Master Data Management
What is Master Data Management?
Master data management (MDM) is the process of managing, organizing, centralizing, synchronizing, and categorizing data, across departments according to a certain set of predefined rules.
MDM is an early output of many organizations’ data governance efforts. Whilst data governance is the higher-level, strategic approach a company envelopes around its data, MDM is a common tactic for achieving data governance goals.
Imagine a huge pile of books of every possible genre. A librarian would have to sort through that pile and take time to categorize each book and arrange them alphabetically, by genre, or using the beloved Dewey Decimal System.
This is what MDM does for the data in your business.
It organizes and categorizes it so you know where the information you need is and so you can trust that the information is being stored and managed in a way that makes it most useful for decision-making. With proper MDM, your data becomes more and more valuable. You can easily access it, use it, and leverage it for better campaigns, customer service, or improved business processes.
Does all this sound too dull to care about? The process of organizing and structuring data may not be glamorous, but the results can be truly spectacular.
"By 2025, 50% of data and analytics leaders will leverage augmented MDM and active metadata to automate governance policies for master data models, hierarchies and definitions."
Why MDM is Crucial for Technologically-Driven Organizations
The average company uses an average of 34 SaaS solutions. Some of these are mission-critical.
IDS' entire business is based on the fact that systems and technology - ERPs, CRMs, process automation and custom software - help businesses perform what they do better.
Each of the systems gather, store, and display data in different ways. For instance, the accounting department looks at clients differently to the sales and marketing departments. Therefore, they need different tools and analytics. However, when these tools don’t coordinate, and are in their own data silos, data becomes fragmented.
Let’s say your sales reps rely on Salesforce to manage contacts, leads, and new business. One of your biggest clients changes address, and the account manager diligently updates the address in Salesforce.
So far, it looks like a smooth process. However, with the way most organizations are set up, the accounting department may still have the old address on record. Of course, you can always alert other departments via email and have them make the change in their respective systems. But that process is time-consuming and very prone to human errors and inconsistencies.
Now let’s look at it from the customer’s perspective. Someone could buy different products from different departments in the business. Think about a customer with multiple types of insurance policies (life insurance, home insurance, health insurance etc) or someone who leases a car from a local dealership and relies on the same dealership’s service department for maintenance and repair work.
If your data is not properly managed, these customers could feel they are working with more than one company. They’d receive endless irrelevant promotional emails, direct mail pieces, and customer care calls.
It’s an issue for everyone.
Master data management creates a data lake, or a data warehouse, to make sure all your data, regardless of how many software systems you use, is consistent across the board. By creating one source of truth, often called the golden record, every system can use the most updated data at all times, without relying on human data entry or complex manual processes.
Benefits of Master Data Management
Overall, your data management efforts enable seamless integration between your departments and offer your customers exactly what they want: a unified, smooth experience with your business.
When your data is no longer siloed, you have a bird’s eye view over every customer or account. You can then easily send them only relevant offers instead of annoying them with countless promotions and emails for products they may never buy.
Better Customer Service
The moment one of your customers call or email your support department, the rep will know almost everything about that person’s history with the company, without having to browse multiple systems or ask colleagues in a different department.
Your customers are happier and your team is more efficient and effective.
Seamless Business Processes
Forget all about inputting data manually or migrating it from one system to another. With master data management, the goal is to get to the point where all data is updated into the data warehouse automatically.
Let’s follow up on the address change example above.
According to the rules you create, when a customer changes their address and the sales rep updates it in Salesforce, it can automatically be updated in the data warehouse, which then updates it in accounting and other systems as well.
The beauty of master data management is that it’s 100% customizable and adaptable to your business processes and your needs.
Get to Know Your Organization Better
It can be surprising to learn how many hidden gems there are in unused and/or improperly analyzed data. With the right master data management processes, you can answer your most pressing questions and make more effective and timely decisions.
Which department has the most efficient processes?
How much time are your team members spending on repeatable manual tasks instead of focusing on mission-critical tasks?
Which leads are ready to buy and which are simply annoyed by your campaigns?
Data can answer any question you have as long as you know how to leverage it.
Prioritizing Data Quality to Improve MDM
Common symptoms of poor data quality include adverse impacts on data governance and master data management.
As part of a mission to provide 100% data certainty to clients, IDS follows best practices for master data management to ensure consistency in data, especially during migrations and transformations.
The iData toolkit has been engineered to achieve a single point of truth in any organization's data quality for more effective decision-making.