Beyond the Data: Making HCP Analytics Actually Work for Commercial Teams

Kunal Girotra, Senior Manager, Strategy & Enablement, Pfizer

The pharmaceutical industry is in the midst of its most significant transformation in decades. With the rise of specialty medicines, increasing competition, and evolving HCP preferences, our traditional approaches to customer engagement are being pushed to their limits. But here's what's fascinating: while most pharma companies are investing heavily in data collection, many are still struggling to transform that data into meaningful HCP engagement.

The traditional approach to HCP segmentation has been relatively straightforward — prescription volumes, specialties, and perhaps a few basic behavioral indicators. Today's landscape requires far more sophistication. An oncologist in a major academic center might require different engagement strategies than one in a community practice, even if their prescription volumes are identical. These nuances matter, particularly as we see the continued growth of specialty products and increasing complexity in treatment decisions.

The challenge intensified when companies began transitioning to remote sales during the pandemic. Traditional segmentation models, which had served them well for years, suddenly needed complete reimagining. Companies started to realize that building dynamic feedback loops between field teams and analytics systems wasn't just beneficial — it was essential for survival in the new commercial landscape.

Leaders in this space pushed themselves to develop platforms that didn't just deliver insights to sales teams but enabled them to contribute real-world observations back into the system. When a rep noticed changes in HCP behavior or preferences, that information immediately influenced targeting recommendations. This bi-directional flow of information proved crucial in maintaining effective engagement during market disruptions, whether from new product launches, policy changes, or shifts in care delivery models.

A common challenge among commercial leaders is maintaining personalization at scale. With portfolios growing more complex and HCP time becoming increasingly precious, how do we deliver tailored engagement while managing large territories and diverse customer bases?

The answer lies in what I call "guided flexibility" — using descriptive and predictive analytics to identify broad engagement patterns while giving field teams the tools and autonomy to fine-tune their approach based on direct HCP interactions. For instance, our data might indicate that certain oncology KOLs respond best to early clinical data shared through medical science liaisons. However, our field teams might discover that within this segment, engagement preferences vary significantly based on research interests or practice settings. That's where human insight becomes irreplaceable.

Looking ahead, artificial intelligence will undoubtedly enhance targeting capabilities, but it won't replace the fundamental need for human judgment in HCP engagement. The organizations that will excel are those that use AI to augment, not replace, the expertise of their commercial teams.

The future of HCP engagement in pharma isn't about having the most sophisticated technology stack — it's about creating the right blend of data-driven insights and human expertise. It's about building scalable systems that maintain the personal touch healthcare professionals expect and deserve. Most importantly, it's about remembering that behind every data point is a healthcare professional making critical decisions for patient care.

As our industry continues to evolve, the winners will be organizations that can strike this balance — using advanced analytics to inform strategy while empowering their teams to build authentic, value-driven relationships with healthcare professionals.

Kunal Girotra, Senior Manager, Strategy & Enablement, Pfizer