Ten battlegrounds for digital and analytics in life sciences

Life-sciences companies are navigating unprecedented yet uncertain times. The collision of scientific progress, technology disruptions, and innovation in clinical practice has tremendous potential to improve patients’ lives and create corporate value. Yet it is not proving easy to realize that potential.

Most life-sciences executives agree that long-term value creation lies in innovation-led growth, with digital and analytics at its core. And most companies have made significant investments to harness that value, undertaking projects and pilots that give glimpses of the exciting rewards ahead for stakeholders. But the vision of a digitally transformed life-sciences company in which people, data, technology, and partner organizations work together to create a virtuous cycle of innovation and value creation remains tantalizingly out of reach because it has proven hard to scale projects.

Most life-sciences executives agree that long-term value creation lies in innovation-led growth, with digital and analytics at its core.

Pioneering life-sciences companies are now beginning to discover the solution, however, by approaching digital transformations differently. Rather than working on discrete and sometimes random innovation projects, they are taking a more holistic approach that super-scales and supercharges the power of data and analytics by focusing on entire parts of the business system, from innovation and clinical trials to commercialization models. We may see these companies break away from the pack in the next three to five years thanks to the structural advantages gained by getting to scale faster than their peers and being able to anticipate and adopt new technology advances faster too.

Industry battlegrounds

There are ten industry battlegrounds (Exhibit 1). Each is an area of the business system where it is possible to deliver value at scale through a “platform solution,” whereby specific data sets, data and analytics platforms, analytical models, and digital experiences for customers and end users are brought to bear upon a cluster of closely related digital and analytics use cases.

There are ten battlegrounds representing significant value-creation opportunities in life sciences.

For example, in the integrated-evidence-generation battleground, companies can design a solution that uses artificial intelligence (AI) along with real-world data to generate hypotheses at scale and improve testing efficiencies for dozens of use cases across the value chain (Exhibit 2). This can dramatically advance a company’s understanding of disease progression and drug effectiveness, accelerate the search for new indications for existing drugs, and shape value-based pricing decisions. We estimate a pharmaceutical company with revenue of between $20 billion and $50 billion could improve earnings by around $300 million a year within three to five years as a result.

Creating value at scale requires an evidence-generation engine.

In the precise, real-time customer and patient-engagement battleground, AI is deployed to build an agile, customer-centric, commercial model that gets the right message through the right channel to the right customer at the right time. Personalized content is delivered at the speed of the market, with A/B testing conducted to rapidly refine messaging and content, and the results measured in real time. Campaign cycles are measured in days rather than months as a result. The incorporation of new techniques such as reinforcement learning creates a continuous learning loop, while modern marketing technology ensures everything is smoothly integrated across channels.

The question is not whether a business case can be made for any given battleground. Rather, companies should ask in which battlegrounds they are uniquely positioned to place big bets and which offer the best value for their portfolios. It is unlikely they would be able to transform the business in more than a few battlegrounds within a two-year period, as they would lack the necessary leadership capacity, change readiness, assets, and capabilities.

Companies should ask in which battlegrounds they are uniquely positioned to place big bets and which offer the best value for their portfolios.

Choosing the right battlegrounds is therefore a major strategic decision for the CEO that requires the full commitment of the board and support from business sponsors who will help drive through the transition to a new operating model. He or she will also need a strong chief digital and information officer who can design the platform plays and build digital, data and analytics capabilities across the enterprise.

Getting to scale

There are common factors among companies that have successfully deployed digital and analytics at scale. They have a clear strategy built around a compelling vision that links digital and analytics solutions to value. They excel at building solutions by mobilizing the very best people (perhaps just the top 1 to 2 percent of available internal and external talent across disciplines) and by using agile methodologies to repeatedly test and deliver solutions, fast. And they work aggressively to drive adoption at scale from the outset, navigating the complex transition to new systems, new skills, and new ways of working by anticipating and quickly confronting hurdles. Exhibit 3 gives more detail.

To deploy digital and analytics at scale successfully, organizations should consider these three factors.

All elements are key to unlocking value in a battleground approach. The starting point and emphasis will differ depending on the maturity of the battleground, however. Industry progress has been greater in some battlegrounds than others. A company’s experience within a given battleground will also shape its response.

