.
Data synchronization is the backbone of a successful parallel run. The goal is to ensure that both systems have the same data at any given point in time. This is achieved through initial data migration and subsequent delta synchronization. The initial migration loads the historical data from the legacy system to the target system. After the parallel run begins, new transactions are entered in both systems, or data is synchronized from the legacy system to the target system to keep them aligned. The choice of synchronization method depends on the complexity of the data and the frequency of transactions. For high-volume transactions, real-time or near-real-time synchronization may be required. For lower-volume data, batch synchronization at the end of each day might be sufficient. Reconciliation is the process of comparing the data in both systems to identify discrepancies. This should be automated wherever possible. Automated reconciliation tools can compare key fields such as transaction IDs, amounts, dates, and statuses. Discrepancies are flagged for manual review. The reconciliation process should be performed at regular intervals, such as daily or weekly, depending on the criticality of the data. The results of the reconciliation should be documented and tracked to ensure that all discrepancies are resolved before the cutover.
Manual reconciliation is time-consuming and prone to error. Therefore, automated tools and scripts are essential for high-stakes ERP migrations. These tools can extract data from both systems, normalize it, and compare it field by field. The output is a report that highlights any mismatches. The tools should be configurable to handle different data types and business rules. For example, a script might be configured to ignore minor rounding differences in currency conversions. The automation should also include alerts for critical discrepancies that require immediate attention. The project team should develop these scripts during the preparation phase and test them thoroughly before the parallel run begins. The scripts should be version-controlled and documented to ensure that they can be maintained and updated as needed. By automating the reconciliation process, the organization can save time and resources, and ensure that the data is validated consistently and accurately.
Delta data refers to the changes that occur in the legacy system after the initial data migration. This includes new transactions, updates to existing records, and deletions. Handling delta data is critical to maintaining transactional consistency between the two systems. The synchronization process must capture all delta changes and apply them to the target system in the correct order. This is particularly challenging for systems with complex transactional logic, such as inventory management or financial accounting. The synchronization process should include error handling to deal with failed transactions. If a transaction fails to synchronize, it should be logged and retried. The project team should monitor the synchronization process closely to ensure that no data is lost or duplicated. Transactional consistency is verified by comparing the state of the data in both systems at regular intervals. This ensures that the target system is an accurate reflection of the legacy system. By managing delta data effectively, the organization can maintain the integrity of the data and ensure that the parallel run is a valid test of the target system.
The parallel run is not just a technical exercise; it is also an operational and user engagement process. Users must be trained on how to operate in both systems and how to handle discrepancies. This training should be practical and scenario-based, focusing on the specific processes that are being validated. Users should be encouraged to report any issues they encounter, such as missing data, incorrect calculations, or system errors. The project team should establish a clear communication channel for reporting and resolving issues. This could be a dedicated email address, a ticketing system, or a regular meeting. The goal is to ensure that users are engaged and that their feedback is used to improve the target system. User engagement is critical to the success of the parallel run because it provides real-world insights that cannot be obtained through automated testing alone. By involving users in the process, the organization can identify and resolve issues before the cutover, reducing the risk of post-migration problems.
Training users on dual-system operations is essential to ensure that they can perform their jobs effectively during the parallel run. The training should cover the differences between the legacy and target systems, such as changes in user interface, data entry requirements, and reporting capabilities. Users should be trained on how to enter data in both systems and how to verify that the data is synchronized correctly. The training should also cover how to handle discrepancies, such as how to report them and how to follow up on their resolution. The training should be delivered in a format that is accessible to all users, such as workshops, online modules, or job aids. The project team should provide ongoing support during the parallel run to answer questions and resolve issues. By training users effectively, the organization can reduce the risk of user errors and ensure that the parallel run is a valid test of the target system.
Monitoring user feedback is a critical part of the parallel run. The project team should establish a process for collecting, analyzing, and acting on user feedback. This process should be transparent and responsive, ensuring that users feel heard and that their issues are addressed promptly. The project team should track the number and type of issues reported by users and use this data to identify trends and patterns. For example, if many users report issues with a specific module, the project team should investigate the root cause and implement a fix. The project team should also communicate the status of issue resolution to users, providing regular updates on the progress of the parallel run. By monitoring user feedback and resolving issues promptly, the organization can improve the quality of the target system and increase user confidence in the migration.
Performance and security validation are critical aspects of the parallel run. The target system must be able to handle the same transaction volumes and user loads as the legacy system without degradation in performance. This is tested by monitoring key performance indicators such as response times, throughput, and resource utilization. The project team should compare the performance of the target system to the legacy system and identify any areas where the target system is underperforming. If performance issues are identified, the project team should investigate the root cause and implement optimizations. Security validation ensures that the target system has the same level of security as the legacy system. This includes testing access controls, data encryption, and audit logs. The project team should verify that users have the correct permissions in the target system and that sensitive data is protected. By validating performance and security, the organization can ensure that the target system is ready for production use.
Benchmarking performance against legacy systems involves comparing the key performance indicators of the target system to those of the legacy system. This comparison should be done under similar conditions, such as the same transaction volumes and user loads. The project team should use performance monitoring tools to collect data on response times, throughput, and resource utilization. The data should be analyzed to identify any areas where the target system is underperforming. For example, if the target system has slower response times for specific transactions, the project team should investigate the cause. This could be due to inefficient database queries, lack of indexing, or insufficient hardware resources. The project team should implement optimizations to improve performance and re-test the system to verify the improvements. By benchmarking performance, the organization can ensure that the target system meets the performance requirements of the business.
