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The Data Chief | Episode 49


GILEAD SCIENCES’ MURALI VRIDHACHALAM AND ZS ASSOCIATES’ MAHMOOD MAJEED ON THE
MODERN DATA STACK AND DATA MESH


MAHMOOD MAJEED

Managing Partner, Global Leader for Digital and Technology Business

ZS Associates


MURALI VRIDHACHALAM

Head of Enterprise Data and Analytics

Gilead Sciences

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Current EpisodeEP49: Gilead Sciences’ Murali Vridhachalam and ZS Associates’
Mahmood Majeed on the Modern Data Stack and Data Mesh Your browser does not
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42:47


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 Katia on The Data
Chief.

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