Our inaugural Data Science Showcase brought together business leaders and data scientists from around the globe to share breakthrough ideas that are transforming healthcare from end to end. Yet from that panoply of voices emerged a common refrain: As data becomes inseparable from decision-making, how we apply data science becomes an extension of Our Credo in turn.
In fact, you can already see that playing out at Johnson & Johnson today—and it's crucial to how we're shaping the future of health.
Data Science and Decision-Making
Data science connects to many of our decision-making processes at Johnson & Johnson in a literal sense today. That is, we've integrated data science into those processes to the extent that data and decision-making have become inextricably linked.
"We want our decisions to be rooted in data, because we want to drive better business decisions across the board—and have greater visibility into those decisions, too," explained Yuqing Sun, Senior Director, Data Science and Analytics. "The benefit of that is better outcomes, and more impact, for our patients."
Manoj Pandey, Director, Advanced Analytics, Enterprise Supply Chain, seconded Yuqing—in his view, data science and decision-making amount to two sides of the same coin.
At the same time, Yuqing and Manoj sounded a note of caution, too. Namely, while we're leveraging cutting-edge data science to make headway on the greatest health challenges of our time, doing so means being judicious about how, where and why we apply it. And that brings us to the second convergence between data science and decision-making at Johnson & Johnson today.
Data Science and Our Credo
But data science applications come with unique ethical considerations in healthcare: data ownership, data privacy, causation, interpretability and more. In that light, it's particularly important that how, why and where we apply it is anchored in Our Credo.
Yuqing underscored the connection: "Quality and reliability are paramount to everything we do, so manufacturing our products with the highest standards of safety and quality is a key priority."
Manoj articulated the challenge, and the opportunity, when applying data science to improve human health in a similar way. "I’ve spent my career working with data, first doing risk modeling for banks and later analyzing parts and reliability for a global aircraft manufacturer," he said. "But with healthcare, it's a completely different ball game. We're actually touching people's lives. The decisions we make are absolutely critical to the outcomes we drive."
That's why we've built key controls—and why, before exploring potential data science projects, we first stop to ask questions like:
- Is data science the right tool to solve this problem? Why or why not?
- If it is, what will be the long-range implications of that decision—for patients, for doctors, for our own ability to innovate?
Our goal is to positively impact human health holistically, so we're building critical guardrails around how we apply data science to ensure that we meet that directive.
It's also a good example of the fact that there are risks and pitfalls inherent in data science, which Yuqing, Manoj and other data scientists at Johnson & Johnson are working hard to address.
Join Our Community of Data Scientists Today
At Johnson & Johnson, we're applying data science in ways that not only drive real-world impact but fundamentally align with our values—it's the only way to ensure we continue to do well by doing good.
Ready to join a company where you can explore your interests, grow in your career and make a difference in the lives of people around the world? Check out all of the data science roles we're hiring for today.