Master Data Management: An Overview

What is Master Data Management? Why is it important for businesses? Let’s explore Master Data Management! 

Master Data Management (MDM) helps businesses improve the consistency and quality of key data such as product data, customer data, location data, and more. 

Today, many businesses, especially global enterprises, have hundreds of separate applications and systems (like ERP, CRM) where data flows through various departments or divisions. This data can become duplicated or outdated. When this happens, answering even the most basic questions about any business performance indicator or KPI becomes challenging. 

For example, basic questions like “Who are our most profitable customers?”, “Which product has the highest profit?” or “How many employees do we have?” become difficult to answer. 

Accurate, timely information is essential. The number of data sources is increasing, making it a significant challenge to manage them consistently and keep them updated so all departments in the business use the same set of information. 

To address these challenges, businesses turn to Master Data Management (MDM). 

What is Master Data? Understanding Key Data 

Most software systems have a list of data shared and used by several system applications. 

For example, a typical ERP system will have at least the Customer Master, Item Master, and Account Master data lists. This master data is often one of the company’s most valuable assets. In fact, it is not unusual for a company to be acquired mainly to access its Customer Master data.

Basic Definition of Master Data 

Understanding master data starts with grasping the terminology. Some master data elements are well understood and easily identifiable, such as “customer” and “product.” Many people define master data simply by listing agreed master data elements, such as: Customer, Product, Location, Employee, and Asset. 

However, identifying the data elements that need to be managed by an MDM software is much more complex and goes beyond such simple definitions. This complexity has caused much confusion around the question, “What is master data?” 

To provide a comprehensive answer to this question, we can consider six types of data commonly found in companies: 

1. Unstructured Data: Data found in emails, white papers, magazine articles, company intranet portals, product specifications, marketing collateral, and PDF files. 
2. Transactional Data: Data about business events (usually related to system transactions such as sales, deliveries, invoices, incident reports, complaints, and other monetary and non-monetary interactions) with historical significance or necessary for analysis by other systems. Transactional data are unit-level transactions using master data entities. Unlike master data, transactions are temporary and instantaneous. 
3. Metadata: Data about other data. It can reside in formal repositories or in various forms, such as XML documents, report definitions, database column descriptions, log files, connections, and configuration files. 
4. Hierarchical Data: Data storing the relationships between other data. It can be stored as part of an accounting system or separately as descriptions of real-world relationships, such as company organizational structures or product lines. Hierarchical data is sometimes considered a super MDM domain because it is crucial and sometimes uncovers relationships between master data. 
5. Reference Data: A special type of master data used to classify other data or link data to information beyond the enterprise boundaries. Reference data can be shared across master data or transactional data objects (e.g., countries, currencies, time zones, payment terms). 
6. Master Data: Core data describing objects around the business’s operations. It usually changes infrequently and can include necessary reference data for business operations. Master data is inherently non-transactional but describes transactions. Master data includes four domains and sub-domains or entity types within those domains. 

The Four Domains of Master Data: 

• Customer: Includes sub-domains like customers, employees, and salespeople. 

• Product: Includes sub-domains like products, parts, stores, and assets. 

• Location: Includes sub-domains like office locations and geographic divisions. 

• Other: Includes sub-domains like contracts, warranties, and licenses. 

Some of these subdomains can be further subdivided. For example, customers can be categorized based on incentives and history, as your company may have regular customers, first-time customers, and so on. Meanwhile, products can be more deeply divided according to fields and industries. This level of detail is very useful because the requirements, lifecycle, and CRUD cycles for a product in the Consumer-Packaged Goods (CPG) sector can be very different from those for products in the clothing industry. The level of detail in the domains is determined by the degree of difference between the attributes of the entities within them. 

Master Data Management (MDM) Explained 

MDM involves technology, tools, and processes that ensure master data is coordinated throughout the enterprise. MDM provides unified master data services that deliver accurate, consistent, and complete master data across the enterprise and to business partners. 

Key Points in this Definition: 

MDM is not just a technology issue: In many cases, fundamental changes to business processes are required to maintain clean master data, and some of the toughest MDM issues are more political than technical. 

MDM includes both creation and maintenance of master data: Investing time, money, and effort to create a consistent, clean master dataset is wasted unless the solution includes tools and processes to keep master data clean and consistent as it is updated and expanded over time. 

