Connected business operations. Flexible deployment.
Learn how to manage ERP parallel run periods effectively. This guide covers data synchronization, reconciliation, risk mitigation, and cutover strategies to ensure a successful migration.
A parallel run period is a critical phase in ERP migration where both the legacy and new systems operate simultaneously to validate data integrity, process accuracy, and system stability before full cutover. This approach mitigates risks associated with data loss, process disruption, and system failures by allowing organizations to compare outputs and identify discrepancies in a controlled environment. The primary goal is to ensure that the new ERP system can handle real-world business operations without compromising financial reporting, supply chain continuity, or customer service. Key risks to control during this phase include data synchronization errors, integration failures, performance bottlenecks, and user adoption challenges. Effective management of the parallel run requires rigorous data reconciliation, clear go/no-go criteria, and a well-defined rollback plan to ensure business continuity and minimize operational downtime.
Determining the duration and scope of the parallel run is essential for balancing risk mitigation with operational efficiency. The length of the parallel run depends on the complexity of the business processes, the volume of data, and the criticality of the modules being migrated. Typically, a parallel run lasts from one to three months, but this can vary significantly based on industry requirements and regulatory constraints. The scope should include all critical business processes, such as financial closing, inventory management, and order processing. It is important to define clear objectives for the parallel run, such as validating data accuracy, testing integration points, and ensuring user readiness. Organizations should also consider the impact on IT resources and user productivity, as running two systems simultaneously can strain both. A phased approach, where less critical modules are run in parallel first, can help manage risks and provide early feedback.
Identifying and prioritizing critical business processes is a foundational step in planning the parallel run. These processes should be those that have the highest impact on revenue, compliance, and customer satisfaction. For example, financial reporting, order-to-cash, and procure-to-pay processes are often considered critical. By focusing on these areas, organizations can ensure that the new ERP system is thoroughly tested in the most important scenarios. It is also important to map out the dependencies between processes and systems to identify potential bottlenecks or integration issues. This mapping helps in creating a comprehensive test plan that covers all critical paths and ensures that no significant business process is overlooked.
Establishing clear objectives and key performance indicators (KPIs) for the parallel run is crucial for measuring success and making informed decisions. Objectives should be specific, measurable, achievable, relevant, and time-bound (SMART). For example, a KPI could be the percentage of transactions that match between the legacy and new systems, with a target of 99.9% accuracy. Other KPIs might include system uptime, response times, and user error rates. By tracking these metrics, organizations can identify trends, pinpoint issues, and make data-driven decisions about when to proceed with cutover. Regular reviews of KPIs should be conducted to ensure that the parallel run is on track and that any deviations are addressed promptly.
Data synchronization and reconciliation are the cornerstones of a successful parallel run. The goal is to ensure that data in both systems is consistent and accurate, allowing for meaningful comparisons. This involves setting up automated data feeds between the legacy and new systems, using middleware or APIs to transfer data in real-time or near real-time. Reconciliation processes should be designed to compare key data points, such as financial balances, inventory levels, and customer records, and flag any discrepancies for investigation. It is important to establish a clear process for resolving discrepancies, including who is responsible for investigating and correcting errors, and how quickly they must be resolved. Regular reconciliation reports should be generated to provide visibility into data integrity and to support decision-making.
Automating data feeds using middleware or APIs is essential for maintaining data consistency during the parallel run. Middleware acts as an intermediary between the legacy and new systems, facilitating the transfer of data and ensuring that it is formatted correctly for the target system. This automation reduces the risk of manual errors and ensures that data is transferred in a timely manner. It is important to test the middleware thoroughly before the parallel run begins to ensure that it can handle the volume and complexity of the data. Additionally, monitoring tools should be implemented to track the status of data feeds and alert the team to any failures or delays. This proactive approach helps in maintaining data integrity and minimizing the impact of any issues on the parallel run.
Implementing robust reconciliation protocols is critical for identifying and resolving data discrepancies. These protocols should define the frequency of reconciliation, the data points to be compared, and the thresholds for acceptable variances. For example, financial balances might be reconciled daily, while inventory levels might be reconciled weekly. The reconciliation process should include automated checks that flag discrepancies above a certain threshold, as well as manual reviews for more complex issues. It is important to document all discrepancies and their resolutions to create an audit trail and to identify patterns that may indicate systemic issues. This documentation also supports the go/no-go decision by providing evidence of data integrity and system stability.
