Defining Master Data Management: examples and benefits

The principle of Master Data Management.

Master Data Management is a recent concept, born of the awareness of the importance of certain types of data and which has developed very strongly with the computerisation of companies and their processes.

The data considered essential are :

• third parties (customers and suppliers);
• financial information ;
• product data.

Definition of MDM

MDM defines a set of concepts and processes for defining, storing, maintaining, distributing and enforcing a complete, reliable and up-to-date view of referential data within an information system, regardless of communication channels, industry sector or business or geographical subdivisions. Numerous Master Data Management tools allow the collection, sorting and normalisation of raw data from different sources. Within companies, these tools are becoming the benchmark for data management to ensure good data governance and quality.  

For IT and DSI teams, the MDM is really thought of as a global repository in terms of an information and product data management solution. It ensures data security, management, traceability and reliability.

Applications

The main tools for managing data and business processes are

• ERP: Enterprise Resource Planning;
• CRM: Customer Relation Management;
• PLM: Product Lifecycle Management;
• the WMS: Warehouse Management System.

All these tools use or produce reference data, sometimes different but often identical. The rational thing to do is to centralize their ownership, to simplify their coherence, uniqueness, protection and availability.

Imagine that your product description is created in a PLM system and coded in an ERP. If you centralize these two pieces of information, all the other systems will come looking for them in one place.

The other systems could even enrich this common database with information "created" by them about this product. For example, the WMS could provide product logistics data (weight, dimensions, packaging, etc.) and the CRM could provide customer consultation statistics over a given period.

MDM objectives

Master Data Management aims to ensure the consistency, quality and management of master data within an organization. The main aim of MDM is to ensure that this data is correct and accessible. To achieve this, Master Data Management is based on a few key points:

• Centralized management: essential data is generally managed centrally, often within a single, collaborative repository accessible to all, such as a PIM for example.
• Integration : MDM presupposes the integration of master data into all the applications, systems and processes that make up a company's digital ecosystem, guaranteeing a single, precise view of the data in question.
• Data consistency and quality : Master Data Management aims to guarantee data consistency and quality, avoiding or even eliminating errors and duplicates that may occur. It emphasizes data quality by introducing data cleansing, standardization and validation processes.
• Data governance . Effective and robust data governance is one of the key aspects of MDM. This requires clearly defined procedures, policies, processes and responsibilities.
• Compliance and security. MDM ensures the security of master data by controlling access and guaranteeing whether or not certain data, which may be sensitive and/or confidential, can be accessed.
• Continuous improvement and scalability. Master Data Management must be created to evolve with changing business needs and industry trends, to adapt to new master data sources.
• Simplification of business processes: by ensuring reliable, consistent and qualitative data, MDM greatly facilitates business processes, particularly in decision-making, customer management and so on.

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MDM is the guarantee of control over what is being done and produced on a subject that is vital to the company. This one, associated with PIMis the assurance of rationalizing your data management and making the work of your business teams more fluid.

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