Master data management with D&TS


Master data management – what you should know

Everyone is talking about it, but hardly any companies are applying it professionally: master data management. We would like to show you the benefits of high-quality master data for your company and the challenges that arise along the way. But let’s start with the basics: What do the terms “master data” and “master data management” actually mean?

What is master data?

Business processes in all industries rely on master data. As the “heart” of a company, they form the basis for analytical evaluations and well-founded decisions, among other things. But what exactly does this mean?

  • Data that remain unchanged in the long term (address, bank details) or are permanently valid (date of birth)
  • Information relevant to multiple applications or business units
  • Classifiable data used globally or locally

The aim is to use this information to clearly identify products, materials or customers. Special reference data also supports the classification of the respective master records. Last but not least, master data also serve to characterize the actual situations.

Overview of key master data domains in manufacturing and logistics:

  • Article/product master data
  • Material master data
  • Customer master data
  • Supplier master data

The life cycle of master data almost always follows the same pattern:

  1. Creation – important: define minimum requirement for completeness
  2. Release – can be integrated if required
  3. Use and maintenance – update, complete, correct, specify
  4. Archiving – obsolete data does not necessarily have to be deleted

What is master data management?

Closely linked to master data is master data management (MDM): It is intended to create a unified view of the information collected and determine the correct records (golden records). Its purpose is also to make them available in one place (single point of truth). This is done by effectively consolidating master records from multiple system sources.

Master data management includes all technology-based and organizational activities that sustainably improve the quality of information throughout the company. In the course of that, data exchange between individual employees and complete departments is also optimized – even if processing takes place on different platforms or in different applications. Close cooperation with the IT department is essential for this.

In practice, master data management has three main tasks:

  • Provides the systematic approach to data integration
  • Ensures consistent use and reuse of data
  • Prevents poor data management: Duplicates, incomplete and incorrect data records

An important basis for being able to fulfill these tasks in a company at all is data governance. It regulates the internal handling of (master) data and defines uniform processes as well as responsibilities – for data entry, release and maintenance.

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MDM challenges: Product and material master data

For smooth production and a functioning logistics chain, qualitative master data of materials and products are indispensable. A typical example is duplicates – that is, ambiguous data because you:

  • give rise to false inventories,
  • distort inventory results and
  • generate high, unnecessary costs.

Other challenges in the area of material and product master data include:

  • Incorrect MRP parameters (quantities, discounts, reorder points, lot sizes)
  • Unclear responsibilities for master records
  • Incorrect assignments of article groups
  • Classification problems

What are the advantages of high-quality material and product master data?

A high quality of master records brings a variety of advantages. This is because it has a fundamentally positive effect on the efficiency of processes and ensures cost savings throughout the company. Thanks to increased data quality, throughput times, inventory levels and warehousing costs are also reduced. This in turn protects on-time delivery and liquidity. If inventories and order quantities can be precisely quantified, it is also easier to identify “idle inventories”. High-quality master data in the global supply chain not only increases customer and supplier satisfaction. The company’s own reporting also becomes more valid and more performant – the best basis on the way to Industry 4.0.


The advantages of high quality material and product master data

How do MDM and digitalization complement each other?

Functional master data management is no longer possible without digitalization – and at the same time an important prerequisite for it. After all, analog master records in paper form are of no use to anyone. Only those who keep their data correct and ready for retrieval at any time can use it effectively for strategic decisions. If, for example, manufacturing processes are to be continuously digitized and automated, maintained product and material master data are indispensable. Going further, they enable the use of big data analytics and business intelligence tools.

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Time for your MDM project?

Whether you should set up a master data management project depends on several factors. However, since every company works with some kind of master data, at least a basic engagement with the topic is recommended.

Ask yourself the following questions:

  • Does my company suffer from poor data quality (duplicates, incomplete data records)?
  • Does the search for materials fail due to a lack of system (classification)?
  • Are there no clear rules on who is allowed to create and maintain data records?
  • Is there a lack of processes for cross-departmental data creation and maintenance?
  • Is there a lack of meaningful analysis and reporting to measure data quality?

If you can answer “yes” to at least one of these questions, master data management is definitely an issue for your company.

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Errors in master data management

Master data management is not self-propelled. This must be clear to anyone who wants to tackle such a project. But there are three other important reasons why companies regularly fail with their master data management:

MDM is only understood as data cleansing

If master records are not continuously maintained, a so-called sawtooth effect occurs: Concentrated, cyclical cleansing of data improves its quality in the short term – only to quickly drop to the old level. The reason: The individual causes of poor data quality are ignored.

Relevance of processes is underestimated

Before a professional master data management solution can be implemented, companies must first become aware of their own processes: How are master records currently handled? What should be different in the future? It is important to consider the departments involved, to define releases and to find out which systems need the respective information.

Clearly defined responsibilities are missing

Data governance is “the” basis for successful master data management – and should be set up at the beginning of a project. For example, it clearly regulates who is allowed to maintain and change data in the company. It also specifies who is responsible for maintaining specific data fields.

This is how D&TS supports you in master data management

Our work is based on three pillars to guide you on your way to high-quality product and material master data:

The basis is a comprehensive consultation, which is followed by our data service. In the course of this, we perform data analysis, duplicate checking, data consolidation and harmonization, classification (ECLASS), and data attribution and enrichment. To ensure the quality of your master records in the long term, we support you with the connection to product databases and our software solutions. Or do you want to outsource master data management completely? We have solutions for that as well.

MDM Excellence Workshops: The optimal start to your master data project.

To the workshops

Our consultants look forward to speaking with you

Please feel free to call us or simply send us your request by mail.

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