The Manufacturing Data Problem: Why Your Factory Has More Data Than Ever and Fewer Answers

Your factory collects more data than ever. Your team still can't answer basic questions without digging through four systems.Every manufacturing plant is drowning in data — ERP transactions, quality measurements, maintenance logs, machine monitoring, institutional knowledge trapped in people's heads. The systems that collect it don't talk to each other. The dashboards built to make sense of it gather dust. And the experienced people who connect the dots are retiring.This book is the field guide to fixing that.Kevin DiGilio has spent over 20 years working with manufacturers from single-facility job shops to multi-plant defense contractors. The Manufacturing Data Problem lays out why traditional approaches — dashboards, integration middleware, cloud AI, ERP modules — keep failing, and what actually works.What you'll learn:Why the "four-system question" is the most expensive question in manufacturing — and how to make it a 10-second conversationWhy 50% of a working manufacturing AI system is data quality, not AIHow to capture institutional knowledge from retiring experts before it walks out the doorWhy on-premise AI costs half as much as cloud and gets better the more you use itHow to connect a new data source in days instead of months using plugin architectureHow to start with a 2-week pilot instead of a 12-month roadmapWritten for plant managers, operations leaders, and engineers — no AI background required. Includes a 15-question self-assessment, a complete manufacturing data landscape reference, and actionable guidance for manufacturers of every size.If you've ever watched an engineer spend half a morning hunting through systems for an answer that should take thirty seconds, this book is about eliminating that problem. Read more