Life Sciences Industry Leads the Way in Customer Master Innovation

Over the years, I’ve seen the industry struggle to achieve the “single view of the customer.” Whether used for manufacturing, retail, financial services or life sciences, MDM systems are well known for being complex, and therefore costly to develop and maintain.

This is not surprising given that MDM hubs were introduced a decade ago as strictly on-premise deployments. Around 2009, the next generation MDM solutions began to appear and offered hosted options to lower costs and provide additional flexibility. But data acquisition, customization, application integration, and internal data stewardship were still left up to the efforts of each individual deploying company.

The life sciences industry has always been at the forefront of utilizing MDM technologies to address issues such as physician spend reporting. So it comes as no surprise to find that it’s now the first to embrace a multitenant cloud customer master with advanced features like built-in third party data, external data stewardship services, and a unique crowdsourcing collaboration model. These capabilities make it efficient and practical for companies of all sizes to benefit from richer, more up-to-date customer information.

Evolving generations of MDM:

In one of our webinar, we examine:

• What’s essential in a customer master for life sciences
• Why the cloud is a critical enabler for accurate customer data
• Where traditional MDM comes up short

We also provide recommended next steps for life sciences companies that may already have implemented a previous generation MDM solution, or those embarking on a “green field” project at smaller or pre-commercial companies.

Life sciences companies are taking advantage of an evolutionary change in customer MDM technology, leading other industries in their innovative use of technology and willingness to collaborate with their peers.

Dan Power is founder and president of Hub Designs a global management and technology consulting firm focusing on master data management (MDM) and data governance.