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Enabling a trusted 360° view of customers & products with centralized data

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“Elsevier is a very complicated business. I like that Semarchy didn’t try to fit us into someone else’s box. Flexibility to meet our complex needs was a critical point when selecting the MDM tool.”

James Carne

Head of Global Product Data at Elsevier

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Company

Who they are

Elsevier, a global leader in scientific, technical, and medical content, publishes over 500,000 articles annually across 2,500 journals while also supporting institutional clients and individual consumers via its e-commerce platform. With an expanding product base and rapidly changing marketplace, Elsevier needed to enhance its product data management and streamline operations. By implementing Semarchy’s Master Data Management (MDM) solution, Elsevier gained visibility and control over its data, enabling more efficient decision-making and better customer interactions.

Goal

Streamlining data management to support global expansion and operational efficiency

As Elsevier expanded its product offerings and global customer base, it encountered significant challenges in managing product and customer data. These issues hindered their ability to provide accurate, consistent, and real-time data across its operations. Below are the key challenges that led them to seek a better way to manage and govern their data.

Disparate data sources
Elsevier’s product data was spread across multiple systems, including acquisitions, legacy platforms, and spreadsheets. This fragmentation led to inefficiencies and challenges in creating consistent, accurate product data.

Data integration issues
The lack of a unified feed for product data created significant resource strain, as employees spent considerable time resolving integration issues instead of focusing on more strategic initiatives.

Ungoverned data
Managing the growing volume of data, especially as they digitized more content and interactions, posed significant governance challenges for Elsevier. Ensuring data could be effectively controlled and analyzed became an urgent need.

Strategy

Centralizing customer data with a unified data management solution

To address these data management challenges, Elsevier chose Semarchy xDM. The strategy focused on creating a single, trusted source of product and customer data to drive operational efficiency and improve the customer experience. Key drivers included:

  • Centralizing data across systems: Elsevier implemented Semarchy’s unified platform to centralize data from disparate sources across their e-commerce and internal systems to get accurate, consistent data.
  • Improving data governance and quality: By standardizing data rules and processes within Semarchy xDM, Elsevier was able to drive better governance practices, improving the quality and consistency of product data across all business domains.
  • Enhancing customer insights and experience: Semarchy’s solution enabled Elsevier to better manage and understand customer data, improving their ability to drive targeted customer experiences and increase satisfaction.
Results

Achieving operational excellence and better customer outcomes

As a direct result of implementing Semarchy’s MDM solution, Elsevier achieved several key business outcomes:

  • Increased data integration efficiency: Elsevier reduced the time spent on data integration by replacing multiple custom data sources with a single, cleansed feed, improving the speed and flexibility of their operations.
  • Improved customer experience: With centralized, accurate product data, Elsevier enhanced its e-commerce platform, enabling customers to easily find the right products and improve overall satisfaction.
  • Enhanced business insights: Real-time reporting and comprehensive analytics enabled Elsevier to gain deeper insights into customer behavior, sales performance, and operational efficiency, supporting better decision-making across the business.
  • Reduced costs and improved compliance: By consolidating its data management processes into one unified system, Elsevier reduced operational costs, freed up resources, and improved regulatory compliance across its data operations.