By Scott Moore, Director of Presales, Semarchy

Introduction to Master Data Management

In today’s data-driven world, one may wonder, what is Master Data Management? Often referred to as MDM, it is the core process used to manage, centralize, organize, categorize, localize, synchronize, and enrich master data, according to the business rules of your company’s unique sales, marketing, and operational strategies.

Why is it important?

You’re probably wondering: why is Master Data Management important? Master Data Management, or MDM, is critical to any business strategy in our increasingly data-driven world. It serves as the backbone for organizing, managing, and interpreting vast amounts of complex data. The emphasis placed on MDM is a testament to the power of quality data in fueling business growth, mitigating risk, and optimizing operations.

Learn more: why is Master Data Management important?

What are the benefits?

The benefits of Master Data Management are manifold. At its core, MDM is about efficiency. By creating a centralized hub of accurate, consistent, and up-to-date data, MDM systems eliminate redundant data processes and streamline information sharing across an organization.

This means that instead of having multiple departments maintaining their own data sets, potentially leading to discrepancies and inaccuracies, there is one trusted source of truth. This reduces administrative overhead and ensures that all departments work from the same playbook, resulting in more efficient processes.

MDM is also a powerful tool for reducing errors. Inaccurate data can lead to a wide range of problems, from poor business decisions and missed opportunities to non-compliance issues and customer dissatisfaction. By implementing robust data validation, quality rules, and automated cleansing processes, MDM systems can significantly reduce the likelihood of these errors, ensuring that the data used in critical business decisions is as accurate and reliable as possible.

But perhaps the most compelling aspect of MDM is its capacity to drive better decisions. Data is often considered the lifeblood of an organization – the raw material that, when correctly interpreted, can reveal valuable insights and guide strategic decision-making. However, for data to fulfill this role, it needs to be reliable, accessible, and intelligible. MDM ensures this by providing a consistent view of key data entities like customers, products, suppliers, and assets across the organization.

By enabling a comprehensive 360-degree view of these entities, MDM allows organizations to uncover trends, identify opportunities, anticipate challenges, and better understand their customers’ needs. This facilitates more informed, proactive decision-making, ultimately driving business success.

Master Data Management in the enterprise

Enterprise Master Data Management (Enterprise MDM) is a strategic approach to managing the most critical data within a business, such as data about customers, products, suppliers, employees, and more. Recognizing data as a key asset, much like human resources, intellectual property, or physical assets, Enterprise MDM aims to govern this crucial information in a systematic and consistent manner across the entire organization.

Enterprise MDM aims to deliver a unified, accurate, and reliable view of an organization’s data, spanning across different departments, business units, locations, and even external partners. This single source of truth is achieved through data consolidation, data integration, data quality enhancement, data governance, and data stewardship processes.

One of the key components of Enterprise MDM is data consolidation. This involves collecting data from multiple disparate sources and bringing it together in a central repository. This allows different parts of the organization to access the same data, eliminating discrepancies and conflicting interpretations.

Strategy for Master Data Management

A Master Data Management strategy serves as a blueprint that outlines how an organization will manage, control, and use its master data to achieve its business objectives. This strategic approach to data handling is critical for ensuring that data is consistent, accurate, and reliable across the entire enterprise.

An effective MDM strategy begins with understanding the organization’s business goals and determining how master data can support those objectives. This may include improving decision-making, enhancing customer service, streamlining operations, complying with regulations, or driving innovation.

The strategy should identify the types of master data the organization relies on, such as customer, product, supplier, employee, or asset data. This helps to prioritize the domains that need to be addressed by the MDM program.

The strategy also defines the processes for handling master data throughout its lifecycle. This includes how data is created or collected, how it is validated and cleaned, how it is stored, how it is integrated with other data sources, and how it is archived or disposed of when it’s no longer needed.

The MDM strategy also covers how master data is modified. For example, it may establish processes for updating data when it changes, merging records when duplicates are found, and enriching data with information from other sources.

Storage strategies are another crucial aspect of an MDM strategy. This includes deciding where data will be stored (on-premises, in the cloud, or in a hybrid environment), how it will be backed up to prevent data loss, and how it will be secured to protect sensitive information.

Finally, the MDM strategy addresses how master data will be retrieved and used. This includes defining who will have access to the data, what they can do with it, and how they can use it. It also involves setting up systems for searching, reporting, and analyzing the data and for sharing data between different systems and business units.

Learn more about Master Data Management strategy.

Frameworks for Master Data Management

Master Data Management frameworks provide a structured and standardized approach to managing, maintaining, and leveraging master data within an organization. They are vital in setting up a robust MDM program and generally consist of four key components: governance, processes, technology, and measurement metrics.

Learn more about Master Data Management frameworks.

