Part I: Data Migration in the Pharma Industry

In a series of four, Senior Project Manager and 7N IT specialist, Lars Søndergaard, focuses attention on what challenges and possibilities he sees with data migration in the pharma industry. Besides management,

Lars possesses data warehouse and business intelligence as core competencies and has more than 20 years of experience within his field. He has gained a lot of his experience within the pharma industry, the latest from an assignment at LEO Pharma as a Project Manager and Data Governance Consultant.

Introduction

Many Pharma companies are moving away from legacy systems to new cloud-based solutions. The trend is particularly strong in Denmark, where key players are renewing their system landscape with the broad offerings from Veeva.

Veeva Systems Inc. is an American cloud-computing company focused on pharmaceutical and life sciences industry applications.

The Veeva Systems (Vaults) are highly configurable, and companies get a head start compared to developing solutions themselves. However, data needs to be moved from the old legacy systems to the new Veeva Vaults. This task is a major cost driver and represents a significant risk.

This article focuses on the challenges and possibilities with data migrations in the Pharma industry, but I guess that it is just as true for other industries.

A unique opportunity

Having done several data migrations or BI solutions for companies within the Financials, Logistics, Publishing, and the Pharma industry, it becomes clear that it is immensely difficult for companies in all industries to maintain a data quality that enables them to harvest business-critical insights from their core data easily and cost-efficient.

Doing a data migration from a legacy system to a new operating system provides a unique opportunity to improve data quality and implement measures to keep a high data quality going forward.
Continuous high data quality requires a strict focus. Without it, process efficiency will decrease over time and eventually lead to yet another expensive and business-critical IT change to implement new operational systems.

Data governance initiatives and BI solutions are all focused on poor data quality. However, what is done here is typically reactive in nature and does not fix the root causes.

Data migrations are often part of highly complex IT projects covering both the configuration of the new system and changed or new reporting capabilities. All three dimensions are highly interconnected and should focus on eliminating insufficient data in order to:

1. Increase the lifespan of the new solution
   
   
2. Increase data value over time