Successful Master Data Management is about aligning standards, systems, and stakeholders to create a single, trusted view of critical data.
Challenges of implementing Master Data Management
Master Data Management (MDM) promises a single source of truth - but getting there isn’t always easy. In this article, we unpack the most common roadblocks organizations face when implementing MDM, and what to consider to overcome them.
Master Data Management (MDM) is the foundational process of discovering, defining, collecting, managing, classifying, synchronizing, combining, repairing, and enhancing master data following organizational requirements.
Since MDM is so versatile, businesses can use it for almost anything.
Time-to-market improvements and production and supplier process optimization are just a few of the manufacturing objectives that might benefit. Moreover, MDM can assist with the removal of data silos, the improvement of data quality, and the dissemination of consistent data across all channels.
However, MDM doesn't come without its set of challenges. You need to consider your company's MDM requirements carefully. This is why we will cover the most common challenges of master data management.
What is Master Data Management?
The goal of master data management is to provide a centralized repository for the most critical data a company uses across its different sectors, including customer information, product information, supplier information, store location information, and personnel information.
The term "master data" refers to a centralized database containing all relevant information. This includes dates, names, addresses, customer identifiers, product specs, and more.
MDM provides a central location to store and organize an organization's most valuable data.
LEARN MORE: The ultimate guide to Master Data Management for media files
Introducing Master Data Management (MDM) can significantly improve how data flows across an organization. By centralizing and standardizing key information, MDM helps eliminate inconsistencies that could harm the business over time. As MDM tools become more widely adopted, they empower companies to make smarter, more informed decisions.
However, implementing MDM comes with its own set of challenges - which we’ll explore below.
1. Creating data standards
One of master data management's challenges is creating a standardized data format.
All of the many forms of data at your disposal must be in sync with the standards you establish for your master data. It would help if you verified that you could accommodate your company's divisions by the criteria you've set. This includes everything from file naming conventions to individual fields in the database.
At the same time, you must keep the format standardized across all users so the data can be easily understood and shared. Data standardization requires careful forethought and advanced preparation. If you don't prepare, you will have a lot of issues later down the line.
2. Choosing a data storage solution
A significant challenge businesses face when attempting to implement master data management, is the sheer number of data storage options available.
Databases, customer relationship management systems, enterprise resource planning systems, and so on are just a few examples of the many business solutions that large firms may have.
Assessing and managing this volume of data effectively is s a substantial hurdle to overcome.
A universal data platform that can quickly discover and aggregate disparate data sources is challenging when data is stored in isolated silos.
According to Convert More experts, an organization's main priority should be eliminating data silos and connecting data from customers, products, and vendors to create a single source of "truth" for your data.
3. Selecting the primary data set
It is crucial to carefully choose the data components that will be "mastered" for MDM to be successfully implemented.
In large organizations, departments may have divergent priorities, gaining consensus on a common set of data items a contentious process.
For example, the non-life division of an insurance company may place a high value on a client's email address, whereas the division of the pension is interested in learning whom the consumer works for. Furthermore, it is important for product data management.
Because of this, it's crucial to develop a generally accepted consensus on which standard to use. In this regard, developing a common data model (CDM) may be useful. The goal of a CDM is to provide a standardized model that is obvious and accessible to all parties involved by presenting data entities and their mutual interactions in the most straightforward way feasible.
4. Choosing the right Master Data Management tools
You may choose from a wide variety of Master Data Management solutions while making your decision.
However, the more tools you have, the more complicated your solution will be. Choose your Master Data Management carefully to ensure it meets all your data management needs.
It is crucial to consider your company's needs, your end goals and objectives, and the advantages each tool offers. You may avoid the hassle of switching tools later by keeping an eye on your current and anticipated demands when you define your scope.
5. Integration of data
Master Data Management necessitates integrating information from several business applications and sales channels.
Even though cutting-edge tools have made it much less labor-intensive, data integration is still a time-consuming task. Data movement from one program to another is rife with potential for error. It's also possible that certain fields would move without a hitch from one system to another while others could encounter challenges.
6. Data stewardship
If you want to keep the integrity of your data intact, you will need to establish data stewardship.
If you use inaccurate data, the process of consolidating master data will be slow, and you will have problems managing your data over the long term. Because of this, your MDM deployment will suffer if you don't practice good data stewardship. Important things to think about are:
- Implementing a role-based system for data stewardship
- Allocating administrative duties concerning master data
- Being able to see and edit master data
Conclusion
In conclusion, MDM is a must for every company that deals with data. This is despite the common challenges of master data management.
However, being aware of the potential obstacles you might face during the implementation process puts you in a position to recognizing and addressing challenges before they develop into major problems.
Ready to take control of your data?
Master Data Management is only as powerful as the system behind it. Discover Fotoware Alto - the platform helping you unify your data for smarter decisions.
