Supply chain planning has evolved technologically, but its underlying processes remain rooted in historic practices that no longer fit today’s volatile, complex environment. Packaged applications promise faster, lower-cost, lower-risk business outcomes, yet extensive customization, fragmented data, and rigid workflows often undermine that promise. Cloud data and AI platforms like Databricks and Snowflake offer an alternative: build interoperable applications on top of existing planning systems to address gaps in direct procurement, plan consumption, bullwhip reduction, operational planning, and dynamic master data. The opportunity is not simply to automate existing processes with AI and agentics, but to redefine how work gets done through end-to-end orchestration, value-based trade-offs, and clear decision governance.