Sarah Tyler

Building AI Cloud Infrastructure for consumer packaged goods operations isn't like deploying generic enterprise cloud services. The unique computational demands of trade promotion optimization, the real-time requirements of demand forecasting during high-velocity promotional periods, the security complexities of collaborative planning with retail partners, and the massive data volumes from sell-in and sell-out metrics create infrastructure requirements that standard cloud architectures simply don't address. Yet CPG companies approaching cloud migration often work from checklists designed for different industries, leading to expensive misconfigurations, underperforming AI implementations, and infrastructure that can't scale when promotional planning cycles demand maximum computational capacity. This comprehensive checklist addresses the specific infrastructure components that CPG organizations need to support advanced analytics, AI-driven decision-making, and competitive tra...

After fifteen years managing trade promotion programs for a multinational CPG company, I thought I had seen every challenge the industry could throw at me. Late nights reconciling promotion ROI spreadsheets, tense category review meetings where we defended our trade spend allocation decisions with incomplete data, and the perpetual struggle to forecast promotional lift across hundreds of SKUs and dozens of retail partners. Then our executive team mandated a digital transformation initiative, and my world changed completely. What I learned implementing advanced cloud-based AI systems to manage our trade promotion operations fundamentally altered not just how we work, but what we believed was possible in promotion effectiveness analytics. The journey began when our VP of Sales challenged us to improve our promotional cadence decision-making by thirty percent within eighteen months. Traditional business intelligence tools were not going to cut it. We needed something that could process re...