Leveraging digital and analytics in biopharma operations: Six principles
30/05/2021 12:49
As biopharma companies continue to cope with the COVID-19 pandemic and position themselves for recovery, digital and analytics can be a powerful tool in manufacturing and operations. It can drive the next wave of business optimization by transforming operational performance, shortening time to market, improving quality and yield, reducing supply chain volatility, and accelerating technology transfers.
Yet while many biopharma companies have already undertaken digital-and-analytics transformations, many have made little progress. More than 70 percent of organizations have been stuck in “pilot purgatory” as they struggle to scale their projects and deliver successful digital-and-analytics transformations.1
The application of digital and analytics to biopharma operations tends to fall short against three success factors:
- The vision for the business transformation. Companies often fail to define a holistic vision of their transformation and its goals and priorities, resulting in scattered proof of concept and meager benefits. Senior leaders may be unaware of the transformational potential of digital and analytics, and of what it can already do.
- The vision for the technology landscape. Companies need a clear picture of their IT and systems landscape and where it may hinder transformation efforts. For example, reducing unnecessary complexity in systems architectures and using dashboards that align IT solutions with key performance indicators (KPIs) can accelerate transformations.
- The vision for the organization model. Companies often assign individual projects to large and unwieldy teams that make slow progress. They may lack the necessary technical resources, such as data scientists, engineers, and business translators. And they may also lack the central governance and culture of collaboration needed to manage and coordinate deployment across the business.
The following six principles can help biopharma leaders identify critical blind spots and lead successful transformations in their manufacturing operations.
1. Start with a leadership-backed, impact-driven strategy and road map
2. Accelerate transformation with experienced leaders, skilled staff, and multifunctional teams
3. Implement a strategy, architecture, and governance for data
4. Build a tried-and-tested delivery methodology for digital-and-analytics solutions
5. Construct a fit-for-purpose technology stack
6. Drive adoption and business change by engaging with the front line