I have participated in many discussions about master data management (MDM) being “just” about improving the quality of master data. Although master data management includes the discipline of data quality, it has a much broader scope. MDM introduces a new approach for managing data that isn't in scope of traditional data quality solutions.

Here are three questions I normally hear about the intersection of MDM and data quality.

1. What make MDM different from data quality?

MDM consists of the processes, policies, standards and tools to consistently manage master data and provide a single point of reference. On the other hand, data quality, at its core, is about the fitness and usability of data. Data quality focusses on correctness and completeness of the individual records as well as the consistency and de-duplication in sets of records.

As you can see, these definitions differ  in scope and approach. Data quality is part of master data management, although it's not the only  aim of an MDM initiative.

2. What are the added capabilities of Master Data Management compared to Data Quality?

MDM brings capabilities to the table that data quality does not offer. MDM focuses on data issues that arise because of the distributed system landscape and complex distributed supply chains of today's organizations. MDM has a much stronger focus on processes (on the system and organization level) to collaboratively improve master data throughout the whole corporation. With its focus on processes and organization, MDM acts while data is processed in the company’s various business processes. Let me elaborate this a little further by asking the question: What is the typical goal of an MDM project?

In many cases, MDM is about synchronizing and merging information stored in multiple operational systems. The goal might be to sync customer records in the ERP system with all other systems – and to make sure that, when a customer contacts the organization through any channel, he or she can be correctly identified and addressed. MDM can also provide a consolidated product and supplier data reference, allowing the purchasing department to track all supplier, purchased materials and related element.

To accomplish these goals, master data needs to validated and corrected but also synchronized throughout the whole system landscape of the supply change. So, the sole intention of MDM is to integrate into existing business processes and ensure high-quality master data to be available in all systems at any time.

For example, if a corporation maintains everything in one ERP system, an MDM project wouldn’t be needed. Data quality would still be important to make sure the individual data records are fit for purpose. But, there are few organizations that have just one system of record. Companies need MDM when they try to synchronize data elements across systems and organization units. The value of MDM is to link and sync data from multiple sources to better leverage data about business partners, materials and its related items.

3. What additional benefit does Master Data Management offer?

MDM allows the business to  function better and grow faster. The reason companies invest into MDM is because they want to leverage digital business channels, both internal and external.

The first business value of MDM is to improve the business processes in the digital economy rather than focusing  solely on the quality of data. Here, data quality isn't the goal, but it is rather an important component that helps enable the primary goal which are automated supply chain processes internally and externally. With the increasing need to automate business processes with partners and customers, the value of a true master data hub increases both in operations and in analytics.