What is the Best Way for Life Sciences Companies to Eliminate Data Silos?

  • April 06, 2023
Two people seated in a lab workstation comtemplate and discuss what they see on a large computer monitor

With so much data being collected and used by life sciences companies in an increasingly competitive industry, organizations must have an optimal data strategy to maintain a financially feasible product development process. But having all that data won’t do anyone any good if they are being hampered by disparate datasets that won’t work across different systems. That is why an essential element of a successful data strategy is the creation of a unified data ecosystem that eliminates data silos. Life sciences companies can streamline how they access and analyze data by creating a federated insights ecosystem to deliver real-time predictive and preventive insights across the value chain.

Unify your data to improve efficiency

In an ideal world, this unified ecosystem would provide a single version of the truth across all collaborators within the life sciences organization and create an environment that allows for the free exchange and visibility of insights across the value chain. While one may be excused to view this as a technology problem, eliminating data silos is a business challenge, requiring life sciences organizations and their stakeholders to compare and visualize the interconnectedness of datasets as diverse as chalk and cheese.

For instance, life sciences organizations may be able to measure R&D output and manufacturing delays by comparing the data on impurities that can influence the quality and efficacy of a therapy that may appear to be efficacious in small quantities but does not demonstrate the same properties in larger quantities. To that end, these companies need to identify commonalities across large datasets or define a set of properties they seek to retain as consistent features across diverse datasets and determine the nature of the data integration desired.

The second phase after such data curation is to engage in a data federation model. The concept of data federation is relatively new. It can be an important technology-driven approach to help organizations navigate the rough waters of data silos and integration. The federated insights ecosystem would help create a network of datasets across the organization in a scalable fashion through a data lake environment. This ecosystem could help each department within the organization “federate” or segregate the insights as needed across the diverse functions through localized artificial intelligence programs that are otherwise called “Edge AI” modules.

The deployment of Edge AI modules would help resolve the challenge of localization and adaptability, as these modules would be federated or installed across varied departmental units. Through localized and federated AI models, it becomes feasible for organizations to unify datasets at the core and deliver insights that, while being specific and functional, also offer a globalized view to the organization by helping deliver a single version of the truth.

The concept of the federated insights ecosystem coupled with Edge AI principles is quickly finding application across use cases in sales and marketing. At the same time, it continues to have a developing presence across other aspects of the life sciences value chain. Investing in a federated insights ecosystem is critical for a company’s data strategy. It offers the possibility of eliminating data silos and achieving business objectives by unifying and making sense of datasets for collaborative stakeholders across the healthcare provider, health plan, and life sciences community.

Stay ahead of the competition with an optimal data strategy

The journey of data strategy for life sciences is evolving. It will require agile organizations with a solid digital mindset to leverage data as a competitive advantage to succeed in life sciences. Given the complexity and interdependencies around capturing the right data sets and creating a unified ecosystem across patients, providers and payers, a digital data strategy's success starts and ends with the resolve of leadership embracing a digital mindset. As is true with most digital transformations, the role of technology in helping drive a successful, data-driven enterprise is merely that of an enabler. Success relies heavily upon the ability of companies to answer this simple question: “What business are we in?”

Once that question has been answered, visit our Life Sciences practice to learn more about maximizing value from your investments with our cutting-edge services and solutions.

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Bhuvaneashwar Subramanian

Bhuvaneashwar Subramanian has more than 20 years of experience as a thought leader in the healthcare and life sciences. He has published extensively, including peer-reviewed academic articles on cloud computing in life sciences, digital health and nanobiotechnology commercialization. Bhuvaneashwar is a qualified biotechnologist and holds a master’s degree in molecular and human genetics from Banaras Hindu University India, a diploma in molecular biology from the Hungarian Academy of Sciences and an MBA from Edith Cowan University Australia.


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