Microsoft Dynamics 365 and Plytix
Integration Agency & Consultants
Product data errors stop being a nuisance and start becoming a commercial risk when inconsistent records delay launches across multiple sales channels. We connect Plytix with Microsoft Dynamics 365 to ensure enriched product data from marketing becomes accurate operational records for finance and fulfilment. At scale, this prevents the manual corrections that lead to overselling, incorrect pricing, and damage to brand reputation. We build reliable connections that protect the integrity of your ERP while maintaining the agility of your PIM.
Auditing ERP and PIM system architecture
We connect Microsoft Dynamics 365 and Plytix quickly, ensuring your ERP and PIM systems work together efficiently. Our consulting services are invaluable, with our system audit uncovering integration issues and inefficiencies across Microsoft Dynamics 365, Plytix, ERP, and PIM platforms. This enables both our consultants and your team to take decisive action, keeping your tech ecosystem running smoothly and efficiently. As a result, you can deliver a consistently excellent experience to your customers.
Solution Design
The design establishes Plytix as the central source of truth for enriched product data, which is then synchronised into Dynamics 365 for operational use. A key trade-off involves synchronisation frequency: while immediate updates for all attribute changes can increase system load, a scheduled approach for heavy data assets maintains ERP stability. High-priority fields such as pricing are typically sequenced for more frequent updates. We clearly define data ownership between the enriched marketing content in Plytix and the operational item records in Dynamics 365. This structure ensures finance teams rely on stable ERP data for reporting, while ecommerce teams manage channel consistency from the PIM, reducing manual errors across the product lifecycle.
Synchronising attributes and product variant records
The integration organises the flow of product information between Plytix and Dynamics 365, typically positioning the PIM as the source for enriched marketing data and the ERP as the record for operational item details. We map attributes between systems to ensure item records are synchronised without manual re-entry. The process handles product variants to maintain consistency across the entire catalogue. Data integrity is managed through validation steps that identify missing information before it is pushed to the ERP. Built-in monitoring detects failed updates or mapping errors promptly, ensuring that your sales channels receive accurate information and that backend inventory records remain reliable.
Orchestrating secure flows via accredited middleware
Leveraging IPaaS with ISO 27001 and SOC 2 and above accreditations ensures secure, efficient integration between Microsoft Dynamics 365 and Plytix, connecting ERP and PIM systems. IPaaS simplifies connecting Microsoft Dynamics 365 with Plytix, automating ERP and PIM data flows while maintaining strict security standards. This approach reduces manual effort, minimises risk, and supports compliance, making integrations reliable and secure for businesses handling sensitive information.
Surfacing synchronisation exceptions and data drift
Dashboards are often insufficient for detecting the subtle data inconsistencies that occur when PIM and ERP systems become misaligned. Effective visibility involves identifying when product updates in Plytix fail to reach Dynamics 365 due to technical or validation issues. We surface these exceptions before they lead to incorrect pricing or missing product information on sales channels. Monitoring covers common issues such as failed updates or attribute mapping gaps. Rather than discovering errors through customer feedback, your team can access alerts that identify the specific data records requiring attention. This level of oversight ensures the integrity of your product information across your operational systems.
Practical handover for daily system operations
Handover ensures your ecommerce, operations, and finance teams own the new operating model. Training is anchored in the specific design decisions of your Dynamics 365 and Plytix setup, focusing on daily operational checks rather than technical theory. We define ownership for common exception types, such as attribute mapping errors or synchronisation delays. Your team learns to interpret alerts from the integration layer to prevent data drift before it impacts sales channels. All documentation is provided as an operational reference for the people running the business, ensuring teams know what to check periodically to maintain data integrity. This approach provides a practical guide for maintaining consistency between your PIM and ERP systems.
Maintaining long term data integrity post-launch
Support focuses on the ongoing reliability of the synchronisation between Dynamics 365 and Plytix. We monitor the integration for potential issues, such as data transfer failures or mapping discrepancies that could affect your product information. Our process ensures that technical exceptions are identified and addressed based on their operational importance. We move beyond reactive troubleshooting by checking for data consistency to help prevent errors from compounding over time. This approach ensures that your systems stay aligned as your business grows. We provide the oversight necessary to maintain your product data integrity, allowing your team to focus on daily operations.
