To achieve success, businesses must sell their products swiftly, seamlessly, and at the lowest possible cost. This begins with efficient product data management. Simplifying data management and minimizing IT involvement can shorten the time needed to bring a product to market, enabling faster sales. Empowering business teams to manage product information, rather than relying on IT, ensures smoother data management. Additionally, reducing the need for specialized IT roles helps keep costs low.
However, achieving this balance often leads to conflicts between business objectives, data governance, master data management, data quality, and product information management (PIM). inriver offers two solutions to address these conflicts: an admin-centric approach and a business user approach. Known as “Field Sets” and “Specification” methods, these approaches are tailored to meet the needs of both business channels and IT entities.
The FieldSets method
The FieldSets method allows users to create individual FieldSets to organize products or items at the entity level. This enables users to search for items and view only those that match specific fields, effectively reducing the number of fields displayed by categorizing them. This feature does not require custom extensions, and entities cannot be duplicated. For larger entities with numerous categories and fields, it’s important to consider and benchmark performance.
The Specification method
The Specification method enables the creation of Parent and Child templates to facilitate product data inheritance and field copying. By managing entities hierarchically, data can be updated in the parent template and propagated to all associated entities. Child templates can be created and modified under the parent template while retaining inherited fields. Although the concept of categories remains unchanged, this feature requires custom extensions. Additionally, search capabilities differ under this model, and larger entities will benefit from enhanced field performance.
By adopting one of these methods, businesses can streamline their product data management processes, reduce conflicts between different areas, and continue to sell products successfully. Efficient product data management is not just a technical necessity but a strategic advantage that can drive business success in a competitive market.
