Mastering global data management

Executive summary

Explore how Master Data Management (MDM) drives operational excellence, supports the Global Business Services (GBS) model, and leverages cloud-native platforms to enable scalable, efficient, and sustainable growth for global enterprises.

MDM is the foundation for operational excellence in global enterprises, enabling data consistency, governance, and seamless integration across regions and functions. As companies embrace the GBS model, MDM plays a critical role in unifying diverse systems and driving efficiency, innovation, and value creation.

This paper highlights:

• The role of MDM in GBS: How MDM aligns with the GBS model to support integrated service delivery and scalability

• Key MDM models: An exploration of consolidation, registry, centralized, and transactional styles, and their use cases in modern enterprises

• The cloud-native advantage: How cloud-based platforms empower scalable, real-time MDM implementation.

Pairing MDM with GBS and cloud-native technologies allows organizations to simplify operations, make smarter decisions, and drive sustainable growth.

Introduction

MDM is essential for global enterprises to maintain data consistency, support operational excellence, and leverage cloud-native platforms to drive efficiency and growth.

Data is the lifeblood of modern enterprises yet managing it across global operations remains one of the most complex challenges for multinational organizations. With diverse markets, evolving regulations, and fragmented systems, maintaining consistency and reliability in master data is crucial for driving operational excellence and informed decision-making.

MDM addresses these challenges by harmonizing critical data assets like customer profiles, product information, and supplier details into a unified source of truth. This enables organizations to overcome data silos, reduce inefficiencies, and ensure compliance across geographies and functions.

The increasing adoption of the GBS model further underscores the strategic importance of MDM. By centralizing and standardizing key operational and analytical processes, GBS relies on a robust MDM framework to deliver scalable, value-driven services across regions.

The global MDM market reflects this growing importance, with its value rising from USD 15.33 billion in 2024 to a projected USD 36.48 billion by 2029, achieving a compound annual growth rate (CAGR) of 18.93%, according to Mordor Intelligence (Mordor Intelligence, 2025)¹.

This rapid growth underscores MDM’s critical role in enabling sustainable growth and operational agility for global enterprises.

Cloud-native platforms have further transformed how MDM is implemented, offering unprecedented flexibility, scalability, and real-time data-sharing capabilities. These technologies empower enterprises to seamlessly integrate MDM processes with modern business systems, enabling faster decision-making and greater agility in responding to market demands.

Let’s explore how MDM supports the GBS operating model, outlines critical master data domains, and examines modern implementation pathways. By leveraging cloud-native solutions, global organizations can unlock the full potential of MDM to achieve operational efficiency and long-term growth.

Emergence of the GBS operating model

Large enterprises are adopting the GBS model to centralize and optimize support functions. This is driving efficiency, standardization, and value creation across geographies and business units.

The GBS operating model has emerged as a transformative approach among large global enterprises to streamline and optimize their support functions. It primarily consists of centralized service delivery models that encompass shared services, outsourcing, and centers of excellence to serve multiple business units. The scope can include finance, IT, HR, and procurement, as well as other functions, and can be delivered onshore or offshore. This model emphasizes delivering standardized, scalable, and value-driven services across business units and geographies.

Key drivers behind the emergence of GBS

• Demand for operational efficiency
  Large enterprises face the challenge of managing complex global operations with cost pressures and competitive demands. GBS helps address this by consolidating services, leveraging economies of scale, and eliminating redundancies.

  
  

• Focus on standardization and scalability
  GBS emphasizes creating consistent processes and standards across the organization, ensuring seamless service delivery regardless of location. This standardization not only enhances quality but also enables the model to scale effectively as the organization grows.

  
  

• Advances in technology
  The proliferation of digital technologies, such as robotic process automation (RPA), artificial intelligence (AI), and cloud computing, has made it possible to centralize and automate many support functions. GBS leverages these technologies to enhance efficiency, agility, and innovation.

  
  

• Shift to value-driven services
  Unlike traditional shared services models, which focus primarily on cost-saving, GBS aims to deliver measurable business value. By aligning its objectives with strategic business goals, GBS evolves into a partner in driving growth and innovation.

  
  

• Globalization and market expansion
  As enterprises expand into new markets, the need for a cohesive support structure becomes critical. GBS facilitates this by providing centralized governance and streamlined processes that adapt to global operations while remaining responsive to local needs.

  
  

• Regulatory and compliance demands
  Operating in multiple regions exposes enterprises to varying regulatory environments. GBS ensures compliance by implementing uniform policies and maintaining centralized oversight of critical processes like data management and reporting.

