Master Data Management for Life Sciences
Master data management refers to a system and a practice for businesses to collect, process, and validate information used by different areas of their organization. All businesses rely on data for key activities and analytics. MDM improves efficiency and data quality, enabling better insights. Such timely information sharing may be your competitive advantage. Click here to learn more.
Data Collection for Master Data Management
From a life sciences perspective, master data management starts with collecting healthcare professional (HCP) information from various sources. Information like HCP affiliations to healthcare organizations (HCO), HCP contact details, and what kinds of patients HCPs are seeing is entered into a CRM or Data Warehouse after some type of engagement.
A field sales representative calls on a doctor for the first time. They enter the doctor’s contact information into their sales CRM with his name, John Smith, and his email, which is his preferred method of contact. This information is saved in the sales CRM and sent to the MDM.
The next component of MDM is data validation. Information entered by field reps is validated against trusted database repositories like the National Provider Identifier Registry and other paid vendors. This process verifies that the information provided by field representatives is accurate.
The MDM validates John Smith is an active HCP based in Boston, Massachusetts by comparing his name, address, and any other identifying attributes against the NPI Registry. It confirms that “John Smith at 123 North Street” is John A. Smith, MD, NPI 1234567891, licensed in Family Medicine in MA.
Data governance is a crucial part of master data management. Incoming data enhances the existing master data with updates about HCPs and HCOs, but it’s not always accurate. In most cases, master data from a trusted third-party source will take precedence over data entered by a sales rep. This mitigates conflicts that may arise, like address or name spelling differences. However, sometimes more recent or timely data will win over third-party data.
A field sales rep calls on Dr. Smith but finds that he isn’t practicing in Massachusetts anymore. Turns out, he completed a residency at Mass General, but he’s completing his fellowship in New York now. The NPI Registry hasn’t been updated since 2017 when he was first licensed as a medical student in training. In 2021, Dr. Smith is practicing in New York and the master data should be updated to reflect that.
Insights and Analytics
The most compelling use of master data management is enabling cross-functional analytics to help all departments draw better insights from organizational data. Data that is central to the organization and shared across functional areas is stored in the MDM to make it easily accessible to all areas for reporting and analytics.
The sales team is reporting on customer conversion rate. Medical Affairs is analyzing customer engagements by channel. Both teams benefit from shared information about HCPs and engagements with them. With an MDM, this information is not isolated in each team’s CRM. Starting from the same master data enables these reports to provide actionable insights.
How can master data management help your business?
Master data management enhances data quality and enables actionable insights. With data central to your business’s success readily available to all functional areas, you maximize efficiency and transparency throughout the organization.
In today’s data-driven world, a good MDM is not just valuable—it’s imperative to maintain quality master data to drive analytics and enable evidence-based decision making, especially in the life sciences industry.