Season 9, Episode 4 - Patrick Moore, AVP, Human Health Data Strategy & Governance, Merck

·31 min·1 clip

Patrick Moore describes augmented analytics as AI, ML, and NLP in one system that can ask, answer, and act.

1. Data Science Perspectives features Bill Franks interviewing Patrick Moore about a 30-year Merck career in pharmaceutical analytics and data strategy. 2. Patrick Moore is Merck’s AVP of Human Health Data Strategy & Governance, and Bill Franks says he managed an analytics leadership program where Moore regularly participated. 3. The episode asks why Moore stayed at Merck for decades and how commercial analytics changed from early forecasting and sales analysis to modern data governance. 4. Moore says he began as an undeclared undergraduate, took quantitative courses in psychology, economics, and business, and then pursued a PhD in applied research and evaluation. 5. He says his PhD internship brought him into health care, first in health services research for managed care providers and acute care hospitals, and then into pharmaceutical commercial analytics. 6. Moore says Merck’s mission is “using cutting edge science to improve and save lives of patients throughout the world,” and he links that mission to the company’s patient-first culture. 7. He describes Merck as a place with ethics, integrity, dignity, respect, and strong professional development, which he says made it possible to build a long tenure. 8. Moore says he arrived at Merck just as commercial analytics capabilities were starting to grow, which he calls “the right place at the right time.” 9. He says commercial analytics in pharma includes forecasting models, go-to-market analytics, and identifying health care professionals likely to have interest in products. 10. Moore contrasts that with clinical trials, which he describes as core to drug development rather than the commercial side of the business. 11. He says the commercial analytics workforce changed from statisticians, a couple of operations researchers, and one IT professional into teams with data strategists, data analysts, data stewards, data engineers, data scientists, data product owners, and MLOps staff. 12. Moore says the number of data suppliers also exploded from one or two suppliers serving most of the industry to literally hundreds of suppliers. 13. He says some people now spend part of their job tracking new suppliers, evaluating them, and purchasing inventories of data vendors. 14. Moore says business sponsorship changed from a “prove it” mindset to a culture where leaders say, “I need data and insights to make all these different important business decisions and actions.” 15. He says his own leadership approach starts with listening carefully enough to separate a business customer’s needs from wants and to identify the real question being asked. 16. Moore says he focuses on gaining trust so he can deliver reliable, valid, best-available insights and avoid becoming a simple order taker. 17. He says another major skill is building and leading high-performing data and analytics teams by identifying talent, keeping people challenged, and helping them feel valued. 18. The tone is conversational and reflective, with Bill Franks pressing for examples while Moore answers in practical terms and uses direct frameworks like “prove it” versus “I need it.” 19. Listeners who work in pharma analytics, data governance, or early-career corporate analytics will get the most from this episode. 20. People looking for a technical deep dive into model code or drug development science may skip it.

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