How to implement Master Data Management

Master Data Management implementation is a comprehensive process that involves the deployment of strategies, technologies, and best practices to manage an organization’s critical data. It’s an essential task for businesses aiming to enhance data quality, streamline data sharing across different departments, and improve overall operational efficiency.

Here’s a deeper look at the key steps involved in MDM implementation.

Governance: Governance forms the backbone of any MDM framework. It provides the policies, standards, and rules that guide how master data should be collected, stored, processed, and used. It sets out the roles and responsibilities of different organization members, including the data stewards who are primarily responsible for managing and maintaining the data. Additionally, governance involves ensuring compliance with legal and regulatory requirements related to data handling.
Establishing Policies: Policies are the foundation of an effective MDM program. These rules and guidelines determine how master data will be handled within the organization. They cover a wide range of topics, such as data privacy, data quality, data access, data archiving, data security, and data governance. These policies provide a clear framework for what is acceptable in terms of data management and what is not, ensuring all data is handled in a way that aligns with the organization’s objectives and complies with applicable regulations.
Developing Processes: Once the policies are in place, the next step is to develop the processes needed to manage the master data. This includes defining the procedures for creating, collecting, validating, storing, maintaining, and disposing of master data. The processes should be designed to ensure data accuracy, consistency, and completeness. They should also facilitate effective data sharing and collaboration across the organization. Importantly, these processes need to be flexible enough to adapt to changing business needs and technological advancements.
Integrating Technologies: The right technologies are crucial to support the MDM policies and processes. This includes MDM software that provides a centralized repository for master data, data integration software to combine data from various sources, data quality tools to cleanse and enrich the data, and data analytics tools to extract meaningful insights from the data. These technologies should be chosen based on the organization’s specific needs, the type and volume of data it handles, and its overall business goals.
Training and Change Management: Implementing MDM often involves significant changes in how people work with data. This means it’s essential to provide adequate training for all staff members who will manage and use the master data. This includes data stewards, who have a primary role in overseeing the data, as well as other users who need to understand the importance of maintaining data quality and following the established policies and processes.
Continuous Monitoring and Improvement: MDM implementation isn’t a one-time project but an ongoing process. It requires continuous monitoring to ensure that the policies, processes, and technologies deliver the desired outcomes. This involves regularly measuring the quality of the master data, the efficiency of the MDM processes, and the value that the MDM program is bringing to the organization. Based on these measurements, adjustments can be made to improve the effectiveness of the MDM program further.

Learn more about Master Data Management implementation.

Master Data Management scope

Master Data Management (MDM) carries an extensive scope, reaching into diverse domains of an organization’s critical information, such as customer profiles, product specifications, asset records, and geographic location data. Through MDM, businesses can ensure the accuracy of this data, minimizing errors and discrepancies across different systems and departments. Additionally, MDM promotes uniformity and semantic consistency, meaning that shared master data is standardized, interpreted, and used the same way across the entire organization.

Learn how to scope our your Master Data Management requirements.

What is Master Data Management software? Systems, platforms and tools

Master Data Management (MDM) software is a sophisticated system designed to define, manage, and provide access to master data entities, acting as a central repository for an organization’s critical information. It represents the technological heart of an MDM strategy, providing the necessary tools and functionalities to implement MDM principles effectively. By facilitating the execution of MDM practices, such as data integration, data quality control, and data governance, an MDM solution plays an instrumental role in maintaining accurate, consistent, and reliable master data across an enterprise.

Learn more: what is Master Data Management software?

Types of MDM

There are several Master Data Management types, each focusing on a particular kind of master data. Understanding these types helps an organization choose the right MDM strategy based on its specific needs and priorities.

Party

Party Master Data Management type concerns data about parties or entities involved in the organization’s business transactions. It includes:

Supplier Master Data Management: This involves managing data related to suppliers, including contact information, contractual details, product or service specifics, and performance metrics.
Materials Master Data Management: This involves managing data about materials or resources used in the production process, including their characteristics, quantities, and sources
Customer Master Data Management: This involves managing data about customers, including personal information, transaction history, preferences, and feedback. It’s vital for improving customer service and personalizing marketing efforts.

Place and location

Location Master Data Management manages data about physical and virtual locations, such as addresses, coordinates, shipping routes, store locations, and warehouses, typically by using location MDM software. It’s crucial for logistics, supply chain management, and service delivery.

Products and services

This involves managing data related to the products or services offered by the organization. It includes:

Product Master Data Management: This involves managing data, often using product MDM software about products, such as specifications, pricing, availability, and lifecycle stages, typically by using product MDM software. It supports product development, marketing, sales, and customer service.
Service Master Data Management: This involves managing data about services, such as descriptions, pricing, availability, and performance metrics. It helps improve service delivery and customer satisfaction.

