Assess reporting dependencies early
Before starting an ERP migration, it’s crucial to audit your current reporting estate and understand which reports are tied to the existing ERP. Many businesses unknowingly hard-code their reporting structures directly into the ERP, meaning that when the ERP changes, reporting breaks.
- Identify the mission-critical reports that decision-makers rely on daily.
- Determine which reports are ERP-dependent and which pull data from multiple sources.
- Analyse historical data needs — will your new ERP structure support month-over-month (MoM) and year-over-year (YoY) comparisons?
By assessing dependencies early, businesses can plan for a smoother transition and prevent reporting disruptions.
Conduct a change management and skilling plan
ERP migrations are not just technical changes, they impact employees, workflows, and decision-making processes. A common ERP migration mistake companies make is focusing only on system implementation while neglecting the people using the data.
- Conduct training sessions for employees on how the new ERP will impact reporting.
- Create a change management plan to guide teams through the transition.
- Ensure data analysts and business users understand how reporting structures will evolve.
Without proper training and communication, employees may struggle to trust the new system, leading to confusion, inefficiencies, and adoption challenges.
Implement a data platform for continuity
To prevent ERP dependency from disrupting reporting, companies should implement a centralised data platform that acts as a single source of truth.
- Extract and store historical data from the legacy ERP before the transition.
- Establish a data pipeline that ingests data from both the old and new ERPs.
- Use cloud-based storage to enable scalability and future-proof analytics.
This approach ensures that reporting is not tied to a single system, making it more resilient to future changes.
Enable historical comparisons for better insights
One of the biggest pitfalls of ERP migrations is the loss of historical data needed for trend analysis and performance benchmarking. If companies don’t structure their data correctly, they may struggle to compare past and present metrics accurately.
- Store and map historical data so that reports remain consistent.
- Ensure that key business metrics remain unchanged, even if the ERP’s structure evolves.
- Use a data transformation layer to standardise data across both ERPs.
Without proper mapping, businesses could experience inconsistent KPIs, leading to misaligned reports and incorrect strategic decisions.
A data readiness assessment before migration starts helps surface ERP data migration challenges before they become costly to fix.
Automate data pipelines to reduce manual effort
Relying on manual data extraction, such as exporting reports to Excel, is not sustainable, especially during an ERP transition where data complexity increases. Automating data pipelines ensures that data flows seamlessly without human intervention.
- Set up automated ETL (Extract, Transform, Load) processes to pull data from multiple systems.
- Reduce dependency on manual reconciliations, which can become more complex with new ERP structures.
- Use real-time or scheduled data refreshes to ensure reports are always up to date.
By automating data flows, companies can reduce reporting downtime, improve accuracy, and free up employees to focus on analysis rather than data wrangling.
Test before going live to prevent disruptions
Even with a well-planned migration, unforeseen challenges can arise. Before fully switching to the new ERP, companies should test their data platform and reporting environment to catch issues before they impact business operations.
- Run a parallel reporting environment, comparing data from both the old and new ERPs.
- Validate critical reports to ensure they match historical trends.
- Conduct stress tests and scenario analysis to check for inconsistencies.
Testing helps businesses identify gaps and fix errors early, ensuring a smooth transition without data inconsistencies, reporting delays, or decision-making blind spots.
Uninterrupted, with access to old and new data.
