Companies currently generate vast amounts of data from their systems. But while all this data is certainly a valuable asset, effectively managing it becomes more and more complex.

This is where Master Data Management (MDM) comes into play. MDM is an approach to managing a company’s data to provide a single point of truth. According to TechTarget, “master data management (MDM) is a process that creates a uniform set of data on customers, products, suppliers and other business entities across different IT systems.”

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What is Master Data Management?

Typically, master data includes information about products, suppliers, customers and locations. It differs from transactional data since it doesn’t change frequently and is used across various systems and processes. But if it’s not managed properly, master data can become outdated, inconsistent or duplicated, which can lead to inefficiency and reporting errors. In fact, a study by Experian found that 85% of organizations believe bad data is undermining their business processes and efficiency, highlighting the need for improvements in data management.

Having a well-planned MDM strategy brings multiple benefits such as improved data quality, streamlined operations, better customer experiences and reliable analytics. The business gains an accurate, 360-degree view of operations enabling smarter, faster decision-making. Plus, as a company embarks on digital transformation project, MDM establishes a foundation for success.

“Every year, poor data quality costs organizations an average of $12.9 million.”

Gartner

MDM Strategies

Define Objectives

When beginning to build an MDM strategy, start with your business objectives. For example, are you striving to align customer records after a merger, streamline production data, or comply with industry regulations? Matching your MDM initiative with specific goals helps ensure the project delivers value, as highlighted by a recent article in Pragmatic Institute.

Data Domains

Next, identify which types of data or “data domains” will result in the greatest impact. For instance, a retail company might focus on product and customer data, where a manufacturer might prioritize inventory and product data. Take a phased approach, focusing on one or two high-impact domains before expanding to others. This way you can build quick wins and momentum.

Data Governance

Ensuring data quality isn’t a one-time task. It’s a continuous process. Establishing a clear data governance policy leads to trust in the data across the company, and lays the groundwork for any technology, analytics and automation to come. Governance involves assigning data owners who manage day-to-day data quality, and establishing standards for how data is defined, entered, and used. Once policies are in place, defining some key performance indicators (KPIs) such as reduction in duplicates or improvement in data completeness helps track progress and uncover areas for improvement.

Change Management

As with any substantial company initiative, change management is important to ensure that your MDM initiative is successful. Changing the way that company data is handled often affects workflows and responsibilities. Employees might resist the changes, so planning regular communications, training and continuous feedback is key to ensure adoption.

MDM Challenges

While a solid MDM strategy helps to ensure accurate data is available to improve processes, streamline workflows and improve decision-making across the organization. But implementing master data management can bring some challenges as well. Not the least of which is data quality. According to a McKinsey study, “82 percent of respondents spent one or more days per week resolving master data quality issues.” This is where data governance comes into play. As the saying goes, “garbage in, garbage out.” With strong governance policies in place, companies can ensure that accurate and complete data entry will yield actionable master data.

Another issue which may affect MDM implementation is technology. Specifically, the existence of legacy systems—and the data they hold—while moving toward more modern technology like AI-powered MDM solutions. When selecting any additional technology, consider its ability to integrate with your legacy systems, as well as costs which may be incurred from a rip-and-replace of the old system and subsequent data migration.

Final Thoughts on MDM Strategies

With terabytes of data being created by companies each day, Master Data Management is no longer a nice to have; it’s a must. MDM sets the stage for trustworthy enterprise information which can be used for strategic planning, customer engagement, and operational improvements. Companies that invest in solid MDM strategies can leverage the vast amounts of available data to gain and maintain their competitive advantage.

Need help building your MDM strategy? Reach out to Ultra’s data management experts by requesting your free discovery call today. We’ll help you align data governance, business goals, and technology to create a strategy that delivers value.