In a world where data is the most powerful asset for business growth, Master Data Management (MDM) is a core function of every business. According to a research report by Markets and Markets, the global market for master data management is expected to grow to 27.9 billion US dollars by 2025.
Why Implement Master Data Management?
MDM aims at the creation of a single source of the most valuable data that is used by departments across an organization. It includes data on customers, products, suppliers, locations, and employees.
Master data is described as a single source of truth as it functions as a master file of dates, names, addresses, customer IDs, product specifications, and other attributes.
MDM offers a repository to manage business-critical data on an ongoing basis. Implementation of MDM can boost the data flow of the company. It also eliminates data discrepancies, which can cause long-term damage to the business.
At STAEDEAN, we enable organizations to take data-driven decisions with our range of Data Management Solutions.
However, the implementation of MDM is not free from challenges. As MDM focuses on the consolidation of the most-used data in the organization, most of the hindrances in the implementation process arise during consolidation.
Categories of Master Data
Master data can be classified into four categories: people, places, concepts, and things.
| Sl. No. |
Category |
A few examples |
| 1. |
People |
Customers, employees, suppliers |
| 2. |
Places |
Office locations, sites, geographical divisions |
| 3. |
Concepts |
Contracts, warranty, licenses |
| 4. |
Things |
Products, equipment, assets |
5 Challenges in MDM Implementation
Now, let us look at the common challenges you might face during the implementation of MDM.
1. Model Agility
The master data model you select would make a massive difference to your business operations. Your MDM software needs to be agile and adapt to the changes in complex systems. An ambiguous and inactive master data model would only add fuel to the existing problems. Hence, it is essential to define the different layers of the master data model for seamless integration.
The key steps to consider are:
- Creating the data model
- Defining the business rules
- Defining data validation controls
- Defining roles and security measures
2. Data Standards
Setting the standard is one of the most challenging tasks of MDM implementation. The data standard you set for your master data should be in agreement with all the data types in your company. The standard you set needs to be adaptable to data of various departments of your organization. Hence, if not planned well, standardization can be a cumbersome process.
3. Data Governance
Despite the introduction of definite models and standards, MDM implementation can be complicated. Strong policies and business rules can address the complexity of the master data. Governance is a vital element without which it would be impossible to get a clear overview of the data operations.
Data governance is not a one-time data cleansing exercise. A data governance process is needed to identify, measure, capture, and rectify data quality issues in the source system.
A thumb rule to remember is to build an MDM strategy only when you have a well-managed data governance framework.
4. Data Integration
Integrating MDM with other data applications can be a laborious task. The data transfer from one application to another might cause errors and take a lot of time. Furthermore, during the integration process, a few fields might transfer seamlessly while others might not.
The key steps to consider are:
- Defining data integration policies
- Managing integration with internal, external, and cloud-based applications
5. Data Stewardship
Establishing data stewardship is essential for you to maintain the quality of data. Bad data would not only hamper the consolidation of master data but would also create long term data management problems. Thus, in the absence of efficient data stewardship, your MDM implementation would suffer.
The key steps to consider are:
- Organizing data stewardship tasks by roles
- Managing tasks related to master data
- Accessing and authoring master data
Tip for the Success of MDM Implementation
Even when you have taken care of all the factors that can affect MDM implementation, if you miss out on educating your stakeholders, then your MDM implementation may fail. A misaligned team of stakeholders who lack clarity in data domains can cause the failure of your MDM strategy. So, it’s very essential that your key stakeholders are aligned with the goals of your MDM strategy.
Summary
To summarize, though MDM implementation has considerable challenges, it is a must-have for every business dealing with data. These challenges can extend the implementation process and cause revisions. However, if you understand the issues you might face during implementation, you would be better prepared for the process.
MDM can provide a 360° view of your information by connecting and sharing data from different systems such as ERP, CRM, eCommerce platforms, and more. If you are just getting started with MDM, it would help to download our beginner’s guide eBook.
Download this eBook if you are looking to control master data management within Microsoft Dynamics 365 for Finance and Supply Chain Management ERP. Our eBook explains how defined processes in master data management help you improve data quality and control data distribution.
Jerry Caous
