What is master data management?
Master data management (MDM) provides a unified view of data across multiple systems to meet the analytic needs of a global business. In other words, MDM creates a single source of truth for your company’s data, thereby ensuring it's both trustworthy and readily available. This uniform set of identifiers is often called a “golden” or “master record.”
What is master data?
“Master data” refers to information that’s shared across operational systems. It can encompass many different types, including:
- Customer data. Information pertaining to consumers, such as contract details, purchase histories, and preferences.
- Product data. Details about the products or services your organization provides, like descriptions, specifications, and prices.
- Financial data. Any information related to the organization’s financial transactions, accounts, and reports.
- Employee data. Information regarding the workforce, such as personal information, job history, and salary.
- Supplier data. All data related to an organization’s vendors, partners, and third-party relationships.
Most companies rely on master data for a variety of core business functions. From payroll and compliance to sales and marketing, there are countless operational applications that depend on consistent, accurate, and reliable access to critical data.
Challenges of master data management
The trouble most organizations face when it comes to master data is keeping it consistent, complete, and controlled across the entire enterprise. With multiple sources of information spread across the company, it becomes exponentially more difficult to synchronize data at scale. And, because it changes over time, datasets quickly become fragmented, outdated, or redundant.
In other words, it’s all too easy for data quality (DQ) to fall by the wayside. Simply put, DQ determines a dataset’s utility. Low-quality data can’t produce reliable insights, which means it isn’t very useful in the first place. For instance, executives can’t trust information if it’s based on incomplete, error-prone, or inaccurate data, as it could lead them down the wrong path.
Worse yet, poor DQ can have costly repercussions, such as imprecise analytics, profit loss, misguided business decisions, and operational inefficiencies. Recognizing these potential consequences, many companies are taking steps to improve data quality over time. Gartner estimates that through 2024, 50% of organizations will adopt modern DQ solutions to support digital business initiatives.
The good news is that master data management practices and solutions can address these challenges altogether. By standardizing business entity definitions, improving data quality, and aggregating and distributing data across the organization, MDM affords you one holistic view of the entire enterprise.
Benefits of master data management
Businesses have a lot to gain by investing in master data management. Not only do MDM strategies help you avoid costly mistakes and bad decisions, but they also drive organizational efficiencies from top to bottom. By supporting all lines of business in one fell swoop, MDM empowers you to unlock your data’s true potential.
Let’s discuss three ways master data management can give your business a competitive advantage:
1. Improved data processes
MDM consolidates data into one master record, eliminating the consequences caused by conflicting and inaccurate sources of information. Moreover, this process optimizes the entire data management lifecycle from start to finish.
For example, implementing an MDM strategy improves data collection by reducing manual entry and minimizing the risk of human error. It also facilitates better storage and governance practices, allowing you to ensure peak data quality through centralized management. In turn, employees and customers alike can confidently access and retrieve information knowing it's the latest and most reliable on record.
Ultimately, outdated records must be safely disposed of. With a master record, you can quickly identify irrelevant information and destroy it as necessary. Likewise, MDM enhances visibility, thereby making it easier to generate reports and prove compliance with strict regulations.
2. Streamlined operations
Unnecessary, redundant, and time-consuming workflows are a major hindrance to enterprise productivity. Even worse, information silos make it difficult to collaborate across departments, which is especially problematic for distributed workforces.
That’s why it helps to have all critical data in one place. MDM strategies house all information under one roof, allowing teams to save time and effort they’d otherwise have spent searching for the right data. More importantly, it ensures everyone is working with the same, accurate dataset—not old, disparate information.
By the same token, MDM automates data processing. This both reduces time-consuming and error-prone steps while saving and optimizing critical resources. For instance, modern MDM solutions are powered by machine learning (ML). As a form of artificial intelligence (AI), ML capabilities automatically discover, classify, map, and analyze data, drastically reducing manual labor.
3. Enhanced decision-making
Perhaps the most significant advantage of having a centrally managed and uniform master record is how it supports decision-making at all levels of the enterprise.
According to McKinsey, today’s organizations are only sporadically applying data-driven approaches throughout their business. Consequently, they’re leaving money on the table and creating inefficiencies. But, by 2025, nearly all employees—frontline and C-suite included—will naturally and regularly leverage data to support their work.
Indeed, a master data management strategy will be pivotal to making that happen. As a comprehensive view of the entire company, MDM empowers all employees to extract more value from their data. With rich, meaningful, and accurate insights, teams can make sound business decisions no matter how large or small. Whether it be a marketing director planning an upcoming campaign or an executive forecasting the next fiscal year, synchronized master data takes the guesswork out of the equation.
MDM use cases
In truth, there are virtually endless applications for a master data management strategy. As data becomes ingrained in almost every business function, it’s becoming increasingly clear that MDM stands to touch all aspects of modern work. That said, here are three examples of use cases where MDM solutions are poised to make an impact:
- Mergers and acquisitions. When one business acquires or merges with another, they must also combine their data. This often involves integrating multiple, disparate systems where information is stored in different formats. MDM can help identify commonalities and reconcile differences, bridging the gap between the two sources.
