Novartis and Snowflake: Driving Healthcare Data Innovation

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Global health company Novartis uses Snowflake technology as a platform to both improve business processes and bring life-changing medicines to market faster.

Loïc Giraud, global head of digital platform and product delivery at Novartis, explained to VentureBeat how the company first adopted Snowflake in 2017. The company is using the technology as part of an organization-wide data and digital initiative called Formula One, which aims to digitize operations and bring data to the heart of its business processes.

Novartis employs 2,000 data scientists who use the company’s integrated data platform to support a range of activities from researching new drugs to creating insights that help improve operational performance.

The company continues to explore how the technology can be used to exploit new opportunities and recently joined Snowflake’s newly launched Healthcare Data Cloud, which aims to create an integrated and cross-cloud data platform.

Here, Giraud explains to VentureBeat how Novartis is placing Snowflake at the center of its integrated data stack and how it is using this platform to drive insights generation processes.

VentureBeat: What was the business challenge you wanted to solve when you adopted Snowflake in 2017?

Loïc Giraud: “In the past, technologies had to do everything from start to finish: recording, curation, integration. But I think the further we go, you can see how certain data technologies play a specific role in your organization. Business entities want to access their own data and do their own work. So we tried to create an abstract self-service layer via Snowflake that can start fetching our data, after which employees can use their own tools to analyze data or generate insights. Our use of Snowflake was intended to help our employees generate data and then embed that information into other business processes.”

VentureBeat: Why did you choose Snowflake over other tools on the market?

Giraud: “Our Formula 1 platform is best-of-breed – and Snowflake is part of that architecture. When we embarked on this journey to the cloud and tried to build our data platform, we looked for a range of possibilities. For each of the capabilities, we looked to see if the native cloud provider could provide a capability that supports the feature set we needed. We have conducted several evaluations for different solutions. And we decided to use Snowflake in our layer of refinement, which is about creating aggregated data to serve certain purposes. But over time that has changed – and Snowflake has evolved as a product too, so we started in one area, but it’s now being used in other areas.”

VentureBeat: How is Snowflake integrated into your daily processes?

Giraud: “It’s in three key areas. So we use it to generate analytics – we ingest data into a big data platform, like AWS or Azure. Snowflake can work across multiple clouds. The second thing we do is prepare the data to generate insights for various use cases, such as research and development, field sales representatives compensation, sustainability targets, and financial targets. The other thing we use is the Snowflake Data Marketplace to integrate information from other sources. So in the process we used to have, we bought datasets from different vendors and then we integrated that information through APIs on our platform. But with the Data Marketplace, some of the third-party information we need, such as market and industry data, is already available.”

VentureBeat: How easy is it to create an integrated data stack?

Giraud: “I think it takes time. We have been running our Formula 1 program for three years and it requires a lot of investment in finance and human resources on my part and also on the business side. I think the biggest difficulty is that technology is changing relatively quickly. So, how do you get to a maturity level where you can start delivering results, and then again, how do you avoid creating technical debt? You will have these two types of processes running continuously. And if you wait for the tech stack to be completely ready before delivering the results, the company has gone elsewhere. So you need to constantly update your capabilities in the stack as you deliver value. And in our case we split the two – we have a platform team and we have use case driven teams. And then these teams meet somewhere in the middle so that the platform can deliver the roadmap, while the use case delivers the result.”

VentureBeat: How do you want to develop your use of Snowflake in the coming months?

Giraud: “Scale, scale, scale – we have a huge pipeline of use cases and products that we want to build. We are not only multicloud, but also multiregion. So we have a region in Europe and the US, and we implemented our data solution in China. Snowflake is not present in China yet, but we hope it will be soon. So it’s all about scaling the product and then across regions so we can make sure we can meet the needs of the business.”

VentureBeat: What does participating in Snowflake’s Healthcare Data Cloud mean for your business?

Giraud: “We want to collaborate with other healthcare organizations to develop industry standards. One of the things we think about is: ‘Can we create a solution together with other partners that can be used by everyone?’ The other thing we think about is, ‘How do we connect our data ecosystem with prescribers, suppliers and other pharmaceutical companies?’ There are many connections in the system to integrate and interconnect. You can deliver much more patient value if you can connect the entire supply chain. I believe there is much more to gain for everyone if you can share your information openly.”

VentureBeat: What else do you want to achieve in the next 12 to 24 months?

Giraud: “We’ve created our insights platform and now I’m trying to build Formula 1 as the company’s digital ecosystem. So I’m going to look for automation, blockchain, and self-service development solutions to create a true digital ecosystem for the organization. We conduct 500 drug trials per year. It is important that we can answer important questions, such as: ‘What are we investing our money in, in which trials and when should we decide to continue or stop that trial?’ These are activities that are now driven from business processes that are supported by the data platform we have created.”

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