Master data management (MDM) is the discipline of creating one trusted master reference (a single version of the truth) for all important business data, such as product data, customer data, asset data, finance data, and more. MDM helps ensure businesses don’t use multiple, potentially inconsistent versions of data in different parts of business, including processes, operations, and analytics and reporting.
Master data management is changing fast with increased digitization and acceleration in the move to cloud for applications. The coronavirus pandemic has increased the pace for that move. Some of the key trends observed in the MDM market are as follows:
With the growing amount of data being processed, the demand for more automation is growing as well. In master data maintenance processes this includes value proposals, duplicate detection, or suggesting actions to improve the data quality. Most companies establish MDM to aim for two key goals. One is to reach and sustain high master data quality, the other is to become more efficient in their operations. Artificial intelligence / machine learning (AI / ML) is generally expected to take on a bigger role in enterprise applications in the future. To better support managing more and more data, smart mechanisms will help to achieve higher automation and higher data quality. AI / ML can contribute to those goals, along with rule-based task execution.
MDM in the Cloud
The adoption of cloud-based services for MDM (and other core enterprise applications) is growing. As the center of data gravity continues to shift beyond the firewall, a cloud-native solution such as cloud MDM will likely have advantages over on-premise solutions with respect to integration with cloud-sourced data and applications.
Analysts describe a trend not only in MDM products but also in internal or cross-company workgroups to become multi-domain. Often information in day-to-day use cases is required from more than one domain (for example, brand, location, store and product), often coming from a need to provide 360-degree insights. In traditional single domain approaches, this usually means that existing silos need to be connected afterwards, not from the beginning. In a multi-domain approach, the growing demands would typically result in expanding the existing structures, based on the broader foundation – which is by far easier than connecting a variety of silos.
The concept of a 360-degree view brings together different information around a single master data entity. This can include core and application-specific master data, related transactional data as well as documents or analytical reports. 360-degree as a term has existed in the industry for some time, but recently pure MDM vendors have started building products around a 360-degree view of master data for their users. The value proposition of the 360-degree view is highlighted as improved efficiency of customer or procurement processes, single view across operations and transactional systems, discovering possible relationships, compliance and privacy management.
Application Data Management (ADM)
Application master data refers to the maintenance of application-specific master data including some rudimentary MDM capabilities offered within the transactional application context provided by the different LoBs. Application master data is essential for the transactional environments and needs to be handled locally in the same environment. Business platforms designed for enterprise-wide processes carry complex and robust data models of application master data, to provide flexibility to control LOBs, regions, or unit-specific processes while still having an enterprise-wide identifiability. By that, there’s also a high attention towards data quality in the application master data. Master data management solutions need to address both the enterprise level needs (unique identification, accuracy on global/core attributes) as well as the needs across the variety of units (for example, different ERP systems per LoB or region).