Common failures
SKU length and format mismatches
Operational impact: Dynamics 365 Business Central can impose a 20-character limit on its item 'No.' field. If SKUs generated in Plytix are longer, the integration may truncate them or fail to create the item record entirely. This leads to incomplete product catalogues in the ERP, preventing Sales Orders from being created and breaking the link between inventory, sales, and financial ledgers.
Prevention / Action: The integration's design phase must include a strict definition for SKU formatting, owned by the ERP but enforced within Plytix using its validation capabilities. This ensures SKUs are compliant before they are synchronised. The integration itself should feature robust exception handling to quarantine non-compliant item records and alert an operator, rather than permitting silent data loss or sync failures.
Incorrect Unit of Measure conversions
Operational impact: A product may be defined in Plytix as a single unit ('Each') but is managed in Dynamics 365 using different Units of Measure (UoM) like 'Case' or 'Pallet'. If the integration logic fails to apply D365's UoM conversion tables correctly, inventory levels become unreliable, causing significant overselling or showing items as out of stock. This disrupts fulfilment, forces manual inventory counts, and corrupts demand planning data.
Prevention / Action: Establish Dynamics 365 as the sole source of truth for all UoM schedules and conversion factors. The integration must be built to query these tables when handling any data related to inventory, purchasing, or sales. All product records should be sourced from Plytix using a consistent base unit, with all subsequent conversions handled exclusively by the logic within the ERP during transaction processing.
Inventory location mapping failures
Operational impact: Available-to-sell inventory calculations often aggregate stock from multiple warehouses defined in Dynamics 365. If these warehouse codes do not have an exact, case-sensitive match to the location identifiers used in Plytix or the sales channel, stock updates will fail. The result is stale and inaccurate stock data on the frontend, leading to overselling, cancelled orders, and a poor customer experience that requires manual intervention from the CX and fulfilment teams.
Prevention / Action: Centralise ownership of all warehouse and location codes within Dynamics 365. The integration layer should contain a flexible mapping table to translate these codes into the specific values required by Plytix and other endpoints. A critical part of process design is creating a clear operational procedure for adding new stock locations, ensuring they are configured in the integration mapping before becoming active in the ERP.
Frequently asked questions
If we use both systems, which one is the master for product data?
Plytix should be treated as the source of truth for marketing and enrichment data, such as descriptions, images, and specifications. Microsoft Dynamics 365 then becomes the operational source of truth for logistical and financial data like inventory levels, cost, and pricing for specific sales channels. This model ensures that rich product content from Plytix doesn't conflict with core operational data in the ERP.
Our SKUs in Plytix are longer than 20 characters. Will this cause issues with Dynamics 365 Business Central?
Yes, this is a common failure point we plan for. The default 'No.' field for an Item record in Dynamics 365 Business Central is limited to 20 characters, so a direct mapping of a longer Plytix SKU will cause the integration to fail. The correct approach involves mapping the SKU to a different field and using a compliant, system-generated number for the primary 'No.' field.
We sell products in individual units and in cases. How does the integration handle different units of measure?
This requires careful mapping during implementation, because the two systems handle this differently. While Plytix typically holds the base product information, Microsoft Dynamics 365 manages the specific Unit of Measure (UoM) conversions for sales and warehousing. If the link between a Plytix SKU and the corresponding D365 UoM schedule is wrong, you risk inaccurate stock levels and incorrect pricing on sales orders.
How do you ensure rich data from Plytix (like GTINs) is usable in Dynamics 365?
Data must be mapped to functionally correct fields, not just synchronised into the nearest available one. For instance, a GTIN from Plytix must be mapped to the specific item identifier table or alias in Dynamics 365 that is used for barcode scanning and order processing. Placing it in a simple text attribute would make the data visible but operationally useless, defeating the purpose of enriching it in Plytix.