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Key Capabilities of MDM for Material Data (MDM Summer Series Part 7)

Key Capabilities of MDM for Material Data (MDM Summer Series Part 7)

  • Jean-Michel Franco
    Jean-Michel Franco is Director of Product Marketing for Talend. He has dedicated his career to developing and broadening the adoption of innovative technologies in companies. Prior to joining Talend, he started out at EDS (now HP) by creating and developing a business intelligence (BI) practice, joined SAP EMEA as Director of Marketing Solutions in France and North Africa, and then lately Business & Decision as Innovation Director. He authored 4 books and regularly publishes articles, presents at events and tradeshows and can be followed on Twitter: @jmichel_franco
  • August 18, 2014

In this “summer series” of posts dedicated to Master Data Management for Product Data, we’ve gone across what we identified as the five most frequent use cases of MDM for product data. Now we are looking at the key capabilities that are needed in MDM platform to address each of these use cases. In this post, we address the MDM for Material Data.

As we will further discover through this post, strong data integration and data cleansing capabilities will be needed, together with the ability to model and maintain a uniform semantic view of the data across multiple models inherited from legacy applications and/or commercial off the shelf software. Standardization capabilities are important too, so that product can be easily browsed and searchable and product data can be electronically shared between business partners or regulation authorities when applicable. Strong stewardship capabilities will be needed as well.

MDM for Material Data apply for companies that are facing inefficiencies in their supply chain because of poor accuracy, accessibility or actionability of product data. This issue is generally not new, so there is often a lot of disparate data sources to consider, and a lot of moving parts too, sometimes hundreds of thousands or even millions.

Evaluating the efforts to create the single source of trusted data may not be straightforward, because the company may not know with precision the content of the data that they will have to deal with.

As a result, the MDM solution must enable progressive implementation. It may just start with gathering the data and assessing it with a data profiling environment before even starting to model the master data. Strong data quality management, including profiling, standardization, categorization and matching, together with flexible modeling, are therefore key capabilities needed. The standardization and categorizing capabilities should be of particular importance, because this will drive the accessibility of the product data: it will enable hierarchy browsing, faceted search or search by synonyms.   In some industries, codification standards exist to ease the exchange of production information between business partners or ensure compliance to regulation, so then your MDM solution should support those standards based on relatively complex well defined XML schemas.

The data integration capability is an also an important component for this use cases too:  The implementation style of MDM often starts generally with a so-called consolidation style where the data flows from the operational system to the MDM, in batch mode. Then the trusted data can flow back to the source system, through a batch mode too. Some companies prefer to start with a model where the MDM is connected real time in a bidirectional way to the source applications, but the prerequisite is that those existing applications have well defined access points such as web services that can be reused for the MDM project. This may be the case for companies that have achieved high maturity in adopting strong architectural standards for application interoperability across their IT landscape. Otherwise, the batch mode should be an easier, less intrusive and faster way to connect applications and start you MDM for Material Data initiative.

In any case, real time or batch, integration is an important building bloc, especially with regards to integration with ERP and PLM solutions. Because the data integration side would represent a significant portion of the development efforts needed to roll out and maintain this use case, the capabilities of your MDM solution in this area will impact significantly the total cost of ownership of the platform.   Note that the integration capability will be of particular value for companies that see their business applications progressively moving to the cloud. Analysts such as Ventana research have shown that cloud tends to augment the needs for efficient integration capabilities: for example, to fulfill a customer order, different cloud applications may be used from CRM to billing across warehouse management and distribution. MDM for material would then be a key component to provide a uniform and shareable product view across those applications, but then its ability to connect easily and efficiently to those external applications would be key.

The data stewardship capabilities are important to consider too. In order to be implemented incrementally, MDM for Material Data should have minimal impact in the way material data is authored in the system, in the existing ERP and/or PLM applications.  The goal is generally not to re-engineer those steps, but to add data governance capability to ensure data accuracy, trustability and accessibility. As a result, data quality issues linked to reconciliation, accessibility, categorization and standardization of data has to be managed a posteriori in this use case: it will requires data stewardship involvement on an ongoing basis.

Continued on Part 8.



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