“ If you are in a certain domain for a very long time you become more of a subject matter expert and depth-oriented person rather than becoming somebody who can think beyond the traditional way of approaching things. For AI & Analytics which is more of a horizontal function, it works well if you come with a cross-industry experience. If you see many of the successful leaders in the analytics space they don't come from a single domain and are generally able to set up teams with the curiosity to learn about the new domain. The cross-pollination of ideas across industries is what sets them up for success”

– Excerpt from the interview with Bharathram Ramakrishnan

Today is Episode 21 of the Interview series on Expert-Talks, with Thought Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Bharathram Ramakrishnan ( Bharath ), Global Head of Data Science and AI, at Novartis.  Before Novartis, Bharath was the Global Head of Data Science and Analytics at Dupont. He also held  Analytics leadership roles at Shell, TCS and Mu Sigma. Bharath holds a PhD in AI, an MBA in Systems and a Bachelor in Electronics Engineering.

We are listing below a few key points from the interview :

·         Bharath highlights the significance of understanding domain-specific challenges and being able to communicate effectively with business stakeholders. He emphasizes the need for collaboration within analytics teams and across departments to achieve success in delivering analytics solutions.

·         Key functional areas for business analytics in Pharma include operations, research, and distribution, each requiring high accuracy and reliability.

·         In the pharmaceutical industry, there's a push for faster delivery of impactful analytics, necessitating innovative approaches like synthetic data to bypass red tape.

·         Generative AI is predominantly used in research and development within Pharma, aiding in summarizing large volumes of documents for decision-making, while explainable AI remains crucial for ensuring safety, reliability, and compliance within the industry.

·         The interview touches upon the shift towards freelance and remote work arrangements in the industry, necessitating adaptability from both organizations and employees.

·         The top 3 areas an aspiring analytics professional needs to develop, are curiosity about domain challenges; effective communication with business stakeholders; and a collaborative work approach

 You can watch/listen to the interview on our Website, YouTube, Apple, Amazon Music and Spotify podcasts on the links given in the comments section below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, Facebook and Twitter.