My guest this week is John Thompson, Global Head of Artificial Intelligence & Rapid Data Lab at CSL Behring, who is in the BioPharma space. The company is over 100 years old and has over 300 plasma donation centers across the United States. Once donated the “human plasma is then processed or fractionated into therapies for rare diseases like hemophilia A, hemophilia B, primary immunodeficiency disease, and other diseases like that.” The company brings an interesting mix of healthcare and analytics.
John has published two books and is about to publish his third book. His second book Building Analytics Teams: Harnessing Analytics And Artificial Intelligence For Business Improvement was how we originally connected. I liked that John was talking about the teams and organizational aspects of analytics teams. He said “nobody was really talking about the difference in analytics teams and why analytics teams are different. You know, when I talk to C-level executives, they always thought, oh, an analytic team is an IT team. They're developing forms and databases and things like that. And they're not. They're completely different. So, an analytics team is more like an artistic team.” This creative and artistic endeavor changes how you “need to work with and treat your data scientists as if they're somewhat artistic in their approach. And I think if you do that, you will have much more success. One of the things that I can say is that I've only lost one data scientist in the past four years. I don't think there's too many teams that can say that.”
John’s next book is The Future of Data: What Happens to Your Data which is less technical and more for the general public. “It was pretty clear that not many people understood what happens with and happened to your data in the current environment that we live in.” The book is in three parts. The first part cover “what happens to your data.” And the middle part “talks about all the different rules and regulations and laws that are coming to be about data ownership and data privacy and data monetization.” The last part is about what “you can do as an individual to get ready to own and proactively manage and monetize your data.”
His books and ideas also manifest in how he runs his own teams. “Our subject matter expert teams and our data teams and analytic teams are integrated tightly together.” He also communicates “as often and as freely and as fully as we possibly can.” This communication happens around timelines too “we tell people, yeah, we think this is a six month project and probably it could be done in four, it could be done in eight. So we don't give any hard and fast dates as an end point, but we do give people what we think is a reasonable range.”
A critical consideration of John’s team has to do with working with medical data. It’s crucial to use data responsibly. To use medical data right “we go to the most restrictive position possible. So in our analytics, we strip away all the identifying information. We don't even bring that information into our analytical systems. So we never have anything that identifies a patient, a donor, a person.” To do that technically they “de-identify and de-dupe and de-aggregate data in the most fundamental way that we possibly can. So we work really hard to make sure that no one can question that our analytics are anonymous and based on factors and features and data that is aligned with all the laws and regulations.”
Check out the episode to hear even more of John’s thoughts on how data engineers can become machine learning engineers, how he has 50 direct reports and loves it, and why he dislikes Agile. This is a deep conversation that you won’t want to miss.