Core characteristics of GBS

• Integrated delivery model: GBS combines functions previously managed in isolation into a unified service delivery framework.

• Customer-centric approach: Internal business units are treated as "customers," with a focus on meeting their specific needs efficiently.

• Technology-driven: The model harnesses advanced analytics, automation, and digital platforms to drive process improvement and decision-making.

• Governance and accountability: Strong governance structures ensure accountability and alignment with enterprise goals.

• Agility and flexibility: The model adapts to changing business environments, enabling quicker responses to market shifts.

Benefits of the GBS model

• Cost optimization: Significant reductions in operational costs through process centralization, standardization, and automation

• Improved service quality: Enhanced accuracy, consistency, and reliability of services delivered across regions.

• Faster decision-making: Centralized data and insights, to enable quicker, more informed decisions.

• Innovation enablement: A unified approach, allowing enterprises to adopt and scale new technologies effectively.

• Global collaboration: Improved coordination and collaboration across geographically dispersed teams.

What is MDM?

MDM centralizes and standardizes critical business data to ensure accuracy, consistency, and reliability across an organization.

MDM is a comprehensive process, framework, or set of technologies used by organizations to manage, organize, and maintain the accuracy, consistency, and reliability of their critical business data, known as "master data." Master data represents the core entities of an organization, such as customers, products, parts, suppliers, and employees, which are essential for business operations and decision-making.

MDM ensures that master data is consistent, accurate, and unified across different operational and analytical systems, departments, and geographic locations. By creating a single, trusted source of truth, MDM helps eliminate data silos, reduce errors, and improve the efficiency of business processes.

The role of MDM in the GBS model

MDM is essential for ensuring data consistency, standardization, and accuracy, enabling the efficiency, scalability, and value creation central to the GBS operating model.

The adoption of the GBS operating model has elevated the importance of MDM as a strategic enabler for large enterprises. GBS integrates various support functions, such as finance, HR, IT, procurement, and supply chain into a centralized, cohesive framework, emphasizing efficiency, standardization, and value creation. In this context, MDM has become indispensable for managing the complexities of global data, ensuring consistency, and driving the effectiveness of the GBS model.

Key factors for the increased importance of MDM in the GBS model

• Unified data foundation for integrated services
  GBS thrives on the integration of diverse functions across geographies. MDM ensures a unified data foundation with a common data model by harmonizing critical data assets, such as customer records, supplier information, parts or products, and financial data across the enterprise. This consistency is essential for delivering seamless and reliable services through the GBS framework.

  
  

• Standardization across functions and regions
  A cornerstone of the GBS model is the standardization of processes and workflows. MDM facilitates this by defining and enforcing consistent data standards, policies, and governance mechanisms, reducing variability and inefficiencies across regions and functions.

  
  

• Enhanced decision-making through accurate data
  The GBS model depends on high-quality data for making informed decisions. MDM ensures data accuracy and completeness, providing reliable inputs for advanced analytics, business intelligence (BI), and real-time decision-making. This is critical for GBS’s role in supporting enterprise-wide strategies.

  
  

• Seamless technology integration
  GBS often relies on advanced technologies like RPA, AI, and cloud-based platforms to enhance service delivery. MDM enables seamless integration between these technologies and underlying systems (e.g., Enterprise Resource Planning or Customer Relationship Management), ensuring that automated processes are powered by clean and consistent data.

  
  

• Improved compliance and risk management
  Operating in a global context exposes enterprises to complex regulatory requirements. GBS benefits from MDM’s ability to maintain accurate, traceable, and auditable data, ensuring compliance with global and local regulations, such as the General Data Protection Regulation (2016) or the Sarbanes-Oxley Act (2002).

  
  

• Support for scalability and agility
  As GBS expands to support new markets or integrates additional business functions, MDM provides the scalability and flexibility required to manage data growth and adapt to changing business needs. This enables enterprises to rapidly onboard new regions, technologies, or processes without data inconsistencies.

  
  

• Optimization of cost and efficiency
  GBS focuses on driving efficiency and cost savings through centralized operations. MDM minimizes operational redundancies and inefficiencies caused by poor data quality, ensuring that resources are utilized effectively across the organization.

  
  

• Enhanced customer and employee experience
  GBS aims to deliver high-quality services to internal and external stakeholders (employees and customers). MDM ensures that customer and employee data is consistent and up to date, enabling personalized interactions and efficient service delivery.

