Cloud is no longer an emerging technology. As adoption accelerates, it’s becoming a ubiquitous delivery option for all kinds of IT.
There are several constraints from which your company will have to break free before it can embrace the cloud. For example:
- Legacy platforms. Transitioning away from outdated technology such as mainframe computers and standalone servers and storage can be complicated, even when the financial incentives are compelling.
- Governance. Ownership of the hundreds of applications in an organization’s IT estate rests not only with the IT organization, but with stakeholders in all areas of the business.
- Budget and time. Even if the cloud promises savings through pay-as-you-go pricing without major upfront capital investments, budget and time are required to manage the transition securely.
- Contractual limitations. Licenses for the software or hardware currently in use, or outsourcing agreements may limit a company’s options by presenting additional costs for a move to cloud, or there may be prohibitive switching fees.
- Process limitations. Modernization of technologies demands modernization of business process. Cloud tends to demand changes to procurement (to be less CapEx-centric), ways of working between the business and IT, finance, legal, security, vendor management, and integration.
- Cloud skills limitations. IT professionals in a cloud-first enterprise need to know how to broker the right services and innovate for competitive advantage in a market that is changing constantly, while integrating cloud services into all other systems, cloud and non-cloud.
- Legal and compliance limitations. Laws and regulations can dictate how companies must treat particular types of data and where data can be stored, especially in sectors like financial services, healthcare and life sciences. Some enterprises play it safe by “over-engineering” to compliance laws, forcing them to avoid cloud technologies that are traditionally compliant.
Public Cloud Challenges and Possibilities
Life sciences companies have operated in a highly regulated environment for decades. These regulatory challenges affect all areas of the value chain and their respective GxP workload.
|Research and development||Siloed and legacy infrastructure||De-risk and advance R&D with AI/ML tools that work across diverse data sets to accelerate and improve drug development.|
|Clinical trials||Slow, costly, low success rate, and stringent regulatory requirements||Improve and augment clinical trials with real-time data and biometrics to enhance intelligence, insight, and accuracy.|
|Manufacturing and distribution||Track-and-trace compliance through supply chain and quality events||Optimize manufacturing with ML and business insights, and highly secure IoT technology to modernize your manufacturing.|
|Post market surveillance||Product safety and product recalls||Proactively and securely monitor large volumes of real-world data that is distributed across disparate sources with compliance and security-built in.|
|Customer, patient||Data security risks||Improve patient value, adherence, and engagement by drawing integrated data and actionable insights from drugs, devices, and software.|
Managing Risks, Becoming Cloud-First
Cloud is no longer an emerging technology; as adoption accelerates, it’s becoming a ubiquitous delivery option for all kinds of IT.
It is important to recognize and manage risks in order to become a cloud-first company.
- Data confidentiality and privacy. Cloud service providers (CSPs) and their customers share responsibility for security in the cloud. While there have been no successful violations of CSP-operated cloud infrastructure to date, for many businesses the grave consequences of a possible data breach or loss of sovereignty preclude public cloud options.
- Data availability. Businesses demanding 99.999% availability for their most critical systems may prefer on-premises alternatives to a cloud architecture spread across multiple availability zones to improve resiliency.
- Business continuity. Downtime caused by technology change, data migration and service issues must be minimized for revenue-generating activities and customer experience.
- Disaster recovery. How to ensure nothing is lost and resume normal business operations as quickly as possible.
- Service provider failure. How would a failure of CSP architecture impact the business?
- Service quality management. Enterprises depend on a high quality of service from providers and carriers and need the tools to measure it accurately.
- Organization transformation. What if we can’t get people to work in the new way that is needed to realize the full potential of a cloud operating model?
USDM’s Cloud Assurance supports a cloud-first strategy for life sciences companies through continuous compliance. Flexible cloud technologies enable the digital transformation that enterprises must achieve to keep pace with expectations for speed to market, compliance, cost effectiveness, scalability, and security. Making cloud-first a reality is the only way to ensure that IT operations can support the demands of the business. Enterprises that fail to make the transformation to the cloud risk being left behind.
Cloud 101 Blog Series
In Part 1 of this Cloud 101 blog series, we introduced the three cloud service models with examples, and provided links to digital transformation resources.
In Part 2, we talk about vendor management and scaling to the cloud.
In Part 4, we get into automation in the cloud.