Why is MDM Important for Businesses? 

Depending on the technology used, MDM can include a single domain (customer, product, location, or other) or multiple domains. The benefits of multi-domain MDM include consistent data management experience, minimized technology footprint, the ability to share reference data across domains, lower total cost of ownership, and higher return on investment. 

For information departments, finding valuable data is like “panning for gold.” Therefore, safeguarding and managing these valuable assets is a tough job due to competitors’ scrutiny. MDM not only aims to keep information within the enterprise safe from breaches and theft but also organizes this data clearly and accessibly. 

In summary, the advantages of MDM for businesses include: 

• Eliminating duplicate data: MDM helps eliminate duplications or inconsistencies in core data, reducing errors and data loss. 

• Enhancing data quality: MDM improves the quality of core data by establishing standards, rules, processes for data collection, analysis, and maintenance. This results in a reliable data source that supports assessment and reporting. 

• Saving time and effort: Using MDM in managing large data sets significantly saves time and effort in data entry, verification, and information updates. Business processes like sales, marketing, and supply chain management are effectively optimized. 

• Security: MDM ensures the security of the business’s system, protecting it from cyber-attacks and unauthorized data access through advanced security measures. 

Key Elements of an Effective MDM Program 

Given that MDM is not just a technology issue, meaning you cannot simply install a piece of technology and organize everything, what does a strong MDM program require? 

Before starting a master data management program, your MDM strategy should be built on six principles: 

• Governance: Management directives, policies, principles, and qualities to promote access to accurate and certified master data. Essentially, this is the process through which a cross-functional team defines various aspects of the MDM program. 

• Measurement: How are you performing based on stated goals? Measurement should consider data quality and continuous improvement. 

• Organization: Choosing the right people for the positions throughout the MDM program, including master data owners, data managers, and governance participants. 

• Policy: Requirements, policies, and standards that the MDM program must adhere to. 

• Process: Defined processes within the data lifecycle used to manage master data. 

• Technology: Master data hubs and any supporting technology. 

Considerations when Starting Your MDM Program 

PRO TIP: Starting with a few master data sources is an easy path. If proven successful, you can then decide to expand.

Your MDM project plan will be influenced by requirements, priorities, available resources, timelines, and the scale of the problem. Most MDM projects include at least the following stages: 

• Identify master data sources 
• Identify producers and consumers of master data 
• Collect and analyze metadata for your master data 
• Assign data management roles 
• Implement a data governance program and data governance council 
• Develop a master data model 
• Choose a toolset 
• Design infrastructure 
• Create and test master data 
• Modify production and consumption systems 
• Implement maintenance processes 

As you see, MDM is a complex process that can take a long time. Like most things in software, the key to success is to implement MDM step by step so the business realizes short-term benefits while the complete project is a long-term process. 

Moreover, no MDM project can succeed without the support and participation of business users. IT professionals lack the domain knowledge to create and maintain high-quality master data. Any MDM project that does not include changes to the processes for creating, maintaining, and validating master data is likely to fail. 

Conclusion on Master Data Management 

MDM (Master Data Management) is the process of managing, updating, and synchronizing key data within an organization. It is the bridge that helps businesses enhance the consistency and quality of essential data, such as information about products, customers, locations, and many other aspects. 

In today’s context, businesses, especially global corporations, use hundreds of different applications and systems (like ERP, CRM). Data often flows through many departments and can easily become duplicated or inconsistent. To overcome these challenges, businesses have turned to master data management (MDM). 

Simplifying Your MDM Journey with SimpleMDG 

To further enhance the MDM experience, SimpleMDG, a comprehensive master data governance solution on SAP BTP, offers a streamlined and user-friendly approach to managing your master data. SimpleMDG provides a comprehensive suite of tools designed to address the common challenges faced by businesses in maintaining accurate, consistent, and up-to-date master data across various domains.  

With its intuitive interface and robust features, SimpleMDG ensures that businesses can easily implement and sustain effective MDM practices. By integrating seamlessly with existing systems, SimpleMDG reduces the complexity of data management, allowing businesses to focus on leveraging their master data for strategic decision-making and operational efficiency.