Master Data Management 101

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Over the past 6 weeks, I have been working tirelessly on pre-study program together with two other colleagues for a client who is a large enterprise that has presence in over 100 countries. (I can't share more details about what they do)

The client is facing challenges related to their massive amount of DATA. They have different enterprise systems such as ERP, CRM, Product Management, Order Management, and etc in different regions and none of them is connected to the other, and there are little to no governance around them. This has resulted issues that they have no clue how to overcome, not only millions of dollars are being wasted every year, but also they are unable to make any sense from their data unless with manual intervention and help of excel and some other tools. Another issue is the duplication of data, for instance their customer data is stored in CRM system, but then it has been manually copied over to the Order Management system for creating the Order without any synchronisation around it. The duplication of data has also caused massive issue around searching for items in the inventory systems. We were on-boarded on this project as a part of an initiative to come-up with an action plan around executing the following activities:

  • Analyse the current systems landscape such as ERP, CRM, Inventory, and etc to figure out which systems can be depreciated.
  • Provide a set of recommendation around implementing new Business Process, and Data governance for managing and maintaining the systems.
  • Provide Recommendation around implementing a Master Data Management System.
The rest of this post is going to be about the third activity which was related to Master Data Management System....

So, What is Master Data, and What is Master Data Management?
The best definition for Master Data I found is from Gartner that define Master Data as:
Master data management (MDM) is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets.

How can it be implemented? 
I am gonna put the following in a very simple way, In order to implement Master Data an organisation need first to define which domain in their system do they want to call as Master for example: Customer, Order, Employee, and etc.
The next thing you want to do is to identify which properties are Master Data, for example speaking of Customer, maybe we want to have Customer Name, and Address as a part of Master data but not his/her last 4 digit credit card number.
Once these things are decided which is actually harder to do than to say, then you can start crafting your Master Data implementation.

There are conventionally four different approaches in implementing Master Data system which are:
  1. Transactional Style,
  2. Consolidation Style,
  3. Registry Style,
  4. and Coexistence style  
You can read in detail how they are different here in this blog post that I found, having said that they are all more and less similar in they outcome which is to consolidation data from different sources and group them together.

I used the following diagram to illustrate my thought to our client in one of the presentation about what we mean when we say master data, as you can see below the Customer entity is stored in several different systems, and in this diagram that entity has been consolidated into one single hub with reference data to each sub-system.


Example of Master Data 1.0.1 


 



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