Show Notes
Data scientists are trained to build better models. But stakeholders don't wake up hoping for a better model. They wake up hoping to make better decisions. And the gap between those two things is where most data science value quietly disappears. In this episode, Adam DeJans Jr joins Dr Genevieve Hayes to share what it actually looks like when an organisation stops optimising for better predictions and starts building systems that enable better decisions - that is, decision factories. You'll discover: What separates a decision factory from a machine learning pipeline [02:11] Why uncertainty is an input into good decision making [10:51] How to test a decision policy before it costs you real money [12:11] Why giving stakeholders options beats giving them the optimal solution [18:48] Guest Bio Adam DeJans Jr. is a decision scientist and optimisation expert who has led high-stakes decision systems in complex, uncertain environments, at companies including Amazon, Toyota and Ford. He is the co-founder of AI and decision intelligence consultancy Bit Bros and co-author of The Decision Factory: A Novel About Decisions Under Uncertainty. Links Connect with Adam on LinkedIn Bit Bros website Connect with Genevieve on LinkedIn Be among the first to hear about the release of each new podcast episode by signing up HERE
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