Employee Master Data Management

Employee Master Data Management manages data about employees, including personal information, job roles, performance evaluations, and training records, typically by using employee MDM software. It’s important for human resources management, performance management, and workforce planning.

Reference Master Data Management

Reference Master Data Management involves managing data that is used to classify or categorize other data, such as product categories, department codes, and industry standards. It’s essential for data integration, reporting, and analysis.

Multidomain Master Data Management

Multidomain Master Data Management manages multiple types of master data within a single MDM system (or, in other words, a multidomain MDM system). It provides a holistic view of the organization’s master data, facilitating cross-domain insights and improving overall data consistency and quality.

Learn more about master data types.

What MDM Isn’t

Master Data Management (MDM) does not include transactional or log data, which are fundamentally different from master data.

Transactional Data: Transactional data is not master data. It involves data generated from all business transactions, such as sales, deliveries, or invoices.
Log Data: Like transactional data, log data is not master data. This is data generated by computer servers, often used for troubleshooting or security auditing.

How does master data ‘metadata’ fit in?

Metadata, often described as ‘data about data’, plays a pivotal role in Master Data Management (MDM). It provides critical information about the master data, such as its origin, structure, type, and purpose, which aids in understanding and utilizing the master data effectively. Additionally, metadata establishes and describes relationships between different master data entities, enabling a more coherent and interconnected view of an organization’s data assets.

How does Master Data Management ‘big data’ fit in?

Big data, characterized by its volume, velocity, and variety, often lacks the structure and consistency inherent in master data. By integrating Master Data Management (MDM) with big data, organizations can inject a level of structure and standardization into their vast data stores, enhancing data usability and integrity. This amalgamation can lead to more comprehensive and accurate data analyses, bolstering decision-making capabilities and driving more strategic business outcomes.

Master Data Management in various industries

Master Data Management (MDM) is a linchpin in numerous industries, enabling organizations to manage their unique data sets effectively. Let’s explore the role of MDM in some key sectors.

Healthcare: Healthcare Master Data Management is used to manage data related to patients, treatments, medical records, healthcare providers, and medical supplies. It enhances patient care by providing a unified view of patient information, streamlines medical inventory management, and supports regulatory compliance. Healthcare organizations with complex data requirements should consider using specialized healthcare MDM software.
Finance: Financial institutions use finance MDM software to manage data related to customers, accounts, transactions, and regulatory reports. Master Data Management for financial services aids in risk management, enhances customer service, supports accurate financial reporting, and promotes compliance with financial regulations.
Insurance: Insurance Master Data Management is used to manage data about policyholders, policies, claims, and risk assessments. It supports accurate underwriting, improves claims processing, helps detect fraudulent activities, and assists in meeting regulatory requirements.
Education: Educational institutions leverage MDM to manage data about students, teachers, courses, grades, and resources. Master Data Management in higher education improves student services, enhances academic planning, facilitates research, and promotes effective resource allocation.
Retail: Retailers use retail MDM software to manage data related to customers, products, sales, and inventory. Retail Master Data Management aids in personalizing customer experiences, optimizing inventory management, enhancing product management, and boosting sales analysis.
Manufacturing: Manufacturing Master Data Management is used to manage data about products, materials, suppliers, production processes, and quality checks. It enhances supply chain management, improves production planning, ensures product quality, and supports accurate product costing, especially when specialized manufacturing MDM software is used.

Best practices

Adherence to best practices is crucial in Master Data Management (MDM) to optimize its effectiveness and utility. Master data management best practice begins with establishing robust data governance, which involves defining clear policies, procedures, and roles to control how master data is created, updated, used, and maintained across the organization. It also involves using a robust data governance software.

Additionally, ensuring data quality in Master Data Management is paramount. It’s vital to implement stringent validation, cleansing, and enrichment processes to maintain the accuracy, consistency, and completeness of master data.

Lastly, providing continuous monitoring and maintenance of master data is necessary to promptly detect and rectify any issues, guarantee data integrity over time, and accommodate changes in business requirements or data landscapes.

Case studies and examples

Now that we know what it is, and how to do it well, how about some examples of Master Data Management?

Semarchy’s MDM solutions have transformed data management in various organizations, leading to improved data quality, streamlined operations, and enhanced decision-making capabilities. To illustrate this, let’s delve into some Master Data Management case studies, and learn how Shake Shack, Red Wing Shoes, and Chantelle Group have harnessed the power of Semarchy’s MDM solutions.

Shake Shack

Overview: Shake Shack embarked on its MDM journey with a need for a solution that could get up and running quickly and scale with its growth. They found their answer in Semarchy.

