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Your New Planning Tool Won't Fix Bad Data. It'll Make Wrong Decisions Faster, and With More Confidence.
AI-powered planning tools don't fix bad data. They amplify it, generating wrong purchase orders faster and with more apparent confidence than the manual process they replaced. Below roughly 85% BOM and inventory accuracy, the tool stops helping and starts working against you, and teams don't catch it right away. A couple months in, once the pattern of wrong orders is undeniable, they quietly start keeping a parallel spreadsheet again.
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Manufacturers Don't Have a Data Problem. They Have a Follow-Through Problem.
A researcher who talked with thirty plant managers found that manufacturing exception data wasn't the problem: every system already caught the defect and flagged it. What was missing sat one step further, a designed process for who owns the fix, on what deadline, with automatic escalation if it stalls, instead of a manager personally chasing it down by hand every time. The piece argues this gap is a process design failure, not a technology gap, and stays that way even in a fully automated plant, since deciding what to do about a flag is still human work.
Manufacturers Lead in AI Adoption. Most of It Isn't AI.
Manufacturers lead the mid-market in one category of AI adoption, according to Kaufman Rossin's latest survey: automation and RPA. The same survey has them trailing on generative AI, the chatbots and drafting tools that get the stage time at every conference. Repeat the first part in a boardroom, an...
ERP Migrations Are Business Archaeology, Not Software Configuration
Most ERP migrations don't fail on the software. They fail on the workarounds nobody wrote down, the ones that only surface after go-live as a "coverage gap" instead of a bug. This piece walks through how to find those workarounds before they find you, and the one question that tells you whether to drop them or build them in for good.