Critical global master domains

Core master data domains are vital for ensuring consistency, efficiency, and seamless operations across global enterprises.

Global enterprises in industries such as CPG, Manufacturing, and Logistics operate in highly complex ecosystems that rely on the accuracy and consistency of master data across regions and functions. Below are the critical global master data domains that are essential for enabling seamless operations, efficient procurement, and manufacturing:

Types of global MDM models and implementation pathways

Global MDM models offer varying levels of control, scalability, and integration, each suited to different organizational needs and cloud-native platforms.

1. Consolidation-style analytical MDM

The consolidation style aggregates master data from multiple source systems into a central repository for analysis and reporting, without altering the source data. This model is focused on creating a "single view" of the data, allowing for consistent and accurate reporting.

Key features:

• Master data is collected and reconciled, but it is not actively updated in the source systems

• The system acts as a central "read-only" hub, primarily used for data analysis         

This is the simplest type of MDM to implement, requiring less upfront and ongoing investment, as it does not update source systems. Instead, consolidated MDM data is typically used by analytical applications, such as BI reporting, data science, and more. Analytical MDM is commonly found in large enterprises, where it serves trusted data for BI, analytics, and data science use cases. Analytical MDM is typically built on modern cloud data platforms such as Snowflake, Databricks, BigQuery, and others.

Fig. 1: Regional consolidation-style analytical MDM implementation and the creation of a global master table using near real-time, cross-regional data sharing

2. Registry style MDM

This style links and reconciles master data across systems using a central index or registry. Instead of storing the data itself, the registry maintains pointers to the original source systems.

Key features:

• Provides a "virtual" single view of data

• Master data remains in the source systems, with the registry resolving duplicates and inconsistencies

• Low control over master data residing in source systems

Registry-style MDM is easier and faster to implement, as it maintains an index for master data without updating the data in source systems. However, creating global master tables with this approach typically requires additional steps, as the registry itself contains only indexes. This type of MDM implementation is also uncommon in global enterprises.

 Fig. 2: Regional registry-style MDM implementation

3. Centralized (co-existence) style operational MDM

The centralized model creates a master copy of data in a central hub, which becomes the authoritative source for downstream systems while allowing coexistence with source systems.

Key features:

• The central hub both stores and distributes master data

• It enables updates in both the hub and source systems in near real-time, ensuring synchronization

It requires a high upfront and ongoing investment, a longer timeline to implement, and alignment with operational systems that both contribute to and consume master data. This MDM style has historically been popular with large enterprises that require the highest level of control over business-critical master data for operational and analytical systems. Various vendors provide custom MDM platforms (e.g., Informatica, Reltio, Boomi Data Hub, Profisee).

Fig. 3: Regional MDM implementation with bi-directional integration with operational systems and the creation of a global master table using cloud-native data platforms

4. Transactional-style MDM

The transactional style MDM integrates master data governance into the organization’s transactional systems. It enforces data consistency at the point of data creation or update.

Key features:

• Master data updates are tightly integrated with operational transactions

• Real-time data validation and synchronization and ensured

• This type ensures enterprises do not need to build any downstream MDM processes to manage master data

This type of MDM is ideal for every global enterprise; however, it is extremely difficult to achieve, as it requires a significant investment of time, effort, and cost to apply MDM governance directly at the source, given the number of disparate source systems and processes within a global enterprise.

Fig. 4: Transactional enterprise systems with embedded MDM governance

Conclusion

The synergy between MDM and cloud-native platforms empowers enterprises to achieve operational excellence, streamlined processes, and data-driven growth.

Global MDM is a cornerstone for enterprises embracing the GBS operating model, ensuring data consistency, accuracy, and reliability across functions and regions. The success of GBS hinges on seamless collaboration, operational efficiency, and informed decision-making — all of which depend on unified and trustworthy master data.

Managing global data across customers, suppliers, products, parts, and employees is no small task. A well-executed MDM strategy aligned with the GBS framework simplifies this complexity, creating a strong foundation for integrated and efficient operations.

Modern cloud-native platforms have transformed the way organizations implement MDM by providing scalability, flexibility, and real-time cross-regional data sharing. These platforms enable businesses to centralize governance while allowing for local customization. They leverage features like data virtualization, automation, and built-in compliance tools to streamline the creation and maintenance of global master data.

By harnessing the combined potential of GBS and cloud-native MDM solutions, enterprises can optimize processes, boost agility, and uncover consistent, data-driven insights.