The case for cloud in life sciences
Cloud computing has come of age. From its origins in the tech sector more than a decade ago, it has spread to a wide array of industries that value the resilience, speed, and scalability it confers—and all without the need for heavy capital expenditure. Leading life-sciences companies are discovering the potency of cloud in enabling analytics, shrinking innovation cycles, and standardizing processes across global operations, among other benefits. Accordingly, recent cloud deals in life sciences have become a significant share of the industry’s IT investment.
Industry leaders are increasingly aware of the transformative nature of cloud technology. Moderna, for example, was able to deliver its first clinical batch of its COVID-19 vaccine candidate to the US National Institutes of Health for Phase I trial only 42 days after the initial sequencing of the virus by using cloud technology. Why? Said Stéphane Bancel, Moderna CEO, “Because you don’t have to reinvent anything. You just fly.”
Or, more broadly, as Johnson & Johnson’s enterprise chief information officer Jim Swanson put it, “Ubiquitous data, together with elastic, scalable cloud and edge computing, is part of what’s enabling us to innovate and scale in such unprecedented ways.”
He is not alone: in recent company reports and press releases, 16 of the top 20 pharmaceutical companies refer to cloud technology.
The applications they mention span the value chain, with research and early development, market access, commercial, and medical applications dominating mentions. “My vision is … to deliver transformative therapies and better experiences to patients, physicians, and payers faster than previously possible,” said Takeda CEO Christophe Weber in a press announcement of the company’s strategic partnership with a cloud provider.
Although belief in the value of cloud is widespread, a clear understanding of precisely where that value resides—and how to capture it—is often lacking, leading to misguided strategies and faulty implementation. One common assumption is that cloud’s primary value comes from upgrading IT and reducing technology costs. In fact, analysis shows that the greatest benefits derive from enabling business innovation through improvements in automation, scalability, resilience, and data analytics. McKinsey research indicates that businesses can capture enormous value from cloud through both cost optimization and value-oriented business use cases. Our estimates suggest that the potential value creation for Fortune 500 companies could reach $1 trillion in run-rate earnings before interest, taxes, depreciation, and amortization (EBITDA) by 2030. This may be a conservative estimate, since emerging cloud-enabled technologies such as augmented reality and automatic machine learning are likely to offer additional opportunities for value capture. When analyzing cloud migrations in Fortune 500 pharma and medtech companies, McKinsey found that, on average, companies stood to gain about $10 billion to $15 billion in improved 2030 EBITDA run rates from the rejuvenation of IT, but roughly twice as much—about $25 billion to $30 billion—from business innovation. For the pharma companies in the sample,
the estimated potential value amounted to $20 billion to $40 billion, an improvement of 9 to 19 percent. With so much value at stake, technology and cloud strategy is no longer a matter for the chief information officer alone but a critical topic for the entire leadership team.
This article outlines how life-sciences companies can create value from cloud, explores the challenges of making the shift, and draws lessons from successful cloud migrations.
How can life-sciences companies create value from cloud?
Drawing on our experience of cloud migrations with companies across sectors, we have identified five main ways in which life-sciences companies can use cloud technology to create business value by rejuvenating IT and driving innovation.
Rejuvenating IT
The two main benefits of upgrading IT architecture and systems are that it enables data and analytics and allows global standardization of processes.
Enabling data and analytics. Cloud platforms enable analytics use cases to be quickly scaled and deployed along the entire value chain, from early development (such as supporting lead selection) and clinical trials (such as optimizing protocols) to manufacturing and supply chain (such as improving yields) and customer engagement (such as tailoring field-force contacts). Analytics can also be readily deployed to enhance enabling functions such as demand forecasting. For smaller pharma companies with fewer resources, cloud can provide access to the low-cost, unlimited computing power needed to develop and capitalize on analytics use cases. A few examples serve to illustrate the range of possibilities opened up by cloud, such as one company’s cloud-powered AI platform that can perform in silico analytics to uncover hidden relationships between molecules, targets, and disease. In another example, a biotech company uses its cloud-based AI platform to convert complex medical data such as genomic profiles into valuable clinical insights for healthcare professionals. And a global pharma company applies cloud-enabled analytics to improve supply-chain performance and forecasting.
