What is Master Data Management?

Gartner defines Master Data Management (MDM) as:

“…a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets. Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies, and chart of accounts.”

Understanding Master Data Management

Businesses that follow a master data approach accept the necessity of using multiple data systems in today’s fast paced digital world, but recognize the overall limitation of these systems to work together and support the needs of the business.

Generally, three types of data systems are used in enterprises: transactional data, analytical data, and master data systems. In short, transactional data is operational data that describes time and numbers around business events, think sales, ordering, billing data found in critical information systems. Businesses can then analyze their transactional data to determine business performance, refining it as analytical data. Master data is core business data that describes key organizational entities typically used across many systems, think customers, products, inventory, suppliers, employees, and site locations. These are important non-transactional data points that provide context to events described in transactional data (a purchase is made more significant when a customer’s information is attached to it). The ability of an organization to manage these different data sets directly impacts its competitiveness.

Reltio is a next-generation MDM solution. It offers best in class master data management system capabilities, including identity resolution, data quality, dynamic survivorship for contextual profiles, universal ID across all your operational applications, hierarchies, enterprise data management capabilities and connected graph to manage relationships, progressive stitching to create richer profiles over time, and data governance capabilities.

Master Data Management Domains

Master Data Management (MDM) platforms are designed to pull together multiple domains of data as if it were one. Called multi-domain master data management, these solutions overcome the challenge of using purpose-built single domain MDM solutions traditionally used in legacy systems to manage each master data domain individually. The following single domain solutions are critical for most businesses and implementable under multi-domain platforms.

• B2B or B2C Customer master data management
• Product master data management
• Supplier master data management
• Reference data master data management
• Location master data management
• Asset master data management
• Employee data master data management

This list is limited, however. Most industries will have to track much more industry specific master data, for example, hospitals may keep master data on patients, insurance providers, contracts, beneficiaries, etc. while airlines keep master data on their fleet of planes, and their facilities and equipment. These complex enterprises are well suited to take advantage of MDM’s benefits.

Benefits of Master Data Management

Integrating master data management across all domains grants enterprises the overarching benefit to enforce control over master data throughout the organization and thereby improve the overall quality and connectedness of data. This results in dramatically fewer data errors, reduced redundancy and overall increased operational performance.

Implementing a master data strategy lends the following benefits.

• Improved data quality
• Reduced data duplication
• Increased business efficiencies and agility
• Revealed or improved business insights and decision capabilities
• Reduced time and costs for data stakeholders
• Enhanced regulatory compliance

In particular, cloud MDM solutions benefit large, global enterprises reliant on highly distributed data across multiple locations and systems.

What Differentiates Legacy Master Data Management from Reltio’s Cloud Master Data Management Solution?

The differentiation between the legacy master data management systems and Reltio’s cloud-native MDM solution can be boiled down to three areas. First, legacy MDM systems are too slow for demands today. Second, they lack the ability to scale effectively. Third, they are too rigid to respond to changing business needs in near real-time.

Reltio’s next-generation MDM solution is a highly secure and compliant cloud-native data management platform. It is available on day one and is easy to configure, so you can go live and gain business value very quickly. All updates are pushed without any disruptions.

Reltio’s MDM solution enables an MDM program with an API first approach, which allows you to quickly onboard new data sources or connect to new consuming systems. You can also add or remove attributes on a fly without downtime.

It enriches thousands of attributes with:

• Relationships and hierarchies across people, products, and places with connected graph technology.
• Omnichannel transactions and interactions including functions, channels brands, and geographies
• Actionable insights from data science and analytics including preferences, behavior and intent

Consent & communication preferences with configurable workflows, reference data, task management, granular audit trails, and support for regulations such as GDPR and CCPA.

MDM Examples

MDM in Healthcare

Data errors and inconsistencies in the healthcare industry lead to patient stress and hospital frustration. In one case, a healthcare provider was overwhelmed by a mounting caseload of denied claims due to mismatching provider data in their own systems. After exploring the problem, the provider adopted the implementation of a MDM platform that created a single-source-of-truth so patient data was aligned across domains. Afterwards, there was new confidence and trust in the accurate data they maintained for their 10 million plus patients with an average visitation of 6.5 visits.

MDM for Insurance

Insurance providers rely on accurate data to make millions of claims decisions every year, resulting in billions of dollars in payouts. Without master data management technology and MDM processes in place, client data, premiums data, claim data, and payout data would accumulate separately in siloed departments, leaving a very real opportunity for over and underpayments, or abuse and fraud.

