Problem Statement

The client’s reliance on an ERP system limited their ability to manage comprehensive product information. The ERP held only basic product data, making it challenging to maintain detailed information and syndicate it seamlessly across various output channels, including their website, eCommerce platforms, and third-party marketplaces.

Key Challenges

• Incomplete & Scattered Product Data

  Product data was dispersed, with only basic information in the ERP, resulting in incomplete datasets across channels.

• Data Management Complexity

  Managing product information with all necessary attributes was difficult without a dedicated platform.

• Inconsistent Data Standards

  Manual data enrichment led to inconsistent and unstandardized data.

• Manual Processes

  Product data management relied heavily on manual tasks, reducing productivity and increasing errors.

• Asset Mapping Issues

  Product and asset data were stored in separate systems, complicating the process of associating media assets with multiple products.

• Lack of Data Governance

  Any user could make changes, leading to inconsistent data quality and unreliable information across systems.

Solution Implemented

A comprehensive Pimcore-based digital platform was deployed in four months, integrating PIM, DAM, and MDM systems to centralize and streamline data management.

• Centralized Product Data Management (PIM): Implemented a PIM system to ensure detailed, consistent, and accessible product data across channels.

• Unified Digital Asset Management (DAM): Introduced a DAM solution to store all media assets, such as images and videos, in a single platform for easier access and association.

• Master Data Management (MDM) Integration: Integrated MDM to manage critical data, including brands, categories, and subcategories, ensuring a unified approach to data organization.

• Custom Development for Data Mapping: Developed custom solutions to accurately associate assets with multiple products, enhancing the accuracy of product-asset connections.

• Data Governance Implementation: Established governance policies to validate and approve data changes, safeguarding data quality and consistency.

Business Impact

• Improved Data Quality

  Data governance policies enhanced data reliability, reducing unauthorized access and improving data accuracy.

• Increased Productivity

  Automated product data enrichment streamlined workflows, reducing manual input and speeding up processes.

• Reduced Data Silos

  Centralized management of product, asset, and master data minimized data fragmentation and improved accessibility.

• Enhanced Operational Excellence

  Streamlined and automated data management processes increased efficiency and operational effectiveness.