Validating security controls and access rights is essential to ensure that the target system is secure and compliant with organizational policies. The project team should test the access controls to ensure that users have the correct permissions in the target system. This includes verifying that users can access the data and functions they are authorized to use and that they cannot access data or functions they are not authorized to use. The project team should also test data encryption and audit logs to ensure that sensitive data is protected and that all actions are logged. The project team should compare the security controls in the target system to those in the legacy system and identify any gaps. If gaps are identified, the project team should implement additional controls to close them. By validating security controls, the organization can ensure that the target system is secure and ready for production use.
The go/no-go decision is the final step in the parallel run process. It determines whether the organization is ready to cutover to the target system and decommission the legacy system. The go/no-go criteria should be defined at the beginning of the project and agreed upon by all stakeholders. These criteria should include data integrity, performance, security, and user readiness. For example, the go/no-go criteria might include that all critical data discrepancies have been resolved, that the target system meets performance benchmarks, that security controls are validated, and that users are trained and ready to operate in the new system. The project team should review the go/no-go criteria at the end of the parallel run and make a recommendation to the steering committee. The steering committee should make the final decision based on the project team's recommendation and the overall risk assessment. By defining clear go/no-go criteria, the organization can make an informed decision about the cutover and reduce the risk of post-migration problems.
Measurable success metrics are essential to evaluate the success of the parallel run. These metrics should be defined at the beginning of the project and tracked throughout the parallel run. Examples of success metrics include the number of data discrepancies resolved, the percentage of transactions processed successfully, the average response time, and the number of user issues reported. The project team should use these metrics to evaluate the progress of the parallel run and identify areas for improvement. The metrics should be reported to the steering committee regularly to provide visibility into the status of the project. By establishing measurable success metrics, the organization can make data-driven decisions and ensure that the parallel run is successful.
The cutover runbook is a detailed document that outlines the steps required to cutover to the target system. It should include the sequence of activities, the responsible parties, and the estimated duration of each step. The runbook should also include the rollback plan, which outlines the steps required to revert to the legacy system if the cutover fails. The rollback plan should be tested during the parallel run to ensure that it is effective. The project team should review the cutover runbook and rollback plan with all stakeholders before the cutover to ensure that everyone understands their roles and responsibilities. By preparing a detailed cutover runbook and rollback plan, the organization can reduce the risk of cutover failures and ensure a smooth transition to the target system.
Managing risks is a continuous process throughout the parallel run. The project team should identify potential risks, assess their likelihood and impact, and develop mitigation strategies. Common risks include data synchronization failures, performance degradation, user resistance, and integration issues. The project team should monitor these risks closely and take action to mitigate them as they arise. For example, if data synchronization failures are detected, the project team should investigate the root cause and implement a fix. If performance degradation is detected, the project team should optimize the target system. If user resistance is detected, the project team should provide additional training and support. By managing risks effectively, the organization can reduce the impact of disruptions and ensure a successful parallel run.
Data integrity risks are among the most significant risks in an ERP migration. These risks include data loss, data duplication, and data corruption. The project team should implement controls to mitigate these risks, such as automated reconciliation, data validation, and backup and restore procedures. The project team should also monitor the data synchronization process closely to detect and resolve any issues. By identifying and mitigating data integrity risks, the organization can ensure that the data in the target system is accurate and complete.
Integration and customization challenges are common in ERP migrations. These challenges include compatibility issues with third-party add-ons, changes in API contracts, and differences in business logic. The project team should test all integrations and customizations thoroughly during the parallel run to identify and resolve any issues. The project team should also work with vendors to ensure that all add-ons and customizations are compatible with the target system. By addressing integration and customization challenges, the organization can ensure that the target system is fully functional and ready for production use.
After the parallel run is complete and the go/no-go decision is made, the organization should focus on stabilizing the target system and decommissioning the legacy system. Stabilization involves monitoring the target system closely to detect and resolve any issues that arise. The project team should establish a hypercare period during which the project team provides additional support to users and monitors the system closely. Decommissioning involves shutting down the legacy system and archiving its data. The project team should ensure that all data is backed up and that the legacy system is securely decommissioned. By stabilizing the target system and decommissioning the legacy system, the organization can complete the migration and realize the benefits of the new ERP system.
Monitoring system stability during hypercare is essential to ensure that the target system is operating correctly. The project team should monitor key performance indicators, user feedback, and system logs to detect and resolve any issues. The project team should also provide additional support to users to answer questions and resolve issues. By monitoring system stability during hypercare, the organization can ensure that the target system is stable and ready for normal operations.
Decommissioning legacy systems safely involves shutting down the legacy system and archiving its data. The project team should ensure that all data is backed up and that the legacy system is securely decommissioned. The project team should also ensure that all users are aware of the decommissioning and that they have access to the archived data if needed. By decommissioning legacy systems safely, the organization can complete the migration and reduce the cost of maintaining the legacy system.
Common questions on this topic. Talk to our team for anything specific to your business.
The duration varies based on complexity, but typically ranges from 4 to 12 weeks. High-stakes migrations with complex financial processes often require longer periods to ensure thorough validation.
Data reconciliation involves automated comparison of key fields such as transaction IDs, amounts, and statuses. Discrepancies are flagged for manual review and resolution.
It is possible but risky for high-stakes migrations. One month may not be sufficient to capture all business cycles and validate complex processes. A minimum of two months is often recommended.
Long parallel runs increase costs, user fatigue, and the risk of data divergence. They can also delay the realization of benefits from the new system.
Custom reports should be validated to ensure they produce accurate results in the target system. Any discrepancies should be investigated and resolved before cutover.
Yes, user training is essential to ensure that users can operate effectively in both systems and report issues accurately.
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