Data utilization has become the go-to for businesses seeking to scale operations and output. But as businesses discover new problems to manage with data, new technologies, tools, and approaches emerge. Master data is in its infancy, but many organizations have started leveraging it for data-driven business activities. If you find yourself in the situation of pitching MDM to your bosses, you may have to go easy on all the terms. That is why this introduction to master data management may come in handy.
Master Data Management Defined
There are several concepts and definitions to master data management as a term. Usually, the context differs based on the angle or lens the term is being considered. And the more you review master data, the more you see the lines blurring with other terms like reference data. Determining whether they are the same or not may be confusing.
They are different sides of the data coin pointing to the same thing. But the differences might not be evident until all of these terminologies are deconstructed to the core of reference data or metadata is about. We can first look at master data management through the definition and the rising importance of master data.
A business entity’s master data refers to all data that provides context for its business transactions. Master data sets are extended attributes used to describe a particular organization and its business processes. Some types of master data include customer data, reference data, product master data, etc. Based on this foundation, what is master data management (MDM)?
MDM is a discipline that enables businesses to ensure the uniformity, accuracy, stewardship of an organization’s master data assets. MDM involves a set of techniques and operational methods to manage enterprise data from multiple domains. Today, many organizations have large volumes of data from different sources running through several CRM applications and systems. Different departments and divisions using these applications sometimes create duplicates and fragments that significantly affect data quality. MDM arose out of the need to bring some form of sanity into an organization’s data warehouse.
How it Works
Master, data management solutions go through a series of steps. But the entire process of a master data solution doesn’t begin until there is a clear problem at hand that needs solving. Whether it’s a workflow issue or supplier mismanagement, this problem can determine the direction of an MDM project and the steps to follow. Generally, the MDM process includes the following steps:
- Identifying master data sources
- Defining the organization’s master data stakeholders
- Metadata collection and analysis
- Determining data stewards
- Setting up a data governance team to oversee the master data program
- Developing a data model for your master data assets
- Choosing a toolset and creating a data infrastructure for applications
- Generating and testing your master data program
- Evaluate and make adjustments if test results don’t match the problem at hand
- Develop a maintenance routine for your master data program
Master data might be a small part of an organization’s data volume. But they are complex and valuable to manage. Some benefits of master data management include:
1. Operational Efficiency
Master data management affords businesses more control over their core entities like customer base, chart of accounts, suppliers, etc. Using data analytics for these functions instead of hiding behind operational traditions can be a great way to ensure efficiency. And even better, MDM affords data professionals in search of efficiency a cost-effective approach to find it. Businesses can manage complex relationships across products, vendors, locations, and customers from a uniform system. And that can significantly reduce IT costs in managing independent data silos.
2. Customer Relationship Management (CRM)
Master data management empowers data consumers. Having an organization’s master data in one place provides easy access for personalized marketing and customer solutions.
3. Supply Chain Optimization
When a business increases, it can become hard to identify an underperforming supplier out of several lots. But not when all suppliers have been reduced to zeros and ones with KPIs tracking performance in real-time. Master data management affords businesses that bird’s eye view to connect business functions from production to final consumption.