Solving 3 Common Pre-Launch Field Planning Challenges with Modern Projected Data

Static, pharmacy-based projections no longer meet the needs of pre-launch field planning, even though many biopharma companies still use them. Not only is this data limited and rigid, but it does not provide full visibility into the market. This can impact top-line revenue and complicate the launch process. Commercial operations teams need expansive modern projected data capabilities that deliver value in the moment and adapt to changing market trends over time.

To better understand how modern projected data can support today’s dynamic launch environment, let’s examine three common field planning challenges where legacy data falls short.

Challenge 1: Complex markets

Increased innovation in biopharma is significantly changing how brands, both large and small, approach pre-launch strategies. Personalized medicine, new types of therapy – like gene editing – and small, difficult-to-reach patient populations have created more complex markets. This makes retail pharmacy-based projections less valuable because they do not capture data associated with these emerging trends, creating an incomplete view of these growing markets.

Challenge 2: Fragmented data sources and software

Complex products and therapies result in complex data sets. Projected data for non-retail products is highly fragmented and does not account for new parameters like facility sell-in and claims data. In-house, custom integrations and point solutions also contribute to a fragmented data ecosystem with little common infrastructure. This can block speed, accuracy, and advanced analytics.

Challenge 3: Dynamic launch scenarios with fluid inputs

Field planning typically begins as early as two years ahead of launch. However, in an industry with constant innovation, change is a near certainty. Rigid, one-time data pulls and set market baskets are an increasing liability to launch success and will require rework and data reconciliation for even minor changes to the market basket.

How modern projected data helps

Using modern projected data that includes brands with pharmacy or medical claims only and hybrid brands that include both types of claims helps support a patient-centric approach to field planning. This data may also represent hard-to-find prescribers who treat in a medical setting or patients receiving treatment within a clinic. It also provides access to all types of healthcare interactions between a patient and the healthcare system, ensuring a broader understanding of clinical behavior. This includes open sources like clearinghouses and switches and closed sources like pharmacies and payers. Bringing these sources together can provide a more complete and accurate view of what’s happening in the healthcare space.

Unlimited access to relevant data can also reduce the time and resources your team spends analyzing specific data sets. With modern projected data, you can directly query data at your discretion. This can help your team stay on top of changing market dynamics, especially if there is a new market entrant or treatment paradigm.

Commercial readiness and launch planning are both continuous processes which require looking at data constantly. Traditionally, teams execute a handful of use cases once at the 18-24 month mark and then again right before the launch date. Modern projected data lets field planners continuously refine use cases throughout the launch process. This helps improve launch readiness and avoid gaps created by traditional, static data. Having a more comprehensive picture of your market can also help you be more agile in planning and responding to the dynamic launch environment.

Read our eBook to learn more about how modern projected data can help accelerate your field planning efforts.