ExpertOur team pushed a 2,000-SKU consumer goods catalog with 36 months of history through nine demand planning platforms, generating SKU-week forecasts and grading each against a naive seasonal baseline. The surprise: the tools with the fanciest AI rarely beat the ones that let a planner override the number by hand and keep the audit trail.
Our team ran a discrete-and-batch shop pilot through nine APS platforms, building the same finite-capacity model, triggering machine outages, and pushing rush orders into every scheduler. The finding we kept returning to: the ERP integration layer, not the algorithm, decides which APS survives quarter two.
We loaded the same 12,000-SKU catalog into 10 distribution ERPs over six weeks and ran the same operational scenarios on each: a 200-line purchase order, a multi-warehouse transfer, a lot-traceable recall simulation, and an order routed across two channels. The platforms diverged sharply on what they treated as easy versus what required a customization. The cleanest tools all shared one trait: they were built for distribution from day one rather than adapted from a manufacturing or general-ledger base.