{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"The Agentic Allocator","title":"Data Readiness: The Critical First Step for AI Adoption at Makena Capital Management","html":"","width":"100%","height":180,"duration":1282,"description":"Breanna Genecov and Kunal Koppula of Makena Capital Management discuss how the firm is rebuilding its data architecture as a prerequisite to AI integration. They detail the transition from fragmented, Excel-dependent workflows to a unified, cloud-based data stack, and explain why institutional investors who skip this foundation will struggle to extract reliable value from AI. Practical guidance on change management, leadership buy-in, and phased execution makes this essential listening for LPs & allocators at the early stages of their own transformation.\nMakena Capital Management is nearly two decades into its institutional investing history and one year into a deliberate, firmwide data transformation. In this episode, Breanna Genecov (Portfolio Solutions & OCIO) and Kunal Koppula (Data Engineering) explain the technical shift from managing \"Keyman risk\" in isolated Excel files to building a unified cloud infrastructure. They discuss the practicalities of porting tools into a modern data stack, the necessity of firm-wide upskilling, and the phased roadmap from structured data consolidation toward AI-enabled unstructured data analysis. \nThe conversation cuts through AI noise: before any meaningful automation or intelligence layer can be built, your organizational data foundation must be sound. The guests detail how siloed Excel workflows, manual data pulls, and keyman risk have constrained the firm's analytical capacity, and how a centralized data stack is changing that.\nWhat You'll Learn:\n-        Why Makena treats data infrastructure as the non-negotiable prerequisite for AI adoption-        How a $22B OCIO moved from fragmented, Excel-based workflows to a centralized, cloud-native data architecture-        What \"one source of truth\" means operationally and why inconsistent data across teams leads to incongruous decision-making-        How to manage the cultural and skills gap when moving analysts from Excel to SQL and BI tooling, without making data engineering...","thumbnail_url":"https://img.transistorcdn.com/QigjduDJIqFTeeJFynBiyzGolv4eHG5zocOf8vY173o/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hZGY5/NTNkMjIzZGE0NWFj/YWEzYzY0ODU1ZTYx/NzE2Zi5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}