Managing integration and API dependencies is a critical aspect of the parallel run, as many business processes rely on seamless data exchange between systems. During the parallel run, both the legacy and new systems may need to interact with third-party applications, such as CRM, e-commerce platforms, and payment gateways. It is important to map out all integration points and ensure that they are configured correctly in both systems. This includes testing API endpoints, authentication mechanisms, and data formats to ensure that data is exchanged accurately and securely. Any changes to integration configurations should be documented and tested in a staging environment before being applied to the production systems. Regular monitoring of integration health is essential to detect and resolve issues promptly.
Thorough testing of API endpoints and authentication mechanisms is crucial for ensuring reliable data exchange during the parallel run. This includes testing for functionality, performance, and security. Functionality tests should verify that data is transmitted and received correctly, while performance tests should measure response times and throughput under various load conditions. Security tests should ensure that authentication and authorization mechanisms are working as expected and that data is encrypted in transit. It is important to test these APIs in a staging environment that mirrors the production environment to identify and resolve any issues before they impact the parallel run. Regular regression testing should be conducted to ensure that any changes to the APIs do not introduce new issues.
Monitoring integration health is essential for detecting and resolving issues in real-time during the parallel run. This involves implementing monitoring tools that track the status of API calls, data feeds, and middleware components. Alerts should be configured to notify the team of any failures, delays, or anomalies in data exchange. This proactive approach helps in minimizing the impact of integration issues on business operations and ensures that data integrity is maintained. Regular reviews of monitoring data should be conducted to identify trends and to make informed decisions about system configuration and resource allocation. This monitoring also supports the go/no-go decision by providing evidence of integration stability and reliability.
User training and adoption are critical for the success of the parallel run and the overall migration. Users must be comfortable with the new ERP system and understand how to perform their daily tasks in both systems. This requires a comprehensive training program that covers all critical business processes and provides hands-on practice in a staging environment. Training should be tailored to different user roles and should include both initial training and refresher sessions. It is important to gather feedback from users during the parallel run to identify any usability issues or gaps in training. This feedback should be used to improve the training program and to make necessary adjustments to the system configuration. User adoption metrics, such as login frequency and task completion rates, should be tracked to measure the effectiveness of the training program.
Designing role-based training programs is essential for ensuring that users receive the training they need to perform their specific tasks. This involves identifying the key roles in the organization and mapping out the tasks and processes associated with each role. Training materials should be tailored to each role, focusing on the most relevant features and functions of the new ERP system. Hands-on practice in a staging environment is crucial for building user confidence and competence. It is important to provide ongoing support and resources, such as user guides and video tutorials, to help users troubleshoot issues and learn new features. Regular feedback sessions should be conducted to gather insights from users and to improve the training program.
Tracking user adoption metrics is essential for measuring the effectiveness of the training program and identifying areas for improvement. These metrics should include login frequency, task completion rates, error rates, and user satisfaction scores. By tracking these metrics, organizations can identify trends and patterns that indicate user readiness and system usability. For example, a high error rate in a specific process may indicate a need for additional training or system configuration changes. Regular reviews of adoption metrics should be conducted to make data-driven decisions about training and support. This data also supports the go/no-go decision by providing evidence of user readiness and system usability.
Risk mitigation and rollback planning are essential for ensuring business continuity during the parallel run and cutover. The parallel run should be treated as a high-risk activity, with a clear plan for identifying, assessing, and mitigating risks. This includes defining risk owners, establishing risk registers, and implementing controls to reduce the likelihood and impact of risks. A rollback plan should be developed to outline the steps for reverting to the legacy system if the new system fails to meet the go/no-go criteria. This plan should include clear triggers for rollback, such as data integrity issues, system downtime, or user adoption failures. The rollback plan should be tested in a staging environment to ensure that it is feasible and effective. Regular reviews of the risk register and rollback plan should be conducted to ensure that they remain relevant and up-to-date.
Defining clear go/no-go criteria is essential for making informed decisions about when to proceed with cutover. These criteria should be based on the objectives and KPIs established during the planning phase. For example, go/no-go criteria might include data accuracy thresholds, system uptime requirements, and user adoption metrics. The criteria should be specific, measurable, and agreed upon by all stakeholders. Regular reviews of the criteria should be conducted to ensure that they are being met and to identify any areas of concern. If the criteria are not met, the team should investigate the root causes and implement corrective actions before proceeding with cutover. This disciplined approach helps in minimizing the risk of a failed cutover and ensures that the new system is ready for production use.
