Episode 7: Building a Commercial Function for Emerging Pharma: Challenges & Learnings

Matt Bachman is in charge of the Commercial Operations for Milestone Pharmaceutical company, a biotech company launching a novel treatment for patients with PSVT. Jasmeet and Matt discuss the intricacies of building a commercial function for an emerging pharma company, with Matt highlighting distinctions between working in a large pharmaceutical company versus a smaller one. They also delve into crucial factors influencing decision-making for the future, with a particular emphasis on the formidable challenge of navigating data considerations. Matt introduces a compelling and reflective concept, emphasizing that decisions must be "Fit for Purpose.” That is sound learning, no matter the size of your organization.

In This Episode, We Cover:

• [2:32] Matt discusses the key differences between working for large pharmaceutical companies and his current position 
• [3:41] Matt explains his vision for setting up the commercial function
• [5:50] Matt discusses how he decides what priorities are needed for Milestone to benefit the company
• [8:05] Matt shares what components he wants to implement to build a foundation for data-driven commercialization, and he is developing a data governance system
• [13:16] Matt speaks to the technologies and capabilities that they are planning for the future and how he is putting his team together 
• [17:27]  Matt shares what he has learned in the process of setting up the commercial function

Key Takeaways:

• In a smaller company, when you don’t have the resources of a large entity, you have to determine the must-haves and what things would be nice to have. You need to be able to make adjustments quickly for growing or scaling back.
• Connecting with stakeholders, department heads, and other management figures in a smaller organization is more straightforward. The absence of a sprawling corporate structure, as seen in larger companies, facilitates smoother and faster communication.
• A company can make a big mistake by spending resources on collecting data, and then they find out it needs to be more accurate data. The perfect time to make data governance decisions is when you are starting out before you start collecting massive amounts of data you won’t ever use.