Allowing global standardization of processes. Migrating to cloud technology can serve as a catalyst to simplify and standardize business processes. For instance, off-the-shelf cloud solutions incorporating mature processes can help enforce standards and avoid lengthy blueprinting—a common cause of overruns in traditional IT implementation. Migrating to the cloud can also generate momentum for moving from local to global processes in areas such as using research data across systems and functions, optimizing supply chains, and standardizing sales operations.
Driving business innovation
A shift to cloud can also accelerate and scale up innovation by shrinking technology-innovation cycles, building an open platform or ecosystem, and providing for rapid scaling.
Shrinking technology-innovation cycles. Successful companies structure their operating models around products and platforms and accelerate development by setting up cross-functional teams that work in short iterative cycles. With cloud technology, companies can deliver brand-new services in less than six months, step up release frequency from quarterly to weekly, and slash deployment lead times from days to hours. This is because businesses can have the development, quality, and production components side by side so that changeover between them becomes easy. Automating infrastructure deployment and operations also helps to bolster an organization’s agility and resilience.
With cloud technology, companies can deliver brand-new services in less than six months, step up release frequency from quarterly to weekly, and slash deployment lead times from days to hours.
Becoming a platform or ecosystem operator. Building an open platform or ecosystem not only generates operational improvements (such as minimizing production downtime by using real-time data on ingredient or material stock levels at suppliers) but also offers new ways to engage with customers (such as creating dedicated patient portals to help individuals manage specific diseases). Cloud-enabled platforms can help companies capture value from data by integrating end-to-end processes and standardizing workflow management. For instance, some contract manufacturing organizations provide customers with access to their data sets so that they have real-time transparency on production and can deploy advanced analytics to optimize parameters throughout the manufacturing process.
Scaling rapidly. Scalability is one of cloud’s biggest advantages. Almost all essential business capabilities can be supported by cloud systems, meaning that application maintenance requires only a lean IT organization. This allows smaller biotechs using cloud technology to grow rapidly without substantial capital expenditure. It also reduces integration costs and timelines in M&A transactions, enabling new acquisitions to be brought on board more easily. Moreover, experience from the financial-services sector indicates that institutions have been able to cut the cost of entering a new geographical market by 40 to 50 percent after adopting cloud, while also reducing the time to market from four months to less than one.
Common challenges in cloud migration
Our experience of supporting organizations from a range of sectors in moving to the cloud indicates that migrations can present challenges in realizing business value, achieving compliance, managing costs, and acquiring talent.
Realizing business value. A McKinsey survey revealed that executives’ biggest barrier in cloud migration is the ability to make a compelling business case for the target state of cloud adoption.
In addition, many organizations experience delays in their migration or reap fewer benefits than expected. Likely underlying causes include flawed assumptions about where the true value lies; the emergence of unforeseen technical hurdles; a lack of standards, which poses security, resiliency, and compliance risks; and difficulty in extending the use of cloud across the whole business. This is especially true with the fragmented R&D environments found in many pharma companies. To preempt such issues, leading companies design a holistic migration strategy that prioritizes the business value enabled by cloud and focuses on domains where mutually reinforcing workloads allow this value to be captured in full. In fact, executing a successful strategy requires effective collaboration between IT and non-IT functions to drive process changes. As a result, IT cannot be a “back office” function; rather, it must be a fundamental enabler for capturing business value.
Navigating data protection, security, and compliance. Traditional cybersecurity approaches were never designed to cope with the agility and speed of cloud-enabled operations. Leading organizations are turning instead to new “security as code” approaches in which cybersecurity policies and standards are automatically incorporated into configuration scripts for provisioning cloud systems and deploying at-risk code. This helps to protect cloud workloads, improve system security, and increase business-value delivery. As for compliance, requirements depend on the legislature governing both the provider and the consumer of cloud services. From a technical perspective, companies can encrypt data transfer, storage, and processing to mitigate compliance risk.
Managing costs. First, the excitement of migrating infrastructure, platforms, or software to the cloud can lead to a proliferation of applications and a lack of governance—both of which drive up costs. Adopting strict financial-management methods can help control expenditure. For example, companies can track which departments register accounts for which service packages at a software-as-a-service provider, and can monitor which analytics group uses the most virtual machines with the highest computing power at an infrastructure-as-a-service provider. Second, the migration toward cloud itself entails one-time costs, such as for an enterprise resource planning transformation, which need to be managed in a value-based approach. With such an approach, decisions about what to purely migrate and what to upgrade can be made more easily. Third, costs for managing legacy and cloud technology in parallel need to be considered. To keep these under control, it is pivotal to really migrate—and not duplicate—IT capabilities into the cloud and turn off legacy infrastructure and applications.