Master data management platforms guarantee the accuracy, integrity, and validity of shared data elements and ensure there is a single-source-of-truth (SSOT) representing an agreement of the critical values across all data domains. In the case of an insurance provider, the same client-based critical values would be shared across all systems. By “connecting” master data, providers then can be sure a client is caught up on their premiums before any payouts and then payout appropriately.

Types of Master Data

There are various types of master data, each relevant to different areas of business operations. The most common types of master data include:

• Customer Data: Information related to customers, such as names, contact details, purchase history, and preferences. Proper management of customer data is crucial for enhancing customer experience and maintaining accurate sales and marketing information.
• Product Data: Details related to the products or services a business sells, including product descriptions, specifications, pricing, and inventory levels. MDM helps ensure that product data is accurate and consistent across sales channels, marketing platforms, and supply chain systems.
• Supplier Data: Information about suppliers or vendors, including contact information, terms of agreements, and transaction history. Accurate supplier data is essential for managing procurement processes and vendor relationships.
• Location Data: Geographical data related to locations of interest, such as office addresses, store locations, or warehouses. Proper management of location data helps organizations in logistics, supply chain optimization, and customer service.

Key Components of Master Data Management

To implement MDM effectively, businesses typically rely on several key components that help manage and govern their master data. These components are essential to ensuring the success of an MDM initiative and include:

• Data Governance: Data governance is the process of establishing policies, standards, and procedures for managing master data. It involves assigning roles and responsibilities to individuals or teams within the organization to ensure that master data is consistent, compliant, and properly managed across all systems. Governance also helps ensure that data-related decisions align with organizational objectives and regulations, and it defines how master data should be used, updated, and maintained.
• Data Integration: MDM requires seamless integration across different systems, databases, and applications where master data is stored. Data integration is essential for ensuring that master data is consistent and synchronized across all relevant platforms. This component often involves the use of Extract, Transform, Load (ETL) processes and Application Programming Interfaces (APIs) to enable the smooth flow of data between various systems.
• Data Quality: Ensuring data quality is a cornerstone of MDM. Data quality initiatives focus on eliminating duplicates, correcting errors, and ensuring that data is accurate, complete, and consistent. Automated data cleansing and validation tools are commonly used to ensure the quality of master data. High-quality data allows organizations to make better business decisions, improve customer experiences, and drive operational efficiencies.
• Data Stewardship: Data stewardship involves assigning individuals or teams with the responsibility for managing and maintaining master data throughout its lifecycle. These data stewards are responsible for ensuring that master data is accurate, complete, and aligned with data governance policies. Data stewardship ensures accountability for data management and helps mitigate the risk of data becoming outdated, duplicated, or inaccurate.
• Data Security and Privacy: Master data often contains sensitive information, such as customer data or financial records. Ensuring the security and privacy of this data is a critical component of MDM. MDM solutions must comply with data privacy regulations, such as the General Data Protection Regulation (GDPR), and protect data from unauthorized access, breaches, and cyber threats. Encryption, access control, and auditing mechanisms are often part of MDM security practices.
• Data Synchronization: Synchronizing master data across an organization is a critical function of MDM. Data synchronization ensures that changes made to master data in one system are reflected across all other systems that rely on that data. This helps maintain consistency and reduces the risk of errors caused by outdated or incorrect information being used in decision-making processes.

Putting Master Data Management into Practice

Master data management is crucial for organizations aiming to maintain accurate, consistent, and complete data across their systems. By centralizing core business information, MDM ensures that data related to customers, products, suppliers, and other critical entities is harmonized and accessible across different departments. Effective MDM leads to improved decision-making, streamlined operations, and enhanced customer experiences. It also mitigates risks associated with duplicate or outdated data, leading to better compliance, and it provides a foundation for analytics and digital transformation efforts.

Reltio’s Multidomain Master Data Management (MDM) platform stands out for its ability to offer a modern, cloud-native solution that delivers agility, scalability, and real-time insights. Built with an API-first approach, Reltio integrates seamlessly with other business systems, ensuring that data is up-to-date and available when needed.

One of the platform’s key strengths is its ability to provide multi-domain MDM, which allows organizations to manage data across various domains such as customer, product, location, and supplier, within a single platform. Its advanced machine learning capabilities help in resolving data conflicts, enriching data quality, and automatically merging duplicates. Furthermore, Reltio provides flexible deployment options, robust security features, and compliance with industry standards, making it an ideal choice for businesses that prioritize data quality, security, and real-time operational insights.