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In this podcast episode, I’m joined by Piyush Das, Director at Bank of Montreal, and Souryojit Ghosh for a deep discussion on what truly separates interesting analytics from decision-grade analytics in large enterprises. A central insight that repeatedly surfaces in boardrooms: Most organizations don’t have an insights problem. They have a trust and actionability problem. Dashboards can explain what happened. But when decisions matter, leaders need answers to three tougher questions: Why did it happen? (causality, not correlation) What should we do next? (clear, contextual recommendations) Can we rely on it? (governance, traceability, and consistency) This conversation explores why causality, rigor, and outcome-first thinking are now non-negotiable for enterprise analytics teams and executive leadership. It also reflects the philosophy behind how we are building Fire AI: focusing on causal analytics and decision confidence so insights don’t just look good, they drive measurable action. Grateful to Piyush and Saourjit for the time, intellectual honesty, and thoughtful push. Conversations like these sharpen both the product and the mission. If you are designing, buying, or leading analytics for real business decisions, this episode will resonate.