It’s common knowledge that the success of a launch sets the long-term trajectory of a pharmaceutical brand. In past decades, companies would double down on their research investments with massive sales forces, reaching every plausible potential prescriber, but in today’s environment, promotional resources often are limited. This means that targeting the right customers is increasingly important to ensuring that a new brand’s launch is successful.
Headlines proclaiming the latest healthcare merger, consolidation or vertical integration are hitting our screens with increasing frequency. The U.S. healthcare ecosystem is changing pretty rapidly now. Care delivery models are shifting, and cross-industry collaborations are more commonplace.
key account management,
Artificial intelligence, predictive analytics and other such technologies are coming to a pharmaceutical company near you. In fact, some would say that they’ve already arrived. But just how ready are pharma companies to embrace and integrate these technologies, and can AI really deliver?
data and analytics,
enterprise cloud technology
It used to be that pharma companies could start with the new drugs—their inventions—when planning their go-to-market strategies, but that inside-out approach doesn’t work in an increasingly customer-centric marketplace. It’s time for drug manufacturers to transition from their inside-out business models to an outside-in approach, realigning their structures and rethinking their research and resources to better assess and adapt to the changing healthcare ecosystem, and to better meet their stakeholders’ evolving needs.
reinvent go-to-market strategy,
This is the final post in a three-part series on artificial intelligence in healthcare.
Of all of the marketplace dynamics and advances currently posing a threat to pharma’s traditional methods and models, artificial intelligence and advanced data science are causing their fair share of consternation. I recently addressed this issue with my colleague John Piccone, a ZS principal and advanced data science expert who previously led IBM Watson Health’s life sciences offerings, and he succinctly stated the commercial transformation challenge that lies ahead: “Pharma’s role is going to change from educating people to educating algorithms.” How can pharma get there? What steps can companies start taking now to adapt? John has some ideas.
artificial intelligence & pharma,
AI blog series