- Customer experience. Salesforce reports that 73% of consumers expect companies to understand their unique needs and expectations. By consolidating master data and keeping a 360-degree view of customer information, sales and marketing teams can deliver personalized experiences on an individual, granular level — thus enhancing customer lifetime value.
- Supply chain management. MDM enables supply chain professionals to create a precise inventory of materials and products based on location, region, or client. Plus, having real-time, updated information helps them avoid stockouts, overstocks, and other costly disruptions.
Key components of a master data management strategy
MDM strategies don’t support themselves. There are several must-have components involved in the process, each of which plays an equally significant role in creating, managing, and maintaining the master record.
1. Data governance
The National Institute of Standards and Technology (NIST) defines data governance as a “set of processes that ensures data assets are formally managed throughout the enterprise.” In simple terms, it establishes parameters for how data must be handled by the organization.
Governance effectively creates the backbone of the MDM strategy. It oversees the availability, usability, integrity, and security of all master data, rendering it integral to the overall MDM architecture.
Additionally, data governance intends to enhance the value derived from data. It does this by ensuring MDM initiatives are aligned with business objectives, thus driving master data delivery and reconciliation. What’s equally important is that governance enforces rules and standards, defines clear roles and responsibilities, and fosters accountability for all who access critical data.
2. Data modeling
Data modeling is a process of analyzing data objects used in a business context and identifying their relationships to one another—a bit like a flowchart. Data models tailored to specific business functions can provide a solid foundation for your MDM strategy.
More specifically, the role of modeling in MDM is to identify how certain entities interact with each other. This helps organize and structure data in a way that’s easy to understand, use, and maintain. Plus, it allows you to eliminate redundancies, establish data quality standards, and integrate various data sources into one coherent structure.
3. Data integration
At its core, master data management is about creating a single source of truth, but this wouldn’t be possible without data integration. As the name implies, it’s a process of synchronizing and consolidating information from disparate systems into a centralized set.
The key to data integration lies in its ability to aggregate many diverse data types and transform them into a format that can be easily accessed and used.
4. Data quality management
As previously mentioned, a dataset is only as good as its quality allows. Data quality is even more paramount to MDM, as it provides the basis for creating a holistic and trusted reference for the entire organization.
Generally, there are five characteristics that determine data quality:
5. Data stewardship
Lastly, data stewardship is indispensable to any MDM strategy. Stewards play a mighty role in ensuring data is accessible, trustworthy, usable, and secure. As a position of oversight, data stewards take on the following responsibilities:
- Developing policies and procedures for monitoring and enforcing governance standards
- Establishing guidelines for data handling and security
- Tracking data quality, resolving data-related issues, and enforcing compliance with regulatory requirements
- Standardizing data entry, curating datasets, and decommissioning outdated data
Best practices for master data management
Implementing a master data management program isn’t an easy task. Fortunately, there are several actions you can take to support your transition to an MDM architecture. For example, effective MDM best practices include:
- Data cleansing. Also known as data scrubbing, cleansing is the process of correcting or removing inaccurate information from a database. Some data may be improperly formatted or input incorrectly, which can lower its overall quality. Large organizations often use automated solutions to identify and correct inaccuracies at scale.
- Stakeholder involvement. MDM is just as driven by people as it is by technology. To reach the goal of sharing data, stakeholders must agree first on definitions before establishing the teams, policies, and procedures that are needed.
- Frequent assessments. MDM isn’t a one-time rollout; it’s a major change that demands continuous improvement. Evaluate the outcomes of your MDM strategy regularly to identify areas where you can enhance processes and support the initiative.
Choosing the right MDM solution
Introducing a master data management strategy is much easier with the help of a good MDM solution. With the right platform, you can gain a portfolio of essential tools for coordinating and automating MDM at scale.
But what should you look for in the ideal solution? Here are a few must-have capabilities:
- Multi-domain management. A worthy MDM platform will support multiple domains, eliminating the need to buy various point solutions and products.
- Comprehensive data consolidation. Look for a provider that allows you to unify master data from numerous heterogeneous systems and channels.
- Enterprise automation. The right solution will mitigate the risk of poor data quality by managing data architecture, metadata, data quality, hierarchies, and governance across the entire enterprise.
Though the next few years of the business landscape remain unwritten, data-driven organizations will certainly be a large part of how the story unfolds. As such, it’s never been more important for enterprises to manage uncontrolled data growth and put it to good use. Undoubtedly, that’s why it pays to have an effective master data management solution at your side.
With a cloud-ready analytics platform like Teradata VantageCloud, you can unlock data and uncover valuable insights you never thought possible. Leverage integrated, unified information from a single source of truth and prepare your business for the challenges of tomorrow.
Connect with us to learn more about Teradata VantageCloud and how we can help your organization reap the benefits of master data management.