Gilead Sciences’ Murali Vridhachalam and ZS Associates’ Mahmood Majeed on the Modern Data Stack and Data Mesh

Episode Overview

Sometimes data’s worth can feel intangible. But in the healthcare and life sciences sectors, the stakes are clear: having the right data at the right time can be the difference between life and death. While these industries have historically been slower to change, current global health needs and the technological possibilities to meet them are creating opportunities for more rapid transformation.

Today’s guests are Mahmood Majeed, Managing Partner at ZS Associates, and Murali Vridhachalam, the Head of Enterprise Data and Analytics at Gilead Sciences. ZS Associates is a firm dedicated to helping its customers, many of who are in the healthcare industry, develop great products by way of effective analysis, use of technology, and strategy implementation. And Gilead Sciences is a company focused on increasing worldwide health by developing medicines to help people with life-threatening diseases.

On this episode of The Data Chief, Mahmood and Murali share their fascinating perspectives on digital transformation in healthcare and the ways that patient outcomes are improving with data and analytics.

Key Moments:

How has the pandemic driven digital transformation in healthcare and life sciences? (05:34)
Why has healthcare and life sciences historically been behind in terms of digital transformation? (11:37)
Does data mesh add to confusion? (19:59)
How has modern data and analytics delivered better patient outcomes? (25:21)
How do you effectively upskill and reskill your people? (30:41)

Key Takeaways:

How do you create a data-driven culture on a legacy technology stack? (13:10)
“We are trying to disrupt that culture by enabling self-analytics. And by the way, we position parts part as that strategic tool to enable self analytics.” - Murali Vridhachalam

The democratization of data and rise of self-service analytics in business means that time is ripe for meaningful cultural change. With easier access to insights, every business person on every team has the ability to be more data-driven.
Why must modern IT pro's expertise span cross-disciplinary boundaries? (36:28)
“Data scientists have to work in the business units that are central IT teams and gain that experience because having the knowledge of the business process, how the business works, and gaining the domain knowledge is absolutely crucial in developing good machine learning algorithms.” - Murali Vridhachalam

Although Mahmood and Murali each articulate it differently, they both agree data professionals need to have a diverse skillset that spans technical prowess and business acumen. As the world has grown more complex, workers are constantly required to learn more and adapt quickly to new concepts.
How is data and analytics really delivering improved patient outcomes? (25:21)
“The ecosystem has been quite sophisticated, talking about the AI use cases, you actually can predict the likelihood of a prescriber writing a script before a script is being written. You can actually prescribe, can actually predict a patient dropping a therapy before it actually drops, or you can actually predict a plan changing their formulary status before it actually happens.” - Mahmood Majeed

The opportunities for greater healthcare system efficiency through the implementation of AI and machine learning are great. Already improved outcomes are seeing patients and providers benefiting from better and more timely care.
What does the convergence of data, AI, and cloud mean for modern data leaders? (08:56)
“The convergence of data, AI, and cloud, and we have a lot of enterprise data on the cloud, and we will apply AI and machine learning on top of it. It yields special use cases. There was never before possible because data was always in silos, And the scale of the cloud lets us work on data better by scale data.”

We are in the early days of this data-rich frontier. So much data that has been in existence is finally now converging, and so much more potential lies still untapped. The life sciences and healthcare industries are moving quickly to increasing data and digital acceleration.

Key Quotes:

“We are trying to disrupt that culture by enabling self-analytics. And by the way, we position parts part as that strategic tool to enable self analytics.” - Murali Vridhachalam

“Data scientists have to work in the business units that are central IT teams and gain that experience because having the knowledge of the business process, how the business works, and gaining the domain knowledge is absolutely crucial in developing good machine learning algorithms.” - Murali Vridhachalam

“The ecosystem has been quite sophisticated, talking about the AI use cases, you actually can predict the likelihood of a prescriber writing a script before a script is being written. You can actually prescribe, can actually predict a patient dropping a therapy before it actually drops, or you can actually predict a plan changing their formulary status before it actually happens.” - Mahmood Majeed

“The convergence of data, AI, and cloud, and we have a lot of enterprise data on the cloud, and we will apply AI and machine learning on top of it. It yields special use cases. There was never before possible because data was always in silos, And the scale of the cloud lets us work on data better by scale data.”

Mentions:

Zhamak Dehghani

Data Mesh

About Mahmood Majeed

Mahmood is a managing principal and leads ZS‘s global digital and technology practice area. For the past 22 years, he has partnered with 100-plus global life sciences companies advising clients on delivering measurable business outcomes by realizing and optimizing value of investments in technology, digital and AI that directly contribute to the growth initiatives of the organization

Get even more insights from data and analytics leaders like Mahmood and Murali on The Data Chief.

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