_______________________________________________________________________________________________________ Agentic
AI
The expertise that corrects your planning system has never been written down. By Will Dutton
Manufacturing has had an answer to volatility for the better part of two decades, and it was a rational one. Cheaper global supply was bought with stock. US Census data shows manufacturing inventory cover rising from roughly 35 days at its 2005 trough to nearer 45 days now, a considerable commitment of working capital to the business of absorbing uncertainty.
What the same period did not deliver was productivity. BLS figures put US manufacturing productivity growth at approximately 0.5 percent since late 2019 against around 2.1 percent for the wider economy, so the sector has been improving at roughly a quarter of the pace of the economy around it while carrying materially more stock than it once did. That is the most important fact in the present debate about AI in manufacturing, because it establishes, before any technology is discussed, that the constraint was never a shortage of buffer. Extra stock protects a business inside a network whose lead times it can plan around. It does very little when the network itself is being rebuilt underneath it.
The systems were built for one configuration
So, what happens to the systems running planning? They were built on the opposite assumption, which was not a mistake at the time. ERP and planning platforms were designed to hold one agreed version of the truth and to make change deliberate, traceable and owned, and every auditor, customer and finance director still requires
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