The life sciences industry is undergoing seismic change as it shifts from a product to a patient outcome orientation and embraces all forms of exciting new science -- from digital therapeutics to gene therapy. Data is more available than ever before, and companies are connecting disparate data sets and developing more personalized treatments. Healthcare is attracting significant investment from global tech giants, such as Amazon, Google and Apple. These companies and more are looking to disrupt traditional care models and change our understanding of wellness - leveraging AI, analytics, blockchain and other emerging technologies in the process.
Just as data and the intelligent interpretation of that data changed the face of retail, a similar revolution is happening in healthcare as science, technology and regulation all advance to change how and where patients’ health and wellness needs are met. Accenture research shows that 99% of life sciences executives expect the volume of data exchanged with their ecosystem partners to increase over the next two years. There is no doubt that for life sciences, data is key to future success. Some data in life sciences is still difficult to come by. But life sciences CIOs must re-imagine their technology architectures and determine how to extend their enterprises into an ecosystem of partners that’s wider than before.
The combined impact of the availability of data, massive advances in computing power, and the application of “intelligence” (predictive and cognitive analytics, etc.) will drive change in traditionally siloed life sciences business models. Ultimately this change will enable a more continuous and virtuous cycle of interaction between patients and healthcare companies that will help deliver better outcomes. This new “intelligent enterprise” will research, develop, distribute and commercialize solutions for patients and healthcare consumers in ways that are very different from the past.
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We have looked toward the future and have identified the technology trends that will have the greatest near-term impact on the life sciences industry as it reconfigures itself to deliver patient and economic outcomes.
Data Veracity
Delivering on the new industry standard of value-based outcomes requires a comprehensive picture of every patient. And that’s something no business can achieve solely from the data it holds internally. As healthcare becomes ever more consumerized, and technologies grow in sophistication, the range of data sources will continue to proliferate.
What may be concerning is that only one in three life sciences executives that we surveyed said that they have high confidence in their current data and that data is about to grow significantly and become much more complex. Whether companies are accessing the data flowing from a patient’s wearable device, retrieving financial information or tapping into a patient’s EMR or genomic data, one thing is certain: the range of data that they need to access to deliver better outcomes - not just products - will grow exponentially. Enterprises must secure and validate a growing number of data sources to ensure quality and operational effectiveness while addressing areas where gaps exist. Along with the challenge of managing these exploding quantities of data, life sciences companies must also understand and assure the “truth” of the data they use and exchange with others. Right now, there’s clearly work to be done in this important space.
Frictionless Business
We are witnessing that companies in all industries increasingly compete through strategic partnerships, and when these partnerships are technology-based, they can expand partner networks faster and into more ecosystems than ever before.
But legacy business systems - often built in silos and only intended to operate within the enterprise walls - weren’t constructed to support these technology-based partnerships. Now, as life sciences companies expand their networks to engage in ecosystems that will include start-ups, other life sciences companies, payers and providers – not to mention unanticipated new partners from beyond the traditional healthcare ecosystem - these outdated systems will present major obstacles to growth. From a technology perspective, the large-scale, internally focused systems that have served companies well over the past 30 years of globalization will need to be re-architected to take advantage of microservices to aid interoperability as blockchain to ensure appropriate security and control.
Life sciences companies that invest in the technology required to build a frictionless business today will redefine how they interact and transact in the future and become the partner of choice for industry redefining, disruptive collaborations.
Citizen AI
Although many life sciences companies have eagerly embraced “entry-level” AI (robotic process automation, for example) to drive operational efficiency, particularly in research and development, the next stage of AI adoption offers far greater promise—as well as bigger challenges. In fact, 85% of life sciences executives that we interviewed indicated that AI is advancing faster than their organization’s pace of adoption.
As industry adoption matures AIs will no longer simply be used to replace highly repeatable and manual activities and instead will become valuable members of the team. Life sciences companies will need to focus attention on ensuring that their AIs are as unbiased, accountable and transparent as possible throughout their use. In other words, they will need to “raise” their AI as a responsible representative of the business and a partner in delivering better outcomes for patients.
In conclusion, the life sciences industry is experiencing major disruption and the leaders of tomorrow will be those that embrace new business models that are intelligent, open, innovative and above all else solve for patients. Technology will be a major enabler of these new business models and the winners of tomorrow will start investing in these new capabilities now.
Author Biography
Geoff Schmidt is the global lead for Accenture’s Life Sciences Technology business. In this role he is responsible for offerings, alliances, sales and delivery of technology consulting and outsourcing solutions for our Life Sciences clients around the world.
Prior to this role he led Accenture’s global R&D Technology business and was instrumental in bringing to market innovative platforms including the Accenture Life Sciences Cloud, PV First and the Research Life Sciences Cloud - envisioning, creating and taking to market novel technology platforms that enable our client’s operations from research through clinical development and pharmacovigilance to commercial.
Geoff has been with Accenture since 1996 and has spent his entire career working with Life Sciences clients. He initially specialized in architecting, implementing and running global application development and maintenance organizations and since then has held roles of increasing responsibility in sales, client account leadership, and business leadership. He has bachelor’s degrees in management and Computer Science from State University of New York (SUNY) Geneseo.