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Our client, a manufacturing company based in The Netherlands, decided to combine multiple ERP systems into MS Dynamics 365.  Versatyle was tasked with assisting the data migration of one specific manufacturing service ERP system, utilised by around only 30 companies worldwide. This case study showcases how Versatyle’s DataFlow migration service and specifically Versatyle’s Fit-Gap analysis allows for efficient resource allocation and realistic planning.

Challenges:

    • Enigmatic, industry specific source system
    • Different structure of source and target systems

Solutions:

    • Intelligent Mapping: Versatyle used AI-assisted mapping to identify relevant fields in the source ERP system. Efficiently finding the fields that were needed for the migration, and which were missing.
    • Identifying Gaps: Versatyle identified gaps between the source and target system, noting that the source system had no implementation of Bill of Materials whereas this was expected in MS Dynamics 365.
    • Resource focussing: Due to Versatyle identifying the gaps between the source and target system, the client could focus their scarce resources efficiently, on pain points.

Results:

    • Successful migration of data from the industry-specific ERP system to Microsoft Dynamics 365.
    • Creation of Bill of Materials data for Microsoft Dynamics 365 to compensate for the missing feature in the source system.
    • The project was planned realistically, with enough room for day-to-day operations next to the migration efforts.
    • Minimal disruption to the client’s operations during the migration process.
    • Improved data accuracy and accessibility within the new system.
    • Enhanced efficiency and productivity for the client’s manufacturing processes post-migration.

Key takeaways: This case study highlights the benefits of using the Versatyle DataFlow Migration Service for more industry specific ERP systems. We focus on identifying pain points rapidly, so resources can be focussed there quickly and efficiently for a realistic planning.