The battlegrounds fall into two groups (Exhibit 4). In the first group, most of the key digital and analytics problems have yet to be solved. Companies are grappling to understand where the value of digital and analytics might lie and how it might translate into use cases and platform plays. In the unlocking-disease-understanding battleground, for example, companies and academic labs are experimenting with multimodal AI to revolutionize their understanding of biological systems and accelerate target identification and molecular design. MIT researchers have recently used a machine-learning algorithm to discover a novel antibiotic, for instance.1 To unlock value in these battlegrounds, companies need to align on a vision, pioneer use cases, envisage the platform play that delivers synergies from a thematic cluster of use cases, then establish proof of value to build conviction and momentum.

Some industry battlegrounds are more mature than others.

The second group incorporates the more mature battlegrounds—those in which companies have already made significant investments in people, capabilities, and even platforms, and are now running pilots that offer evidence of impact. Most of the core digital and analytics problems have been solved and the components of the platform play are well understood. There is still headroom for innovation here, as not all use cases yet have a solution. But the major value creation opportunity lies in adoption and scaling. Solutions will need to be embedded in the fabric of the company through building new capabilities, reworking entire operating models, and evolving the technology stack. At this stage, solutions will cease to “bootstrap” the business—they become the business. The operational excellence in development battleground belongs in this group, along with precise, real-time customer and patient engagement.

Categorizing battlegrounds in this way helps companies understand where and how competitive advantage can be created. But they should bear in mind that battleground maturity is not static or even linear, progressing from low to high. Technological innovation is constant, which means today’s mature battlegrounds will be tomorrow’s less mature ones. Cutting-edge analytics techniques such as deep learning, transfer learning, and reinforcement learning will disrupt areas that have already been transformed by advanced analytics, for example. And cognitive computing and natural language generation can drive further productivity advances in business processes that have been automated with robotic process automation.

Cutting-edge analytics techniques such as deep learning, transfer learning, and reinforcement learning will disrupt areas that have already been transformed by advanced analytics.

The companies that get ahead will therefore be those that seek opportunities to advance their platform plays continuously and find the next generation of solutions before others do. And because a key component of building a platform solution for any given battleground depends upon modernizing the technology foundation, those same companies will have the flexibility to accommodate further technology shifts with ease, extending a structural competitive advantage over those already left behind.


Many companies have made strides toward transforming their businesses with digital and analytics. Their future competitiveness depends on scaling up fast. We contend that this will be possible only if they focus their human and financial capital on emerging industry battlegrounds. To speed them on their way, management teams and boards should ask themselves the following questions:

  • What are our priority battlegrounds? Each company has an opportunity to break away from the pack, but could squander it if energy and other resources are spread thinly over all potential use cases.
  • Do we have the right executive sponsorship and digital leadership to win in those battlegrounds? Behind every successful transformation is a great technology leader. But companies also need a business sponsor who has spotted industry disruption before others and is willing to stake his or her career on keeping ahead. Without such sponsorship and a narrative that makes clear the need for change, most business leaders will stay focused on short-term profit and loss targets, lacking any incentive to do things differently.
  • Have we established a clear link to value? It cannot be assumed that if investments in people, data, and technology are made, value will follow. A business case must be made at the outset, then reviewed at least quarterly to ensure the link to value holds firm. Metrics that track business outcomes and platform capabilities are required.
  • Do we know how we will shift the organization from the comfortable status quo? High industry margins, long product life cycles, organizational silos, and compliance issues have all reinforced legacy systems, processes, and ways of working that hold companies back. To move ahead, leaders will need a clear picture of the endpoint of a transformation in a battleground, foster an understanding that it can only be reached through continuous testing and learning, make it clear what it means for specific individuals and functions within the business, and develop a compelling case for change. They will also need to overinvest in all the formal and informal initiatives that make change stick.
  • Do we know our starting point? Whether tackling a mature or less mature battleground, companies should step back and assess their capabilities. It is the only way to chart a course from the often messy collection of people, vendors, systems, and pilots that exists today, to a full-scale solution and a new operating model. So, in each battleground, understand the use cases and the data sets, platforms, expertise, and technical skills that will be required to deliver on them. Then gauge how the company measures up along each dimension, identifying and filling the critical gaps.

Life-sciences companies are on the cusp of a digital revolution. There are wondrous opportunities to leverage digital and analytics to address significant unmet patient need if these technologies and capabilities can be deployed at scale. A focus on industry battlegrounds enables exactly this. And companies with such a focus might find themselves in an unassailable lead.

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