What developers must know about master data management

Until now, as a developer, you’ve been able to develop specialized mobile applications, APIs, and internal workflow applications without a lot of interference from the data architecture, analytics, and marketing departments. Now, for the first time, they’re asking you about integrating a new application you are developing with an MDM (master data management) platform.

If you’re trying to understand what master data management is all about, you’re not alone. The practice has a rich history. Modern systems appeared in the 1990s, but they weren’t easy to adopt. Many businesses struggle to maintain clean customer contact lists, improve data quality, and institute proactive data governance, but it’s only been in the past several years that master data management has become more mainstream.

As more companies invest in analytics, improve customer experiences, and respond to increasing regulations, organizations can drive significant competitive advantages with a master data management program.

To understand what these systems do, it’s best to consider a working example.

Improving the retail customer experience with master data management

Let’s say the application that you are developing is a basic e-commerce mobile app that allows users to select one of a handful of products to purchase, register with the site, and then submit a credit card for payment. You estimate the features with your agile development team and expect to build a few Web pages, several database tables, and an integration with the payment engine.

Your application is not the only one querying and updating customer and product data. Several other small e-commerce applications and other mobile apps support customer programs. Internally, the marketing department uses several SaaS tools to interact with customers and reach new prospects. The finance department has its own data lake for forecasting, and the fulfillment teams use several tools to complete orders.

The data on customers, products, supply chains, and fulfillment is spread across many databases. As one of the lead developers, you can see there’s mounting technical debt maintaining the data across these systems. It’s a painful, somewhat manual process to update all of these systems when new products become available, but it’s not something that’s done very often.

But then one of several things change that can make master data management strategically important:

• As customers interact with your company’s products and services in stores, apps, and other channels, there is greater value in personalizing their experiences and tailoring marketing campaigns to their needs.
• Many retail companies update their product lines frequently and must share more detailed product information with consumers.
• Increased supply chain risks mean that many organizations must track all steps in the manufacturing process.
• Organizations looking to acquire other retail businesses may need streamlined ways to connect data across multiple customer, product, and fulfillment systems.
• Regulations such as General Data Protection Regulation on customer data, EU 1169 on food labeling, and GS1 standards on the supply chain are also driving data quality and data mastering standards.

There are missed opportunities and risks when key business data is stored in disconnected data silos. You can gain long-term benefits by centrally managing critical data throughout your organization.

Master data management also has uses in other industries, including banking, insurance, manufacturing, pharmaceuticals, life sciences, and consumer packaged goods.

What types of data require master data management

Master data management aims to centralize information on the key entities used in business transactions. They define the who, what, and where on business transactions.

• Who your organization works with, such as customers, employees, suppliers, vendors, distribution channels, and other partners.
• What attributes define the products or services offered, as well as assets owned or managed by the organization.
• What additional contextual information, such as location data, is referenced by other entities and in transactions.

How master data management systems work

You can think of a master data management system as a two-way clearinghouse between multiple systems that read and write data about a business entity. If five different systems need access and create data about customers, then they can publish and subscribe to customer data through the MDM system.

MDM systems provide automation and tools to manage this data. For example, if two systems try to update a customer’s address, the MDM should be configured with the logic to decide which address to accept. MDMs often have tools for data stewards who can step in and resolve conflicts that the business logic can’t solve.

As the MDM system becomes this clearinghouse, it can provide many services that aid in compliance. Data can be archived with full data lineage so compliance teams can research when, by whom, and how data was modified. Policies around data access rights, encryption, and data masking can also be centralized.

As many MDM systems now operate in the cloud, they also serve as master data repositories. That means that instead of every application storing local copies of customer, product, and other entity data, they can query and update the data directly in the MDM system. This creates a trade-off between convenience and cost. Applications with lower transaction volumes may be designed with thinner back-end databases and instead, connect to the MDM’s APIs for entity data. In contrast, it may be more reliable to replicate this data for higher volume systems. Either way, the MDM system stores the source of truth of the entity data.

Some MDMs are domain-specific and provide out-of-the-box starting schemas for common and industry-specific entities. For example, customer 360 platforms (sometimes called customer data platforms) specialize in storing customer data, and product information management systems are specific to product information. MDMs provide generalized approaches that work for customers, products, and other entities.

Recognize that a CRM system is not a customer master data management platform, nor can most e-commerce platforms easily act as data masters. These systems provide workflow around customer and product data sets, but in general, they’re not designed with the data models, services, and tools to master data across many connected applications.

Where to learn more about master data management

As with all business practices, instituting the system often requires more than the technical steps of installing and integrating the technology. Establishing a master data management platform usually requires changes to business processes, new organization roles, and training for new responsibilities.

If this technology interests you, consider reading this free ebook on master data management, reviewing these nine master data management certifications, or joining one of these LinkedIn groups on data management.