The Problem: The primary asset Shake Shack aimed to master was the “Shack List,” a comprehensive database of all their restaurants, which necessitated a reliable MDM solution.

The Solution: Semarchy helped Shake Shack centralize data from diverse sources and systems, significantly enhancing data accuracy and quality. Their iterative approach to project implementation led to remarkable improvements in digital transformation and operational efficiency.

Red Wing Shoes

Overview: With rapid expansion in both retail and e-commerce, Red Wing Shoes turned to Semarchy’s xDM to establish a central data hub for managing customer data, thereby enriching the customer experience with a 360° view across all company divisions.

The Problem: Red Wing Shoes identified the need for a central data hub to manage their burgeoning customer data more effectively, enabling a comprehensive view for all departments and thus augmenting customer knowledge.

The Solution: Semarchy empowered Red Wing Shoes to address their data quality and Master Data Management issues within a single system. This resulted in the creation of a unified golden record for each customer, providing real-time data access to marketing, sales, and customer service teams.

Chantelle Group

Overview: Chantelle Group selected Semarchy xDI for a digital transformation initiative aimed at adapting to customer communication channels and experimenting with new sales models. This included the implementation of omnichannel strategies to improve the customer experience.

The Problem: As a multi-brand company and a creative studio, Chantelle Group’s business model has transitioned towards individual brands opening their own stores, both physical and online. This expansion necessitated a comprehensive and agile system to manage their B2B and B2C requirements across multiple companies and information systems.

The Solution: Semarchy allowed Chantelle Group to become significantly more agile, enabling them to respond quickly to new business use cases and have greater flexibility. The resource availability and faster response times have been hailed as the best improvement in the Information System Department in recent years.

Statistics

MDM is gaining importance across industries, a fact reflected in various Master Data Management statistics. In 2020, Gartner reported that the MDM market was valued at $1.61 billion, showcasing the substantial investment that organizations are making in this area.

This figure is expected to surge in the coming years as businesses increasingly recognize the critical role of high-quality, well-managed data in driving operational efficiency, enhancing decision-making, and improving customer experience.

In fact, according to a report by MarketsandMarkets, the MDM market size is projected to grow from $11.3 billion in 2020 to $27.9 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 19.8% during the forecast period. This consistent rise is a testament to MDM’s integral role in a company’s data strategy and its capacity to deliver value.

Check out more Master Data Management statistics.

Next steps and resources for starting your MDM journey

Embarking on your Master Data Management (MDM) journey can be a game-changer for your organization. Here are some valuable resources to assist you in understanding MDM better and starting your journey.

Resources for further reading

Driving Modern Business with Governed Data Integration eBook

Governed data integration is becoming integral to modern businesses. It merges three key processes: discovering data across the enterprise, integrating data for analytics or operations, and governing data with features such as MDM and cataloging.

An increasing number of organizations are embracing these platforms to streamline their data management. Eckerson Group’s Tech Opportunity Brief will help you understand the challenges that governed data integration addresses, its key functionalities, and the specific use cases across various industries. It also includes recommendations from leading industry analysts.

Get a copy of Driving Modern Business with Governed Data Integration eBook

Eckerson Group Report – Best Practices in Master Data Management: Improving Intelligence through Data Governance

Master data management involves creating a trusted, comprehensive set of records for the core entities of a business by sourcing information from a wide array of systems. These records provide a centralized source of truth, enhancing organizational understanding and decision-making. Succeeding with an MDM strategy involves careful planning from both a technical and procedural perspective. This whitepaper from Eckerson Group will guide you through the necessary steps.

Get a copy of Eckerson Group Report – Best Practices in Master Data Management: Improving Intelligence through Data Governance

Data Integration and Governance for the Modern Enterprise

This best practices report offers insights on how to utilize Master Data Management and Data Integration tools to achieve your data compliance objectives.

Get a copy of Data Integration and Governance for the Modern Enterprise

Next steps

Master Data Management Solution Selection Guide

This independent assessment tool, created by industry expert Henrik Liliendahl, is designed to help you select the MDM solution that best fits your organization’s needs.

Read the Master Data Management Solution Selection Guide

Explore Semarchy’s xDM for Master Data Management

Semarchy’s xDM solution is a scalable, flexible, and easy-to-implement tool that can transform your organization’s data management approach. It enables you to rapidly create and deploy data-rich applications, achieve high-quality golden records, and significantly enhance your data governance.

Get familiar with Semarchy’s xDM for Master Data Management

Schedule a custom demo

Finally, to get a hands-on experience and understand how Semarchy’s xDM solution can work for your organization, schedule a custom demo. This will allow you to see the platform’s capabilities in action and learn how it can address your specific data management needs.

What Is Master Data Management? Unleashing the Power of Organized Data.