For many businesses today, data’s importance as a valuable company asset is rising, putting a premium on more effective data management. Complexity is a challenge as digital transformation, data governance, flexible platforms, and third-party providers of data, technology, and cloud services all come into play. Focusing on your most important and most frequently shared data assets, such as your customers, suppliers, employees, and more, can help. This is why master data management (MDM) becomes vital, requiring a well-thought-out, long-term plan for success.

Before we dive deeper into MDM, let’s start with a definition. According to Gartner, “Master data management (MDM) is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets.”

Do you know how your company’s master data management strategy is doing? Below we cover some highlights from a recent blog post from TIBCO’s Senior Director of Data Management Thought Leadership, Robert Eve, which includes five paths to MDM success:

1. Start with your digital transformation strategy: Data analytics professionals should approach their MDM platforms and practices with the company’s overall digital transformation strategy in mind. Start by asking what success looks like, such as improving customer engagement, innovation, or operational excellence.

2. Build your MDM program on a flexible platform: Since strategies and objectives can alter or change altogether, long-term success requires the flexibility of an MDM platform that allows you to evolve your efforts and grow.

3. Establish proper MDM governance from the start: Establish data management roles and responsibilities, including data managers and analysts, across the organization from the get-go. It’s also important to ensure company-wide data consistency using shared workflows, common processes, and master data standards.

4. Deliver small wins using focused teams and iterative methods: Like implementing any long-term plan, data leaders are encouraged to call out and celebrate near-term along the way to success. According to the TIBCO post, “Key steps in this iterative methodology include: specification, design, development, testing, and deployment.”

5. Leverage third-party expertise and resources: To accelerate your efforts and support your internal team in the early stages of a project, companies should consider getting outside help. This can come in the form of business consultants and specialist systems integration (SI) firms.

If you’d like to learn more about successful master data management, you can read this use case on Netspend to see how the company manages volumes of diverse financial data with a unified, single source of intelligence for employees.