In this episode, Amir welcomes Barb Wixom, Principal Research Scientist at MIT Sloan’s Center for Information Systems Research, to unpack what data monetization truly means and why most organizations misunderstand it. Barb shares insights from three decades of research and her new book, explaining the three real ways to convert data into financial value and the core capabilities companies need to do it right. This is a must-listen for anyone serious about turning data into measurable business impact rather than just buzzwords.Key Takeaways• There are only three ways to monetize data: improving internal processes, wrapping analytics around products or services, and selling informational solutions.• Success in data monetization starts with managing data as an asset, not just accumulating it.• Five core capabilities define maturity: data management, data platform, data science, customer understanding, and acceptable data use.• Companies should begin with internal improvements before moving to external monetization like data products or solutions.• Having “a lot of data” is irrelevant if it’s not usable, trusted, and aligned with strategy.Timestamped Highlights(01:17) Barb’s research journey from data warehousing to modern data monetization(03:30) Why no one agrees on what data monetization means—and why that matters(08:41) The three true paths to monetizing data: improving, wrapping, selling(14:46) The five core capabilities every organization needs before chasing advanced monetization(18:04) Why small startups can outperform big enterprises with fewer data assets(24:32) The “drinkable water” analogy for usable data(28:34) How to connect data, insight, action, and value realization(31:49) Why mastering the basics still determines success in GenAI and beyondA Thought That Sticks“It’s not about how much data you have. It’s about how smart you are with the data you have.” – Barb WixomPro TipsStart with improving internal processes using data analytics before moving to external data monetization. Build capabilities methodically and always evaluate acceptable data use as your organization scales.Call to ActionIf you enjoyed this episode, share it with a colleague who’s navigating data strategy. Subscribe and follow for more conversations that connect people, impact, and technology.