Navigating the Path From Advanced Analytics to Artificial Intelligence

Arun Shastri and Sagar Madgi

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Pharmaceutical companies have a long history of making data-driven decisions and growing their business with innovative analytics and technology. They’ve been on the leading edge of leveraging new algorithms to design territories, using optimization techniques to design call plans, and applying increasingly sophisticated analytical approaches to determine customer segmentation.

Pharma commercial organizations’ analytical quotient has steadily increased over the years, with the application of newer methodologies, the ability to analyze larger volumes of data and to integrate multiple data sources, and the ever-improving ability to make data-driven decisions. They’ve also developed increasingly sophisticated and data-driven business planning processes, which have spawned organizational changes in the form of new departments such as commercial operations, marketing analytics and insights, and brand analytics.

The pharma industry has progressed relatively speedily along the analytics maturity curve, but the analytics landscape is undergoing another massive shift—and this time it’s different. What worked in the past will not easily translate to success in this new realm. Why? The data, infrastructure, operating model and more require a different approach and mindset.

About the Experts

Arun Shastri is a principal in ZS’s New York office, and has more than 20 years of experience working with data and analytics. He provides strategy and advisory services, helping clients build their analytics capabilities and leverage their data and analytics for greater commercial effectiveness. He currently works with clients on a broad range of analytics needs that span multiple industries, including insurance, asset management, travel and transportation, pharmaceuticals, high-tech and healthcare.

Sagar Madgi is a manager in ZS’s Bangalore, India, office. He has a decade of experience in consulting and analytics for the life sciences industry, and has been involved in multiple initiatives in ZS’s R&D space. His areas of expertise include RWE and clinical trial analytics, NLP healthcare ecosystem characterization, marketing mix, resource allocation and customer segmentation. Sagar primarily works with pharmaceutical clients on broad range of analytics, involving real world (RWD) and R&D data.