What Tools Are Used in Data Management?

What Is Master Data?

Master data is the core data you use to run your operation. This includes the names of customers, leads, suppliers, financial accounts, websites, hierarchical chains, etc. Master data does not refer to transactional data, meaning it references the core entity rather than a series of different events attached to that entity. For instance, master data examples might refer to a customer’s ID number and contact information, as opposed to every product purchased by the customer.

Usually, master data is owned by both business leaders and the IT team to ensure that the data is both uniform and accurate. There needs to be a clear understanding of who is responsible for each component if master data is to be properly maintained. Without master management data, the results can become skewed.

Why Master Data Management Is Important?

Master data management (MDM) is the key to centralizing your master data, so it’s visible across the organization. Master data is critical to the decisions the company makes and the long-term strategies they implement. If you’re unable to keep track of it all, you can only see half the picture.

Better production information management and master data management ensures that everyone is on the same page. Not only is it clear who owns certain tasks, such as updating MDM software or inputting a supplier change, but it’s easier to analyze and interpret the data once it’s brought all together.

The right MDM implementation steps can improve data governance, applications, and systems. Poor master data management process flow is what leads to fundamental arguments about what’s driving the organization forward and how to best steer the ship. It can cause leaders to misunderstand who their customers are and what they want. It’s one thing to argue about the nuances of strategy, it’s another to disagree about the main facts of the business.

Imagine a scenario where marketing is collecting leads from a digital campaign while sales is collecting leads from a cold-calling campaign. The marketing team finds that high-income neighborhoods are the most responsive group to their efforts. However, sales is finding that their most promising candidates are people from middle-class backgrounds. If there isn’t a way for the two teams to aggregate and reconcile their data, it can lead both teams to misunderstand who their best customers are and how to reach them.

Better MDM may help them see that both brackets are viable options for company growth, but that the two sets of people need to be approached differently. It can make for more effective outreach which, in turn, results in more sales and revenue growth. Once all the processes have been established, data governance will instantly improve.

Collaboration will also be easier, not just with internal departments but with external vendors and partners as well. This is not to say that all master data needs (or should be) provided to everyone. MDM principles allow for discretionary sharing when it improves the operations of the company. For instance, a company might share their full product catalog with a supplier. In order to do this, though, that product catalog needs to be up-to-date.

What Are the Different Types of MDM?

Master data is a somewhat loose definition and it can apply differently to different organizations. To account for this, there are different types of master data management. We’ll look at MDM types and what to keep in mind before choosing one:

• Registry: Registry MDM starts with centralizing all data. It goes into one location where it can be cleaned and aligned. It should be noted that cleaning the data doesn’t mean altering it. If there are changes, they occur within the single source system rather than different MDM databases. This approach can be a good way for companies with disparate data to bring it all together. However, it can take a long time to perfect this strategy, and it may compromise the data’s reliability along the way.

• Consolidation: With consolidation, the team creates what’s known as a golden record, meaning it’s a verified version of data that is stored in a centralized system. Unlike the Registry MDM type, there’s oversight for every golden record. A team member must go through everything to ensure that it’s correct before solidifying it in the system. This approach leads to reliable data, but it can be a costly one to implement.

• Coexistence: With coexistence, an MDM database and original data sources can coexist in real-time. So you would have one or several places for raw data and then another where that data is organized for further analysis. Data inconsistencies are solved by linking the systems together. This way, when one record is updated, it will automatically update the records in another.

• Centralized: This MDM solution puts the central repository of data on a pedestal. The other data sources would have to subscribe to the central repository to verify consistency, as opposed to both leaning on the other for updates. If you’re looking for MDM solutions that result in a true system of record, this would be one to explore.

What Tools Are Used in Data Management?

The right master data management tools depend on the type of data you’re managing. For companies that manufacture physical products, Customer Relationship Management (CRMs) is used to store customer contact information and sales opportunities. Product Lifecycle Management Systems (PLM) record and manage the engineering process, including design and manufacturing. Increasingly, Product Information Management (PIM) is used to centrally manage product data and product-related digital assets.

Master Data Management vendors who account for the variability of data typically provide the best ROI. For instance, while Product Information Management (PIM) is a useful tool, it doesn't allow for digital assets like owner's manuals or spec sheets to be added to the repository. In this case, a Digital Asset Management (DAM) component is needed to flesh out a company's data strategy. Not all vendors will be able to provide this.

If you're looking for a Master Data Management example to base your decision on, consider how most companies benefit from simplicity. When data can be complex enough in its own right, its management needs to simplify and organize. Some of the most well-known tools on the market do boast incredible benefits, but it may sap your team's resources to both set up the system and maintain it over the years.

Instead, companies like Lumavate have come up with out-of-the-box features, including DAM, that are easier to configure by marketing teams (instead of IT). If you want a single source of truth, it could be the all-in-one solution you're looking for.