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Why ViiV Healthcare is Decentralizing Analytics Innovation

Natasha Gray, VP, Head of Data and Analytics at ViiV Healthcare, shares how democratization and people are underpinning ViiV’s data-driven transformation

Enterprises that successfully leverage data and analytics have been found to outperform their competitors. But as companies undertake these transformation journeys, their data functions must also evolve to keep up with the demands of a data-driven business.

In this week’s Business of Data podcast, Natasha Gray, VP, Head of Data Analytics for HIV/AIDS researcher and pharmaceutical company ViiV Healthcare, shares how she’s spearheading the firm’s analytics capability modernization. 

“The driver behind all this is to make sure that we're getting more medicines to the patients who need them,” she says. “This means looking at opportunities to leverage AI and machine learning to optimize the business and bring about new chances for collaboration.”

"The other thing might be a bit basic,” she adds. “But it’s ensuring that our reporting and our performance is clear and accessible to all. So, democratizing data, making sure that we're having the right conversations.”

Leveraging Data Talent from Across the Business

Naturally, successful data projects in one department can lead to increased demand for data insights across the organization, stretching the data team’s resources. Gray faces the same challenge as many data leaders – balancing organizational demand with her team’s capacity. That’s why she says it’s important to make the most of co-workers outside the team with a passion for data.

Gray says: “One of the things we’re thinking about is the need for more manpower. You could say my team is the center of excellence. But there’s also an opportunity to develop the talent elsewhere in the organization.”

“If we try to hold too much centrally, we’ll become kind of bogged down, and I think that will stop us innovating,” she continues. “We have many great people within the business who have data- and analytics-related roles. In my view, that's a key to our success. If you don't have those people who are trained and can take on some of the work and drive the strategy locally, the transformation would stall eventually.”

Key Takeaways

  • Democratize data across the enterprise. Data democratization encourages inter-functional collaboration and shows value in data and analytics
  • Plan for increased demand for data. As demand for data-driven insights grows in an enterprise, data team efficiency becomes critically important
  • Make the most of data champions. Where resources are limited, developing data champions within different departments can drive the data strategy locally