Clinical trial programs are generating more digital information than ever before. That information is an invaluable resource for timely and accurate decision-making, but ONLY if you can consolidate all the information to create one cohesive and accurate picture. Unfortunately, if your data was not generated with the goal of being compiled, you will not be able to see the complete picture, leaving you to make decisions based on incomplete or inaccurate information.

This is why a Master Data Management (MDM) program, once considered nice-to-have, is becoming essential. An MDM helps you define, manage, and leverage the most critical shared data of your organization by providing a single point of reference for the information across all systems. Without it, compatibility of the information is left somewhat to chance.

For example, primary investigator of the clinical trial site is used across multiple clinical trial applications. If the primary investigator data (first name, last name, etc.) is not mastered, then each system could have variations of this data (Joe vs. Joseph vs. Josef), making it nearly impossible to pull the data together.

An MDM program with a single, centralized data management hub provides a number of benefits:

• Since the data is governed at the corporate level, it reduces data management workload at the departmental level.

• Data quality improves, enabling better cross-department reporting, which in turn drives improved decision-making.

• It reduces time to market for new applications, as they can be connected to the master data management hub for the critical enterprise data.

• Improves business continuity during major transformational events, such as a merger or an acquisition.

Establishing an MDM program is a large but increasingly necessary part of a successful company’s infrastructure. Here are a few things to keep in mind when you begin your implementation:

• Build your governance model deliberately. Establish your MDM data standards and context based on input from all affected departments, and consider industry standards and norms.

• Don’t do it all at once. Pick a starting point with limited scope that proves the technical approach, then expand to more complex entities. For example, for managing clinical trials: start with the compound identifier (you might have a few), then incorporate the study identifier (you might have a few 10s), and then bring in the clinical trial sites (100s to 1000s).

• Plan for a marathon, not a sprint. An MDM program is not a once-and-done thing. Create a strategy for maintaining the model as the company evolves to prevent degradation of the data quality.

• Select the right tool. There are a number MDM tools readily available, so know what your organization needs. Consider factors such as multiple domains, integration connectors, deployment type, cost of ownership, and complexity of implementation (as well as support).

An MDM is the most valuable investment you can make to get the most out of your shared information assets. While a large undertaking, the benefits to the business in better decision-making and faster time to market are undeniable.