Data, Digitization and Disruption
Biopharma confronts the innovator's dilemma
White Paper
Sep 30, 2019

Over the last decade a series of market and technological changes has challenged biopharma companies to reimagine how they engage with key customers – and even to reconsider which customers are most important. As physicians increasingly share their central role in treatment decisions with other, often institutional stakeholders, manufacturers' traditional commercial model risks diminishing returns. The treatment decision-making process is shifting as rapid digitization amplifies the explosion of healthcare data sources and information. While the personalization of treatment strategies shows tantalizing promise, it rests upon the integration of multiple sources of information, drawn from multiple stakeholders, to provide tailored, precise treatments. Companies must envision a different model, designed to work across a more complex, multi-stakeholder landscape, in which their own role must evolve.

For many companies, the involvement of multiple decision-makers presents a central challenge, since the prevailing commercial model rests upon the physician as its cornerstone. Today, manufacturers must navigate more complex ecosystems in which physicians play only one part. As these ecosystems develop around therapeutic areas, knitting together a diverse mix of stakeholders – payers, patients, hospital administrators, trial sites, registries, regulators, patient groups, and other data owners – how can companies ensure they remain a critical part of the value chain? Around which customers should companies organize? At what things must a company excel to demonstrate and deliver value to a complex, evolving stakeholder mix? At minimum, companies must confront the transformation of the value chain and secure a lasting role within it.

In this paper, we explore the principal pressures buffeting the industry’s commercial model and identify the elements necessary to succeed in this more complex environment. We also identify some notable risks, including some tempting strategic choices likely to fail.

By considering these drivers of change, companies can develop an operating model fit for purpose and quickly adaptable to the scope and speed of changes necessitated by an increasingly interconnected, data-rich customer ecosystem.


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