The Business Situation:
A startup Pharmaceutical company was launching its first drug (drug commercialization process) after years in the FDA approval process with a specialty sales forces of 180 drug sales reps that needed to cover over a million prescribers  (physicians and other health care providers) (click will take you to the Glossary section) in the US.

To facilitate adoption of the drug, free drug samples were to be distributed to qualifying prescribers. However under the Federal prescription drug marketing act (PDMA) to qualify to receive drug samples, prescribers need to have a valid state medical license. To complicate matters, a prescriber could be licensed to practice in multiple states {eg: (NY, NJ, CT) (CA, OR) (CA, NV) etc} and samples could be dropped off only in the state the prescriber is licensed in.  The penalty for non-compliance is $10,000 per incident.

It was important to the Sales & Marketing Operations (SMOPS) team (larger companies separate Marketing Operations Data & Sales Operations Data) to have accurate data for a 360 degree view  of the prescriber to ensure high potential prescribers were not missed due to prescription data associated with different practice addresses.

What was done:
The drug Commercialization sales team was enabled via a crm system on the front end. Data cleansing, data synchronization and customer data integration (aka prescriber master) was automated with the help of ETL tools that fed into the data warehouse.  Off the shelf data integration software and data integration tools were not utilized as the cost of modifying the data model was prohibitive.

On the backend a data warehouse was designed & implemented to enable strategic and tactical BI reporting needs that were rendered via a dashboard. Data systems were designed to scale to the changing data volumes as raw data sources could be added or subtracted on short notice to match business needs.

It was also anticipated that the data analysis needs would significantly change within the first six months. For this reason data cleansing, data synchronization and reporting dashboards were designed for change and version two of the data warehouse would be released within six months. With this in mind, a decision was made not to integrate the sales data warehouse with the Enterprise data warehouse.

A “Prescriber Master” was created to ensure compliance with the regulatory requirements of the FDA, DEA & PDMA. Data from multiple systems including the CRM system, prescription data from  IMS DDD prescription drug data on a monthly & weekly basis, Sample drop data was included in the Prescriber master.

Multiple cross references were created to enable consistent, accurate and a trusted Prescriber Master Data.

Segmentation of the prescriber master was performed using over 30 criteria that was then matched to leverage sales force capacity (Sales Capacity).

Analysis was performed to identify Key Opinion Leaders (KOL) with the Data warehouse and certain raw data files acting as sources. These Key Opinion leaders were in the top segment for drug reps to call on as they usually speak at conferences.

Business Results:
Drug reps were able to target hi-potential segments which resulted in an adequate number of prescriptions being written consequently meeting investor and wall street analyst expectations.

Prescriber behavior was model in response to contact from drug reps. This enabled refining of custom segmentation and target lists and identifying appropriate methods & channels of contact resulting in increased significant savings.

Technical Environment:
To facilitate commercialization the following systems were put in place:
CRM System: Siebel
Database warehouse Platform: Oracle
Data model: Custom
Data Cleansing: Custom rules
ETL Tools: Informatica, Custom SQL
Customer Data Integration: Custom

Glossary
Prescriber: A health care professional authorized to write a prescription drug. Includes, Physicians, Nurses, Nursing Assistants, etc.

Contact Us to get answers to your specific Data Challenges and find out how we can help you achieve your business objectives through better data management.