Testing the rollback plan is crucial for ensuring that it is feasible and effective. This involves simulating a rollback scenario in a staging environment and measuring the time and resources required to revert to the legacy system. The test should include all critical steps, such as data restoration, system configuration changes, and user communication. It is important to document the results of the test and to identify any areas for improvement. Regular testing of the rollback plan should be conducted to ensure that it remains effective as the system and processes evolve. This testing also helps in building confidence among stakeholders and in ensuring that the organization is prepared for any unexpected issues during cutover.
Cutover execution is the final step in the parallel run, where the organization transitions from the legacy system to the new ERP system. This process should be carefully planned and executed to minimize downtime and ensure business continuity. A detailed cutover plan should be developed, outlining all the steps, responsibilities, and timelines for the transition. This plan should include a freeze window, during which no changes are made to the systems, to ensure a stable environment for cutover. Final data loads should be performed, and all integration points should be verified. Communication with stakeholders should be clear and timely, providing updates on the cutover progress and any issues that arise. Post-migration stabilization involves monitoring the new system, resolving any issues, and providing ongoing support to users. This phase is critical for ensuring that the new system operates smoothly and that any remaining issues are addressed promptly.
Executing the cutover plan requires careful coordination and communication among all stakeholders. The plan should be reviewed and approved by all relevant parties before execution. During the cutover, a dedicated team should be in place to monitor the systems, resolve issues, and communicate progress to stakeholders. It is important to follow the plan strictly and to make any necessary adjustments based on real-time data. Any deviations from the plan should be documented and communicated to all stakeholders. The cutover should be completed within the planned timeframe to minimize downtime and ensure business continuity. Regular status updates should be provided to keep stakeholders informed and to manage expectations.
Post-migration monitoring and support are essential for ensuring the long-term success of the new ERP system. This involves implementing monitoring tools to track system performance, data integrity, and user activity. Alerts should be configured to notify the team of any issues, such as system downtime, data discrepancies, or user errors. A dedicated support team should be in place to resolve issues and provide assistance to users. Regular reviews of monitoring data should be conducted to identify trends and to make informed decisions about system configuration and resource allocation. This ongoing support helps in ensuring that the new system operates smoothly and that any remaining issues are addressed promptly, leading to a successful migration and improved business operations.
Common questions on this topic. Talk to our team for anything specific to your business.
The duration of an ERP parallel run period typically ranges from one to three months, depending on the complexity of the business processes, the volume of data, and the criticality of the modules being migrated. Organizations should define the duration based on their specific needs and risk tolerance.
The main risks of running two ERP systems simultaneously include data synchronization errors, integration failures, performance bottlenecks, user adoption challenges, and increased operational costs. Effective risk management and monitoring are essential to mitigate these risks.
Data reconciliation between legacy and new ERP systems involves setting up automated data feeds, comparing key data points, and flagging discrepancies for investigation. Regular reconciliation reports should be generated to provide visibility into data integrity and to support decision-making.
You should stop the parallel run and cut over when the go/no-go criteria are met, indicating that the new ERP system is stable, accurate, and ready for production use. This decision should be based on data integrity, system performance, and user adoption metrics.
Middleware plays a crucial role in parallel run operations by facilitating data transfer between the legacy and new systems. It ensures that data is formatted correctly and transferred in a timely manner, reducing the risk of manual errors and maintaining data integrity.
User training during a parallel run should be comprehensive and role-based, covering all critical business processes. Hands-on practice in a staging environment is essential for building user confidence and competence. Regular feedback sessions should be conducted to improve the training program.
Discover how modernizing retail ERP systems enables coordinated planning across merchandising, supply chain, and finance, reducing silos and improving operational visibility.
Learn how to design critical User Acceptance Testing (UAT) scenarios for ERP migrations to identify data, process, and integration risks before go-live, ensuring operational continuity and reducing post-migration failures.
Learn how to minimize operational risk during ERP cutover. This guide covers downtime planning, rollback strategies, data validation, and business continuity best practices for IT leaders and ERP consultants.
Discuss your workflows, modules and deployment options with our team.
Back to resources