Good practices of MDM (Master Data Management) implementation

17.09.2020 Angelika Siczek
implementation of good practices in Master Data Management MDM

What is MDM? The English abbreviation is Master Data Management. According to Garnter’s definition, it is a complex concept, based on technology, in which business and IT work together inseparably, ensuring uniformity, accuracy, semantic consistency, efficient management and responsibility for common resources of master data in the enterprise.


Both small and global companies are constantly trying to increase their business value by improving data management. Such activities are perfectly illustrated by the telecommunications industry, where efficient data flow is extremely important. In a situation where individual departments would not have this type of communication with each other, it would happen that a customer using the services of a telecommunications operator would receive separate bills for each service (e.g. for various types of domestic and foreign connections). Moreover, due to inconsistent data, it is likely that he would also receive messages with offers for which he has already signed up. All of these would be unacceptable errors in customer service that would indicate erroneous and unprofessional data management.


This type of inconsistency concerns not only the aforementioned industry, but many other business sectors around the world. Without system integration, duplication of data takes place, which directly translates into the inability of the organization to efficiently and effectively serve customers and creates serious frustration for them.


To prevent such situations, it is worth using an MDM solution. It will help you manage the quality and integrity of the data elements. It will also allow you to remodel the data strategy that is necessary to accelerate the company’s development. So see how to correctly implement Master Data Management and why it will be useful in your company!


What exactly is MDM?

The concept of MDM covers both the IT sphere and business functions. From a business perspective, it refers to identifying and managing an organization’s critical data assets as well as creating a single information source for all of these assets. So it includes analytical data and reference data to help you make key decisions. In turn, from an IT point of view, MDM refers to a set of tools that help to standardize data, eliminate duplicate records, and store them in the master file. It should be emphasized, however, that not all data is basic.


What is Master Data?

Master Data is simply basic data. To clarify what exactly they are, it’s worth taking a look at the rest of the data that will show us exactly. Let’s start with unstructured data.


Unstructured data creates the entire range of data stored in various formats. So they include white papers, intranet repositories, emails, videos, etc., as well as PDF files, product specifications, and other marketing materials.


The next batch of data is transaction data. It includes both monetary and non-monetary data derived from business activities. So these are all kinds of sales reports, deliveries, invoices, complaints, goods release receipts and other such items. Unlike master data, transactional data is time-based and often serves as an essential part of the analysis by other systems.


Another important type of data is metadata. It includes file specifications, image names, tags, etc. It can be in a repository or not categorized in log files, reports, XML documents, and other formats.


The job of hierarchical data is to define relations between data points. Most often, it is a part of a separate system, descriptions of the company’s organizational structures or information about products.


And the last type of data necessary to explain is the reference data. It belongs to a special category of master data that associates the data with information from outside the enterprise. Most often they have a cross link with the main or transactional datasets.


Now that you know all the important types of data in your business, we can go to the heart of this rallying, which is the basic data. MD is, as the name suggests, basic data on the organizational pillars – customers, products, suppliers, locations and assets. This type of information changes extremely rarely. It is worth emphasizing that the master data does not include the transaction data, although it describes the transactions themselves.


4 good MDM implementation practices


1. Executive sponsorship

At the beginning of the MDM implementation process, it is worth remembering that the project will surely end in failure if it is based solely on the IT sphere. Of course, it can bring technical benefits, but without delivering adequate business value, MDM will not deliver tactical efficiency. Therefore, as with other enterprise projects, providing executive sponsorship is the best way to align IT and business priorities.


2. Implementation in stages

The main point in implementing a solution is to execute it sequentially. So let’s start with developing business use cases to purchase the right tools. So before you implement MDM in your business, set goals for each phase and prioritize highly dependent workflows. This will help streamline the entire project.


For example, your immediate business need may be to clear your email data to run an email campaign efficiently. So this is a priority over the consolidation of contact numbers.


3. Standardized semantics

As there is a great need for optimized analysis and reporting in every enterprise, we often deal with the integration of data from multiple sources with a central data warehouse. However, despite this, there are discrepancies in the data related to their names. It often turns out that the terms are used in different files and contexts – for example, “customer” and “product.” This type of inconsistency leads to unreliable reports and even gaps in all corporate communications. For this reason, it is important to standardize the semantics, which should be prioritized at the beginning of each MDM implementation project.


4. Cooperation with stakeholders

Unfortunately, managing data quality is a difficult task. To obtain the best possible results, specialists working in this field work closely with key stakeholders from different teams. From members of the business team, to IT teams, vendors, to system integrators. It is very important to avoid chaos.


You already know what to focus on to correctly implement MDM. However, using all the tips can prove to be a tough challenge. Especially if your organization is not used to introducing frequent changes and the work between teams is not always smooth. For this reason, it is worth considering enlisting the help of an implementation partner who will help you streamline your workflows, set realistic implementation goals, and also provide you with a clearly defined project map, thanks to which you will know what to do step by step. Such a solution, combined with the efforts of all members, a quickly adapted organizational culture and well-established business goals, will enable the quick implementation of the MDM system. It will start to run smoothly, make it easier to use marketers’ ideas, improve data interoperability, and ultimately – provide higher business results.

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