Building and acquiring suitable talent. Moving to cloud mostly means a shift in technology away from well-known legacy systems toward modern architecture and technology stacks. On this journey, it is crucial to transform workforce capabilities along with the tech transformation. This might be via upskilling of the internal workforce with the help of external support during the transition or by strengthening it through hiring. Moving toward cloud usually makes it easier to attract and excite new talent who, with their fresh perspectives and methods, could increase the business value enabled by cloud even further.
Companies looking to tackle these and other challenges can draw helpful insights from those organizations that have gone before them.
Lessons from successful cloud migrations
Life-sciences companies can take a few key steps in technology prioritization, governance, operations, and delivery to help smooth the path of cloud adoption.
Pace and prioritization. Successful companies involve the business up front when prioritizing cloud applications to focus efforts. They also ensure that application and architecture modernization takes place at the best time (whether before or after migration). They determine how to segment applications to shift them to the cloud piece by piece, and continuously refresh app configurations.
Governance. Best practice in governance involves establishing a rigorous framework and processes for managing cloud consumption, monitoring cloud spending, and reconfiguring applications to reduce usage costs under utility-pricing models. It also involves periodically reevaluating service providers’ tools and capabilities to identify opportunities to improve security and stability.
Operations. Operational lessons include launching early change-management and training efforts to scale up internal capabilities for migrating applications, planning the decommissioning of data centers and retirement of applications well in advance, and constantly striving to boost organizational agility and improve operations.
Delivery. For the delivery of a cloud transformation, the right ecosystem of partners and setup of these partnerships is necessary—not only from a technical point of view but even more so from a business standpoint with aligned incentives. This creates a win–win situation, creating business value and driving cloud adoption at the same time.
Approach for successful cloud migrations
Successful cloud migration depends on an integrated approach that involves both IT and the business, and comprises three main streams of work: the program strategy and management, business-domain-based adoption, and foundational capabilities (exhibit).
Exhibit 1
The program strategy sets out how the organization will progress toward a clearly defined target state, with full alignment between business and IT objectives, investments, and risk appetite. The strategy is supported by stringent program management that tracks the value and progress achieved at each stage of the transformation to ensure its success.
Business-domain-based adoption is critical in scaling the transformation beyond its technical aspects. Progressing domain by domain or app by app ensures that value is captured across the entire business via end-to-end automation, innovation, scalability, resiliency, the ability to analyze big data, and other gains. Similarly, as there is no single path to the cloud, the route to adoption is defined separately for each use case, with the organization weighing the pros and cons of cloud migration or remediation and re-architecture efforts to determine the scope and timeline of each step.
Foundational capabilities are the technologies and processes needed to enable safe, secure cloud operations. They fall into three categories. Cloud services and architecture, including internal standardization and governance, comprise the organization’s choices of cloud offerings and configurations, which drive investments and run costs. Cloud risk and security management is a policy-driven approach to automate security configurations and allow real-time transparency that supports compliance. Completing the picture, cost optimization ensures the organization is efficient and effective in its move to cloud, with control over consumption, clear governance, conformity to policy, and cost transparency, along with a commitment to performance and service levels. A company’s choice of cloud configuration and optimization levers can create a significant cost differential.
The right starting point will depend on an organization’s context and needs. For example, one biopharma company began by developing a granular multiyear strategy that enabled it to negotiate deals with a cloud service provider and a system integrator to capture savings that would fund its full-scale transition to the cloud. In contrast, a large financial institution with stringent security and resiliency requirements started by investing in foundational capabilities as a basis for building critical workloads in the cloud. Together, these three streams of work are iterative and mutually reinforcing, and while all are essential, the relative emphasis each one receives will vary throughout the transformation process.
Across the globe, more and more organizations are unlocking the benefits of cloud computing. Life-sciences companies are no exception. An understanding of likely challenges, common pitfalls, and the value at stake can help leaders navigate a successful migration.
