# AllSaints Built a Single Source of Truth Using Boomi Master Data Hub (MDH)

## Client Overview

AllSaints is a globally recognized fashion brand known for its distinctive design aesthetic and strong digital-first presence. Operating across retail, wholesale, and e-commerce channels, the organization manages complex product lifecycles across multiple regions. With a strong focus on innovation, consistency, and customer experience, the brand relies on scalable technology platforms to support its global operations.

## Business Objective

The fashion brand wanted to modernize its product data landscape by establishing a single, trusted source of truth across the enterprise. Over time, fragmented, point-to-point integrations had created inconsistencies, duplication, and operational inefficiencies that slowed down product launches and impacted downstream systems. The organization recognized the need for a more structured and scalable integration model to support its growing global footprint.

The primary objective was to eliminate siloed data flows and replace brittle integrations with a centralized, well-structured architecture. By doing so, the brand aimed to accelerate reliable product lifecycles – from design and enrichment through distribution and sales, while ensuring both retail and wholesale operations had access to accurate, synchronized information. A key priority was enabling downstream platforms such as ERP, order management, and partner systems to consistently receive validated, timely product data.

###### Industry

E-commerce/Retail

###### Platform

Boomi

###### Service

Master Data Management

## Challenges

### Fragmented Product Data

Product data was distributed across PIM, a legacy TMS, and downstream systems, leading to duplication, inconsistencies, and a lack of a single version of the truth.

### Spreadsheet-Driven Processes

Product enrichment, validation, and exports relied heavily on spreadsheets, increasing operational effort, error rates, and time-to-market.

### Legacy Systems

Both PIM and TMS lacked modern APIs, forcing the business to depend on scheduled, file-based transfers with limited visibility and control.

### Absence of PLM System

Without a PLM, early-stage product lifecycle activities such as design, sourcing, and costing remained manual and disconnected from downstream processes.

### Complex Downstream Integration

Product data needed to flow reliably to multiple systems, including TMS, Neo Order, and BigQuery, each with different data format requirements.

### Limited Data Governance

Clear data stewardship, attribute ownership, and governance rules were still evolving, making it challenging to enforce consistency across channels.

## Solutions

### Centralized Product Data Architecture

We designed a unified architecture with Boomi as the integration layer and Boomi Master Data Hub (MDH) as the central system of reference. This replaced brittle integrations with a governed, scalable model that simplified data flows and reduced operational risk.

### Golden Product Record with Boomi MDH

NeosAlpha consolidated product attributes in Boomi MDH to create a Golden Product Record. MDH standardized, cleansed, and enriched product data before distributing it to consuming systems.

### Modernized File-Based Integrations

Our Boomi experts implemented robust, scheduled SFTP integrations using Boomi to automate product data movement. This ensured reliable, traceable data transfers without disrupting existing legacy systems.

### Canonical Data Distribution

Each downstream system required product data in a different format, creating duplication and rework. By leveraging Boomi, we transformed Golden Product Records into system-specific canonical formats. These were delivered consistently to NetSuite, Fabric OMS, and external systems, ensuring data alignment across channels.

### Improved Data Governance

Lack of clear data ownership and governance reduced trust in product information. We introduced data quality rules, matching logic, versioning, and role-based access within MDH. This established clear stewardship, auditability, and confidence in product master data.

### Future-Ready Architecture

While the initial implementation remained file-based, our client needed a path to evolve. Our team defined a roadmap toward event-driven integrations, improved observability, and PLM adoption. This ensured the architecture could scale and adapt as business and technology needs grow.

## Results

### Single Source of Truth

Established a trusted Golden Product Record, ensuring consistent and accurate product information across all consuming systems.

### Reduced Manual Effort and Errors

Automation replaced spreadsheet-driven processes, significantly lowering manual intervention and improving operational efficiency.

### Improved Data Quality

Standardized data models, validation rules, and governance controls delivered higher-quality product data across retail and wholesale channels.

### Faster Data Flows

Product data updates reached downstream systems more quickly and predictably, supporting smoother product launches and updates.

## Technology Stack