McKinsey has a digital prescription for pharma processing

Given the recent surge in interest in generative AI, it’s no wonder that consultancies like McKinsey are making hay of the situation. The consultancy recently argued that “Rewired pharma companies will win in the digital age.” In a separate feature, it noted that generative AI could boost biopharma R&D productivity by billions, as we reported on Drug Discovery & Development.

It is true that the pharma sector faces significant headwinds as digital and analytical capabilities reshape healthcare. To keep up with this rapid pace of change, McKinsey argues that pharma companies must tap digital technologies to improve patient outcomes, increase efficiency and drive growth. Many firms are hiring chief digital and technology officers, it noted, but digital adoption in pharma generally remains at an early phase.

Building a solid digital foundation

McKinsey advocates for a strong foundation as the bedrock for effective digital transformation. This encompasses updated operating models, data strategies, and capabilities. Novel operating models can catalyze decision-making, bolster collaboration and expedite delivery. Further, strategic implementation of DataOps and MLOps can enhance data quality, maintain regulatory compliance and foster innovation. DataOps, or data operations, uses automated methodologies to streamline data flows and provide fast, high-quality data analytics. MLOps, or machine learning operations, enables collaboration between data scientists and IT teams to automate the machine learning lifecycle and deploy models at scale.

But McKinsey’s emphasis on the human element behind successful digital transformation is also worth noting. The consultancy underscores the need for pharma companies to hire and retain talented digital and analytical professionals. In their view, a culture that prizes innovation, continuous learning and cross-functional collaboration is poised for successful. This perspective also extends to the value of partnerships with digital health startups.

Navigating the digital maze

McKinsey, like other consultancy and analyst firms, backs a strategic shift from a scattershot approach, common in pilot projects, to a more targeted, large-scale digital transformation. Such a sharp focus may be more common now than a couple of years ago, as Deloitte as noted.

From Deloitte’s perspective, biopharma companies that were traditionally slow embrace digital technologies such as AI, cloud the computing and the Internet of Things in their operations have ramped up their digital transformation following the pandemic. Deloitte sees digital innovation as a competitive differentiator, underscoring a need for dedicated funding, a sound digital innovation strategy and the right talent​.

In such endeavors, McKinsey stress the need for continuous monitoring of user feedback and adoption rates. In December, the firm wrote that life science companies should ensure the value of digital projects at 90-day intervals.

Taking the first steps

According to the consultancy, embarking on the digital transformation journey requires aligning leadership around shared objectives and devising a clear roadmap. McKinsey advises that pharma companies should focus investments on fundamental changes such as revamping operating models, enhancing data and analytics strategies, attracting digital talent, and forming strategic alliances. Significantly, the organization’s research finds that the most successful pharma firms spend at least 20% of their EBITDA on digital and analytics.

As digital technologies transform the landscape, pharma companies must adapt or risk becoming obsolete. PwC has conlcuded that the more detailed data captured from digital processes can translate to fewer errors in production, less risk for patients and more efficient processes. Similar to McKinsey, PwC also warns about common pitfalls in digital transformation exercises, such as a lack of vision and strategy.